cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/8s4r67b9tz.2
title: LINF_140012300

description: Ketoacyl-CoA synthase | Fatty acid elongase | ELO-2; Leishmania infantum (strain JPCM5)
DOI: 10.5281/zenodo.14795176
title: SPI_SPEI_MCI_HSTR_China_part3
DOI: 10.5281/zenodo.14795177
title: SPI_SPEI_MCI_HSTR_China_part3
DOI: 10.17632/46y2fpbfjj.1
title: LINF_140012200

description: fatty acid elongase Leishmania infantum (strain JPCM5)
DOI: 10.17632/46y2fpbfjj.2
title: LINF_140012200

description: Ketoacyl-CoA synthase | Fatty acid elongase | ELO-1; Leishmania infantum (strain JPCM5)
DOI: 10.17632/svb8d9hmmd.1
title: LINF_140010900

description: hypothetical protein - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/svb8d9hmmd.2
title: LINF_140010900

description: Hypothetical protein - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.15468/dl.9nyvq3
title: Occurrence Download

description: A dataset containing 40546 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is VMM - Rat control occurrences in Flanders, Belgium"
 ]
}

 The dataset includes 40546 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009430-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/bbp9tcdrwy.1
title: Research on Machine Vision-Based Detection Method for Status Monitoring of Printhead in Inkjet 3D Printing

description: This dataset supports the research titled "Research on Machine Vision-Based Detection Method for Status Monitoring of Printhead in Inkjet 3D Printing". It includes: (1) raw and preprocessed jetting images captured from transparent inkjet nozzles; (2) output results from the Pixel-weighting and Multi-feature Fusion (PMF) algorithm used for initial rule-based defect evaluation; and (3) training and validation datasets for lightweight convolutional neural networks (CNNs), along with corresponding classification labels and model outputs. These data were used for nozzle-level defect detection and printhead health assessment, enabling accurate classification of normal, intermittent, and failed jetting states. The dataset facilitates further research in intelligent fault diagnosis, image-based monitoring, and machine learning applications in inkjet-based additive manufacturing.
DOI: 10.57745/bifkzf
title: SR-variants.vcf.gz
DOI: 10.15468/dl.nqg42a
title: Occurrence Download

description: A dataset containing 810 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Forsythia suspensa (Thunb.) Vahl"
 ]
}

 The dataset includes 810 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009433-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60776/edq4se
title: Providing adjoint optimized GEKO model coefficients for film cooling predictions of trench designs.

description: The data represent coefficients for the Generalized k-omega (GEKO) turbulence model used to solve the Reynolds-averaged Navier-Stokes equations (RANS) of wall-bounded film cooling flows involving the trench design. This model, with these coefficients, can be applied in Computational Fluid Dynamics (CFD) simulations using the commercial solver Ansys Fluent (version 2022 R1 or higher). The coefficients were tuned to match the 3D temperature field (temporal-averaged) of a Large Eddy Simulation (LES). The CFD case simulated for the RANS and LES was based on an optimized trench design by Peter Schreivogel at a momentum ratio of I=1 and a density ratio of 2. The LES and resulting RANS solution predicted the experimental results of Peter Schreivogel's optimized trench design and the transverse trench at I=1. At I=8, the tuned GEKO model still led to a better prediction than the standard model, but it was not as accurate as at I=1.
description: Bereits auf Mendeley Data veröffentlicht: 
Fischer, Lukas; Pfitzner, Michael (2023), “Providing adjoint optimized GEKO model coefficients for film cooling predictions of trench designs.”, Mendeley Data, V1, doi: 10.17632/5f7xcv8dgv.1
DOI: 10.17632/m8hg26cghc
title: Moderate time grazing in the warm season maintained the diversity and complexity of soil microorganisms by regulating nutrient cycling and decomposition function

description: It includes all the processes of data processing and analysis in the manuscript.
DOI: 10.17632/m8hg26cghc.1
title: Moderate time grazing in the warm season maintained the diversity and complexity of soil microorganisms by regulating nutrient cycling and decomposition function

description: It includes all the processes of data processing and analysis in the manuscript.
DOI: 10.15468/dl.f7ntuc
title: Occurrence Download

description: A dataset containing 4895 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhizophora stylosa Griffith"
 ]
}

