cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15493/dffe.ccis.42102024
title: Future Flood index: Ensemble 10th,50th and 90th percentiles of Annual maximum consecutive 5-day precipitation (Rx5day) for 3.0 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15493/dffe.ccis.38102024
title: Future Flood index: Ensemble 10th,50th and 90th percentiles of Annual number of very heavy rainy days: annual count of days when PRCP ≥ 20mm (r20mm) for 3.0 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15493/dffe.ccis.36102024
title: Future Flood index: Ensemble 10th,50th and 90th percentiles of Annual number of very heavy rainy days: annual count of days when PRCP ≥ 20mm (r20mm) for 1.5 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15493/dffe.ccis.39102024
title: Future Flood index: Ensemble 10th,50th and 90th percentiles of Annual maximum consecutive 5-day precipitation (Rx5day) for baseline period of 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15493/dffe.ccis.40102024
title: Future Flood index: Ensemble 10th,50th and 90th percentiles of Annual maximum consecutive 5-day precipitation (Rx5day) for 1.5 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15493/dffe.ccis.33102024
title: Future Extreme heat index: Ensemble 10th,50th and 90th percentiles of Annual heatwave number: the number of heatwaves (hwn) for 3.0 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15493/dffe.ccis.41102024
title: Future Flood index: Ensemble 10th,50th and 90th percentiles of Annual maximum consecutive 5-day precipitation (Rx5day) for 2.0 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15493/dffe.ccis.43102024
title: Future Flood index: Ensemble 10th,50th and 90th percentiles of Annual maximum consecutive 5-day precipitation (Rx5day) for 1.5, 2.0 and 3.0 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.17632/m7788yc9sf.2
title: Raw data corresponding to "Chaperone Hsp70 helps Salmonella survive infection-relevant stresses by reducing protein synthesis"

description: Uncropped images corresponding to the various gels presented in the figures in the manuscript.
DOI: 10.17632/m7788yc9sf.1
title: Raw data corresponding to "Chaperone Hsp70 helps Salmonella survive infection-relevant stresses by reducing protein synthesis"

description: Uncropped images corresponding to the various gels presented in the figures in the manuscript.
DOI: 10.17632/ptvwj47yr4.3
title: Dataset of "Mitochondrial CCN1 drives ferroptosis via fatty acid β-oxidation"

description: Result data of three lipidomics in "Mitochondrial CCN1 drives ferroptosis via fatty acid β-oxidation" were included. In lipidomics 1, H1299 and H1299 CCN1 KO cells were treated with DMSO or RSL3 for 3 h. In lipidomics 2, H1299 and H1299 cells with CCN1 KO or CPT2 KO were treated with DMSO or RSL3 for 3 h in the presence of 13C-labeled palmitate and L-carnitine . In lipidomics 3, serum of (cell-derived xenograft) CDX mice models fed with normal chow diet (NCD) or high-fat diet (HFD) were collected. In lipidomics 4, tumor tissues of CDX mice models fed with NCD or HFD were collected. In lipidomics 5, CDX mice models fed with NCD or HFD were intraperitoneally injected with Solvent, IKE or etomoxir. At the endpoint, the serum was collected.
DOI: 10.17632/c7hx32y7j4.1
title: Multi-analytical Techniques Reveal： Why Jian Kiln Hare’s Fur Glaze Tea Bowls Were the Best in Song Dynasty Tea Competition (Doucha) Culture

description: This attachment contains the results of micro-CT tests on the body of typical tea bowl from Jian kilns, Jizhou kilns, and Jingdezhen kilns of the Song Dynasty, including 3D reconstruction using VoxelStudio Recon software and results using Dragonfly 3D visualisation software. LHP-1 is a Jian kiln hare’s fur glaze tea bowl, MAL-1 is a Jizhou kiln black-glazed tea bowl, and FWC-1 is a Jingdezhen kiln bluish-white porcelain tea bowl; more details are given in the main text section.
DOI: 10.5281/zenodo.10463523
title: Phylogenetic diversity of the Pristimantis anaiae species group,with description of a new rainfrog of genus Pristimantis (Anura, Craugastoridae), from Cerro Candelaria, Tungurahua, Ecuador.

