cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8237523
title: GISD Facility-level CO2 emission data

description: The GISD facility-level CO<sub>2</sub> emissions along with the publication on Nature Climate Change.
DOI: 10.6084/m9.figshare.22266814.v1
title: TrainingDataset&ModelWeight

description: The CT slices with labeled images used for training. The model weight of Swin Transformer which was trained with patch size 672<sup>2 </sup>and hybrid loss
DOI: 10.17632/r825m4n3tt.1
title: Glycolytic pathway enrichment in T cell subclusters of affected and unaffected dominant dystrophic epidermolysis bullosa and healthy skin

description: Supplemental Figure 1. Glycolysis rate-limiting genes are upregulated in affected dominant dystrophic epidermolysis bullosa-associated GATA3+ Th2 cells. Gene expression of HK1 (hexokinase-1), PKM (pyruvate kinase), and PFKL (phosphofructo-1-kinase isozyme B) were fitted on a kernel density estimation algorithm to estimate probability density using the Nebulosa R package. The black horizontal line in the middle of each box plot indicates the median; the top and bottom borders of the box mark the 75th and 25th percentiles, respectively, and the vertical lines mark the minimum and maximum of the data. Supplemental Figure 2. GATA3+ Th2 cells in affected dominant dystrophic epidermolysis bullosa (DDEB) skin show positive enrichment for glycolysis pathway. Single sample gene set enrichment analysis of T cell subclusters in affected and unaffected DDEB and healthy skin. Normalized enrichment score for canonical glycolysis pathway across clusters is highlighted in the left plot. The black horizontal line in the middle of each box plot indicates the median; the top and bottom borders of the box mark the 75th and 25th percentiles, respectively, and the vertical lines mark the minimum and maximum of the data. In the right plot, a ridge plot is used to visualize the normalized enrichment score across clusters and between groups to show modal scores. Cluster 3 GATA3+ Th2 cells in DDEB affected group shows positive enrichment for canonical glycolysis as shown by positive modal peaks as compared to healthy cells in the same cluster which shows negative modal peaks.
DOI: 10.17632/5hgj345svc.1
title: The Effects of Abortion Decision Rightness and Decision Type on Women’s Satisfaction and Mental Health - Cureus 2023

description: Data from the survey utilized and described in "The Effects of Abortion Decision Rightness and Decision Type on Women’s Satisfaction and Mental Health" Cureus 2023. All information required to understand and utilize the data are described in the published paper
DOI: 10.34740/kaggle/dsv/6583680
title: LUFlow Network Intrusion Detection Data Set
DOI: 10.17632/6bmm3mmtd5.1
title: 16S rDNA sequences of feces from Puerariae lobatae Radix-dosed mice

description: Raw sequencing data associated with microbial analysis in study of gut microbiota from Puerariae lobatae Radix-dosed mice prevent chronic high salt induced kidney disease. 16S file includes 16S rDNA sequences of feces from CON、PLR and HS droup mice, while 16S-FMT file includes 16S rDNA sequences of feces from CON、PLR-FMT and HS-FMT group mice.
DOI: 10.17632/t9wc5vznwy.1
title: Overrepresentation test of differentially expressed genes from GATA3+ Th2 cell-specific clusters

description: PANTHER ORA of GATA3+ Th2 cells (Cluster 3 and Cluster 0) using Fisher's exact test on Biological Process annotation dataset and FDR method for multiple testing p-value adjustment. Differentially expressed genes were obtained by using FindAllMarkers function of Seurat on the T cell subset of the integrated single cell RNA sequencing dataset of affected and unaffected dominant dystrophic epidermolysis bullosa and healthy skin. Cluster-specific DEGs were obtained by first annotating each DEG for cluster occurrences using a custom R script, and subsequently filtering genes that have expression on other clusters. Besides enrichment for T cell-related pathways, multiple glycolysis-related terms are enriched only in Cluster 3.
DOI: 10.6084/m9.figshare.24224821
title: test

description: test for use
DOI: 10.6084/m9.figshare.24224821.v1
title: test

description: test for use
DOI: 10.6084/m9.figshare.24225490
title: ChatGPT KBA questionnaire

description: The dataset is the questionnaire about students, teachers, and administrators technology acceptance.
DOI: 10.5281/zenodo.8331918
title: Ultra-High Granularity Pixel Vertex Detector (PXD) signature Images

