cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.26308922.v1
title: Additional file 1 of Dihydroorotase MoPyr4 is required for development, pathogenicity, and autophagy in rice blast fungus

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.26749286
title: Additional file 3 of Comprehensive and deep evaluation of structural variation detection pipelines with third-generation sequencing data

description: Additional file 3: Table S4. The proportions of pipelines reporting DUP as INS and INS as DUP under different sequencing platforms.
DOI: 10.6084/m9.figshare.26749286.v1
title: Additional file 3 of Comprehensive and deep evaluation of structural variation detection pipelines with third-generation sequencing data

description: Additional file 3: Table S4. The proportions of pipelines reporting DUP as INS and INS as DUP under different sequencing platforms.
DOI: 10.6084/m9.figshare.26749289
title: Additional file 4 of Comprehensive and deep evaluation of structural variation detection pipelines with third-generation sequencing data

description: Additional file 4: Table S5. Precision, recall, and F1 scores for different samples from various sequencing platforms at a sequencing depth of 25× under different minimum support numbers.
DOI: 10.6084/m9.figshare.26749289.v1
title: Additional file 4 of Comprehensive and deep evaluation of structural variation detection pipelines with third-generation sequencing data

description: Additional file 4: Table S5. Precision, recall, and F1 scores for different samples from various sequencing platforms at a sequencing depth of 25× under different minimum support numbers.
DOI: 10.6084/m9.figshare.26749331
title: Additional file 8 of Endometrial senescence is mediated by interleukin 17 receptor B signaling

description: Additional file 8: Fig. S8. Original, uncropped immunoblots of Fig.1B, 1D, 5B-C and 6A-B. Red regions are saturated areas.
DOI: 10.6084/m9.figshare.26749331.v1
title: Additional file 8 of Endometrial senescence is mediated by interleukin 17 receptor B signaling

description: Additional file 8: Fig. S8. Original, uncropped immunoblots of Fig.1B, 1D, 5B-C and 6A-B. Red regions are saturated areas.
DOI: 10.25919/6pj1-b656
title: Parkes observations for project PX500 semester 2025OCTS_15

description: This proposal relates to time purchased by the Chinese Academy of Sciences for Parkes follow-up confirmation and timing of FAST discoveries. As the observing time has been purchased this proposal (and the related PX501) does not require TAC grading. The primary reason for submitting a proposal is to ensure an outreach statement and that the proposal is entered into OPAL for the data archive to access. The Chinese team have two time requests. The time scheduled for the first, relating to this proposal, will be allocated in blocks of 24 hours and the data will become available in the data archive with an 18 month embargo period. The second type of time will be scheduled in shorter blocks and the data archived with a 10 year embargo.
DOI: 10.15468/dl.bgjhc3
title: Occurrence Download

description: A dataset containing 33 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is one of (Chinese Taipei, China)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "VerbatimScientificName is Onychodactylus zhaoermii"
 ]
}

 The dataset includes 33 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068116-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18079701
title: Dataset on student satisfaction in non-school distance learning programs in a rural context: Evidence from the Technological Institute of the Valley of Etla, Mexico

description: This dataset contains anonymized responses from 71 undergraduate students enrolled in non-classroom-based distance education programs at the Technological Institute of the Valley of Etla (ITVE), Mexico.Data were collected through a structured questionnaire using a five-point Likert scale and organized into five dimensions identified through exploratory factor analysis: cognitive autonomy, emotional and social self-regulation, cognitive presence, perception of the virtual learning environment, and contextual conditions.The dataset supports descriptive analysis, methodological replication, and secondary research on student satisfaction in distance higher education, particularly in geographically dispersed and socially vulnerable contexts.
DOI: 10.6084/m9.figshare.30962069
title: Dataset for - Medical Malpractice Analyses Using Commercial Legal Research Databases

description: This dataset contains the extracted data for a systematic review and methodological evaluation of medical malpractice studies utilizing commercial legal research databases (Westlaw, LexisNexis, and VerdictSearch).
DOI: 10.6084/m9.figshare.30962069.v1
title: Dataset for - Medical Malpractice Analyses Using Commercial Legal Research Databases

description: This dataset contains the extracted data for a systematic review and methodological evaluation of medical malpractice studies utilizing commercial legal research databases (Westlaw, LexisNexis, and VerdictSearch).
DOI: 10.15468/dl.3tds6y
title: Occurrence Download

description: A dataset containing 41 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Papua New Guinea",
 "OccurrenceStatus is Present",
 "TaxonKey is Palaia pulchra"
 ]
}

