cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/icpsr38002.v1
title: Stroke Initiative for Gait Data Evaluation (STRIDE), [United States], 2012-2020
title: Version 1

description: STRIDE is an initiative based at the University of Southern California to create an inter-institutional, public database containing de-identified demographic and kinematic, kinetic, and spatiotemporal measures assessed via gait analysis in individuals post-stroke, to provide a larger and more heterogeneous research dataset than that typically amassed at a single institution. The data in STRIDE can be used to run pilot analyses and power calculations for research studies, design and validate statistical models to test associations between gait variables, provides data for simulation-based biomechanical studies in stroke, and provides data to assess the reproducibility of research findings, without the added data collection requirements.
description: The purpose of the study was to understand how persons post-stroke generate symmetric steps and how the resulting gait pattern relates to the metabolic cost of transport.
description: 55 persons post-stroke walked on an instrumented treadmill under two conditions: preferred walking and symmetric stepping (using visual feedback). Kinematic, kinetic, and metabolic data during both conditions were recorded.
description: Datasets: DS1: Stroke Initiative for Gait Data Evaluation (STRIDE), [United States], 2012-2020
description: Survivors of a first, unilateral stroke between 18 and 90 years of age across the United States who are able to walk on a treadmill for more than 2 minutes.
description: Data contributors for the database are: Ryan T. Roemmich, Ph.D., Johns Hopkins University James M. Finley, Ph.D., University of Southern California Gelsy Torres-Oviedo, Ph.D., University of Pittsburgh Trisha M. Kesar, PT, PhD., Emory University
DOI: 10.5281/zenodo.10496732
title: Dataset for the paper: Dynamic surrogate fitness landscapes in expensive bi-objective optimization
DOI: 10.5281/zenodo.10496733
title: Dataset for the paper: Dynamic surrogate fitness landscapes in expensive bi-objective optimization
DOI: 10.34740/kaggle/dsv/7409299
title: Full TMDB Movies Dataset 2023 (930K Movies)
DOI: 10.34740/kaggle/dsv/7409250
title: SnakeChat (datasets)
DOI: 10.34740/kaggle/dsv/7409323
title: Trending Youtube Video Statistics (113 Countries)
DOI: 10.34740/kaggle/dsv/7409433
title: Daily Public Opinion on Israel-Palestine War
DOI: 10.6084/m9.figshare.25000421
title: Annotated Assembled Genomes - Georgia, USA

description: The draft genomes of antibiotic-resistant bacteria isolated from imported fresh produce in Georgia, USA.
DOI: 10.6084/m9.figshare.25000421.v1
title: Annotated Assembled Genomes - Georgia, USA

description: The draft genomes of antibiotic-resistant bacteria isolated from imported fresh produce in Georgia, USA.
DOI: 10.34740/kaggle/dsv/7409467
title: Public Opinion on Climate Change (Updated Daily)
DOI: 10.34740/kaggle/dsv/7409488
title: Delicious,Fast, Satisfaction
DOI: 10.5517/ccdc.csd.cc2gjtsm
title: CCDC 2280291: Experimental Crystal Structure Determination

description: Related Article: Walla Alelwani, Afaf Almasoudi, Saad Alghamdi, Muhammad Nawaz Tahir, Ahmad Raheel, Ameer Hamza, Muhammad Babar Taj, Heba Alshater|2024|J.Mol.Struct.|1300|137271|doi:10.1016/j.molstruc.2023.137271
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.cc2glkk6
title: CCDC 2281958: Experimental Crystal Structure Determination

description: Related Article: , Lata Rana, Dheeraj Kumar, Geeta Hundal|2023|CSD Communication|||
description: Related Article: Lata Rana, Rughani Kashyap Mahendrabhai, Dheeraj, Meghal A. Desai, Geeta Hundal|2024|J.Mol.Struct.|1298|137103|doi:10.1016/j.molstruc.2023.137103
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: 10.35097/1446
title: Laboratory Equipment, Software, Consumables, and Tribological Specimens for Tribological Experiments - Sapphire on Copper - FAIR Dataset

description: This dataset contains FAIR records which describe the laboratory equipment, software, consumables, and tribological specimens utilized in the Materials Tribology Lab at the Karlsruhe Institute of Technology.
DOI: 10.35097/1457
title: Raw Data to Publication in Tribology Letters "Waviness Affects Friction and Abrasive Wear"

description: Raw Data behind publication "Waviness Affects Friction and Abrasive Wear"
DOI: 10.5281/zenodo.7768713
title: S-LDSC reference files

description: #1/15/2024: New version includes 107 independent summary statistics in the file sumstats_indep107.tgz#8/28/2023: New version includes the file hm3_no_MHC.list

Files required to partition heritability with S-LDSC.

