cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/dddwx5wvnx.1
title: Usability and Clinical Performance of a Low-Cost 3D-Printed Video Laryngoscope: A Mixed-Methods Evaluation

description: This study demonstrates that a low-cost, 3D-printed videolaryngoscope can achieve usability and safety outcomes comparable to a commercial gold-standard device in both simulated and clinical usability environments. It also introduces a replicable, structured evaluation model aligned with international human factors and regulatory standards.
DOI: 10.17632/nd5jzp3p5r
title: Artificial pore networks with varying inter-pore flow variability

description: This dataset comprises detailed information on pore networks characterized by diverse inter-pore flow variability. The data files are stored in the .pnm format, which is defined by the OpenPNM framework (version 2.6.1). To work with this dataset, users are required to read and process the data using the OpenPNM library within a Python environment. Additionally, a Python script is provided to facilitate the reading of the data and the calculation of the inter-pore flow variability index (denoted as chi). Before executing the script, please ensure that the necessary dependencies are installed using the following command:
pip install openpnm==2.6.1
DOI: 10.15468/dl.esmayb
title: Occurrence Download

description: A dataset containing 31487 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "OccurrenceStatus is Present",
 "TaxonKey is Aquila fasciata"
 ]
}

 The dataset includes 31487 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049561-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/nd5jzp3p5r.2
title: Artificial pore networks with varying inter-pore flow variability

description: This dataset comprises detailed information on pore networks characterized by diverse inter-pore flow variability. The data files are stored in the .pnm format, which is defined by the OpenPNM framework (version 2.6.1). To work with this dataset, users are required to read and process the data using the OpenPNM library within a Python environment. Additionally, a Python script is provided to facilitate the reading of the data and the calculation of the inter-pore flow variability index (denoted as chi). Before executing the script, please ensure that the necessary dependencies are installed using the following command:
pip install openpnm==2.6.1
DOI: 10.17632/8mdb9xfbnx
title: Lung CT Radiomics Dataset of Clinically Healthy Adults

description: This dataset contains structured lung CT radiomics features from 100 clinically healthy adults acquired on a single scanner using a homogeneous routine chest CT protocol. Lungs were segmented with TotalSegmentator to generate anatomically consistent ROIs: individual lobes, left lung, right lung, and both lungs combined. Radiomics features were extracted with PyRadiomics using a fixed, fully documented configuration under a 2×2 design: two attenuation ranges (raw: −1000 to 200 HU; parenchyma-focused: −950 to 0 HU) and two anatomical mask modes (including intrapulmonary vessels and airways vs parenchyma-only). The dataset provides feature tables with more than 100 first-order, shape, and texture descriptors per ROI, accompanied by anonymized demographics, a detailed data dictionary, a README file, and the Python extraction script with the full PyRadiomics settings. This resource is intended for methodological benchmarking, exploring feature stability across windows and mask definitions, and constructing normative reference ranges for studies of diffuse and region-predominant pulmonary diseases. Raw DICOM/NIfTI images are not distributed due to legal and ethical constraints.
DOI: 10.17632/8mdb9xfbnx.1
title: Lung CT Radiomics Dataset of Clinically Healthy Adults

description: This dataset contains structured lung CT radiomics features from 100 clinically healthy adults acquired on a single scanner using a homogeneous routine chest CT protocol. Lungs were segmented with TotalSegmentator to generate anatomically consistent ROIs: individual lobes, left lung, right lung, and both lungs combined. Radiomics features were extracted with PyRadiomics using a fixed, fully documented configuration under a 2×2 design: two attenuation ranges (raw: −1000 to 200 HU; parenchyma-focused: −950 to 0 HU) and two anatomical mask modes (including intrapulmonary vessels and airways vs parenchyma-only). The dataset provides feature tables with more than 100 first-order, shape, and texture descriptors per ROI, accompanied by anonymized demographics, a detailed data dictionary, a README file, and the Python extraction script with the full PyRadiomics settings. This resource is intended for methodological benchmarking, exploring feature stability across windows and mask definitions, and constructing normative reference ranges for studies of diffuse and region-predominant pulmonary diseases. Raw DICOM/NIfTI images are not distributed due to legal and ethical constraints.
DOI: 10.17632/cv72xsz6yf
title: Dataset for Efficiency Analysis and Identification of Critical Success Factors in the Development of National Firepower
DOI: 10.17632/cv72xsz6yf.1
title: Dataset for Efficiency Analysis and Identification of Critical Success Factors in the Development of National Firepower
DOI: 10.15468/dl.cxtdqf
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is ITA.15_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Asplenium adiantum-nigrum adiantum-nigrum"
 ]
}

 The dataset includes 12 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049563-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/ghwfsdshv2
title: Predictive chatbot for student success: source code and database schema

description: This dataset contains the full source code, cron job scripts, and database schema used in the study “Early detection and personalized academic support using a predictive chatbot for student success” (submitted to PeerJ Computer Science). The system integrates a high-performance LightGBM predictive model with an AI-powered WhatsApp® chatbot based on the GPT-4o-mini model to identify at-risk students and deliver early, personalized academic support.