description: The data matrix has up to 3864 BP and 46 terminals from the group of species Pristimantis anaiae

12S = 1 - 889;

16S = 890 - 2046;

ND1 = 2047 - 3299;

RAG1 = 3300 - 3864
DOI: 10.5281/zenodo.13710169
title: Data for Glacial isostatic adjustment reveals Mars' interior viscosity structure

description: Present-day Martian interior models used in Broquet et al. (2024). All models use the following naming convention: Profile_NorthPole_Mars-TAYAK-dc-rho_south[-rho_north], where dc is the crustal thickness at the InSight landing site in km, rho_north and rho_south are the bulk density of the northern and southern hemisphere crust in g cm^-3. If added, XGRS provides the crustal heat producing element enrichment factor (X) with respect to the nominal Gamma Ray measured average of 49 pW kg^-1. 

Files with _60deg provide quantities averaged over the northern regions (>60°N) and _AVG give averages for the whole planet. Models with case numbers are from Plesa et al. (2018) [https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2018GL080728]. 

Data Columns:------------------------------Column 1: Radius [m]Column 2: Temperature [K]Column 3: Viscosity [Pa s]Column 4: Shear Velocity [m/s]Column 5: Density [kg/m3]Column 6: Shear Modulus [Pa]
DOI: 10.5281/zenodo.13254108
title: MD SIMULATION DATA for cytochromeP450 with SCC and AFB1.

description: MD simulation data submission.
DOI: 10.5281/zenodo.10055840
title: IMTA of European lobster and oyster

description: Data set obtained from research conducted within the AquaVitae project, with the aim to evaluate co-cultivation of the European lobster (Homarus gammarus) and the European flat oyster (Ostrea edulis) in a sea-based system adapted to local conditions. The data originates from the Swedish west coast and includes growth and survival of lobster juveniles and oysters cultured in different systems and at different depths, measured at different time points after deployment.
DOI: 10.5281/zenodo.10055841
title: IMTA of European lobster and oyster

description: Data set obtained from research conducted within the AquaVitae project, with the aim to evaluate co-cultivation of the European lobster (Homarus gammarus) and the European flat oyster (Ostrea edulis) in a sea-based system adapted to local conditions. The data originates from the Swedish west coast and includes growth and survival of lobster juveniles and oysters cultured in different systems and at different depths, measured at different time points after deployment.
DOI: 10.5281/zenodo.11394587
title: The nociceptive withdrawal reflex during spinal analgesia in pigs undergoing veno-arterial extracorporeal membrane oxygenation: a prospective observational study.
DOI: 10.5281/zenodo.13192209
title: MD SIMULATION DATA for cytochromeP450 with SCC and AFB1.

description: MD simulation data submission.
DOI: 10.5281/zenodo.13946854
title: Annex C_Prioritisation of project proposals

description: EU;XLSX;EN;CSO@efsa.europa.eu
DOI: 10.5281/zenodo.13640518
title: 3D ED/MicroED Data of Dye Type Peroxidase Aa from Streptomyces lividans

description: 3D ED/MicroED data of of Dye Type Peroxidase Aa from Streptomyces lividans (DPtAa) collected on a Titan Krios cryo-TEM (ThermoFisher Scientific) operating at 300 kV and equipped with a Ceta-D CMOS detector. 

Datasets 1-19 were collected using a 1.5 µm beam, C2 aperture of 20 µm and spot size 9, resulting in a measured flux of 0.115 eÅ.2s-1.

Datasets 20 and 21 were collected using a wider beam of 3 µm beam and spot size 8 , with fluence measured to 0.210 eÅ-2.
DOI: 10.15468/dl.w66ysu
title: Occurrence Download

description: A dataset containing 1419 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Phytoplankton microscopic observations from the FjordPhyto Citizen Science Project of the 2017-2018 Antarctic season"
 ]
}

 The dataset includes 1419 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011552-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.