cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17784826
title: Simulation data from "Radiative hydrodynamic simulations of FIP fractionation in solar flares"

description: Exact code and simulation data used to produce the figures in "Radiative hydrodynamic simulations of FIP fractionation in solar flares" by Reep et al, 2025.  Each zip file includes one simulation in whole.  

The naming convention is to list what sort of footpoint spikes were used (narrow, wide, or mixed), with the electron beam's energy flux (e.g. F1e11 = 1 x 10^11 erg/s/cm^2), and if the heating is asymmetric "_asym" is appended.  The two with "_f4" appended assume spikes with amplitude f = 4, rather than f = 5 in the rest.  

The simulation data is found in the "Results" folder, and includes a few .eps files plotting basic variables.
DOI: 10.5281/zenodo.17220862
title: Simulation data from "Radiative hydrodynamic simulations of FIP fractionation in solar flares"

description: Exact code and simulation data used to produce the figures in "Radiative hydrodynamic simulations of FIP fractionation in solar flares" by Reep et al, 2025.  Each zip file includes one simulation in whole.  

The naming convention is to list what sort of footpoint spikes were used (narrow, wide, or mixed), with the electron beam's energy flux (e.g. F1e11 = 1 x 10^11 erg/s/cm^2), and if the heating is asymmetric "_asym" is appended.  The two with "_f4" appended assume spikes with amplitude f = 4, rather than f = 5 in the rest.  

The simulation data is found in the "Results" folder, and includes a few .eps files plotting basic variables.
DOI: 10.3886/e240842
title: Provisional Death Counts for Coronavirus Disease (COVID-19)

description: Provisional COVID-19 Deaths by Week<br>
DOI: 10.3886/e240842v1
title: Provisional Death Counts for Coronavirus Disease (COVID-19)

description: Provisional COVID-19 Deaths by Week<br>
DOI: 10.17605/osf.io/8p64y
title: Identity dysfunction in borderline personality disorder: an experimental analogue of how negative self-views may interfere with building positive relationships
DOI: 10.17605/osf.io/meu3c
title: Earthworm response to metal pollution

description: This project aims at understanding how earthworm respond to metal pollution in urban environments.
DOI: 10.13140/rg.2.2.23227.07201
title: Grafico de Análisis Virtual: La guerra por la Supremacía de la IA (2025)
DOI: 10.15468/dl.u4xmrk
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Checklist of the species of Macrobrachium Spence Bate, 1868 (Decapoda: Caridea: Palaemonidae) from the lower Parnaíba River basin, Piauí, Brazil"
 ]
}

 The dataset includes 5 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021562-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17784867
title: BTCH-fused terrestrial water storage anomalies in the Three-River-Source Region, China (1988–2020)

description: This dataset contains the monthly Terrestrial Water Storage Anomaly (TWSA) time series for the Three-River-Source Region (TRSR) from 1988 to 2020. Methodology: The data was generated by fusing three GRACE/GRACE-FO based products (CSR, GSFC, JPL) from the GTWS-MLrec dataset (Yin et al., 2023) using the Bayesian Three-Cornered Hat (BTCH) method. The fusion weights were calculated specifically for the TRSR. Usage: This dataset supports the findings and figures in the manuscript "Ecological Restoration Enhances Terrestrial Water Storage in the Three-River-Source Region".
DOI: 10.5281/zenodo.17784866
title: BTCH-fused terrestrial water storage anomalies in the Three-River-Source Region, China (1988–2020)

description: This dataset contains the monthly Terrestrial Water Storage Anomaly (TWSA) time series for the Three-River-Source Region (TRSR) from 1988 to 2020. Methodology: The data was generated by fusing three GRACE/GRACE-FO based products (CSR, GSFC, JPL) from the GTWS-MLrec dataset (Yin et al., 2023) using the Bayesian Three-Cornered Hat (BTCH) method. The fusion weights were calculated specifically for the TRSR. Usage: This dataset supports the findings and figures in the manuscript "Ecological Restoration Enhances Terrestrial Water Storage in the Three-River-Source Region".
DOI: 10.15468/dl.eb3sng
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ClassKey is Aves",
 "OccurrenceStatus is Present",
 "GbifId is 4513733791",
 {
 "not" : {
 "DatasetKey" : [
 "is EOD – eBird Observation Dataset"
 ]
 }
 }
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021563-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tvkrdm
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Japan",
 "OccurrenceStatus is Present",
 "TaxonKey is Sasa occidentalis"
 ]
}

