cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/gzbtsxp2f6.1
title: Heavy Mo isotope observed in continental subduction-related mafic magmatism: implications for crust-mantle interaction and geodynamic process in continental subduction zone

description: Supplementary data
DOI: 10.17632/rj9ntc7tzn
title: NGAMMA: A Monte Carlo generator for multiphoton production in e+e− annihilation

description: We present the NGAMMA Monte Carlo event generator for QED processes of e+e- annihilation into a multiphoton final state, e+e- → Nγ(N ≥ 2). These processes are an important source of background in the study of e+e- → hadrons processes with a multiphoton final state, especially for experiments at low energy e+e- colliders like SND, CMD-3, KLOE and for the BESIII experiment. For generation, NGAMMA exploits the exact tree-level amplitude.
DOI: 10.17632/rj9ntc7tzn.1
title: NGAMMA: A Monte Carlo generator for multiphoton production in e+e− annihilation

description: We present the NGAMMA Monte Carlo event generator for QED processes of e+e- annihilation into a multiphoton final state, e+e- → Nγ(N ≥ 2). These processes are an important source of background in the study of e+e- → hadrons processes with a multiphoton final state, especially for experiments at low energy e+e- colliders like SND, CMD-3, KLOE and for the BESIII experiment. For generation, NGAMMA exploits the exact tree-level amplitude.
DOI: 10.15468/dl.fe257z
title: Occurrence Download

description: A dataset containing 3346 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Lagocephalus sceleratus)",
 "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 3346 records from 56 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015429-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/tfzdnz7vwx
title: VirtualFluids – open source parallel LBM solver

description: This paper accompanies the publication of the open source lattice Boltzmann solver VirtualFluids [DOI: 10.5281/zenodo.10283048]. Key features of VirtualFluids are the cumulant collision operator, the ability to run multi-scale simulations based on compact interpolation grid refinement and its implementations for both GPU and massively parallel CPU systems. The differences in data structure for the different systems are explained in detail.
DOI: 10.17632/tfzdnz7vwx.1
title: VirtualFluids – open source parallel LBM solver

description: This paper accompanies the publication of the open source lattice Boltzmann solver VirtualFluids [DOI: 10.5281/zenodo.10283048]. Key features of VirtualFluids are the cumulant collision operator, the ability to run multi-scale simulations based on compact interpolation grid refinement and its implementations for both GPU and massively parallel CPU systems. The differences in data structure for the different systems are explained in detail.
DOI: 10.17632/38v4nphmn6
title: data

description: (1) validating a novel spatial cognition assessment system and (2) quantifying multidimensional SC profiles across a large cohort of healthy adults. By addressing calls for methodologically rigorous, ecologically valid spatial assessments (Uttal et al., 2024), this work resolves inconsistencies arising from fragmented measurement approaches and establishes a novel paradigm for investigating spatial cognition dynamics in lifespan developmental and cognitive aging research.
DOI: 10.15468/dl.6gqfx9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Linum grandiflorum",
 "Country is India",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015430-250914085247600/datasets/export for details.
DOI: 10.17632/38v4nphmn6.1
title: data

description: (1) validating a novel spatial cognition assessment system and (2) quantifying multidimensional SC profiles across a large cohort of healthy adults. By addressing calls for methodologically rigorous, ecologically valid spatial assessments (Uttal et al., 2024), this work resolves inconsistencies arising from fragmented measurement approaches and establishes a novel paradigm for investigating spatial cognition dynamics in lifespan developmental and cognitive aging research.
DOI: 10.5258/soton/d3661
title: Dataset supporting thesis titled: Investigation of monitoring technologies to deliver 'Pill-in-the-Pocket' oral anticoagulation in atrial fibrillation

