cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.31275
title: Dataset on pore evolution and mechanical performance of 3D printed CCF/PEEK in vacuum versus atmospheric environments
title: Dataset on pore evolution and mechanical performance of 3D printed CCF/PEEK in vacuum versus atmospheric environments

description: This dataset comprises raw and processed data supporting the investigation into the mechanical performance and pore evolution of 3D-printed continuous carbon fiber-reinforced polyether ether ketone composites under vacuum and atmospheric environments. Prepreg filaments with varying impregnation qualities were fabricated using a custom-built impregnation device. A Taguchi experimental design was employed to systematically evaluate the effects of nozzle temperature, printing speed, layer thickness, and impregnation quality under both conditions.​The dataset includes:​​​Raw Material and Prepreg Characterization:​​ Thermogravimetric analysis data and fiber volume fractions of prepreg filaments with different impregnation qualities.​Processing Parameters:​​ Full factorial parameter sets based on the Taguchi method, including environment, temperature, speed, layer thickness, etc.​Mechanical Property Data:​​ Tensile strength, elastic modulus, and other relevant data for specimens printed under all experimental conditions.​Structural and Morphological Analysis:​​ Crystallinity data obtained from DSC; pore morphology, distribution, size, and surface roughness data acquired via optical microscopy and CT scanning.​Theoretical Model Parameters:​​ Key parameters and calculation results supporting the proposed pore evolution mechanism and the theoretical model for predicting fiber volume fraction.
description: This dataset comprises raw and processed data supporting the investigation into the mechanical performance and pore evolution of 3D-printed continuous carbon fiber-reinforced polyether ether ketone composites under vacuum and atmospheric environments. Prepreg filaments with varying impregnation qualities were fabricated using a custom-built impregnation device. A Taguchi experimental design was employed to systematically evaluate the effects of nozzle temperature, printing speed, layer thickness, and impregnation quality under both conditions.​The dataset includes:​​​Raw Material and Prepreg Characterization:​​ Thermogravimetric analysis data and fiber volume fractions of prepreg filaments with different impregnation qualities.​Processing Parameters:​​ Full factorial parameter sets based on the Taguchi method, including environment, temperature, speed, layer thickness, etc.​Mechanical Property Data:​​ Tensile strength, elastic modulus, and other relevant data for specimens printed under all experimental conditions.​Structural and Morphological Analysis:​​ Crystallinity data obtained from DSC; pore morphology, distribution, size, and surface roughness data acquired via optical microscopy and CT scanning.​Theoretical Model Parameters:​​ Key parameters and calculation results supporting the proposed pore evolution mechanism and the theoretical model for predicting fiber volume fraction.
DOI: 10.57760/sciencedb.20810
title: qualitative data about students' aspirations
title: qualitative data about students' aspirations

description: These are written sheets with data about students' life projects from a comprehensive school of academic and vocational tracks.
description: These are written sheets with data about students' life projects from a comprehensive school of academic and vocational tracks.
DOI: 10.57760/sciencedb.31265
title: Zinc ferrite-based materials prepared via different methods for phosphorus adsorption
title: Zinc ferrite-based materials prepared via different methods for phosphorus adsorption

description: This repository contains raw and processed data associated with the study "Phosphate removal from water using zinc ferrite-based materials prepared via different methods: insights into adsorption performance and reusability"The dataset includes:X-ray diffraction (XRD) patterns of synthesized materialsTGABET isotherms
description: This repository contains raw and processed data associated with the study "Phosphate removal from water using zinc ferrite-based materials prepared via different methods: insights into adsorption performance and reusability"The dataset includes:X-ray diffraction (XRD) patterns of synthesized materialsTGABET isotherms
DOI: 10.5281/zenodo.17608117
title: 2010-2019 climate data for energy project

description: Selection of relevant atmospheric variables for energy production in the periodi 2010-2019 in France
DOI: 10.5281/zenodo.17608118
title: 2010-2019 climate data for energy project