 The dataset includes 17 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021564-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17784825
title: Sustainable Fashion for Children's Clothing:  Exploring Permanent Pleating for Adaptive Fit and Textile Waste Reduction

description: Textile waste has become a serious global problem, leading to pollution, resource depletion, and overcrowding in landfills. To overcome these problems, sustainable design strategies that reduce resource consumption, minimize waste, and maintain ecological balance are needed. Additionally, children's rapid growth demands regular clothes changes, which generates a lot of fabric wastage. This highlights a serious research gap in creative, adaptable, waste-reducing ideas for children's clothing, which affects the sustainability of the textile industry. This study explores the potential of permanent pleating in children’s clothing to develop sustainable, innovative designs that minimize waste and improve garment durability. In particular, permanent pleating in both the lengthwise and widthwise directions are investigated, and the durability and fit of pleated garments are assessed, as well as manufacturing limitations and challenges. Permanent pleating was applied to 100% polyester, a polyester-cotton blend, and 100% cotton fabrics using pleating moulds and three distinct methods: oven drying, oven drying with water mugs, and steaming. The results revealed that the steaming method yielded the most successful permanent pleats on 100% polyester fabric, outperforming the polyester-cotton blend and 100% cotton fabrics. Permanent pleating reduces frequent clothing replacement by allowing the fabric to expand and fit various body sizes without losing structural integrity. This aids in sustainable children's clothing development by providing a new method to cut textile waste, benefiting both the fashion industry and customers.
DOI: 10.5281/zenodo.17784824
title: Sustainable Fashion for Children's Clothing:  Exploring Permanent Pleating for Adaptive Fit and Textile Waste Reduction

description: Textile waste has become a serious global problem, leading to pollution, resource depletion, and overcrowding in landfills. To overcome these problems, sustainable design strategies that reduce resource consumption, minimize waste, and maintain ecological balance are needed. Additionally, children's rapid growth demands regular clothes changes, which generates a lot of fabric wastage. This highlights a serious research gap in creative, adaptable, waste-reducing ideas for children's clothing, which affects the sustainability of the textile industry. This study explores the potential of permanent pleating in children’s clothing to develop sustainable, innovative designs that minimize waste and improve garment durability. In particular, permanent pleating in both the lengthwise and widthwise directions are investigated, and the durability and fit of pleated garments are assessed, as well as manufacturing limitations and challenges. Permanent pleating was applied to 100% polyester, a polyester-cotton blend, and 100% cotton fabrics using pleating moulds and three distinct methods: oven drying, oven drying with water mugs, and steaming. The results revealed that the steaming method yielded the most successful permanent pleats on 100% polyester fabric, outperforming the polyester-cotton blend and 100% cotton fabrics. Permanent pleating reduces frequent clothing replacement by allowing the fabric to expand and fit various body sizes without losing structural integrity. This aids in sustainable children's clothing development by providing a new method to cut textile waste, benefiting both the fashion industry and customers.
DOI: 10.6084/m9.figshare.24558427
title: Carini_etal_JEZB_oyster_larvae

description: Supporting datasets and R scripts for Carini et al. 2026Excel datasets: Larval shell length, larval shell thickness, field pH.R scripts: chromatograms.R= create TIC chromatograms, create_expr_objects.R= create MSnSet objects, larval_differences.R= all analyses other than proteomics, MSNID_filter.R= filtering protein identifications, prot_expr_analysis.R= differential protein expression analysis.Fasta files: treatment_proteome.fa= full sequences of filtered treatment shell proteome, control_proteome.fa= full sequences of filtered control shell proteomeFurther details regarding the datasets can be found in the readme file.<br>
DOI: 10.6084/m9.figshare.24558427.v1
title: Carini_etal_JEZB_oyster_larvae

description: Supporting datasets and R scripts for Carini et al. 2026Excel datasets: Larval shell length, larval shell thickness, field pH.R scripts: chromatograms.R= create TIC chromatograms, create_expr_objects.R= create MSnSet objects, larval_differences.R= all analyses other than proteomics, MSNID_filter.R= filtering protein identifications, prot_expr_analysis.R= differential protein expression analysis.Fasta files: treatment_proteome.fa= full sequences of filtered treatment shell proteome, control_proteome.fa= full sequences of filtered control shell proteomeFurther details regarding the datasets can be found in the readme file.<br>
DOI: 10.15468/dl.jz36by
title: Occurrence Download

description: A dataset containing 3032 species occurrences available in GBIF matching the query:
{
 "and" : [
 "PublishingOrg is 3dc9105b-6792-4d2f-8872-c60dded8ae20",
 "TaxonKey is Animalia"
 ]
}

