cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/4s97yg7j9t.1
title: NepTrain and NepTrainKit: Automated active learning and visualization toolkit for neuroevolution potentials

description: As a machine-learned potential, the neuroevolution potential (NEP) method features exceptional computational efficiency and has been successfully applied in materials science. Constructing high-quality training datasets is crucial for developing accurate NEP models. However, the preparation and screening of NEP training datasets remain a bottleneck for broader applications due to their time-consuming, labor-intensive, and resource-intensive nature. In this work, we have developed NepTrain and NepTrainKit, which are dedicated to initializing and managing training datasets to generate high-quality training sets while automating NEP model training. NepTrain is an open-source Python package that features a bond length filtering method to effectively identify and remove non-physical structures from molecular dynamics trajectories, thereby ensuring high-quality training datasets. NepTrainKit is a graphical user interface (GUI) software designed specifically for NEP training datasets, providing functionalities for data editing, visualization, and interactive exploration. It integrates key features such as outlier identification, farthest-point sampling, non-physical structure detection, and configuration type selection. The combination of these tools enables users to process datasets more efficiently and conveniently. Using CSPbI3 as a case study, we demonstrate the complete workflow for training NEP models with NepTrain and further validate the models through materials property predictions. We believe this toolkit will greatly benefit researchers working with machine learning interatomic potentials.
DOI: 10.17632/fsg6jwbf9m
title: LINF_270028400

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/fsg6jwbf9m.2
title: LINF_270028400

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/mgntyf63v4
title: The 14C and 13C abundances of porewater DOC and sediment SOC from a mangrove swamp of southern China

description: This data was derived from creek water collected from the mouth of a tropical mangrove creek (Southern China) over a tidal cycle, as well as three sediment cores collected from the mangrove swamp along the elevation gradient during April and May 2019. The concentrations of dissolved organic carbon (DOC) were analyzed by the high temperature combustion (HTC) method using a Shimadzu TOC-L Total Organic Carbon Analyzer with an ASI-L auto-sampler. The contents of sediment organic carbon (SOC) were analyzed using a Thermo Flash 2000 CHNS/O Analyzer after acidification with 10% HCl. The 13C and 14C abundances were analyzed for both of DOC and SOC, and the UV-oxidation method was used for δ13C and Δ14C analyses. Analyses of Δ14C and δ13C were measured at the National Ocean Science Accelerator Mass Spectrometry (NOSAMS) facilities at Woods Hole Oceanographic Institution (WHOI).
DOI: 10.17632/mgntyf63v4.2
title: The 14C and 13C abundances of porewater DOC and sediment SOC from a mangrove swamp of southern China

description: This data was derived from creek water collected from the mouth of a tropical mangrove creek (Southern China) over a tidal cycle, as well as three sediment cores collected from the mangrove swamp along the elevation gradient during April and May 2019. The concentrations of dissolved organic carbon (DOC) were analyzed by the high temperature combustion (HTC) method using a Shimadzu TOC-L Total Organic Carbon Analyzer with an ASI-L auto-sampler. The contents of sediment organic carbon (SOC) were analyzed using a Thermo Flash 2000 CHNS/O Analyzer after acidification with 10% HCl. The 13C and 14C abundances were analyzed for both of DOC and SOC, and the UV-oxidation method was used for δ13C and Δ14C analyses. Analyses of Δ14C and δ13C were measured at the National Ocean Science Accelerator Mass Spectrometry (NOSAMS) facilities at Woods Hole Oceanographic Institution (WHOI).
DOI: 10.17026/dans-z5m-szsc
title: PAN-00041404 - terra sigillata cup type Drag. 27

