cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/lmism8
title: Replication Data for: THE FIVE-MINUTE APGAR SCORE AND ADVERSE SHORT-TERM OUTCOMES IN NEONATES-A COHORT STUDY IN THE CLINICAL INFORMATION NETWORK HOSPITALS IN KENYA

description: This data contains information on neonates admitted to the newborn units in the various facilities within the Clinical Information Network (CIN) in Kenya between 2018-2022. It contains data on their demographics, clinical history, interventions and management in the newborn unit and outcomes at the end of the neonatal period. The data was used to find the association between the Apgar scores and associated adverse outcomes.
description: <strong>Data Access: </strong>Restricted

Access to these data requires submission of a formal request for consideration by our Data Governance Committee. 
<strong>How to request</strong>

Download and complete the <strong>data request form</strong>
 Email completed data request form to the Data Governance Committee at <strong>dgc@kemri-wellcome.org</strong>
DOI: 10.15468/dl.ufyrgc
title: Occurrence Download

description: A dataset containing 3457 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Amara fulva (O.F.Müller, 1776)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3457 records from 137 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008606-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sf56g5
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Oreobliton Durieu & Moq."
 ]
}

 The dataset includes 11 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008608-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ft6e34
title: Occurrence Download

description: A dataset containing 5087 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Spain, Italy, France, Croatia, Morocco, Libya, Israel, Cyprus, Türkiye, Greece, Albania, Montenegro, Slovenia)",
 "PublishingOrg is 28eb1a3f-1c15-4a95-931a-4af90ecb574d",
 "TaxonKey is Limonium"
 ]
}

 The dataset includes 5087 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014404-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18269789
title: Cunila incana Benth. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:45
DOI: 10.15468/dl.76cbud
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Oxytropis qitaiensis"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014405-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kkqnsy
title: Occurrence Download

description: A dataset containing 683 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Callichthys callichthys",
 "Country is Brazil",
 "HasCoordinate is true"
 ]
}

 The dataset includes 683 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014406-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17592007
title: Unfair Inequality in Education: A Benchmark for AI-Fairness Research

description: Unfair Inequality in Education: A Benchmark for AI-Fairness Research

This dataset proposes a novel benchmark specifically designed for AI fairness research in education. It can be used for challenging tasks aimed at improving students' performance and reducing dropout rates which are also discussed in the paper to emphasize significant research directions. By prioritizing fairness, this benchmark aims to foster the development of bias-free AI solutions, promoting equal educational access and outcomes for all students.

Structure

benchmark contains:



the proposed dataset (dataset.csv), 

the mask for dealing with missing values (missing_mask.csv), and





the meta-columns providing grouping criteria and sample weights for each student (meta_cols.csv).




raw_data includes:



the original dataset (original.csv), and

the intermediate stages of the pre-processing and validation pipelines (split, pre_processed, and validation).


res contains the documentation, including:



the transformation mapping each column of the original dataset to the proposed one, along with the missingness category and original text (meta_data_mapping.csv),

the value type and domains of each column of the proposed datasets (meta_data_stats.json), and





the statistical indices of the validation pipeline  (bias_preservation_results.json).




src contains the source code for running the pre-processing and corresponding analysis:



pre_processing and statscontain the code for the two corresponding tasks, and

pre_processing.py and split.py are two entry points.


Finally, Dockerfile and requirements.txt set up the environment for running the applications across multiple platforms and with Python, respectively.

The synthetic_data file contains a synthetic copy of the same length as the original data set.
DOI: 10.5281/zenodo.11171862
title: Unfair Inequality in Education: A Benchmark for AI-Fairness Research

description: Unfair Inequality in Education: A Benchmark for AI-Fairness Research

This dataset proposes a novel benchmark specifically designed for AI fairness research in education. It can be used for challenging tasks aimed at improving students' performance and reducing dropout rates which are also discussed in the paper to emphasize significant research directions. By prioritizing fairness, this benchmark aims to foster the development of bias-free AI solutions, promoting equal educational access and outcomes for all students.