 The dataset includes 4895 records from 90 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009434-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rntm6y
title: Occurrence Download

description: A dataset containing 6506 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Belgium",
 "GadmGid is BEL.3_1",
 "OccurrenceStatus is Present",
 "PublishingOrg is 28eb1a3f-1c15-4a95-931a-4af90ecb574d",
 "TaxonKey is Hemiptera"
 ]
}

 The dataset includes 6506 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009435-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8s7hfq
title: Occurrence Download

description: A dataset containing 56416 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is Egypt",
 "Geometry POLYGON((30.15866 31.65367,29.877 31.29967,30.24761 30.90619,30.88505 30.12718,31.04812 29.36782,31.32978 29.19973,31.53732 30.12718,32.39712 30.51108,32.60466 31.22364,32.18958 31.65367,31.22601 31.75457,30.15866 31.65367))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Animalia"
 ]
}

 The dataset includes 56416 records from 263 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009414-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hwkjak
title: Occurrence Download

description: A dataset containing 3088 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Jurinea cyanoides (L.) Rchb."
 ]
}

 The dataset includes 3088 records from 109 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009436-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/h73wn2nw56.1
title: Soil Sight: Remote Sensing-Based Soil Fertility Dataset

description: Traditional soil testing in agricultural regions is often expensive, time-consuming, and lacks spatial coverage. This dataset addresses the need for a high-resolution, remote sensing-based alternative to enable faster, scalable, and data-driven soil fertility assessment. The CSV file contains 8,412 georeferenced data points across a 542 km² agricultural region, with each 30 m × 30 m grid cell capturing multiple parameters relevant to soil health and fertility. These include: Latitude and Longitude (WGS 84 coordinates) to spatially locate each point; NDVI (Normalized Difference Vegetation Index), derived from Sentinel-2 bands B8 and B4, indicating vegetation health; EVI (Enhanced Vegetation Index), which improves sensitivity in high biomass regions; SAVI (Soil-Adjusted Vegetation Index), which minimizes soil brightness influence; Soil_Moisture, estimated using Sentinel-1 C-band SAR VV polarization backscatter values; Elevation, derived from SRTM 30 m Digital Elevation Model; and Fertility_Level, a categorical classification into Very High, High, Moderate, or Low fertility zones. All data was preprocessed using Google Earth Engine (2019–2025), applying radiometric calibration, atmospheric correction, and cloud filtering. This comprehensive dataset is ideal for use in precision agriculture, irrigation planning, site-specific fertilizer application, and machine learning-based agro-environmental modeling.
DOI: 10.5281/zenodo.14555222
title: Supplementary material for paper "Inverse modeling of SO2 point source emissions in the Middle East" by Ukhov et al., 2025.

description: Supplementary material for paper "Inverse modeling of SO2 point source emissions in the Middle East" by Ukhov et al., 2025.

List of files:1. plot_emissions_w_uncertanties.py - Python script, which plots the inverted emission rates (same as Fig. 4 and 5 in the paper);2. emissions.csv - information on 134 point sources used during the inversion procedure;3. README - this file;4. supplement_table_min.csv - min inverted SO2 emissions;5. supplement_table_mean.csv - mean inverted SO2 emissions;6. supplement_table_max.csv - max inverted SO2 emissions;7. wrf_grid.txt - description of the WRF-Chem grid. Can be used for remapping using CDO tools, for example;8. emissions_w_uncertanties.png - result of plot_emissions_w_uncertanties.py (same as Fig. 4 and 5 in the paper);9. namelist.wps - description of the WRF-Chem geography projection;10. wrfchemi_00z_d01 - daily gridded emissions during 2016. E_ISO and E_SO2 variables contain elevated and surface SO2 emissions.
DOI: 10.5281/zenodo.14555223
title: Supplementary material for paper "Inverse modeling of SO2 point source emissions in the Middle East" by Ukhov et al., 2025.

description: Supplementary material for paper "Inverse modeling of SO2 point source emissions in the Middle East" by Ukhov et al., 2025.