description: Pixel Vertex Detector <strong>(PXD)</strong> is the innermost sub-detector of Belle II. The configuration of the PXD consists of 40 sensors within two detector layers. The inner layer has 16 sensors, and the outer layer comprises 24 sensors. Thus, each event includes 40 grey-scale images, each with a resolution of 250x768 pixels, resulting in more than <strong>7.5 million pixel channels per event</strong>. Each event in the dataset has the structure of <strong>[40,1,250,768]</strong> where the events are encoded by an event number distributed over 40 sub-directories corresponding to the 40 class labels. 1.1.1/ --&gt; sensor #1<br> ├── event_1<br> ├── event_2<br> ├── ...<br> 1.1.2/ --&gt; sensor #2<br> ├── event_1<br> ├── event_2<br> ├── ... The samples are simulated synthetic background processes by GEANT4 via the basf2 software. This data is used to train/test the IEA-GAN: Ultra-High-Resolution Detector Simulation with Intra-Event Aware GAN and Self-Supervised Relational Reasoning.
description: {"references": ["https://doi.org/10.48550/arXiv.2303.08046", "https://link.springer.com/article/10.1007/s41781-018-0017-9"]}
DOI: 10.5281/zenodo.7936762
title: Virtual sensors benchmark study test timeseries tier 0 - part 1

description: A dataset with time series for testing virtual sensor models for wind turbine aeroelastic loads. Data are in zipped format, with 100 time series available. The test sets in the study are organized with several levels of "difficulty" according to added uncertainties and noise with respect to the training data. This particular dataset (tier 0) is with exactly the same distribution as the training data.
description: Version 0.2 updates: added rotor-equivalent wind direction time series
DOI: 10.5281/zenodo.7936763
title: Virtual sensors benchmark study test timeseries tier 0 - part 1

description: A dataset with time series for testing virtual sensor models for wind turbine aeroelastic loads. Data are in zipped format, with 100 time series available. The test sets in the study are organized with several levels of "difficulty" according to added uncertainties and noise with respect to the training data. This particular dataset (tier 0) is with exactly the same distribution as the training data.
DOI: 10.5281/zenodo.8396376
title: Virtual sensors benchmark study test timeseries tier 0 - part 1

description: A dataset with time series for testing virtual sensor models for wind turbine aeroelastic loads. Data are in zipped format, with 100 time series available. The test sets in the study are organized with several levels of "difficulty" according to added uncertainties and noise with respect to the training data. This particular dataset (tier 0) is with exactly the same distribution as the training data.
description: Version 0.2 updates: added rotor-equivalent wind direction time series
DOI: 10.5281/zenodo.8374018
title: Comparative Analysis of Maternal Gene Expression Patterns: Unraveling Evolutionary Signatures Across Reproductive Modes

description: Dataset used to reproduce the analysis performed in "Comparative Analysis of Maternal Gene Expression Patterns: Unraveling Evolutionary Signatures Across Reproductive Modes" publication. The directory structure is the following: Gene_models - directory containing gene models (.gtf or .gff3 files) used for feature length comparisons across species intermediate_data - directory containing intermediate results from various scripts, the main purpose is to speed up the reproducibility of some longer running scripts batch_adjusted_normalised_gene_expression_matrix.tsv - gene expression matrix used for evolutionary model fitting fc.tsv - fold change matrix used for evolutionary model fitting dated_species_tree.tre - species tree used throughout the model fitting step (newick format) DGE_script_enviorment.RData - saved R environment from differential gene expression analysis downregulated_IDs.RDS - gene IDs which undergo down-regulation throughout maternal-to-zygotic transition maternal_IDs.RDS - gene IDs which meet the cut-off criteria for being considered as maternally expressed N0_blasted.tsv - orthogroup annotations through blasting to a sequence database N0.tsv - orthogroups inferred from OrthoFinder OG_categories.tsv - classification of orthogroups based on them (I) having genes with maternal expression, but no significant down regulation, (II) having genes with maternal expression and significant down regulation throughout maternal-to-zygotic transition or (III) no maternal expression OG_presence.tsv - binary matrix coding for which orthogroup which species have gene expression values Paralog_variances.tsv - matrix containing variance metrics for paralogs in each species from before normalization across species Pannzer2_annotation - directory containing GO annotations for all species from the Pannzer2 tool, used for GO analyses quantification_files - directory containing all salmon quantification outputs transcriptomes - <em>de novo</em> assembled transcriptomes for non-model species
DOI: 10.5281/zenodo.8374017
title: Comparative Analysis of Maternal Gene Expression Patterns: Unraveling Evolutionary Signatures Across Reproductive Modes