description: This zip file contains the spreadsheets for the following publications:
Chapter 3: 'Pill-in-the-pocket' Oral Anticoagulation Guided by Daily Rhythm Monitoring for Stroke Prevention in Patients with AF: A Systematic Review and Meta-analysis.
Briosa E Gala A, Pope MTB, Leo M, Sharp AJ, Tsoi V, Paisey J, Curzen N, Betts TR.
Arrhythm Electrophysiol Rev. 2023 Mar 2;12:e05. doi: 10.15420/aer.2022.22. eCollection 2023.
Chapter 4: "Real-world" performance of the Confirm Rx™ SharpSense AF detection algorithm: UK Confirm Rx study.
Gala ABE, Pope MTB, Leo M, Sharp AJ, Banerjee A, Field D, Thomas H, Balasubramaniam R, Hunter R, Gardner RS, Wilson D, Gallagher MM, Ormerod J, Paisey J, Curzen N, Betts TR.
J Arrhythm. 2024 Sep 3;40(5):1093-1101. doi: 10.1002/joa3.13124. eCollection 2024 Oct.
Chapter 5: Diagnostic performance of single-lead electrocardiograms from a smartwatch and a smartring for cardiac arrhythmia detection.
Briosa E Gala A, Sharp AJ, Schramm D, Pope MTB, Leo M, Varini R, Banerjee A, Win KZ, Kalla M, Paisey J, Curzen N, Betts TR.Hea rt Rhythm O2. 2025 Mar 26;6(6):808-817. doi: 10.1016/j.hroo.2025.03.019. eCollection 2025 Jun.
Chapter 6: Real-time smartphone alerts during atrial fibrillation episodes with implantable cardiac monitors and wearable devices: SMART-ALERT study.
Briosa E Gala A, Sharp AJ, Pope MTB, Leo M, Varini R, Paisey J, Curzen N, Banerjee A, Betts TR.
Heart Rhythm. 2025 Apr 15:S1547-5271(25)02331-8. doi: 10.1016/j.hrthm.2025.04.015. Online ahead of print.
DOI: 10.17632/c4kt7xn2b5.2
title: Velocity datasets of an asymmetric dairy barn model by LDA in BLWT

description: The datasets present high-resolution airflow and turbulence measurements obtained in and around a 1:50 scaled asymmetric dairy barn model using a boundary layer wind tunnel (BLWT), including characterization data of boundary layer profile and airflow measurements at a cross-sectional plane. All instantaneous air velocities were acquired using a two-dimensional Laser Doppler Anemometry (LDA) system. The dataset of 233 point-dataset is primarily designed for validation and refinement of computational fluid dynamics (CFD) models, and includes pointwise instantaneous velocity fluctuations that is ideal for comparing time-series turbulence statistics and transient structures. Researchers in livestock housing design can use this dataset to evaluate and improve ventilation strategies for complex geometries. The spatially resolved measurement points allow for detailed comparisons between experimental and simulated results, supporting robust model calibration and validation efforts. Additionally, the datasets can be employed as references in indoor air quality and emission research, such as assessing ventilation efficacy and studying contaminant transport. The datasets can also serve as a reference for experimental planning and sensor placement optimization in scaled or in-situ airflow studies, enhancing the design of measurement campaigns. In summary, our datasets provide critical references for numerical modelling, and is valuable for further investigations of wind-driven ventilation performance as well as emission characterization in naturally-ventilated livestock buildings.
DOI: 10.5281/zenodo.17153854
title: Dataset and codebook of Teachers' perceptions of inclusive education in secondary, high school, and vocational training: Resources, barriers, and training needs

description: This repository contains the dataset and the accompanying codebook from the study Teachers' perceptions of inclusive education in secondary, high school, and vocational training: Resources, barriers, and training needs. The dataset includes anonymized responses collected from active teachers in secondary education, high school, and vocational training. Data were gathered through a structured questionnaire designed to explore teachers’ conceptions of inclusive education, perceived barriers to its implementation, available pedagogical and organizational resources, and professional training needs. All responses are fully anonymized to comply with ethical and legal standards.

The codebook provides detailed documentation of the analytical framework used in the study. It presents the hierarchical structure of meta-categories (MC), categories (C), and subcategories (SC), each linked to specific research objectives. These cover critical dimensions such as educational center infrastructure (human and material resources, adaptations, and SSESN presence), teaching performance in addressing diversity, continuous professional development (CPD), shortcomings in initial teacher education (ITE), and perceived changes in inclusive practices.