 The dataset includes 41 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068117-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18066872
title: Wordclim processed data from 2021 to 2100
DOI: 10.5281/zenodo.18066871
title: Wordclim processed data from 2021 to 2100
DOI: 10.15468/dl.awjsv3
title: Occurrence Download

description: A dataset containing 1355 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is one of (Chinese Taipei, China)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Animalia",
 "VerbatimScientificName is Aegypius monachus"
 ]
}

 The dataset includes 1355 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068118-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18079803
title: Derived Datasets and Code for Seasonal Net Surface Shortwave Radiation and 3D Urban Morphology Analysis in Beijing (2023)

description: # Derived Datasets and Code for Seasonal Net Surface Shortwave Radiation and 3D Urban Morphology Analysis in Beijing (2023)


## Description

This dataset supports the paper:  

**Investigating the impact of two-dimensional and three-dimensional urban structures on seasonal net surface shortwave radiation**  

by Yang Liu, Shisong Cao*, Jingyi Chen, Huiping Sun, Ling Li, and Nuan Wang  

(submitted to *GIScience & Remote Sensing*)


The dataset contains derived 30 m resolution grids and tabular data for Beijing within the Fifth Ring Road in 2023.


## Contents

- **3D_USPs.gdb**: File Geodatabase containing eight 3D urban structural parameters at 30 m resolution:

  - MBH (Mean Building Height)

  - MBV (Mean Building Volume)

  - SVF (Sky View Factor)

  - FAR (Floor Area Ratio)

  - SCD (Spatial Crowdedness Degree)

  - BSA (Building Surface Area)

  - BU (Building Uniformity)

  - BSI (Building Structural Index)

- **NSSR_0116.gdb**, **NSSR_0305.gdb**, **NSSR_0828.gdb**, **NSSR_1124.gdb**:  

  Net Surface Shortwave Radiation (NSSR, unit: W/m²) grids for four representative dates in winter, spring, summer, and autumn 2023.

  - **Landcover_2D.gdb** (or raster file): Two-dimensional land cover classification data for the study area (derived from Dynamic World or similar).

- **Albedo.gdb** (or raster file): Surface albedo grids used in the NSSR retrieval process.

- **BJ_DSR_CSV.csv** (or .xlsx): Tabular data combining seasonal NSSR values with corresponding 3D urban structural parameters for machine learning analysis.

- **MODISpoint.xlsx**: Validation data extracted from MODIS products and ground observations.

- **Python scripts** (*.py): Key codes for machine learning models (XGBoost, LightGBM, Random Forest, etc.) and SHAP interpretability analysis.


## Software Requirements

- GIS software: ArcGIS or QGIS (to open .gdb files)

- Python 3.x with libraries: pandas, numpy, xgboost, lightgbm, scikit-learn, shap, matplotlib, etc.