Structure

benchmark contains:



the proposed dataset (dataset.csv), 

the mask for dealing with missing values (missing_mask.csv), and





the meta-columns providing grouping criteria and sample weights for each student (meta_cols.csv).




raw_data includes:



the original dataset (original.csv), and

the intermediate stages of the pre-processing and validation pipelines (split, pre_processed, and validation).


res contains the documentation, including:



the transformation mapping each column of the original dataset to the proposed one, along with the missingness category and original text (meta_data_mapping.csv),

the value type and domains of each column of the proposed datasets (meta_data_stats.json), and





the statistical indices of the validation pipeline  (bias_preservation_results.json).




src contains the source code for running the pre-processing and corresponding analysis:



pre_processing and statscontain the code for the two corresponding tasks, and

pre_processing.py and split.py are two entry points.


Finally, Dockerfile and requirements.txt set up the environment for running the applications across multiple platforms and with Python, respectively.

The synthetic_data file contains a synthetic copy of the same length as the original data set.
DOI: 10.5281/zenodo.18269346
title: Divergent Side-Chain Networks of the Mineralocorticoid Receptor Control Mutation-Altered Drug Response

description: This dataset contains the MD trajectories for the folowing project: Divergent Side-Chain Networks of the Mineralocorticoid Receptor Control Mutation-Altered Drug Response.The dataset contains the trajectories of simulations of the Mineralocorticoid receptor and its S810L mutation in complex with eplerenon and finerenon.Each complex was simulated in triplicates for 500 ns each and consits of 1.000 frames each.
DOI: 10.5281/zenodo.18269785
title: Dataset Questionnaire Integrating AI Techniques to Predict Tourist Satisfaction and Loyalty on Smart Tourism Platforms

description: This dataset contains respondents' answers AI-Based Personalization; Digital Service Quality; User–Platform Interaction; Tourist Experience Value; Tourist Loyalty Intention
DOI: 10.5281/zenodo.18269345
title: Divergent Side-Chain Networks of the Mineralocorticoid Receptor Control Mutation-Altered Drug Response

description: This dataset contains the MD trajectories for the folowing project: Divergent Side-Chain Networks of the Mineralocorticoid Receptor Control Mutation-Altered Drug Response.The dataset contains the trajectories of simulations of the Mineralocorticoid receptor and its S810L mutation in complex with eplerenon and finerenon.Each complex was simulated in triplicates for 500 ns each and consits of 1.000 frames each.
DOI: 10.5281/zenodo.18269784
title: Dataset Questionnaire Integrating AI Techniques to Predict Tourist Satisfaction and Loyalty on Smart Tourism Platforms

description: This dataset contains respondents' answers AI-Based Personalization; Digital Service Quality; User–Platform Interaction; Tourist Experience Value; Tourist Loyalty Intention
DOI: 10.15468/dl.j9cyrh
title: Occurrence Download

description: A dataset containing 358 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Diphasiastrum alpinum, Lycopodium alpinum, Diphasium alpinum)",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "Year is greater than or equal to 2010",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "CoordinateUncertaintyInMeters is less than or equal to 50",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 358 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014407-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r49m94
title: Occurrence Download

description: A dataset containing 179213 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Portulaca oleracea"
 ]
}

 The dataset includes 179213 records from 1760 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014285-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d7u8jm
title: Occurrence Download

description: A dataset containing 20850 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Otus senegalensis (Swainson, 1837)"
 ]
}

 The dataset includes 20850 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011701-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tvwzmh
title: Occurrence Download

description: A dataset containing 2461 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Agrimonia repens L."
 ]
}

 The dataset includes 2461 records from 125 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011702-250515123054153/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.30646157
title: FedGraphHE experimental data and preprocessed graph features

description: This repository contains the processed datasets used in the experiments of the manuscript “FedGraphHE: A privacy-preserving federated graph neural network framework with dynamic homomorphic encryption and robust aggregation”.The archive includes preprocessed versions of the Cora, CiteSeer and PubMed citation network benchmarks, as well as the derived data used for our ISIC 2020 dermoscopic image experiments. For the citation networks, we provide commonly used processed graph files and tensors that can be loaded directly for training and evaluation. For the ISIC 2020 setting, we share the image identifiers, labels, train/validation/test splits, feature representations and the graph structure constructed from these features.All underlying raw datasets (the ISIC 2020 Challenge data and the original Cora, CiteSeer and PubMed benchmarks) are publicly available from their official providers. The data in this repository are the corresponding processed versions used in our work and are intended to facilitate replication and reuse of the reported results.
DOI: 10.6084/m9.figshare.30646157.v1
title: FedGraphHE experimental data and preprocessed graph features