description: Dataset used to reproduce the analysis performed in "Comparative Analysis of Maternal Gene Expression Patterns: Unraveling Evolutionary Signatures Across Reproductive Modes" publication. The directory structure is the following: Gene_models - directory containing gene models (.gtf or .gff3 files) used for feature length comparisons across species intermediate_data - directory containing intermediate results from various scripts, the main purpose is to speed up the reproducibility of some longer running scripts batch_adjusted_normalised_gene_expression_matrix.tsv - gene expression matrix used for evolutionary model fitting fc.tsv - fold change matrix used for evolutionary model fitting dated_species_tree.tre - species tree used throughout the model fitting step (newick format) DGE_script_enviorment.RData - saved R environment from differential gene expression analysis downregulated_IDs.RDS - gene IDs which undergo down-regulation throughout maternal-to-zygotic transition maternal_IDs.RDS - gene IDs which meet the cut-off criteria for being considered as maternally expressed N0_blasted.tsv - orthogroup annotations through blasting to a sequence database N0.tsv - orthogroups inferred from OrthoFinder OG_categories.tsv - classification of orthogroups based on them (I) having genes with maternal expression, but no significant down regulation, (II) having genes with maternal expression and significant down regulation throughout maternal-to-zygotic transition or (III) no maternal expression OG_presence.tsv - binary matrix coding for which orthogroup which species have gene expression values Paralog_variances.tsv - matrix containing variance metrics for paralogs in each species from before normalization across species Pannzer2_annotation - directory containing GO annotations for all species from the Pannzer2 tool, used for GO analyses quantification_files - directory containing all salmon quantification outputs transcriptomes - <em>de novo</em> assembled transcriptomes for non-model species
DOI: 10.5281/zenodo.8394002
title: d2_3_4

description: d2_3_4
DOI: 10.5281/zenodo.8394001
title: d2_3_4

description: d2_3_4
DOI: 10.5281/zenodo.8394000
title: d2_2_4

description: d2_2_4
DOI: 10.5281/zenodo.8393999
title: d2_2_4

description: d2_2_4
DOI: 10.25781/kaust-jmb84
title: Data for "The Third Competition on Spatial Statistics for Large Datasets"

description: The enclosed datasets have been generated by the internal spatial data generator tool included in the ExaGeoStat software (https://github.com/ecrc/exageostat). It was used for the 2023 KAUST Competition on Spatial Statistics for Large Datasets (https://cemse.kaust.edu.sa/stsds/news/2023-kaust-competition-spatial-statistics-large-datasets). The competition had four parts (Sub-competition 1a, Sub-competition 1b, Sub-competition 2a, and Sub-competition 2b). The main purpose of the competition was to reassess existing approximation methods on large spatial datasets in a uniform way that guarantees a fair comparison. More information about the datasets can be found in the file "Competition Description and True Model".
DOI: 10.5281/zenodo.8396486
title: Do Agile Scaling Approaches Make A Difference? An Empirical Comparison of Team Effectiveness Across Popular Scaling Approaches

description: This bundle contains supplementary materials for an upcoming academic publication <em>Do Agile Scaling Approaches Make A Difference? An Empirical Comparison of Team Effectiveness Across Popular Scaling Approaches?</em>, by Christiaan Verwijs and Daniel Russo. Included in the bundle are the dataset and SPSS syntaxes. This replication package is made available by C. Verwijs under a "Creative Commons Attribution Non-Commercial Share-Alike 4.0 International"-license (CC-BY-NC-SA 4.0). <strong>About the dataset</strong> The dataset (SPSS) contains anonymized response data from 15,078 team members aggregated into 4,013 Agile teams that participated from scrumteamsurvey.org. Stakeholder evaluations of 1,841 stakeholders were also collected for 529 of those teams. Data was gathered between September 2021, and September 2023. We cleaned the individual response data from careless responses and removed all data that could potentially identify teams, individuals, or their parent organizations. Because we wanted to analyze our measures at the team level, we calculated a team-level mean for each item in the survey. Such aggregation is only justified when at least 10% of the variance exists at the team level (Hair, 2019), which was the case (ICC = 35-50%). No data was missing at the team level. Question labels and option labels are provided separately in Questions.csv. To conform to the privacy statement of scrumteamsurvey.org, the bundle does not include response data from before the team-level aggregation. <strong>About the SPSS syntaxes</strong> The bundle includes the syntaxes we used to prepare the dataset from the raw import, as well as the syntax we used to generate descriptives. This is mostly there for other researchers to verify our procedure.
DOI: 10.17894/ucph.7a8048f2-663f-44d1-be61-878ff36263df
title: Modelling pesticide degradation and leaching in Conservation Agriculture: effect of no-till and mulching
DOI: 10.5519/qd.bufhi1rl
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1108971 records)
DOI: 10.5517/ccdc.csd.cc2797tm
title: CCDC 2064470: Experimental Crystal Structure Determination

description: Related Article: Fawad Ahmad,  Nasir Abbas,  Ayesha Ihsan,  Muhammad Saqib Ghafoor,  Ghulam Shabir,  Aamer Saeed|2023|Transition Met.Chem.|48|343|doi:10.1007/s11243-023-00547-6
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/ccdc.csd.cc27lq2n
title: CCDC 2073561: Experimental Crystal Structure Determination