 The dataset includes 3032 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021565-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17784913
title: Organic matter–mineral associations in organic horizons in high-altitude areas of snowy mountains, northern Japan (Original data)
DOI: 10.5281/zenodo.17784914
title: Organic matter–mineral associations in organic horizons in high-altitude areas of snowy mountains, northern Japan (Original data)
DOI: 10.3886/e240828v1
title: 2022 Environmental Performance Index (EPI)

description: The 2022 Environmental Performance Index (EPI) ranks 180 countries on 40 performance indicators in the following 11 issue categories: air quality, sanitation and drinking water, heavy metals, waste management, biodiversity and habitat, ecosystem services, fisheries, acid rain, agriculture, water resources, and climate change mitigation. These categories track performance and progress on three broad policy objectives, environmental health, ecosystem vitality, and climate change. The EPI's proximity-to-target methodology facilitates cross-country comparisons among economic and regional peer groups. The data set includes the 2022 EPI, component scores, and time-series source data. It is the result of a collaboration of the Yale Center for Environmental Law and Policy (YCELP), Yale University, and the Columbia University Center for International Earth Science Information Network (CIESIN).
description: Downloaded 2025-12-01.
DOI: 10.6084/m9.figshare.30487016.v1
title: Extracted RNA quantity, quality and RIN value

description: Extracted blue, sky-blue and white <i>Clitoria ternatea </i>flower RNA quality, quantity and RIN values.
DOI: 10.6084/m9.figshare.30759137
title: Source data of 《Increased electromagnetic interference shielding and load bearing with a three-dimensional pristine graphene@pyrocarbon skeleton in AZ91D》, manuscript number: NCOMMS-24-86208C

description: The development of electronic devices for communication systems, radar warning, and satellite detection requires lightweight materials that exhibit exceptional electromagnetic interference (EMI) shielding while maintaining mechanical robustness. However, designing three-dimensional (3D) structured pristine graphene (PG) that achieves both high EMI shielding and substantial load-bearing capacity remains a significant challenge. In this work, an innovative method of 3D skeleton preconstruction-infiltration filling is proposed. This approach demonstrates that molten AZ91D is infiltrated into the 3D structured PG@pyrocarbon (PG@PyC), and its 3D structure can be maintained in the AZ91D matrix via a liquid-solid infiltration extrusion method. By utilizing this strategy, PG@PyC reinforced AZ91D matrix (PG@PyC/AZ91D) composites display remarkable comprehensive performance, realizing an EMI shielding effectiveness of 76.70 dB (at 3 mm thickness), ultimate compressive strength of 276 MPa, and ultimate tensile strength of 231 MPa. The developed composites are promising lightweight materials for the integration of structural and functional applications in complex environments.
DOI: 10.6084/m9.figshare.30759137.v1
title: Source data of 《Increased electromagnetic interference shielding and load bearing with a three-dimensional pristine graphene@pyrocarbon skeleton in AZ91D》, manuscript number: NCOMMS-24-86208C

description: The development of electronic devices for communication systems, radar warning, and satellite detection requires lightweight materials that exhibit exceptional electromagnetic interference (EMI) shielding while maintaining mechanical robustness. However, designing three-dimensional (3D) structured pristine graphene (PG) that achieves both high EMI shielding and substantial load-bearing capacity remains a significant challenge. In this work, an innovative method of 3D skeleton preconstruction-infiltration filling is proposed. This approach demonstrates that molten AZ91D is infiltrated into the 3D structured PG@pyrocarbon (PG@PyC), and its 3D structure can be maintained in the AZ91D matrix via a liquid-solid infiltration extrusion method. By utilizing this strategy, PG@PyC reinforced AZ91D matrix (PG@PyC/AZ91D) composites display remarkable comprehensive performance, realizing an EMI shielding effectiveness of 76.70 dB (at 3 mm thickness), ultimate compressive strength of 276 MPa, and ultimate tensile strength of 231 MPa. The developed composites are promising lightweight materials for the integration of structural and functional applications in complex environments.
DOI: 10.15468/dl.958pc2
title: Occurrence Download

description: A dataset containing 14572 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Platyrrhinus"
 ]
}

 The dataset includes 14572 records from 351 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021567-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8jwgj3
title: Occurrence Download

description: A dataset containing 31 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "Country is United States of America",
 "Geometry POLYGON((-90.20062 24.24313,-78.24604 24.24313,-78.24604 31.88732,-90.20062 31.88732,-90.20062 24.24313))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Cassiopea xamachana",
 "Year 2015-2025"
 ]
}

 The dataset includes 31 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021570-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e240843v1
title: Natural Resource Protection and Child Health Indicators, 2022 Release

description: The Natural Resource Protection and Child Health Indicators, 2022 Release, is produced in support of the U.S. Millennium Challenge Corporation (MCC) as selection criteria for funding eligibility. The Natural Resource Protection Indicator (NRPI) and Child Health Indicator (CHI) are based on proximity-to-target scores ranging from 0 to 100 (at target). The NRPI covers 220 countries and is calculated based on the weighted average percentage of biomes under protected status. The CHI is a composite index for 195 countries derived from the average of three proximity-to-target scores for access to at least basic water and sanitation together with child mortality rates. The 2022 release includes a consistent time series of NRPI scores for 2010 to 2022 and CHI scores for 2010 to 2020.
description: Downloaded 2025-12-01.
DOI: 10.15468/dl.c7zzsx
title: Occurrence Download

description: A dataset containing 51 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Micrurus steindachneri"
 ]
}