description: This repository contains the processed datasets used in the experiments of the manuscript “FedGraphHE: A privacy-preserving federated graph neural network framework with dynamic homomorphic encryption and robust aggregation”.The archive includes preprocessed versions of the Cora, CiteSeer and PubMed citation network benchmarks, as well as the derived data used for our ISIC 2020 dermoscopic image experiments. For the citation networks, we provide commonly used processed graph files and tensors that can be loaded directly for training and evaluation. For the ISIC 2020 setting, we share the image identifiers, labels, train/validation/test splits, feature representations and the graph structure constructed from these features.All underlying raw datasets (the ISIC 2020 Challenge data and the original Cora, CiteSeer and PubMed benchmarks) are publicly available from their official providers. The data in this repository are the corresponding processed versions used in our work and are intended to facilitate replication and reuse of the reported results.
DOI: 10.15468/dl.bu7brs
title: Occurrence Download

description: A dataset containing 2435 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ips acuminatus"
 ]
}

 The dataset includes 2435 records from 109 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041416-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mek6n3
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Gabarnaudia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 12 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041417-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.47nnbz
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-107.9688 22.34913, -107.8188 22.34913, -107.8188 22.49913, -107.9688 22.49913, -107.9688 22.34913))"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041419-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.392c23
title: Occurrence Download

description: A dataset containing 21439 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is France",
 "TaxonKey is Timon lepidus"
 ]
}

 The dataset includes 21439 records from 459 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041420-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17034/e314054a-1735-405f-9db6-d1a9b2131150
title: Dataset for "Direct Thermal Imaging of Domain Wall Hot Spots in LiNbO3"

description: This is the dataset associated with the publication: Lindsey R Lynch et al. "Direct Thermal Imaging of Domain Wall Hot Spots in LiNbO3" Small, e08603, 2025 (https://doi.org/10.1002/smll.202508603).

The data files are the raw and processed outputs of Scanning Thermal Microscopy measurements used to plot the spatial maps of temperature in Figure 2,3 and 4 of the main manuscript. The files are .ibw format (a proprietary format used by Wave Metric Igor Pro software for storing scanning probe microscopy data). The file are also supplied in plain text .txt format.

Abstract
Ferroelectric domain wall devices offer a promising route to low voltage, reconfigurable nanoelectronics by confining currents to nanoscale conducting interfaces within an insulating bulk. However, the potential for resistive heating and unregulated temperature increases due to domain wall conduction remains unexplored. Here, we employ scanning thermal microscopy to directly image hot spots in thin-film lithium niobate domain wall devices. Piezoresponse force microscopy shows that the hot spots correlate with nanodomain structure and thermal mapping reveals surface temperature rises of ~ 20 K at most, levels that are unlikely to negatively affect device performance. This is due to the moderate electrical conductivity of domain walls, their voltage-tunable erasure, and distributed current pathways, which inherently limit power dissipation and peak temperatures. Finite element electrothermal modelling indicates that domain walls behave as pseudo-planar heat sources, distinct from the filament-based heating typically observed in resistive switching oxides. These findings highlight the potential for domain wall devices as an energy-efficient, thermally stable platform for emerging memory and logic applications.
DOI: 10.5281/zenodo.17638813
title: The Planck Frequency as a Phase Boundary: How Anti-Phase Neutralization in $\hat{M}_\mu$ Dissolves Spacetime and Resolves UV Divergences in G-MaTT

description: Abstract

We show that in Generalized Mass as Twisted Time (G-MaTT), spacetime does not exist above the Planck frequency $\Omega_0 = c^5 / \hbar G$. At $f > \Omega_0$, phase oscillations become too rapid for stable topological knots to form in the emergent mass-torsional field $\hat{M}_\mu$ — not in the primordial potential $\mathcal{M}_\mu$. Desynchronization via the Twist–UnTwist (TUT) mechanism causes complete decoherence, destroying the phase coherence necessary for spatial geometry and temporal ordering. This resolves the UV divergence problem of quantum field theory not through regularization, but through geometric finiteness: no continuum exists above $\Omega_0$, and all divergences vanish because there is no smooth manifold to quantize.

Furthermore, we show that dark matter and dark energy are not invisible particles — they are geometric manifestations of decoherence:

Dark matter = desynchronized emergent configurations ($k \notin \mathcal{S}$) with non-zero $\mathcal{M}_\mu$ — they exert gravity via fractional entanglement but do not couple to photons,  Dark energy = vacuum expectation of the stress-energy tensor $\langle T_{\mu\nu} \rangle$ for branches whose $\hat{M}_\mu$-knots have lost phase coherence.