description: Related Article: Etienne V. Brouillet, Scott A. Brown, Alan R. Kennedy, Annabel Rae, Heather P. Walton, Stuart D. Robertson|2023|Dalton Trans.|52|13332|doi:10.1039/D3DT02669H
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/ccdc.csd.cc27lq3p
title: CCDC 2073562: Experimental Crystal Structure Determination

description: Related Article: Etienne V. Brouillet, Scott A. Brown, Alan R. Kennedy, Annabel Rae, Heather P. Walton, Stuart D. Robertson|2023|Dalton Trans.|52|13332|doi:10.1039/D3DT02669H
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/ccdc.csd.cc27lq4q
title: CCDC 2073563: Experimental Crystal Structure Determination

description: Related Article: Etienne V. Brouillet, Scott A. Brown, Alan R. Kennedy, Annabel Rae, Heather P. Walton, Stuart D. Robertson|2023|Dalton Trans.|52|13332|doi:10.1039/D3DT02669H
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/ccdc.csd.cc27lq5r
title: CCDC 2073564: Experimental Crystal Structure Determination

description: Related Article: Etienne V. Brouillet, Scott A. Brown, Alan R. Kennedy, Annabel Rae, Heather P. Walton, Stuart D. Robertson|2023|Dalton Trans.|52|13332|doi:10.1039/D3DT02669H
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/ccdc.csd.cc27lq6s
title: CCDC 2073565: Experimental Crystal Structure Determination

description: Related Article: Etienne V. Brouillet, Scott A. Brown, Alan R. Kennedy, Annabel Rae, Heather P. Walton, Stuart D. Robertson|2023|Dalton Trans.|52|13332|doi:10.1039/D3DT02669H
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/ccdc.csd.cc2brrzv
title: CCDC 2167798: Experimental Crystal Structure Determination

description: Related Article: Xiaohui Li,  Bingqian Wang,  Yue Gao,  Guocheng Liu,  Xiuli Wang|2023|Transition Met.Chem.|48|307|doi:10.1007/s11243-023-00544-9
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/ccdc.csd.cc2brs2z
title: CCDC 2167801: Experimental Crystal Structure Determination

description: Related Article: Xiaohui Li,  Bingqian Wang,  Yue Gao,  Guocheng Liu,  Xiuli Wang|2023|Transition Met.Chem.|48|307|doi:10.1007/s11243-023-00544-9
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/ccdc.csd.cc2c6hhl
title: CCDC 2180989: Experimental Crystal Structure Determination

description: Related Article: Songlin Fang, Kaihui Zhong, Shaogao Zeng, Xinwei Hu, Pinghua Sun, Zhixiong Ruan|2023|Chem.Commun.|59|11425|doi:10.1039/D3CC02852F
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/ccdc.csd.cc2c6hjm
title: CCDC 2180990: Experimental Crystal Structure Determination

description: Related Article: Songlin Fang, Kaihui Zhong, Shaogao Zeng, Xinwei Hu, Pinghua Sun, Zhixiong Ruan|2023|Chem.Commun.|59|11425|doi:10.1039/D3CC02852F
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/ccdc.csd.cc2cqb0g
title: CCDC 2196195: Experimental Crystal Structure Determination

description: Related Article: Manish Rana, Hungharla Hungyo, Palak Parashar, Shaban Ahmad, Rabiya Mehandi, Vibha Tandon, Khalid Raza, Mohammed A. Assiri, Tarik E. Ali, Zeinhom M. El-Bahy, Rahisuddin|2023|RSC Advances|13|26766|doi:10.1039/D3RA04873J
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: 10.5281/zenodo.8330995
title: Data on publication volumes for selected open access journals and platforms

description: This dataset accompanies the report 'Scenario Modelling for Open Research Europe', prepared for the European Commission's Directorate-General for Research and Innovation by Rob Johnson of Research Consulting, acting in the capacity of an independent expert. The data was extracted from www.lens.org in May 2023 to asset historic patterns of publication growth for a sample of open access journals and platforms.
DOI: 10.5281/zenodo.8330996
title: Data on publication volumes for selected open access journals and platforms

description: This dataset accompanies the report 'Scenario Modelling for Open Research Europe', prepared for the European Commission's Directorate-General for Research and Innovation by Rob Johnson of Research Consulting, acting in the capacity of an independent expert. The data was extracted from www.lens.org in May 2023 to asset historic patterns of publication growth for a sample of open access journals and platforms.
DOI: 10.34740/kaggle/dsv/6584731
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.5281/zenodo.8393538
title: Simulation data for "Impact of Dynamic Phytoplankton Stoichiometry on Global Scale Patterns of Nutrient Limitation, Nitrogen Fixation, and Carbon Export"

description: Simulation data for our submission to GBC. Some of the files are compressed in order to minimize the size of the archive. Data files are stored as pickled python variables. The code for analysis of this data is in the github repository: https://github.com/georgehagstrom/BGCPaperFigureCode .