description: Selection of relevant atmospheric variables for energy production in the periodi 2010-2019 in France
DOI: 10.57760/sciencedb.24484
title: DRAM catch up project
title: DRAM catch up project

description: patent data on DRAM uspto grant patent and citation DataThis is the research data from Junguo Shi's team, School of Economics and Finance, Jiangsu UniversityDr. Samuel join this topicDram is a very dynamic and important sector in recent decades and will be more important in the fllowing decades.
description: patent data on DRAM uspto grant patent and citation DataThis is the research data from Junguo Shi's team, School of Economics and Finance, Jiangsu UniversityDr. Samuel join this topicDram is a very dynamic and important sector in recent decades and will be more important in the fllowing decades.
DOI: 10.15468/dl.68eusb
title: Occurrence Download

description: A dataset containing 1865862 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is South Africa",
 "OccurrenceStatus is Present",
 "TaxonKey is Tracheophyta"
 ]
}

 The dataset includes 1865862 records from 289 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032856-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ebv738
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Epipremnum pinnatum (L.) Engl.",
 "Country is Lao People’s Democratic Republic"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010720-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15472302
title: Input values and resulting p-values of KO classes with significantly predicted changes between the two recharging strategies

description: The predicted prevalence for the different KO classes among systems and recharging strategies were used to infer possible taxonomic changes resulting in variations in the metabolic functions at the community level. A complete analysis of the distribution of taxa among samples will be published elsewhere.
DOI: 10.5281/zenodo.15472303
title: Input values and resulting p-values of KO classes with significantly predicted changes between the two recharging strategies

description: The predicted prevalence for the different KO classes among systems and recharging strategies were used to infer possible taxonomic changes resulting in variations in the metabolic functions at the community level. A complete analysis of the distribution of taxa among samples will be published elsewhere.
DOI: 10.15468/dl.2a384w
title: Occurrence Download

description: A dataset containing 139006 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Euphilotes enoptes (Boisduval, 1852), Eumecomera cyanipennis (Horn, 1870), Lytta comans Selander, 1960, Anasimyia perfidiosus (Hunter, 1897), Geminaria canalis (Coquillett, 1887), Perdita interrupta Cresson, 1878, Lytta stygica (LeConte, 1851), Amartus tinctus (Mannerheim, 1843), Micralictoides ruficaudus (Michener, 1937), Eschscholzia californica Cham., Chrysobothris mastersii Macleay, 1872, Anilara anthaxoides Théry, 1911, Phyllolyma mituliformis Taylor, 1990, Glycaspis quornensis Moore, 1970, Anoeconeossa morgani Taylor, 1987, Amorbus robustus Mayr, 1865, Paralaea taggorum, Platyobria maddeni Taylor, 1987, Schedotrioza tasmaniensis (Froggatt, 1903), Cryptoneossa vulgaris Taylor, 1990, Blepharocosta subsolana Taylor, 1992, Anoeconeossa copidiformis Taylor, 1987, Paralaea beggaria (Guenée, 1857), Katipo rubrivenosa (Kirkaldy, 1906), Mnesampela privata (Guenée, 1857), Anoeconeossa communis Taylor, 1987, Thaumastocoris freomooreae Noack, Cassis & Rose, 2011, Coccidoctonus psyllae (Riek, 1962), Ophelimus eucalypti (Gahan, 1922), Leptocybe invasa Fisher & La Salle, 2004, Anoeconeossa fuscipennis (Froggatt, 1901), Eurymela distincta Signoret, 1850, Glycaspis granulata (Froggatt, 1901), Aphalara tecta Maskell, 1898, Glycaspis amydra Moore, 1970, Mnesampela lenaea Meyrick, 1892, Amorbus rubiginosus (Guérin-Méneville, 1831), Glycaspis brimblecombei Moore, 1964, Perthida glyphopa Common, 1969, Cleora dargei (Herbulot, 1961), Xanthisthisa nigrocumulata (Warren, 1902), Streblote diplocyma (Hampson, 1909), Parasa ananii Karsch, 1896, Metanastria hyrtaca (Cramer, 1782), Polytelis swainsonii (Desmarest, 1826), Leprosa milga Kim & La Salle, Isoplatoides westralianus (Girault, 1939), Cirrospilus occipitis Girault, 1928, Nambouria ramulorum Boucek, 1988, Psyllaephagus uncinatus Riek, 1962)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 139006 records from 711 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009624-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16960993
title: Dataset for "Determinants of Digital Workspace Adoption in Public Sector Auditing: Evidence from Indonesia"