 The dataset includes 51 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021572-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9hgskf
title: Occurrence Download

description: A dataset containing 1838338 species occurrences available in GBIF matching the query:
{
 "and" : [
 "PublishingOrg is f5fc4e61-b7a0-414b-ab68-b41cb23e7fdc",
 "TaxonKey is Animalia"
 ]
}

 The dataset includes 1838338 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021568-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gzz2as
title: Occurrence Download

description: A dataset containing 773488 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is one of (Canada, Mexico, United States of America)",
 "EventDate is greater than or equal to 2025-10-06",
 "EventDate is less than or equal to 2025-11-05",
 {
 "not" : {
 "Issue" : [
 "is one of (Basis of record invalid, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate precision invalid, Coordinate uncertainty meters invalid, Country mismatch, Country invalid, Geodetic datum invalid, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Country coordinate mismatch)"
 ]
 }
 },
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 773488 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021566-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30758984
title: Prediction files for mace-osaka24-small (Matbench Discovery)

description: This dataset contains the prediction files for the <b>mace-osaka24-small</b> model submitted to Matbench Discovery.<br>All files correspond exactly to the paths referenced in the <code>model_card.yaml</code>.Included files:Phonon κ_103 prediction fileIS2RE-SR geometry optimization prediction files (symprec=1e-2, 1e-5)Discovery task prediction fileThese files are used solely for benchmark reproducibility.License: MIT<br>Model repository: https://github.com/qiqb-osaka/mace-osaka24
DOI: 10.6084/m9.figshare.30758984.v1
title: Prediction files for mace-osaka24-small (Matbench Discovery)

description: This dataset contains the prediction files for the <b>mace-osaka24-small</b> model submitted to Matbench Discovery.<br>All files correspond exactly to the paths referenced in the <code>model_card.yaml</code>.Included files:Phonon κ_103 prediction fileIS2RE-SR geometry optimization prediction files (symprec=1e-2, 1e-5)Discovery task prediction fileThese files are used solely for benchmark reproducibility.License: MIT<br>Model repository: https://github.com/qiqb-osaka/mace-osaka24
DOI: 10.5281/zenodo.17784656
title: Dataset for "Generalized Nagaoka ferromagnetism accompanied by flavor-selective Mott states in an SU($N$) Fermi-Hubbard model"

description: Each .dat file contains raw data corresponding to the figures in the manuscript.
DOI: 10.15468/dl.rxvh5t
title: Occurrence Download

description: A dataset containing 631 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is North America",
 "Country is one of (United States of America, Mexico)",
 "Geometry POLYGON((-98.35803 17.90376,-81.04932 17.90376,-81.04932 31.47645,-98.35803 31.47645,-98.35803 17.90376))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Alligator mississippiensis",
 "Year 2009-2012"
 ]
}

 The dataset includes 631 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021573-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30759011
title: Prediction files for mace-osaka24-medium (Matbench Discovery)

description: This dataset contains the prediction files for the <b>mace-osaka24-medium</b> model submitted to Matbench Discovery.<br>Included files:Phonon κ_103 prediction fileIS2RE-SR geometry optimization prediction files (symprec=1e-2, 1e-5)Discovery task prediction fileThese files are used solely for benchmark reproducibility.License: MIT<br>Model repository: https://github.com/qiqb-osaka/mace-osaka24
DOI: 10.6084/m9.figshare.30759011.v1
title: Prediction files for mace-osaka24-medium (Matbench Discovery)

description: This dataset contains the prediction files for the <b>mace-osaka24-medium</b> model submitted to Matbench Discovery.<br>Included files:Phonon κ_103 prediction fileIS2RE-SR geometry optimization prediction files (symprec=1e-2, 1e-5)Discovery task prediction fileThese files are used solely for benchmark reproducibility.License: MIT<br>Model repository: https://github.com/qiqb-osaka/mace-osaka24
DOI: 10.15468/dl.9a4kwy
title: Occurrence Download

description: A dataset containing 1325 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "TaxonKey is Lasiurus borealis",
 "Year 1950-1965"
 ]
}

 The dataset includes 1325 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021575-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17605/osf.io/4bh5g
title: CONSORT and SPIRIT for Multicentre reporting guidelines

description: Multicentre clinical trials are important tools for innovation and development in drugs and medical devices. Our working group has identified shortcomings in the design and reporting of multicentre trials, especially in terms of heterogeneity among different centres. To address this, we are developing CONSORT-MCT 2020, an extension to the CONSORT 2010 Statement, and SPIRIT-MCT Checklist, an extension to the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) Statement.