Together, the dataset and codebook offer a comprehensive resource for researchers, teacher trainers, and policymakers. The dataset enables empirical analysis of teachers’ perceptions of inclusive education, while the codebook ensures transparency, reproducibility, and clarity in interpreting the variables. This combination supports comparative research, the design of inclusive educational strategies, and the development of teacher training programs tailored to identified needs.
DOI: 10.5281/zenodo.17153855
title: Dataset and codebook of Teachers' perceptions of inclusive education in secondary, high school, and vocational training: Resources, barriers, and training needs

description: This repository contains the dataset and the accompanying codebook from the study Teachers' perceptions of inclusive education in secondary, high school, and vocational training: Resources, barriers, and training needs. The dataset includes anonymized responses collected from active teachers in secondary education, high school, and vocational training. Data were gathered through a structured questionnaire designed to explore teachers’ conceptions of inclusive education, perceived barriers to its implementation, available pedagogical and organizational resources, and professional training needs. All responses are fully anonymized to comply with ethical and legal standards.

The codebook provides detailed documentation of the analytical framework used in the study. It presents the hierarchical structure of meta-categories (MC), categories (C), and subcategories (SC), each linked to specific research objectives. These cover critical dimensions such as educational center infrastructure (human and material resources, adaptations, and SSESN presence), teaching performance in addressing diversity, continuous professional development (CPD), shortcomings in initial teacher education (ITE), and perceived changes in inclusive practices.

Together, the dataset and codebook offer a comprehensive resource for researchers, teacher trainers, and policymakers. The dataset enables empirical analysis of teachers’ perceptions of inclusive education, while the codebook ensures transparency, reproducibility, and clarity in interpreting the variables. This combination supports comparative research, the design of inclusive educational strategies, and the development of teacher training programs tailored to identified needs.
DOI: 10.15468/dl.g4z4xg
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Linum grandiflorum",
 "Country is Iraq",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015431-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.58jrnr
title: Occurrence Download

description: A dataset containing 390 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Linum grandiflorum",
 "Country is Netherlands",
 "HasCoordinate is true"
 ]
}

 The dataset includes 390 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015432-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/fmnr6yy5xz
title: Diabetes

description: Arabic awareness information about diabetes
DOI: 10.17632/fmnr6yy5xz.1
title: Diabetes

description: Arabic awareness information about diabetes
DOI: 10.17632/hm3n4yn3ty
title: Derived Datasets for "Aligning credit-hour expectations with reality: Cluster analysis of study organization in e-textbook logs"

description: De-identified derived datasets (student-level aggregates, per-lecture features, session-level durations) plus a synthetic event-log sample supporting the manuscript “Aligning credit-hour expectations with reality: Cluster analysis of study organization in e-textbook logs.” Raw clickstream logs are not shared due to re-identification risk. Key variables: total_sec (sec), uniq_pages (count), max_sess (sec), offset (min), spread (days), cluster (1–4). Time zone: Asia/Tokyo; timestamps: ISO 8601.
DOI: 10.17632/hm3n4yn3ty.1
title: Derived Datasets for "Aligning credit-hour expectations with reality: Cluster analysis of study organization in e-textbook logs"

description: De-identified derived datasets (student-level aggregates, per-lecture features, session-level durations) plus a synthetic event-log sample supporting the manuscript “Aligning credit-hour expectations with reality: Cluster analysis of study organization in e-textbook logs.” Raw clickstream logs are not shared due to re-identification risk. Key variables: total_sec (sec), uniq_pages (count), max_sess (sec), offset (min), spread (days), cluster (1–4). Time zone: Asia/Tokyo; timestamps: ISO 8601.
DOI: 10.17632/dzxb6jvppd
title: Modeling Marine Atmospheric PM2.5 Concentrations over the Bohai Sea Using a Deep Neural Network: Spatiotemporal Variations under China's Emission Reduction Policies