description: Dataset ini berasal dari survei terhadap 488 auditor pemerintah di Indonesia mengenai faktor-faktor yang memengaruhi niat penggunaan (intention to use) ruang kerja digital berbasis cloud (Google Workspace). Survei dilakukan secara daring menggunakan kuesioner berbasis model UTAUT2. Semua data yang dipublikasikan di sini telah dianonimkan (tanpa identitas pribadi responden).
DOI: 10.5281/zenodo.16960994
title: Dataset for "Determinants of Digital Workspace Adoption in Public Sector Auditing: Evidence from Indonesia"

description: Dataset ini berasal dari survei terhadap 488 auditor pemerintah di Indonesia mengenai faktor-faktor yang memengaruhi niat penggunaan (intention to use) ruang kerja digital berbasis cloud (Google Workspace). Survei dilakukan secara daring menggunakan kuesioner berbasis model UTAUT2. Semua data yang dipublikasikan di sini telah dianonimkan (tanpa identitas pribadi responden).
DOI: 10.5281/zenodo.18312237
title: Supplementary data for MAD-SURF: a machine learning interatomic potential for molecular adsorption on coinage metal surfaces

description: This repository contains the data used to train the MAD-SURF potential, a machine learning interatomic potential based on the MACE-architecture tailored for the adsorption of molecules on coinage metals. The dataset has been acquired with a consistent DFT method: PBE with the Tkatchenko-Scheffler van der Waals correction employing C6 dipole-dipole dispersion coefficients specifically parametrized for surface screening. The dataset was acquired using a multi-source strategy to ensure structurally diverse data, including active learning for adsorption structures, molecular dynamics for distorted geometries, automated interaction site screening for intermolecular interactions, and normal mode sampling for intramolecular interactions. The repository also contains the structures and trajectories needed to produce the Figures in the corresponding MAD-SURF article, and finally, the trained model potentials. 

 

Brief description of file contents:



dataset.zip: contains large and and small training and test datasets for MAD-SURF

dataset_with_config_types.zip: contains the full dataset with annotated entries according to source type, i.e. molecular dynamics, bayesian optimization structure search, normal mode sampling, etc. Can be used to provide custom weights based on data type during (re)training.

models.zip: all of the potentials trained during this work. The MAD-SURF model used in the article is also uploaded here as MAD-SURF.model, corresponding to the same model as in models/finetuned/foundational_model/on_training_subset/

fig_3_aggregated_aromatic_hydrocarbons_cu111.zip: the relaxed structures of the hydrocarbon aggregates on Cu111.

fig_4_organic_monolayers.zip: the relaxed structures of the herringbone (HB) and brick wall (BW) monolayer phases of PTCDA and Pentacene on Cu111, Ag111 and Ag110.

fig_5_beta_cyclodextrin_au111.zip: the relaxed structures of the primary and secondary faces in both clockwise and counter-clockwise hydrogen bonding networks.

fig_6_Au_herringbone_reconstruction.zip: the LAMMPS input and output files for the relaxation of the Au111 herringbone reconstruction model, one with the bottom layer fixed and one where it is fully relaxed, as well 

fig_7_pentacene_large_scale_dynamics.zip: the LAMMPS input and output files for the large scale molecular dynamics simulations of the random tiling pentacene monolayer containing 118 pentacene molecules on a 13.27×13.71 nm^2 Cu111 substrate. The archive also contains the MAD-SURF model converted to LAMMPS type potential (.pt). However, it is recommended that the LAMMPS potential is recreated in the actual computing enviroment that is used.
DOI: 10.5281/zenodo.18312238
title: Supplementary data for MAD-SURF: a machine learning interatomic potential for molecular adsorption on coinage metal surfaces