The repository includes:
• Node.js backend code for the chatbot, implemented using the Baileys WhatsApp Web API, Prisma ORM for PostgreSQL, and the OpenAI API (GPT-4o-mini) for conversational responses and semantic search over course syllabi.
• Automation scripts (cron jobs) that periodically trigger the prediction process, read the academic management database, and update the table of at-risk students used by the chatbot for proactive outreach.
• The complete SQL schema of the institutional database tables involved in the predictive pipeline and chatbot integration, including the structure of the enrollment, grades, and chatbot status tables.
• Configuration and documentation files (README) describing the required software versions, environment variables, and step-by-step instructions to deploy the system in a new institutional context.

For ethical and legal reasons, no real student records are included in this dataset. Instead, we provide the full database schema and example configuration files so that other researchers can adapt the code to their own institutional data while preserving student privacy. This dataset is intended to support transparency, reproducibility, and reuse of the proposed predictive-chatbot architecture in higher education settings.
DOI: 10.17632/ghwfsdshv2.1
title: Predictive chatbot for student success: source code and database schema

description: This dataset contains the full source code, cron job scripts, and database schema used in the study “Early detection and personalized academic support using a predictive chatbot for student success” (submitted to PeerJ Computer Science). The system integrates a high-performance LightGBM predictive model with an AI-powered WhatsApp® chatbot based on the GPT-4o-mini model to identify at-risk students and deliver early, personalized academic support.

The repository includes:
• Node.js backend code for the chatbot, implemented using the Baileys WhatsApp Web API, Prisma ORM for PostgreSQL, and the OpenAI API (GPT-4o-mini) for conversational responses and semantic search over course syllabi.
• Automation scripts (cron jobs) that periodically trigger the prediction process, read the academic management database, and update the table of at-risk students used by the chatbot for proactive outreach.
• The complete SQL schema of the institutional database tables involved in the predictive pipeline and chatbot integration, including the structure of the enrollment, grades, and chatbot status tables.
• Configuration and documentation files (README) describing the required software versions, environment variables, and step-by-step instructions to deploy the system in a new institutional context.

For ethical and legal reasons, no real student records are included in this dataset. Instead, we provide the full database schema and example configuration files so that other researchers can adapt the code to their own institutional data while preserving student privacy. This dataset is intended to support transparency, reproducibility, and reuse of the proposed predictive-chatbot architecture in higher education settings.
DOI: 10.17632/295ntk8vd5
title: Data for: Subnational Impacts of Chinese Education Sector Development Aid on Youth Educational Attainment in Africa

description: This paper investigates the impacts of Chinese education aid on African youth’s secondary and tertiary education attainment. It harmonizes 92 Demographic and Health Survey (DHS) datasets from 27 African countries with AidData’s geocoded data on 2,580 Chinese projects across Africa between 2000 and 2021. The study draws on the education production function theory and employs a difference-in-differences estimator that addresses endogeneity by comparing differences between active and pipeline projects. It finds that proximity to active Chinese education sector projects significantly improves African youth secondary and tertiary school enrolment and completion, with tertiary-level and non-infrastructure projects exhibiting the strongest effects. A causal mediation analysis demonstrates that the aid effect is mediated via household income, rather than infrastructure. Moreover, social and economic sector aid projects exhibit (in)direct spillover effects. Lastly, the paper finds that a selection bias exists, as wealthy and urban areas possess a comparative advantage vis-à-vis exposure to Chinese aid.

The replication package is organized into three subfolders, each containing the materials required to reproduce the tables and figures presented in the paper. The replication package leverages information from diverse databases, presenting raw and synthetic (randomly generated) data due to some restrictions. For instance, since sharing any DHS micro-level data is restricted, either directly or within any tool/dashboard, several variables are represented using synthetic data.
DOI: 10.17632/295ntk8vd5.1
title: Data for: Subnational Impacts of Chinese Education Sector Development Aid on Youth Educational Attainment in Africa

description: This paper investigates the impacts of Chinese education aid on African youth’s secondary and tertiary education attainment. It harmonizes 92 Demographic and Health Survey (DHS) datasets from 27 African countries with AidData’s geocoded data on 2,580 Chinese projects across Africa between 2000 and 2021. The study draws on the education production function theory and employs a difference-in-differences estimator that addresses endogeneity by comparing differences between active and pipeline projects. It finds that proximity to active Chinese education sector projects significantly improves African youth secondary and tertiary school enrolment and completion, with tertiary-level and non-infrastructure projects exhibiting the strongest effects. A causal mediation analysis demonstrates that the aid effect is mediated via household income, rather than infrastructure. Moreover, social and economic sector aid projects exhibit (in)direct spillover effects. Lastly, the paper finds that a selection bias exists, as wealthy and urban areas possess a comparative advantage vis-à-vis exposure to Chinese aid.