Reference, baseline and baseline-LD files for EUR populations:1000G_Phase3_baseline_v1.2_ldscores.tgz1000G_Phase3_baselineLD_v2.2_ldscores.tgz1000G_Phase3_baselineLD_v2.3_ldscores.tgz1000G_Phase3_frq.tgz1000G_Phase3_ldscores.tgz1000G_Phase3_plinkfiles.tgz1000G_Phase3_weights_hm3_no_MHC.tgzbaselineLD_v2.2_bedfiles.tgzGRCh38.tgzreadme_baseline_versions

Sumstats files for EUR populations:sumstats_indep107.tgz (NEW)sumstats.tgz (old)

Reference, baseline and baseline-LD files for EAS populations:1000G_Phase3_EAS_baseline_v1.2_ldscores.tgz1000G_Phase3_EAS_baselineLD_v2.2_ldscores.tgz1000G_Phase3_EAS_plinkfiles.tgz1000G_Phase3_EAS_weights_hm3_no_MHC.tgzList of HapMap3 SNPs outputed when computing LD scores:hm3_no_MHC.list
DOI: 10.5281/zenodo.7768714
title: S-LDSC reference files

description: Files required to partition heritability with S-LDSC. Reference, baseline and baseline-LD files for EUR populations:<br> 1000G_Phase3_baseline_v1.2_ldscores.tgz<br> 1000G_Phase3_baselineLD_v2.2_ldscores.tgz<br> 1000G_Phase3_frq.tgz<br> 1000G_Phase3_ldscores.tgz<br> 1000G_Phase3_plinkfiles.tgz<br> 1000G_Phase3_weights_hm3_no_MHC.tgz<br> baselineLD_v2.2_bedfiles.tgz<br> GRCh38.tgz<br> readme_baseline_versions Sumstats files for EUR populations:<br> sumstats.tgz Reference, baseline and baseline-LD files for EAS populations:<br> 1000G_Phase3_EAS_baseline_v1.2_ldscores.tgz<br> 1000G_Phase3_EAS_baselineLD_v2.2_ldscores.tgz<br> 1000G_Phase3_EAS_plinkfiles.tgz<br> 1000G_Phase3_EAS_weights_hm3_no_MHC.tgz
DOI: 10.5281/zenodo.7796478
title: S-LDSC reference files

description: Files required to partition heritability with S-LDSC. Reference, baseline and baseline-LD files for EUR populations:<br> 1000G_Phase3_baseline_v1.2_ldscores.tgz<br> 1000G_Phase3_baselineLD_v2.2_ldscores.tgz<br> 1000G_Phase3_baselineLD_v2.3_ldscores.tgz<br> 1000G_Phase3_frq.tgz<br> 1000G_Phase3_ldscores.tgz<br> 1000G_Phase3_plinkfiles.tgz<br> 1000G_Phase3_weights_hm3_no_MHC.tgz<br> baselineLD_v2.2_bedfiles.tgz<br> GRCh38.tgz<br> readme_baseline_versions Sumstats files for EUR populations:<br> sumstats.tgz Reference, baseline and baseline-LD files for EAS populations:<br> 1000G_Phase3_EAS_baseline_v1.2_ldscores.tgz<br> 1000G_Phase3_EAS_baselineLD_v2.2_ldscores.tgz<br> 1000G_Phase3_EAS_plinkfiles.tgz<br> 1000G_Phase3_EAS_weights_hm3_no_MHC.tgz
DOI: 10.5281/zenodo.8292725
title: S-LDSC reference files