## Usage Example

```python

import pandas as pd

df = pd.read_csv('BJ_DSR_CSV.csv')

print(df.head())
DOI: 10.5281/zenodo.18079804
title: Derived Datasets and Code for Seasonal Net Surface Shortwave Radiation and 3D Urban Morphology Analysis in Beijing (2023)

description: # Derived Datasets and Code for Seasonal Net Surface Shortwave Radiation and 3D Urban Morphology Analysis in Beijing (2023)


## Description

This dataset supports the paper:  

**Investigating the impact of two-dimensional and three-dimensional urban structures on seasonal net surface shortwave radiation**  

by Yang Liu, Shisong Cao*, Jingyi Chen, Huiping Sun, Ling Li, and Nuan Wang  

(submitted to *GIScience & Remote Sensing*)


The dataset contains derived 30 m resolution grids and tabular data for Beijing within the Fifth Ring Road in 2023.


## Contents

- **3D_USPs.gdb**: File Geodatabase containing eight 3D urban structural parameters at 30 m resolution:

  - MBH (Mean Building Height)

  - MBV (Mean Building Volume)

  - SVF (Sky View Factor)

  - FAR (Floor Area Ratio)

  - SCD (Spatial Crowdedness Degree)

  - BSA (Building Surface Area)

  - BU (Building Uniformity)

  - BSI (Building Structural Index)

- **NSSR_0116.gdb**, **NSSR_0305.gdb**, **NSSR_0828.gdb**, **NSSR_1124.gdb**:  

  Net Surface Shortwave Radiation (NSSR, unit: W/m²) grids for four representative dates in winter, spring, summer, and autumn 2023.

  - **Landcover_2D.gdb** (or raster file): Two-dimensional land cover classification data for the study area (derived from Dynamic World or similar).

- **Albedo.gdb** (or raster file): Surface albedo grids used in the NSSR retrieval process.

- **BJ_DSR_CSV.csv** (or .xlsx): Tabular data combining seasonal NSSR values with corresponding 3D urban structural parameters for machine learning analysis.

- **MODISpoint.xlsx**: Validation data extracted from MODIS products and ground observations.

- **Python scripts** (*.py): Key codes for machine learning models (XGBoost, LightGBM, Random Forest, etc.) and SHAP interpretability analysis.


## Software Requirements

- GIS software: ArcGIS or QGIS (to open .gdb files)

- Python 3.x with libraries: pandas, numpy, xgboost, lightgbm, scikit-learn, shap, matplotlib, etc.


## Usage Example

```python

import pandas as pd

df = pd.read_csv('BJ_DSR_CSV.csv')

print(df.head())
DOI: 10.5281/zenodo.18079560
title: Sistema de Geração de Família de Constantes Harmónicas Universais

description: Investigação e desenvolvimento de um gerador algorítmico de constantes harmónicas universais. O depósito inclui a arquitetura do sistema, fórmulas aritméticas, código-fonte, folhas de cálculo de validação e relatórios de simulação que demonstram a eficácia do método na estabilização de sistemas complexos e regularização numérica.
DOI: 10.15468/dl.rysaa7
title: Occurrence Download

description: A dataset containing 257678 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cyanerpes cyaneus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON((-180 -90, 180 -90, 180 90, -180 90, -180 -90))"
 ]
}

 The dataset includes 257678 records from 171 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068113-251120083545085/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.30962066
title: <b>Benchmark Dataset for Multi-Source Building Footprint Association (Cologne) - MatchGT</b>

description: <b>Abstract:</b><br>This dataset serves as a benchmark for multi-source building footprint data association (matching). It is derived from the "Cologne" experimental area used in the research paper: <i>"MatchGT: A Candidate-Pair Competition Graph Framework for Multi-Source Building Footprint Data Association"</i>. The dataset presents a high-overlap, urban matching scenario with minimal non-linear displacement, suitable for evaluating global optimization and graph-based matching algorithms.<br><b>Data Content:</b><br>The dataset contains two shapefiles representing building footprints from two distinct sources:<b>Source Dataset (ALKIS):</b> Official cadastral data from the German Official Real Estate Cadastre Information System.<b>Target Dataset (OSM):</b> Crowdsourced building data from OpenStreetMap.<b>Ground Truth:</b> Manually annotated matching relationships identifying correspondences between Source and Target (including 1:1, 1:n, m:1, m:n, 1:0, and 0:1 relationships).<b>Study Area:</b><br>Cologne, Germany.Number of Source Buildings: 313Number of Target Buildings: 354Number of Matching Groups: 298<b>File Structure:</b><code>demo_1.shp</code>: Source building polygons.<code>demo_2.shp</code>: Target building polygons.<code>Match_Label.csv</code> (or included in attributes): The reference matching labels.<b>Usage Notes:</b><br>This dataset is intended to ensure the reproducibility of the MatchGT framework and to serve as a testbed for future research in geospatial data fusion.<br><b>Citation:</b><br>If you use this dataset in your research, please cite the associated paper:<br>Qiu, Y., Wu, F., Qian, H., Yin, J., Liu, C., & Gong, X. (2026). MatchGT: A Candidate-Pair Competition Graph Framework for Multi-Source Building Footprint Data Association. <i>Information Fusion</i>. (Under Review).
DOI: 10.6084/m9.figshare.30962066.v1
title: <b>Benchmark Dataset for Multi-Source Building Footprint Association (Cologne) - MatchGT</b>