This is not speculation — it is the inevitable consequence of a pre-geometric ontology where geometry is derived from phase coherence. We predict that cosmic voids — regions of low $\nabla \times \hat{M}$ — will exhibit enhanced neutrino decoherence in DUNE, and that LISA will detect torsion-modulated gravitational waves from primordial $\hat{M}_\mu$-reconfigurations.
DOI: 10.5281/zenodo.17638814
title: The Planck Frequency as a Phase Boundary: How Anti-Phase Neutralization in $\hat{M}_\mu$ Dissolves Spacetime and Resolves UV Divergences in G-MaTT

description: Abstract

We show that in Generalized Mass as Twisted Time (G-MaTT), spacetime does not exist above the Planck frequency $\Omega_0 = c^5 / \hbar G$. At $f > \Omega_0$, phase oscillations become too rapid for stable topological knots to form in the emergent mass-torsional field $\hat{M}_\mu$ — not in the primordial potential $\mathcal{M}_\mu$. Desynchronization via the Twist–UnTwist (TUT) mechanism causes complete decoherence, destroying the phase coherence necessary for spatial geometry and temporal ordering. This resolves the UV divergence problem of quantum field theory not through regularization, but through geometric finiteness: no continuum exists above $\Omega_0$, and all divergences vanish because there is no smooth manifold to quantize.

Furthermore, we show that dark matter and dark energy are not invisible particles — they are geometric manifestations of decoherence:

Dark matter = desynchronized emergent configurations ($k \notin \mathcal{S}$) with non-zero $\mathcal{M}_\mu$ — they exert gravity via fractional entanglement but do not couple to photons,  Dark energy = vacuum expectation of the stress-energy tensor $\langle T_{\mu\nu} \rangle$ for branches whose $\hat{M}_\mu$-knots have lost phase coherence.

This is not speculation — it is the inevitable consequence of a pre-geometric ontology where geometry is derived from phase coherence. We predict that cosmic voids — regions of low $\nabla \times \hat{M}$ — will exhibit enhanced neutrino decoherence in DUNE, and that LISA will detect torsion-modulated gravitational waves from primordial $\hat{M}_\mu$-reconfigurations.
DOI: 10.5281/zenodo.17339272
title: Full Crystallographic Imaging of Hexagonal Boron Nitride Monolayers with Phonon-Enhanced Sum-Frequency Microscopy - Experimental Data

description: This is a data repository for the publication

Full Crystallographic Imaging of Hexagonal Boron Nitride Monolayerswith Phonon-Enhanced Sum-Frequency Microscopy

Niclas S. Mueller, Alexander P. Fellows, Ben John, Andrew E. Naclerio, Christian Carbogno,Katayoun Gharagozloo-Hubmann, Damián Baláž, Ryan A. Kowalski, Hendrik H. Heenen, ChristophScheurer, Karsten Reuter, Joshua D. Caldwell, Martin Wolf, Piran R. Kidambi, Martin Thämer,Alexander Paarmann

published in Advanced Materials

DOI: https://doi.org/10.1002/adma.202510124

It contains the data of all main figures. The repository is organized into subfolders named after the labels of the figures. The content is described by the captions of the figures in the manuscript.
DOI: 10.5281/zenodo.17339273
title: Full Crystallographic Imaging of Hexagonal Boron Nitride Monolayers with Phonon-Enhanced Sum-Frequency Microscopy - Experimental Data

description: This is a data repository for the publication

Full Crystallographic Imaging of Hexagonal Boron Nitride Monolayerswith Phonon-Enhanced Sum-Frequency Microscopy

Niclas S. Mueller, Alexander P. Fellows, Ben John, Andrew E. Naclerio, Christian Carbogno,Katayoun Gharagozloo-Hubmann, Damián Baláž, Ryan A. Kowalski, Hendrik H. Heenen, ChristophScheurer, Karsten Reuter, Joshua D. Caldwell, Martin Wolf, Piran R. Kidambi, Martin Thämer,Alexander Paarmann

published in Advanced Materials

DOI: https://doi.org/10.1002/adma.202510124

It contains the data of all main figures. The repository is organized into subfolders named after the labels of the figures. The content is described by the captions of the figures in the manuscript.