The replication package is organized into three subfolders, each containing the materials required to reproduce the tables and figures presented in the paper. The replication package leverages information from diverse databases, presenting raw and synthetic (randomly generated) data due to some restrictions. For instance, since sharing any DHS micro-level data is restricted, either directly or within any tool/dashboard, several variables are represented using synthetic data.
DOI: 10.5281/zenodo.17816134
title: Radio-frequency charge detection on graphene electron-hole double quantum dots

description: This repository contains the experimental data and the scripts for evaluating the data of the publication "Radio-frequency charge detection on grapheneelectron-hole double quantum dots".
DOI: 10.5281/zenodo.17816133
title: Radio-frequency charge detection on graphene electron-hole double quantum dots

description: This repository contains the experimental data and the scripts for evaluating the data of the publication "Radio-frequency charge detection on grapheneelectron-hole double quantum dots".
DOI: 10.17632/wz934888wc
title: Patterns and Pitfalls: Dermoscopic Differentiation of Early-Stage Mycosis Fungoides, Atopic Dermatitis, and Psoriasis

description: Patterns and Pitfalls: Dermoscopic Differentiation of Early-Stage Mycosis Fungoides, Atopic Dermatitis, and Psoriasis – Supplementary Table and Figures
DOI: 10.6084/m9.figshare.30870705
title: The Defense System Optimizer (DSO) model: a new data-analysis technique to support volleyball coaches’ decision-making

description: Since the emergence of DataVolley, the use of new technologies giving support to coaches and scouters has gained sympathy among volleyball decision-makers, becoming an essential tool to analyse the performance of a team. In this work, we construct a maximal coverage model to understand how a volleyball defensive system works, in terms of the optimal configuration of blockers and defenders to play and their location on the court under an opponent attack. With this in mind, we call it the “Defense System Optimizer (DSO) model.” In order to simulate feasibly the studied scenario, the DSO model involves parameters about the coach strategy, players’ performance and skills, and physical measures. We tested the model mixing simulated parameters and real data from high-level male-professional players of the Mexico’s national team. The results of 100 instances analysed in different scenarios confirm the model convergence, and permit to identify optimal formations and patterns of selected players in dependence of both the input parameters and the efficiency of the players, in reasonable computational times (&lt;5 s). This positions the DSO model as a multi-purpose tool able to reproduce realistic defense systems, which motivates to explore specific scenarios in real-time games, training and scouting of players.
DOI: 10.6084/m9.figshare.30870705.v1
title: The Defense System Optimizer (DSO) model: a new data-analysis technique to support volleyball coaches’ decision-making

description: Since the emergence of DataVolley, the use of new technologies giving support to coaches and scouters has gained sympathy among volleyball decision-makers, becoming an essential tool to analyse the performance of a team. In this work, we construct a maximal coverage model to understand how a volleyball defensive system works, in terms of the optimal configuration of blockers and defenders to play and their location on the court under an opponent attack. With this in mind, we call it the “Defense System Optimizer (DSO) model.” In order to simulate feasibly the studied scenario, the DSO model involves parameters about the coach strategy, players’ performance and skills, and physical measures. We tested the model mixing simulated parameters and real data from high-level male-professional players of the Mexico’s national team. The results of 100 instances analysed in different scenarios confirm the model convergence, and permit to identify optimal formations and patterns of selected players in dependence of both the input parameters and the efficiency of the players, in reasonable computational times (&lt;5 s). This positions the DSO model as a multi-purpose tool able to reproduce realistic defense systems, which motivates to explore specific scenarios in real-time games, training and scouting of players.
DOI: 10.17632/wz934888wc.1
title: Patterns and Pitfalls: Dermoscopic Differentiation of Early-Stage Mycosis Fungoides, Atopic Dermatitis, and Psoriasis

description: Patterns and Pitfalls: Dermoscopic Differentiation of Early-Stage Mycosis Fungoides, Atopic Dermatitis, and Psoriasis – Supplementary Table and Figures
DOI: 10.15468/dl.hd86p6
title: Occurrence Download

description: A dataset containing 1546 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((150.839124 -30.285676, 150.802080 -30.246895, 150.752539 -30.246895, 150.789570 -30.285676, 150.839124 -30.285676))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2015",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 1546 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049564-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/kydbou
title: PAN-00181816 - Roman lock-pin