List of files:1. plot_emissions_w_uncertanties.py - Python script, which plots the inverted emission rates (same as Fig. 4 and 5 in the paper);2. emissions.csv - information on 134 point sources used during the inversion procedure;3. README - this file;4. supplement_table_min.csv - min inverted SO2 emissions;5. supplement_table_mean.csv - mean inverted SO2 emissions;6. supplement_table_max.csv - max inverted SO2 emissions;7. wrf_grid.txt - description of the WRF-Chem grid. Can be used for remapping using CDO tools, for example;8. emissions_w_uncertanties.png - result of plot_emissions_w_uncertanties.py (same as Fig. 4 and 5 in the paper);9. namelist.wps - description of the WRF-Chem geography projection;10. wrfchemi_00z_d01 - daily gridded emissions during 2016. E_ISO and E_SO2 variables contain elevated and surface SO2 emissions.
DOI: 10.5281/zenodo.15260450
title: Supplementary material for paper "Inverse modeling of SO2 point source emissions in the Middle East" by Ukhov et al., 2025.

description: Supplementary material for paper "Inverse modeling of SO2 point source emissions in the Middle East" by Ukhov et al., 2025.

List of files:1. plot_emissions_w_uncertanties.py - Python script, which plots the inverted emission rates (same as Fig. 4 and 5 in the paper);2. emissions.csv - information on 134 point sources used during the inversion procedure;3. README - this file;4. supplement_table_min.csv - min inverted SO2 emissions;5. supplement_table_mean.csv - mean inverted SO2 emissions;6. supplement_table_max.csv - max inverted SO2 emissions;7. wrf_grid.txt - description of the WRF-Chem grid. Can be used for remapping using CDO tools, for example;8. emissions_w_uncertanties.png - result of plot_emissions_w_uncertanties.py (same as Fig. 4 and 5 in the paper);9. namelist.wps - description of the WRF-Chem geography projection;10. wrfchemi_00z_d01 - daily gridded emissions during 2016. E_ISO and E_SO2 variables contain elevated and surface SO2 emissions.
DOI: 10.17632/z2kwnr6wr2.1
title: H5P Technology Dataset: Student Engagement, Performance, and Behavioral Intention at a Sino‑British Joint‑Venture International University

description: This research investigated the relationships among university students' behavioral intention to use H5P technology, their learning engagement, and their performance in an online learning environment through the testing of seven hypotheses. H1: Performance Expectancy (PE) has a positive effect on their Behavioral Intention (BI) to use H5P. H2: Effort Expectancy (EE) has a positive effect on their Behavioral Intention (BI) to use H5P. H3: Social Influence (SI) has a positive effect on their Behavioral Intention (BI) to use H5P. H4: Facilitating Conditions (FC) have a positive effect on their Behavioral Intention (BI) to use H5P. H5: Behavioral Intention (BI) has a positive impact on Learning Engagement (LE). H6: Behavioral Intention (BI) has a positive impact on Learning Performance (LP). H7: Learning Engagement (LE) has a positive impact on Learning Performance (LP). The analysis was conducted using PLS-SEM via SmartPLS software. Results indicate that H3, H4, H5, H6, and H7 are supported, while H1 and H2 are rejected. The data was collected from both undergraduate and postgraduate students who have used H5P technology in their online learning at a Sino-British joint venture international university in China. The dataset includes two Excel files: one named "Scale," which details the questions and descriptions of the integrated scale; and another named "H5P Dataset," containing participants' self-reported responses. Further details about the conceptual model and findings are available in the research paper.
DOI: 10.17632/f8ctdwzf29.1
title: Construction of molecular targets based on gene expression profiling and clinical validation results: CEBPB enables accurate diagnosis of early esophageal carcinoma