description: #8/28/2023: New version includes the file hm3_no_MHC.list Files required to partition heritability with S-LDSC. Reference, baseline and baseline-LD files for EUR populations:<br> 1000G_Phase3_baseline_v1.2_ldscores.tgz<br> 1000G_Phase3_baselineLD_v2.2_ldscores.tgz<br> 1000G_Phase3_baselineLD_v2.3_ldscores.tgz<br> 1000G_Phase3_frq.tgz<br> 1000G_Phase3_ldscores.tgz<br> 1000G_Phase3_plinkfiles.tgz<br> 1000G_Phase3_weights_hm3_no_MHC.tgz<br> baselineLD_v2.2_bedfiles.tgz<br> GRCh38.tgz<br> readme_baseline_versions Sumstats files for EUR populations:<br> sumstats.tgz Reference, baseline and baseline-LD files for EAS populations:<br> 1000G_Phase3_EAS_baseline_v1.2_ldscores.tgz<br> 1000G_Phase3_EAS_baselineLD_v2.2_ldscores.tgz<br> 1000G_Phase3_EAS_plinkfiles.tgz<br> 1000G_Phase3_EAS_weights_hm3_no_MHC.tgz<br> <br> List of HapMap3 SNPs outputed when computing LD scores:<br> hm3_no_MHC.list
DOI: 10.25919/8f4r-bt17
title: ME4OH - EN4.1.1 sampled OFAM3 raw synthetic profiles and monthly gridded OFAM3 sea surface temperature and surface height

description: Evaluating past ocean heat content change using synthetic observations: the MapEval4OceanHeat initiative
DOI: 10.26186/149105
title: P5023 Yathong Magnetic Gradient and Radiometric Survey, NSW, 2023

description: Geoscience Australia (GA), in collaboration with the New South Wales (NSW) Government’s Geological Survey of NSW, undertook a horizontal magnetic gradient and radiometric survey in the Yathong area of NSW. This survey was fully funded by the NSW Government as part of a project to find deep groundwater for use in times of drought.<br>Survey Name: YathongDatasets Acquired: Horizontal Magnetic Gradient, Radiometrics, and ElevationGeoscience Australia Project Number: P5023Acquisition Start Date: 21/05/2023Acquisition End Date: 14/09/2023Flight line spacing: 200 mFlight line direction: East-West (090-270 degrees)Total distance flown: 65,503.75 line-km'sNominal terrain clearance: 80 mData Acquisition: Magspec Airborne Surveys Pty LtdProject Management: Geoscience AustraliaQuality Control: Geoscience AustraliaDataset Ownership: Geological Survey of New South WalesDatum: Geocentric Datum of Australia 2020 (GDA2020)Projection: Map Grid of Australia Zone 55 (MGA55)<br>Included in this release:<br>1. Point-located Data - ASCII-column (.dat) and NetCDF (.nc) format.• Magnetic diurnal;• Magnetic gradient raw-edited;• Magnetic gradient reduced;• Radiometrics raw-edited;• Radiometrics reduced.<br>2. Gridded data - ERMapper (.ers) format.• Gradient enhanced Total Magnetic Intensity (TMI);• Gradient enhanced TMI Reduced to Pole (RTP);• Gradient enhanced TMI RTP with First Vertical Derivative (1VD);• Dose rate (with NASVD and standard processing);• Potassium concentration (with NASVD, standard processing);• Thorium concentration (with NASVD, standard processing);• Uranium concentration (with NASVD, standard processing);• Radar-derived digital elevation model (geoidal).<br>3. Reports.• Calibration report;• Operations and processing summary report.
DOI: 10.5281/zenodo.10515826
title: Fluidsyndicate: Open source materials for performances
DOI: 10.5281/zenodo.10515827
title: Fluidsyndicate: Open source materials for performances
DOI: 10.6084/m9.figshare.25000463
title: Electronic supplementary material from “Synthesis of pyrimido[4,5-b]quinoline -4,6-diones and formylation: Ultrasonically assisted reactions”.

description: Ultrasound-assisted synthesis of 5-aryl-tetrahydropyrimido[4,5-b]quinolindione derivatives 4 and 5 via a multicomponent reaction and subsequent formylation with Vilsmeier-Haack reagent were performed. Compounds were prepared by a one-pot method from 6-amino-3-methyl-2-(methylthio)pyrimidin-4(3H)-one or 6-amino-2-methoxy-3-methylpyrimidin-4(3H)-one, dimedone, and aromatic aldehydes through a Mannich-type reaction sequence, and then functionalized under ultrasound irradiation and Vilsmeier-Haack conditions to give β-chlorovinylaldehyde products. Ultrasonically assisted reactions, experimental simplicity, good yields without using metallic catalysts, and the control of hazardous material release are features of this simple procedure.
DOI: 10.6084/m9.figshare.25000463.v1
title: Electronic supplementary material from “Synthesis of pyrimido[4,5-b]quinoline -4,6-diones and formylation: Ultrasonically assisted reactions”.