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00041404&lt;/p&gt;
description: Modified: 2025-05-13T13:36:18+02:00
DOI: 10.17632/hvkr4bff8v
title: CONFLUX: A standardized framework to calculate reactor antineutrino flux

description: Nuclear fission reactors are abundant sources of antineutrinos for neutrino physics experiments. The flux and spectrum of antineutrinos emitted by a reactor can indicate its activity and composition, suggesting potential applications of neutrino measurements beyond fundamental scientific studies that may be valuable to society. The utility of reactor antineutrinos for applications and fundamental science is dependent on the availability of precise predictions of these emissions. For example, in the last decade, disagreements between reactor antineutrino measurements and models have inspired revision of reactor antineutrino calculations and standard nuclear databases as well as searches for new fundamental particles not predicted by the Standard Model of particle physics. Past predictions and descriptions of the methods used to generate them are documented to varying degrees in the literature, with different modeling teams incorporating a range of methods, input data, and assumptions. The resulting difficulty in accessing or reproducing past models and reconciling results from differing approaches complicates the future study and application of reactor antineutrinos. The CONFLUX (Calculation Of Neutrino FLUX) software framework is a neutrino prediction tool built with the goal of simplifying, standardizing, and democratizing the process of reactor antineutrino flux calculations. CONFLUX includes three primary methods for calculating the antineutrino emissions of nuclear reactors or individual beta decays that incorporate common nuclear data and beta decay theory. The software is prepackaged with the current nuclear databases, including ENDF.B/VIII, JEFF-3.3, and ENSDF, and it includes the capability to predict time-dependent reactor emissions, adjust nuclear database or beta decay inputs/assumptions, and propagate related sources of uncertainty. This paper describes the CONFLUX software structure, details the methods used for flux and spectrum calculations, and provides examples of potential use cases.
DOI: 10.17632/hvkr4bff8v.1
title: CONFLUX: A standardized framework to calculate reactor antineutrino flux

description: Nuclear fission reactors are abundant sources of antineutrinos for neutrino physics experiments. The flux and spectrum of antineutrinos emitted by a reactor can indicate its activity and composition, suggesting potential applications of neutrino measurements beyond fundamental scientific studies that may be valuable to society. The utility of reactor antineutrinos for applications and fundamental science is dependent on the availability of precise predictions of these emissions. For example, in the last decade, disagreements between reactor antineutrino measurements and models have inspired revision of reactor antineutrino calculations and standard nuclear databases as well as searches for new fundamental particles not predicted by the Standard Model of particle physics. Past predictions and descriptions of the methods used to generate them are documented to varying degrees in the literature, with different modeling teams incorporating a range of methods, input data, and assumptions. The resulting difficulty in accessing or reproducing past models and reconciling results from differing approaches complicates the future study and application of reactor antineutrinos. The CONFLUX (Calculation Of Neutrino FLUX) software framework is a neutrino prediction tool built with the goal of simplifying, standardizing, and democratizing the process of reactor antineutrino flux calculations. CONFLUX includes three primary methods for calculating the antineutrino emissions of nuclear reactors or individual beta decays that incorporate common nuclear data and beta decay theory. The software is prepackaged with the current nuclear databases, including ENDF.B/VIII, JEFF-3.3, and ENSDF, and it includes the capability to predict time-dependent reactor emissions, adjust nuclear database or beta decay inputs/assumptions, and propagate related sources of uncertainty. This paper describes the CONFLUX software structure, details the methods used for flux and spectrum calculations, and provides examples of potential use cases.
DOI: 10.17632/yc2gs4skmr
title: 2025/09/25Elsevier Submit

description: 六自由度耦合运动对碱性水电解系统性能的影响，包含横摇2/4/6/8*0.5/0.8/1.0Hz、纵摇4*0.5/0.8/1.0Hz、横荡50mm*0.5/0.8/1.0Hz、纵荡50mm*0.5/0.8/1.0Hz、艏摇4*0.5/0.8/1.0Hz、垂荡40mm*0.5/0.8/1.0Hz，以及三自由度模拟平台运动、六自由度模拟船型运动与静止工况下的极化曲线对比图
DOI: 10.15468/dl.2744ta
title: Occurrence Download

description: A dataset containing 102 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Arundo donax versicolor)"
 ]
}