description: The prevalence of esophageal squamous cell carcinoma (ESCC) among all cases of esophageal carcinoma in Asia exceeds 90%. The absence of reliable biomarkers and noticeable symptoms in the early stages often leads to delayed diagnosis and unfavorable prognosis for patients. The present study employed weighted gene coexpression network analysis (WGCNA) to identify a set of 1204 genes exhibiting strong correlations with stage T1 tumors. Differential analysis revealed 448 upregulated differentially expressed genes (DEGs) that were enriched primarily in immune- and tumor-related pathways. Through cross-analysis, we established a protein–protein interaction (PPI) network and identified seven key genes. Two key genes (CEBPB and CXCL8) were validated in external datasets and demonstrated good diagnostic efficiency according to receiver operating characteristic (ROC) curve analysis (area under the curve [AUC] &gt; 0.8). Immune cell infiltration analysis revealed notable alterations in macrophage populations within ESCC tissues. Verification through Western blotting, immunohistochemistry, and immunofluorescence confirmed that CEBPB has superior identification efficiency. Five distinct cell types were identified in ESCC, and CEBPB expression was observed in all cellular categories. Tissue stem cells and epithelial cells exhibited strong intercellular communication with other cells, whereas TGFB1-(TGFBR1+TGFBR2) was widely expressed throughout all cell types. This study highlights the potential of CEBPB as a valuable biomarker for identifying ESCC, revealing its role in tumor progression and metastasis through immune microenvironment modulation. These results provide valuable insight into the timely identification and precise management of ESCC, with a specific focus on circumstances related to tumor progression.
DOI: 10.17632/xhwbvfh74g
title: LINF_160011800

description: E3 ubiquitin-protein ligase; Leishmania infantum (strain JPCM5)
DOI: 10.17632/xhwbvfh74g.1
title: LINF_160011800

description: E3 ubiquitin-protein ligase; Leishmania infantum (strain JPCM5)
DOI: 10.17632/fxz5dcyf5d.1
title: LINF_160011500

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/stvnypk488.1
title: LINF_160010800

description: NTPase domain-containing protein; Leishmania infantum (strain JPCM5)
DOI: 10.15468/dl.8udb8f
title: Occurrence Download

description: A dataset listing the 3925 species recorded in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is Egypt",
 "Geometry POLYGON((30.15866 31.65367,29.877 31.29967,30.24761 30.90619,30.88505 30.12718,31.04812 29.36782,31.32978 29.19973,31.53732 30.12718,32.39712 30.51108,32.60466 31.22364,32.18958 31.65367,31.22601 31.75457,30.15866 31.65367))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Animalia"
 ]
}

 The dataset's 3925 records were derived from 263 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009432-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/247h9zc32d.1
title: SDI(g)_and_GI_(1996-2019)

description: This dataset complements the SDI-dataset by considering the Governance Climate Index (GI) computed with the World Governance Indicators (WGIs).
DOI: 10.17632/247h9zc32d.3
title: SDI(g)_and_GI_(1996-2019)

description: The SDI(g) dataset complements the SDI dataset by considering the Governance Index (GI) as a measure of the countries' governance climate, computed with the World Governance Indicators (WGIs).
DOI: 10.17632/247h9zc32d.5
title: SDI(g)_and_GI_(1996-2019)

description: The SDI(g) dataset complements the Hickel's (2020) Sustainable Development Index (SDI) by considering the Governance Index (GI) as a proxy of the countries' governance climate and computed with the World Governance Indicators (WGIs).
DOI: 10.17632/247h9zc32d.6
title: SDI(g)_and_GI_dataset

description: The SDI(g) dataset complements Hickel's (2020) Sustainable Development Index (SDI) by considering the Governance Index (GI) as a proxy of the countries' governance climate computed with the World Governance Indicators (WGIs).
DOI: 10.17632/247h9zc32d.2
title: SDI(g)_and_GI_(1996-2019)

description: This dataset complements the SDI-dataset by considering the Governance Climate Index (GI) computed with the World Governance Indicators (WGIs).
DOI: 10.17632/247h9zc32d.4
title: SDI(g)_and_GI_(1996-2019)

description: The SDI(g) dataset complements the Hickel's (2020) Sustainable Development Index (SDI) by considering the Governance Index (GI) as a measure of the countries' governance climate computed with the World Governance Indicators (WGIs).
DOI: 10.17632/247h9zc32d.7
title: SDI(g)_and_GI_dataset

description: The SDI(g) dataset complements Hickel's (2020) Sustainable Development Index (SDI) by considering the Governance Index (GI) as a proxy of the countries' governance climate computed with the World Bank-Worldwide Governance Indicators (WGIs).
DOI: 10.5281/zenodo.14937743
title: Non-thermal electrons open the non-equilibrium pathway of the phase transition in FeRh