description: <b>Abstract:</b><br>This dataset serves as a benchmark for multi-source building footprint data association (matching). It is derived from the "Cologne" experimental area used in the research paper: <i>"MatchGT: A Candidate-Pair Competition Graph Framework for Multi-Source Building Footprint Data Association"</i>. The dataset presents a high-overlap, urban matching scenario with minimal non-linear displacement, suitable for evaluating global optimization and graph-based matching algorithms.<br><b>Data Content:</b><br>The dataset contains two shapefiles representing building footprints from two distinct sources:<b>Source Dataset (ALKIS):</b> Official cadastral data from the German Official Real Estate Cadastre Information System.<b>Target Dataset (OSM):</b> Crowdsourced building data from OpenStreetMap.<b>Ground Truth:</b> Manually annotated matching relationships identifying correspondences between Source and Target (including 1:1, 1:n, m:1, m:n, 1:0, and 0:1 relationships).<b>Study Area:</b><br>Cologne, Germany.Number of Source Buildings: 313Number of Target Buildings: 354Number of Matching Groups: 298<b>File Structure:</b><code>demo_1.shp</code>: Source building polygons.<code>demo_2.shp</code>: Target building polygons.<code>Match_Label.csv</code> (or included in attributes): The reference matching labels.<b>Usage Notes:</b><br>This dataset is intended to ensure the reproducibility of the MatchGT framework and to serve as a testbed for future research in geospatial data fusion.<br><b>Citation:</b><br>If you use this dataset in your research, please cite the associated paper:<br>Qiu, Y., Wu, F., Qian, H., Yin, J., Liu, C., & Gong, X. (2026). MatchGT: A Candidate-Pair Competition Graph Framework for Multi-Source Building Footprint Data Association. <i>Information Fusion</i>. (Under Review).
DOI: 10.15468/dl.9b28tx
title: Occurrence Download

description: A dataset containing 168 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is one of (Chinese Taipei, China)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Animalia",
 "VerbatimScientificName is Anthracoceros albirostris"
 ]
}

 The dataset includes 168 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068121-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18080186
title: Comparative Genomic Insights into MatE Transporters Diversity and Habitat Adaptation of Archaea
DOI: 10.5281/zenodo.18079801
title: Comparative Genomic Insights into MatE Transporters Diversity and Habitat Adaptation of Archaea
DOI: 10.5281/zenodo.18078328
title: The Mechanistic Universe: A Predicting Therapeutic Effects and Risks platform

description:  

The purpose of this record is to provide structured, machine-readable data artifacts that support the analyses described in the associated manuscript.
DOI: 10.15468/dl.9autc9
title: Occurrence Download

description: A dataset containing 45301 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ephippiorhynchus senegalensis",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON((-180 -90, 180 -90, 180 90, -180 90, -180 -90))"
 ]
}