description: This dataset supports the research titled "Modeling Marine Atmospheric PM2.5 Concentrations over the Bohai Sea Using a Deep Neural Network: Spatiotemporal Variations under China's Emission Reduction Policies", with a focus on atmospheric PM2.5 concentrations over the Bohai Sea (37°N - 41°N, 117°E - 122°E) during 2015–2023. It includes raw observational data, model input/output data, and model files, all aimed at ensuring the reproducibility of research results related to deep learning-based marine atmospheric pollutant monitoring and emission reduction policy assessment.
(1) Model Input Data
Data were sourced from the China National Environmental Monitoring Center (PM2.5; hourly), MERRA-2 reanalysis dataset (AOD; hourly, 0.5°×0.625°), and ERA5 reanalysis dataset (T, DEW, U, V; hourly, 0.25°×0.25°). Covering the period 2015–2023, the data were processed via 24-hour averaging and spatial interpolation to form the final dataset.
 (2) Model Output Data 
This consists of estimated atmospheric PM2.5 concentrations over the Bohai Sea output by the PM2.5-DNN model, with a spatiotemporal resolution of daily and 0.1°×0.1°.
(3) Datou Mountain Station Observational Data 
PM2.5 observational data provided by the Shandong Provincial Environmental Monitoring Center, used for model validation and comparison. The temporal resolution is daily, covering the periods 2019–2020 and 2022–2023.
(4) Test Set Data
Randomly selected 10% of the PM2.5 data from the model input, used for model validation.
(5) Shipborne Observation Data
Collected during aerosol sampling campaigns aboard the 'Dongfanghong 2' scientific research vessel in July 2016 and September 2017. These campaigns utilized KC-1000 high-volume samplers (Qingdao Laoshan Electronics Co., Ltd.), equipped with AN-200 Andersen impactors and Whatman 41 filters, to collect total suspended particles (TSP) and PM2.5.
 (6) Reanalysis Comparison Data
PM2.5 data derived from the EAC4 and MERRA-2 reanalysis datasets. The original temporal resolution is hourly, with original spatial resolutions of 0.75°×0.75° (EAC4) and 0.5°×0.625° (MERRA-2), covering 2015–2023. The data were processed via 24-hour averaging and spatial interpolation to form the final dataset.
(7) WRF-CMAQ Comparison Data
Data obtained from the WRF-CMAQ model outputs. The original temporal resolution is hourly, with an original spatial resolution of 12 km. The data were processed via 24-hour averaging and spatial interpolation to form the final dataset.
(8) Model
A Python-based model program built on the TensorFlow + Keras framework.
Full Names and Units of Variables Involved in the Above Data:
- AOD: Aerosol Optical Depth
- T: Air Temperature (K)
- DEW: Dew Point Temperature (K)
- U/V: U/V-Component of the Wind (m s⁻¹)
- PM2.5 (μg m⁻³)
DOI: 10.15468/dl.mfm7cp
title: Occurrence Download

description: A dataset containing 17178 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Poecile montanus",
 "Year 2010-2025"
 ]
}

 The dataset includes 17178 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015433-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/dzxb6jvppd.1
title: Modeling Marine Atmospheric PM2.5 Concentrations over the Bohai Sea Using a Deep Neural Network: Spatiotemporal Variations under China's Emission Reduction Policies