description: The optical excitation of metals initially creates short-lived non-Fermi distributions of the electrons. The electrons and holes excited far above and below the Fermi level quickly relax to hot Fermi-distributions that subsequently cool via electron-phonon scattering. Here, we show that such non-thermal charge carriers beyond the Fermi-distribution speed up the prototypical first-order antiferromagnetic-to-ferromagnetic phase transition in FeRh. In ultrafast x-ray diffraction experiments, we vary the maximum electron temperature by increasing the pump pulse duration up to 10ps. For direct optical excitation of FeRh, ferromagnetic domains nucleate within 8ps as soon as the successively deposited energy surpasses the site-specific threshold energy. In contrast, suppressing the direct optical excitation by an optically opaque Pt layer leads to a nucleation on a 50ps timescale driven by the near-equilibrium heat transport. These findings unambiguously identify the photo-excitation of non-thermal electrons and not electron-phonon non-equilibria to enable the rapid phase transition in FeRh.

This dataset contains all raw data, data evaluation and plot scripts used in the linked publication. The data.rar archive contains 3 folders, linked to the measurements, the simulations and the publication figures. The data analysis scripts as well as the modelling of the laser-induced lattice dynamics are written in Python.
DOI: 10.5281/zenodo.14937744
title: Non-thermal electrons open the non-equilibrium pathway of the phase transition in FeRh

description: The optical excitation of metals initially creates short-lived non-Fermi distributions of the electrons. The electrons and holes excited far above and below the Fermi level quickly relax to hot Fermi-distributions that subsequently cool via electron-phonon scattering. Here, we show that such non-thermal charge carriers beyond the Fermi-distribution speed up the prototypical first-order antiferromagnetic-to-ferromagnetic phase transition in FeRh. In ultrafast x-ray diffraction experiments, we vary the maximum electron temperature by increasing the pump pulse duration up to 10ps. For direct optical excitation of FeRh, ferromagnetic domains nucleate within 8ps as soon as the successively deposited energy surpasses the site-specific threshold energy. In contrast, suppressing the direct optical excitation by an optically opaque Pt layer leads to a nucleation on a 50ps timescale driven by the near-equilibrium heat transport. These findings unambiguously identify the photo-excitation of non-thermal electrons and not electron-phonon non-equilibria to enable the rapid phase transition in FeRh.

This dataset contains all raw data, data evaluation and plot scripts used in the linked publication. The data.rar archive contains 3 folders, linked to the measurements, the simulations and the publication figures. The data analysis scripts as well as the modelling of the laser-induced lattice dynamics are written in Python.
DOI: 10.17632/kk4cmgcjhy.1
title: University Students' Behavioral Intention to Use H5P Technology, Learning Engagement, and Learning Performance Datasets in an Online Environment at a Sino-British Joint Venture International University in China

description: This research investigated the relationships among university students' behavioral intention to use H5P technology, their learning engagement, and their performance in an online learning environment through the testing of seven hypotheses. H1: Performance Expectancy (PE) has a positive effect on their Behavioral Intention (BI) to use H5P. H2: Effort Expectancy (EE) has a positive effect on their Behavioral Intention (BI) to use H5P. H3: Social Influence (SI) has a positive effect on their Behavioral Intention (BI) to use H5P. H4: Facilitating Conditions (FC) have a positive effect on their Behavioral Intention (BI) to use H5P. H5: Behavioral Intention (BI) has a positive impact on Learning Engagement (LE). H6: Behavioral Intention (BI) has a positive impact on Learning Performance (LP). H7: Learning Engagement (LE) has a positive impact on Learning Performance (LP). The analysis was conducted using PLS-SEM via SmartPLS software. Results indicate that H3, H4, H5, H6, and H7 are supported, while H1 and H2 are rejected. The data was collected from both undergraduate and postgraduate students who have used H5P technology in their online learning at a Sino-British joint venture international university in China. The dataset includes two Excel files: one named "Scale," which details the questions and descriptions of the integrated scale; and another named "H5P Dataset," containing participants' self-reported responses. Further details about the conceptual model and findings are available in the research paper.