 The dataset includes 45301 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068122-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.j00186.00930
title: Data for “Research on Dynamic Three-Dimensional Terrain Correction Methods for Quantitative Inversion of Airborne Gamma-Ray Spectrometer”
title: Data for “Research on Dynamic Three-Dimensional Terrain Correction Methods for Quantitative Inversion of Airborne Gamma-Ray Spectrometer”

description: Data 1–3 consist of ground-measured and inversion-derived uranium (U), thorium (Th), and potassium (K) concentrations in the study area, including ground survey data, airborne survey data corrected for flight altitude, and inversion results processed using a dynamic three-dimensional terrain correction method. Specifically, Data 1 were obtained through ground measurements using a GR-320 gamma-ray spectrometer. Data 2 were acquired using a GR-820 gamma-ray spectrometer and subsequently processed in accordance with the Specification for Airborne Gamma-Ray Spectrometric Survey (ETJ 1032–2005) to derive U, Th, and K concentrations. Data 3 represent the U, Th, and K concentrations obtained after processing with the proposed dynamic terrain correction method.Data 1 and Data 2 are provided in Excel format, where the first column represents latitude, the second column represents longitude, and the remaining three columns correspond to K, U, and Th concentrations. Data 3 consist of three .txt files named K, U, and Th , respectively, each containing the concentrations corrected using the dynamic terrain correction method.
description: Data 1–3 consist of ground-measured and inversion-derived uranium (U), thorium (Th), and potassium (K) concentrations in the study area, including ground survey data, airborne survey data corrected for flight altitude, and inversion results processed using a dynamic three-dimensional terrain correction method. Specifically, Data 1 were obtained through ground measurements using a GR-320 gamma-ray spectrometer. Data 2 were acquired using a GR-820 gamma-ray spectrometer and subsequently processed in accordance with the Specification for Airborne Gamma-Ray Spectrometric Survey (ETJ 1032–2005) to derive U, Th, and K concentrations. Data 3 represent the U, Th, and K concentrations obtained after processing with the proposed dynamic terrain correction method.Data 1 and Data 2 are provided in Excel format, where the first column represents latitude, the second column represents longitude, and the remaining three columns correspond to K, U, and Th concentrations. Data 3 consist of three .txt files named K, U, and Th , respectively, each containing the concentrations corrected using the dynamic terrain correction method.
DOI: 10.57760/sciencedb.j00186.00925
title: PMT response data of water Cherenkov using Geant4 simulation
title: PMT response data of water Cherenkov using Geant4 simulation

description: The content of the article is simulation related, therefore all data files are simulation level data and do not include real experimental dataThe data comes from the running results of the WCSim package, which only modified the detector configuration. The optical properties of water and the response properties of pmt were only based on the software default configuration, and no additional adjustments were made for possible application scenarios.The operation of the file should be based on the universal program Root in the field of particle physics: https://root.cern.chSpecific file content and description:• WCSimConstructMysphere.cc: Geometric construction information of spherical detectors• wcsim4_10.root: Simulation results of neutrinos at 4-10MeV• wcsim40k.root: Simulation results of 40K background• output.txt: Neutrino signal reconstruction result set used for reconstructing source direction• getrandom.C: A tool for generating background signal mixed pseudodata
description: The content of the article is simulation related, therefore all data files are simulation level data and do not include real experimental dataThe data comes from the running results of the WCSim package, which only modified the detector configuration. The optical properties of water and the response properties of pmt were only based on the software default configuration, and no additional adjustments were made for possible application scenarios.The operation of the file should be based on the universal program Root in the field of particle physics: https://root.cern.chSpecific file content and description:• WCSimConstructMysphere.cc: Geometric construction information of spherical detectors• wcsim4_10.root: Simulation results of neutrinos at 4-10MeV• wcsim40k.root: Simulation results of 40K background• output.txt: Neutrino signal reconstruction result set used for reconstructing source direction• getrandom.C: A tool for generating background signal mixed pseudodata
DOI: 10.5517/cc5gscr
title: CCDC 163164: Experimental Crystal Structure Determination

description: Related Article: J.Y.Lu, A.M.Babb|2002|Chem.Commun.||1340|doi:10.1039/b200213b
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/cc5gsgv
title: CCDC 163167: Experimental Crystal Structure Determination

description: Related Article: J.Y.Lu, A.M.Babb|2002|Chem.Commun.||1340|doi:10.1039/b200213b
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.