description: This repository contains the data used to train the MAD-SURF potential, a machine learning interatomic potential based on the MACE-architecture tailored for the adsorption of molecules on coinage metals. The dataset has been acquired with a consistent DFT method: PBE with the Tkatchenko-Scheffler van der Waals correction employing C6 dipole-dipole dispersion coefficients specifically parametrized for surface screening. The dataset was acquired using a multi-source strategy to ensure structurally diverse data, including active learning for adsorption structures, molecular dynamics for distorted geometries, automated interaction site screening for intermolecular interactions, and normal mode sampling for intramolecular interactions. The repository also contains the structures and trajectories needed to produce the Figures in the corresponding MAD-SURF article, and finally, the trained model potentials. 

 

Brief description of file contents:



dataset.zip: contains large and and small training and test datasets for MAD-SURF

dataset_with_config_types.zip: contains the full dataset with annotated entries according to source type, i.e. molecular dynamics, bayesian optimization structure search, normal mode sampling, etc. Can be used to provide custom weights based on data type during (re)training.

models.zip: all of the potentials trained during this work. The MAD-SURF model used in the article is also uploaded here as MAD-SURF.model, corresponding to the same model as in models/finetuned/foundational_model/on_training_subset/

fig_3_aggregated_aromatic_hydrocarbons_cu111.zip: the relaxed structures of the hydrocarbon aggregates on Cu111.

fig_4_organic_monolayers.zip: the relaxed structures of the herringbone (HB) and brick wall (BW) monolayer phases of PTCDA and Pentacene on Cu111, Ag111 and Ag110.

fig_5_beta_cyclodextrin_au111.zip: the relaxed structures of the primary and secondary faces in both clockwise and counter-clockwise hydrogen bonding networks.

fig_6_Au_herringbone_reconstruction.zip: the LAMMPS input and output files for the relaxation of the Au111 herringbone reconstruction model, one with the bottom layer fixed and one where it is fully relaxed, as well 

fig_7_pentacene_large_scale_dynamics.zip: the LAMMPS input and output files for the large scale molecular dynamics simulations of the random tiling pentacene monolayer containing 118 pentacene molecules on a 13.27×13.71 nm^2 Cu111 substrate. The archive also contains the MAD-SURF model converted to LAMMPS type potential (.pt). However, it is recommended that the LAMMPS potential is recreated in the actual computing enviroment that is used.
DOI: 10.15468/dl.jpdb5j
title: Occurrence Download

description: A dataset containing 63 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Austria",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Epipogium aphyllum",
 "Year 2020-2026"
 ]
}

 The dataset includes 63 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007197-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sxjh2a
title: Occurrence Download

description: A dataset containing 5595 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Nettenchelys dionisi, Saxicola dacotiae)",
 "Country is Spain",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 5595 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007195-260120142942310/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.29859122.v6
title: A benchmark dataset for the Anaesthetist Rostering Problem

description: A comprehensive benchmark dataset for the Anaesthetist Rostering Problem (ARP), comprising 30 synthetic instances across three complexity levels.<br> DATASET FEATURES: • 30 instances (10 small, 10 medium, 10 large) • 84-day planning horizon (3 months × 28 days) • 17 locations (7 monthly on-call + 10 weekly office/evening) • 14 hard constraints + 14 soft constraints • Bi-level optimization structure (monthly → weekly rostering) • Standardized CSV format<br> STAFF COMPOSITION: • Small: 12 permanent staff (8 Junior + 4 Senior) • Medium: 23 permanent staff (14 Junior + 9 Senior) • Large: 41 permanent staff (23 Junior + 18 Senior)<br> VERSION 3.0 (January 2025) - CRITICAL UPDATE: This version implements feasibility-aware instance generation to guarantee solvability: • Minimum CCT (Consultant Cardiothoracic) qualified staff: ≥ 3 • Minimum SCT (Specialist Cardiothoracic) qualified staff: ≥ 2 • 100% Stage 1 feasibility verified with IBM CPLEX 22.1.1 and Google OR-Tools CP-SAT • Generated with SyntheticGenerator v5.0<br> Previous versions (v1, v2) contained instances where insufficient cardiothoracic-qualified staff could cause solver infeasibility. Version 3.0 resolves this limitation.<br> RELATED PUBLICATION: Abdullah, N., Ayob, M., Lam, M.C., Sabar, N.R. (2025). Advancing anaesthetist rostering quality: A practical approach toward fairness and efficiency. IEEE Access, 13, 10286-10303.
DOI: 10.5066/p1g8mvj8
title: Astrogeology Science Center Eugene Shoemaker Collection