description: Ultrasound-assisted synthesis of 5-aryl-tetrahydropyrimido[4,5-b]quinolindione derivatives 4 and 5 via a multicomponent reaction and subsequent formylation with Vilsmeier-Haack reagent were performed. Compounds were prepared by a one-pot method from 6-amino-3-methyl-2-(methylthio)pyrimidin-4(3H)-one or 6-amino-2-methoxy-3-methylpyrimidin-4(3H)-one, dimedone, and aromatic aldehydes through a Mannich-type reaction sequence, and then functionalized under ultrasound irradiation and Vilsmeier-Haack conditions to give β-chlorovinylaldehyde products. Ultrasonically assisted reactions, experimental simplicity, good yields without using metallic catalysts, and the control of hazardous material release are features of this simple procedure.
DOI: 10.5281/zenodo.10515766
title: dataset for "Type Ia Supernovae Can Arise from the Detonations of Both Stars in a Double Degenerate Binary"

description: Included here are datafiles supplementary to the article "Type Ia Supernovae Can Arise from the Detonations of Both Stars in a Double Degenerate Binary", submitted to ApJ/arxiv in January 2024. For each model, there are files for their final nuclear yields, complete (non-decayed) ejecta in 2D velocity space (Sedona input format), and 2D spectra that are calculated out to around 50 days. Models are labeled based on their progenitor mass, i.e. the model involving the 1.00 solar mass primary and 0.90 solar mass companion is called "m100_m090". The model with the suffix 'nosecdet' has a companion, but it is not ignited.
DOI: 10.5281/zenodo.10515767
title: dataset for "Type Ia Supernovae Can Arise from the Detonations of Both Stars in a Double Degenerate Binary"

description: Included here are datafiles supplementary to the article "Type Ia Supernovae Can Arise from the Detonations of Both Stars in a Double Degenerate Binary", submitted to ApJ/arxiv in January 2024. For each model, there are files for their final nuclear yields, complete (non-decayed) ejecta in 2D velocity space (Sedona input format), and 2D spectra that are calculated out to around 50 days. Models are labeled based on their progenitor mass, i.e. the model involving the 1.00 solar mass primary and 0.90 solar mass companion is called "m100_m090". The model with the suffix 'nosecdet' has a companion, but it is not ignited.
DOI: 10.25345/c52n4zv2z
title: MassIVE MSV000093870 - Single-cell proteomics reveals decreased abundance of proteostasis and meiosis proteins in advanced maternal age oocytes
title: Single-cell proteomics analysis of human oocytes from both young and old women
DOI: 10.17595/20240116.001
title: Atmospheric CH4 and N2O data from the flask air sampling over Surgut

description: This data set contains CH4 and N2O mole fractions observed over Surgut in western Siberia by the flask air sampling.
DOI: 10.5281/zenodo.7618944
title: Spatiotemporal Architecture of High-Grade Serous Ovarian Carcinoma

description: High-grade serous ovarian carcinoma (HGSOC), the deadliest form of ovarian cancer, is typically first diagnosed after it has metastasized and almost always relapses after standard-of-care platinum-based chemotherapy. Targeted therapies and immunotherapies are effective in only a small subset of patients, likely due to advanced tumor stage, inherent heterogeneity, and immune suppression and/or tumor-promoting signaling from the tumor microenvironment. There is a large gap in understanding how spatial heterogeneity and intercellular signaling contribute to HGSOC progression and early relapse. We used Imaging Mass Cytometry (IMC) and a HGSOC tissue microarray of patient-matched pre-chemotherapy primary tumors, synchronous metastases, and metachronous post-chemotherapy recurrent metastases from 42 patients to determine the spatiotemporal arrangement of different cell types during HGSOC progression. We found that tumors from patients with early relapse exhibit distinct patterns of immune cells, fibroblasts, and epithelial cells, including malformed tertiary lymphoid structures and increased presence of podoplanin-expressing fibroblasts. Changes in T cell localization between primary and synchronous metastatic tumors were also associated with early relapse, independent of the concentration of total T cells. Our highly multiplexed IMC data was consistent with data obtained by standard histology and immunohistochemistry and also demonstrated the additive value of highly multiplexed analyses.
DOI: 10.5281/zenodo.7618945
title: Spatiotemporal Architecture of High-Grade Serous Ovarian Carcinoma