description: This dataset supports the research titled "Modeling Marine Atmospheric PM2.5 Concentrations over the Bohai Sea Using a Deep Neural Network: Spatiotemporal Variations under China's Emission Reduction Policies", with a focus on atmospheric PM2.5 concentrations over the Bohai Sea (37°N - 41°N, 117°E - 122°E) during 2015–2023. It includes raw observational data, model input/output data, and model files, all aimed at ensuring the reproducibility of research results related to deep learning-based marine atmospheric pollutant monitoring and emission reduction policy assessment.
(1) Model Input Data
Data were sourced from the China National Environmental Monitoring Center (PM2.5; hourly), MERRA-2 reanalysis dataset (AOD; hourly, 0.5°×0.625°), and ERA5 reanalysis dataset (T, DEW, U, V; hourly, 0.25°×0.25°). Covering the period 2015–2023, the data were processed via 24-hour averaging and spatial interpolation to form the final dataset.
 (2) Model Output Data 
This consists of estimated atmospheric PM2.5 concentrations over the Bohai Sea output by the PM2.5-DNN model, with a spatiotemporal resolution of daily and 0.1°×0.1°.
(3) Datou Mountain Station Observational Data 
PM2.5 observational data provided by the Shandong Provincial Environmental Monitoring Center, used for model validation and comparison. The temporal resolution is daily, covering the periods 2019–2020 and 2022–2023.
(4) Test Set Data
Randomly selected 10% of the PM2.5 data from the model input, used for model validation.
(5) Shipborne Observation Data
Collected during aerosol sampling campaigns aboard the 'Dongfanghong 2' scientific research vessel in July 2016 and September 2017. These campaigns utilized KC-1000 high-volume samplers (Qingdao Laoshan Electronics Co., Ltd.), equipped with AN-200 Andersen impactors and Whatman 41 filters, to collect total suspended particles (TSP) and PM2.5.
 (6) Reanalysis Comparison Data
PM2.5 data derived from the EAC4 and MERRA-2 reanalysis datasets. The original temporal resolution is hourly, with original spatial resolutions of 0.75°×0.75° (EAC4) and 0.5°×0.625° (MERRA-2), covering 2015–2023. The data were processed via 24-hour averaging and spatial interpolation to form the final dataset.
(7) WRF-CMAQ Comparison Data
Data obtained from the WRF-CMAQ model outputs. The original temporal resolution is hourly, with an original spatial resolution of 12 km. The data were processed via 24-hour averaging and spatial interpolation to form the final dataset.
(8) Model
A Python-based model program built on the TensorFlow + Keras framework.
Full Names and Units of Variables Involved in the Above Data:
- AOD: Aerosol Optical Depth
- T: Air Temperature (K)
- DEW: Dew Point Temperature (K)
- U/V: U/V-Component of the Wind (m s⁻¹)
- PM2.5 (μg m⁻³)
DOI: 10.17632/b6t9h9vz9s.2
title: Comparative analysis of the fatty acid profiles and MFGM proteome in human and small ruminant colostrum and mature milk using data-independent acquisition for targeted infant nutrition improvement

description: Supplementary tables and supplementary figures
DOI: 10.5517/ccdc.csd.cc2m52hd
title: CCDC 2417953: Experimental Crystal Structure Determination

description: Related Article: Shubham Ajaykumar Rajput, Sudhadevi Antharjanam, Aravind Kumar Chandiran|2025|J.Mater.Chem.C|13|18856|doi:10.1039/D5TC01454A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2m52jf
title: CCDC 2417954: Experimental Crystal Structure Determination

description: Related Article: Shubham Ajaykumar Rajput, Sudhadevi Antharjanam, Aravind Kumar Chandiran|2025|J.Mater.Chem.C|13|18856|doi:10.1039/D5TC01454A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.17632/kpxp5zkh5f
title: From Human Heuristics to Human–AI Teams

description: This data repository contains data for the manuscript submitted for publication: bin Kamruddin, A., Lam, C., Ghanem, S., Patil, G., Musolesi, M., di Bernardo, M., & Richardson, M. J. (n.d.). From human heuristics to human–AI teams: Modeling multiagent first-person herding using dynamical perceptual–motor primitives.
DOI: 10.17632/kpxp5zkh5f.2
title: From Human Heuristics to Human–AI Teams

description: This data repository contains data for the manuscript submitted for publication: bin Kamruddin, A., Lam, C., Ghanem, S., Patil, G., Musolesi, M., di Bernardo, M., & Richardson, M. J. (n.d.). From human heuristics to human–AI teams: Modeling multiagent first-person herding using dynamical perceptual–motor primitives.
DOI: 10.6084/m9.figshare.28500761
title: Data for: <b>Laser-based pulse oximetry eliminates pigmentation effects on oxygen saturation measurements</b>

description: The data provided here are for the article: <b>Laser-based pulse oximetry eliminates pigmentation effects on oxygen saturation measurements</b>These are the data for a benchtop study and for a clinical study on the effects of pigmentation on LED-based pulse oximeters and on a unique prototype laser-based pulse oximeter.For further information on these data please see the included file Readme.docx.