description: A set of data releases from the Astrogeology Shoemaker collection. This work was funded through an NGGDPP award (2023-0017). They include unpublished works, maps and correspondence.
DOI: 10.15468/dl.gbx6w7
title: Occurrence Download

description: A dataset containing 472 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Phyllotis andium"
 ]
}

 The dataset includes 472 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007198-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2syax9
title: Occurrence Download

description: A dataset containing 546391 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Programme BioObs: observations naturalistes en milieux aquatiques-Observations de BioObs."
 ]
}

 The dataset includes 546391 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007162-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/jbx98yscmd
title: System for Rapid Analysis of Ionospheric Dynamics Based on GNSS TEC Signals

description: System for Rapid Analysis of Ionospheric Dynamics based on GNSS TEC Signals (S-RAID) performs downloading, parsing, and processing of Global Navigation Satellite System (GNSS) signal measurements and their geometry of observations, calculation of slant and vertical total electron contents (sTEC and vTEC) and subsequent visualization for selected band-passes of fluctuations with periods shorter than two hours. In a routine operation, the System processes 15/30 sec GNSS signal measurements over Continental United States (CONUS) from ~2700 stations. Raw GNSS signal measurements are collected from public archives, including The Crustal Dynamics Data Information System (CDDIS), EarthScope/UNAVCO, National Oceanic and Atmospheric Administration (NOAA), and Scripps Institution of Oceanography's Orbit and Permanent Array Center (SOPAC). The System is oriented towards rapid access to GNSS sTEC/vTEC data for the investigation of traveling ionospheric disturbances (TIDs) of various nature, from large scale TIDs to irregularities of ~10s of km and minutes of periods, in particular those driven by atmospheric acoustic and gravity wave dynamics. The details of data processing methodology are provided in the manuscript (1).

Currently, this archive provides an access to high-resolution visualization of processed vTEC mapped over CONUS for years 01/2017-12/2025 (Version 3 to the left - includes full archive).

The structure of the archive:
/YYYY/MM/DD/animation.mp4, where YYYY - year, MM - month, DD - day of month, animation.mp4 - temporally evolving visualization of processed vTEC (see Steps to Reproduce for the details of data processing methodology).

To reference the archive or the methodology for data processing, we suggest to:
(1) Cite the manuscript: Inchin, P. A., Deshpande, K. B., Egan, S., Lay, E. H., Obenberger, K. S., Zettergren, M. D., & Snively, J. B. (2025). Ionospheric disturbances in GNSS TEC data: SpaceX Falcon 9 deorbit maneuvers over CONUS in April–May 2024. Geophysical Research Letters, 52, e2024GL112364. https://doi.org/10.1029/2024GL112364
(2) Cite this archive by its DOI: 10.17632/jbx98yscmd.1, and/or

Being processed in an automated regime, the visualizations may contain errors and bugs and thus should be used with caution as is. If you encounter any issues or wish to obtain data for animation replication, contact P.A. Inchin pinchin@cpi.com, J.B. Snively snivelyj@erau.edu or M.D. Zettergren zettergm@erau.edu.

Research is supported by DARPA Cooperative Agreement HR00112120003. This work is approved for public release; distribution is unlimited. The content of the information does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.