 The dataset includes 102 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016271-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/yc2gs4skmr.1
title: 2025/09/25Elsevier Submit

description: 六自由度耦合运动对碱性水电解系统性能的影响，包含横摇2/4/6/8*0.5/0.8/1.0Hz、纵摇4*0.5/0.8/1.0Hz、横荡50mm*0.5/0.8/1.0Hz、纵荡50mm*0.5/0.8/1.0Hz、艏摇4*0.5/0.8/1.0Hz、垂荡40mm*0.5/0.8/1.0Hz，以及三自由度模拟平台运动、六自由度模拟船型运动与静止工况下的极化曲线对比图
DOI: 10.15468/dl.qgge2r
title: Occurrence Download

description: A dataset containing 462 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Pseudochondrostoma polylepis)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 462 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016270-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/rbs6i8
title: PAN-00170043 - ring unspecified (period unspecified)

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00170043&lt;/p&gt;
description: Modified: 2025-04-30T13:44:35+02:00
DOI: 10.17632/ywxgjf59h8
title: Effects of grass roots on the water retention and water stability of loess

description: Data on water retention and water stability of vegetation soil in the loess region
DOI: 10.17632/ywxgjf59h8.1
title: Effects of grass roots on the water retention and water stability of loess

description: Data on water retention and water stability of vegetation soil in the loess region
DOI: 10.17632/f547zyy7v4
title: Data for: Public Procurement Status and Improvement Needs in Saudi Arabia: Local Content and Saudization

description: This dataset presents key metrics from Saudi Arabia’s public procurement landscape, including localization achievements under the IKTVA program, Saudization trends, SME participation, and procurement’s share of GDP. It supports the analysis in the paper “Public Procurement Status and Improvement Needs in Saudi Arabia”.
Keywords: Saudi Arabia, Public Procurement, IKTVA, Saudization, SME Inclusion, Etimad, Vision 2030
DOI: 10.17632/f547zyy7v4.2
title: Data for: Public Procurement Status and Improvement Needs in Saudi Arabia: Local Content and Saudization

description: This dataset presents key metrics from Saudi Arabia’s public procurement landscape, including localization achievements under the IKTVA program, Saudization trends, SME participation, and procurement’s share of GDP. It supports the analysis in the paper “Public Procurement Status and Improvement Needs in Saudi Arabia”.
Keywords: Saudi Arabia, Public Procurement, IKTVA, Saudization, SME Inclusion, Etimad, Vision 2030
DOI: 10.17632/9sf6wxpgtm
title: LINF_270029000

description: Mitochondrial import inner membrane translocase subunit TIM50; Leishmania infantum (strain JPCM5)
DOI: 10.17632/9sf6wxpgtm.2
title: LINF_270029000

description: Mitochondrial import inner membrane translocase subunit TIM50; Leishmania infantum (strain JPCM5)
DOI: 10.17632/cmrz32r9w4
title: LINF_270028700

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/cmrz32r9w4.1
title: LINF_270028700

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17026/ar/ecqrqj
title: PAN-00090155 - separate prick of Roman spur

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00090155&lt;/p&gt;
description: Modified: 2025-05-13T16:02:17+02:00
DOI: 10.17632/43vc52c57n
title: LINF_270028800

description: SET domain-containing protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/43vc52c57n.1
title: LINF_270028800

description: SET domain-containing protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/ffsx864mkw
title: Disengaging from Others: Determinants of Selective Avoidance in Polarized Argentina