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00181816&lt;/p&gt;
description: Modified: 2025-11-03T12:17:00+01:00
DOI: 10.17632/ckpxd8xx22.2
title: Dynamic regulation of neuronal vault trafficking and RNA cargo by the noncoding RNA, Vaultrc5

description: Vaults are large ribonucleoprotein complexes of unknown function. Here, we report that the vault-associated noncoding RNA, Vaultrc5, is highly enriched at the synapse and is required for activity-dependent vault trafficking in primary cortical neurons. We have discovered that vaults are comprised of unique populations of coding and non-coding RNA, and that this cargo varies dynamically between subcellular compartments. In addition, Vaultrc5 knockdown at the synapse shifts the RNA cargo toward transcripts associated with immune surveillance, and Vaultrc5 knockdown, in vivo, leads to impaired fear learning. These findings suggest that the Vaultrc5 is critically involved in coordinating the experience-dependent trafficking of vaults and related RNA cargo, which represents a novel feature of neuronal plasticity underlying learning and memory.
DOI: 10.17632/3sn6cbzk3p
title: Collision tumors of atypical fibroxanthoma and pleomorphic dermal sarcoma with other cutaneous malignancies: A retrospective cohort analysis

description: Supplemental Data for JAAD Manuscript Collision tumors of atypical fibroxanthoma and pleomorphic dermal sarcoma with other cutaneous malignancies: A retrospective cohort analysis
DOI: 10.17632/3sn6cbzk3p.1
title: Collision tumors of atypical fibroxanthoma and pleomorphic dermal sarcoma with other cutaneous malignancies: A retrospective cohort analysis

description: Supplemental Data for JAAD Manuscript Collision tumors of atypical fibroxanthoma and pleomorphic dermal sarcoma with other cutaneous malignancies: A retrospective cohort analysis
DOI: 10.17632/ck47657dk7
title: Long-term seasonal surface environment dataset of DKH

description: The dataset mainly shares LST, NDVI, FVC, and TVDI within 10 km around the Dushanzi-Kuqa Highway across 4 quarters from 2000 to 2024. This dataset is extracted from MODIS satellite data, with the specific quarterly divisions as follows: Q1: Jan~Mar; Q2: Apr~Jun; Q3: Jul~Sep; Q4: Oct~Dec.
DOI: 10.17632/ck47657dk7.1
title: Long-term seasonal surface environment dataset of DKH

description: The dataset mainly shares LST, NDVI, FVC, and TVDI within 10 km around the Dushanzi-Kuqa Highway across 4 quarters from 2000 to 2024. This dataset is extracted from MODIS satellite data, with the specific quarterly divisions as follows: Q1: Jan~Mar; Q2: Apr~Jun; Q3: Jul~Sep; Q4: Oct~Dec.
DOI: 10.17632/xjy6kbvhb2
title: HLA and AML

description: Using high-resolution genotyping, this study investigates the relationship between HLA Class I and Class II alleles and the risk of developing AML in the Kazakhstani population. Class II alleles, especially those within DQA1 and DPB1, are important genetic factors influencing AML susceptibility in the Kazakhstani population.
DOI: 10.17632/xjy6kbvhb2.1
title: HLA and AML

description: Using high-resolution genotyping, this study investigates the relationship between HLA Class I and Class II alleles and the risk of developing AML in the Kazakhstani population. Class II alleles, especially those within DQA1 and DPB1, are important genetic factors influencing AML susceptibility in the Kazakhstani population.
DOI: 10.17632/z8v8m579z4
title: HUMERIS Global Soil Dataset

description: The HUMERIS Global Soil Properties Dataset offers a comprehensive, 39‐year time series (1985–2023) of annual global soil maps at a 1 km resolution for topsoil (0–30 cm) covering four key soil properties: pH, soil salinity (ECe), nitrogen (N), and organic carbon (OC). The dataset is based on a harmonized collection of soil pedons compiled from the ISRIC‐WISE, OpenLandMap and LUCAS datasets, ensuring a wide coverage of in-situ measurements. Advanced machine learning techniques were employed using 41 environmental predictors, which include climatic variables, topographic indices, land cover data, and remotely sensed vegetation indices, to capture the spatio-temporal dynamics of soil properties.
Users accessing the repository will find freely downloadable multiband maps with descriptive statistics of the reference period. These maps allow for an assessment of the overall state and variability of soil health indicators across different regions and can serve as benchmarks for environmental monitoring and sustainable land management. For those interested in examining annual variations, single-year maps are available exclusively via a Google Earth Engine interface, which offers the flexibility to explore detailed temporal changes and spatial patterns. To download a series of Yearly data at Global scale or for further request please contact the corresponding author.