description: Selective avoidance, defined as the tendency to evade information that challenges political beliefs, weakens deliberative norms in polarized societies. Most studies have focused on the United States and Europe, often attributing avoidance to algorithmic curation. This article examines Argentina, one of the most polarized countries in Latin America, to assess the broader validity of these explanations. Using survey data from ESPOP 2024, we analyze how ideological extremism, partisan identification, political sophistication, and voting intention shape avoidance online and offline. Logistic regression models show that strong partisan ties, extreme ideological views, and greater sophistication significantly increase the likelihood of avoidance. Cognitive Partisans, who combine high sophistication with strong partisan identity, are the most prone to filtering, suggesting that political knowledge enables strategic selectivity rather than openness. Comparative evidence from Argentina demonstrates that selective avoidance reflects identity-protective processes not limited to advanced democracies or digital environments.
DOI: 10.17632/ffsx864mkw.1
title: Disengaging from Others: Determinants of Selective Avoidance in Polarized Argentina

description: Selective avoidance, defined as the tendency to evade information that challenges political beliefs, weakens deliberative norms in polarized societies. Most studies have focused on the United States and Europe, often attributing avoidance to algorithmic curation. This article examines Argentina, one of the most polarized countries in Latin America, to assess the broader validity of these explanations. Using survey data from ESPOP 2024, we analyze how ideological extremism, partisan identification, political sophistication, and voting intention shape avoidance online and offline. Logistic regression models show that strong partisan ties, extreme ideological views, and greater sophistication significantly increase the likelihood of avoidance. Cognitive Partisans, who combine high sophistication with strong partisan identity, are the most prone to filtering, suggesting that political knowledge enables strategic selectivity rather than openness. Comparative evidence from Argentina demonstrates that selective avoidance reflects identity-protective processes not limited to advanced democracies or digital environments.
DOI: 10.17632/95bvxcjjbb
title: LINF_270029300

description: Dual specificity protein phosphatase; Leishmania infantum (strain JPCM5)
DOI: 10.17632/95bvxcjjbb.2
title: LINF_270029300

description: Dual specificity protein phosphatase; Leishmania infantum (strain JPCM5)
DOI: 10.17026/ar/h5ecup
title: PAN-00151375 - finger ring with soldered round bezel

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00151375&lt;/p&gt;
description: Modified: 2025-05-07T13:43:52+02:00
DOI: 10.17026/ar/j03izr
title: PAN-00173183 - iron nail general

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00173183&lt;/p&gt;
description: Modified: 2025-05-20T17:23:00+02:00
DOI: 10.17026/ar/foualz
title: PAN-00166564 - Roman spoon group B

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00166564&lt;/p&gt;
description: Modified: 2025-05-16T14:22:44+02:00
DOI: 10.17026/ar/foj1jd
title: PAN-00151274 - terra sigillata plate with footring

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00151274&lt;/p&gt;
description: Modified: 2025-06-12T09:27:18+02:00
DOI: 10.17632/hs6bcw5gkt
title: Trait prediction in rare marsh plants: a PLSR modeling framework using dominant families and sample size thresholds

description: Plant functional traits serve as crucial indicators for assessing the status of ecosystems. However, accurately predicting leaf traits of rare species using spectral reflectance remains challenging because the limited sample sizes of rare species make it difficult to construct reliable spectral prediction models for them directly. The study hypothesized that the leaf traits of rare marsh species could be inferred from the modeling results of the dominant species, even with a limited sample size. To investigate this, we measured leaf reflectance spectra and eleven leaf functional traits across different species and established Partial Least Squares Regression (PLSR) models based on five combinations of plant families (All-families, Dominant-families, Non-Cyperaceae, Cyperaceae-Poaceae, and Cyperaceae) and six different sample sizes (40, 80, 120, 160, 200, and 240 samples). Our findings revealed that the PLSR models exhibited higher predictive performance for nitrogen (N, R_Val^2=0.87) and leaf water content (LWC, R_Val^2=0.85) compared to the other nine leaf traits. Notably, models constructed using the Dominant-families dataset (excluding rare species) exhibited predictive accuracy statistically comparable to the All-families dataset (which includes rare species) for all eleven traits. Additionally, we found that a minimum of 160 samples in the Dominant-families dataset was required to achieve reliable prediction for most leaf traits. This finding demonstrates that Dominant-families models can not only effectively substitute for All-families models but also provide a valid pathway to infer rare species’ leaf traits. By addressing the data scarcity challenge (i.e., insufficient samples of rare species) through dominant species sampling, prioritizing the collection of Dominant-families datasets meeting the 160-sample threshold offers a practical framework for predicting rare marsh species’ leaf traits.
DOI: 10.17632/hs6bcw5gkt.1
title: Trait prediction in rare marsh plants: a PLSR modeling framework using dominant families and sample size thresholds

description: Plant functional traits serve as crucial indicators for assessing the status of ecosystems. However, accurately predicting leaf traits of rare species using spectral reflectance remains challenging because the limited sample sizes of rare species make it difficult to construct reliable spectral prediction models for them directly. The study hypothesized that the leaf traits of rare marsh species could be inferred from the modeling results of the dominant species, even with a limited sample size. To investigate this, we measured leaf reflectance spectra and eleven leaf functional traits across different species and established Partial Least Squares Regression (PLSR) models based on five combinations of plant families (All-families, Dominant-families, Non-Cyperaceae, Cyperaceae-Poaceae, and Cyperaceae) and six different sample sizes (40, 80, 120, 160, 200, and 240 samples). Our findings revealed that the PLSR models exhibited higher predictive performance for nitrogen (N, R_Val^2=0.87) and leaf water content (LWC, R_Val^2=0.85) compared to the other nine leaf traits. Notably, models constructed using the Dominant-families dataset (excluding rare species) exhibited predictive accuracy statistically comparable to the All-families dataset (which includes rare species) for all eleven traits. Additionally, we found that a minimum of 160 samples in the Dominant-families dataset was required to achieve reliable prediction for most leaf traits. This finding demonstrates that Dominant-families models can not only effectively substitute for All-families models but also provide a valid pathway to infer rare species’ leaf traits. By addressing the data scarcity challenge (i.e., insufficient samples of rare species) through dominant species sampling, prioritizing the collection of Dominant-families datasets meeting the 160-sample threshold offers a practical framework for predicting rare marsh species’ leaf traits.
DOI: 10.17632/ssgspz6zsg
title: urban carbon emissions and its potential influencing factors (2000-2021)

description: this study obtained urban carbon emissions data from annually open-source data inventory for anthropogenic CO2 (ODIAC) (Oda and Maksyutov, 2023). Environmental variables were derived from monthly land surface temperature data (Temp), daily gap-free normalized difference vegetation index (NDVI) , data on the relief degree of land surface (RDLS) , and yearly ratio of ecological functional area (EF), Human activities indicators were sourced from annually nighttime light (NTL) data and yearly ratio of urban and artificial facilities functional area (UAF). All datasets span the period 2000-2021. To ensure temporal consistency, every variable was preprocessed to its annual mean value before analysis. Since administrative divisions in China may change in different years, this study uniformly used 2022 prefecture-level city boundaries to ensure spatial consistency of urban boundaries across all years
DOI: 10.17632/ssgspz6zsg.1
title: urban carbon emissions and its potential influencing factors (2000-2021)

description: this study obtained urban carbon emissions data from annually open-source data inventory for anthropogenic CO2 (ODIAC) (Oda and Maksyutov, 2023). Environmental variables were derived from monthly land surface temperature data (Temp), daily gap-free normalized difference vegetation index (NDVI) , data on the relief degree of land surface (RDLS) , and yearly ratio of ecological functional area (EF), Human activities indicators were sourced from annually nighttime light (NTL) data and yearly ratio of urban and artificial facilities functional area (UAF). All datasets span the period 2000-2021. To ensure temporal consistency, every variable was preprocessed to its annual mean value before analysis. Since administrative divisions in China may change in different years, this study uniformly used 2022 prefecture-level city boundaries to ensure spatial consistency of urban boundaries across all years