description: High-grade serous ovarian carcinoma (HGSOC), the deadliest form of ovarian cancer, is typically first diagnosed after it has metastasized and almost always relapses after standard-of-care platinum-based chemotherapy. Targeted therapies and immunotherapies are effective in only a small subset of patients, likely due to advanced tumor stage, inherent heterogeneity, and immune suppression and/or tumor-promoting signaling from the tumor microenvironment. There is a large gap in understanding how spatial heterogeneity and intercellular signaling contribute to HGSOC progression and early relapse. We used Imaging Mass Cytometry (IMC) and a HGSOC tissue microarray of patient-matched pre-chemotherapy primary tumors, synchronous metastases, and metachronous post-chemotherapy recurrent metastases from 42 patients to determine the spatiotemporal arrangement of different cell types during HGSOC progression. We found that tumors from patients with early relapse exhibit distinct patterns of immune cells, fibroblasts, and epithelial cells, including malformed tertiary lymphoid structures and increased presence of podoplanin-expressing fibroblasts. Changes in T cell localization between primary and synchronous metastatic tumors were also associated with early relapse, independent of the concentration of total T cells. Our highly multiplexed IMC data was consistent with data obtained by standard histology and immunohistochemistry and also demonstrated the additive value of highly multiplexed analyses.
DOI: 10.34740/kaggle/dsv/7409731
title: Public Opinion Russia Ukraine War (Updated Daily)
DOI: 10.5281/zenodo.10515878
title: Swift/BAT-GUANO upper limits fits map for S240109a
DOI: 10.5281/zenodo.10515879
title: Swift/BAT-GUANO upper limits fits map for S240109a
DOI: 10.5281/zenodo.10449844
title: Dataset: A population perspective on international students in Australian universities

description: Dataset that underlies the paper 'A population perspective on international students in Australian universities' by Heller and Leeder, where we explore the contribution to global educational equity through population rates of international student enrolment in Australian universities. Paper is submitted for publication.
DOI: 10.5281/zenodo.10449845
title: Dataset: A population perspective on international students in Australian universities

description: Dataset that underlies the paper 'A population perspective on international students in Australian universities' by Heller and Leeder, where we explore the contribution to global educational equity through population rates of international student enrolment in Australian universities. Paper is submitted for publication.
DOI: 10.5281/zenodo.10515886
title: Dataset: A population perspective on international students in Australian universities

description: Dataset that underlies the paper 'A population perspective on international students in Australian universities' by Heller and Leeder, where we explore the contribution to global educational equity through population rates of international student enrolment in Australian universities. Paper is submitted for publication.
DOI: 10.5281/zenodo.10511420
title: CARLA Simulation Datasets for Training, Validation, and Test Data of the project "Out-Of-Domain Data Detection using Uncertainty Quantification in End-to-End Driving Algorithms"

description: These are CARLA Simulation Datasets of the project "Out-Of-Domain Data Detection using Uncertainty Quantification in End-to-End Driving Algorithms". The simulations are generated in CARLA Town 02 for different sun angles (in degrees).  You will find image frames, command labels, and steering control values in the respective 'xxxx_files_data' folder. You will find videos of each simulation run in the 'xxxx_files_visualizations' folder.

 

The 8 simulation runs for Training Data, are with the Sun Angles : 90, 80, 70, 60, 50, 40, 30, 20 

The 8 simulation runs for Training Data were seeded at 0000, 1000, 2000, 3000, 4000, 5000, 6000, 7000 respectively

 

The 4 simulation runs for Validation Data, are with the Sun Angles : 87, 67, 47, 23

The 4 simulation runs for Validation Data were seeded at 0000, 2000, 4000, 7000 respectively

 

The 29 simulation runs for Testing Data, are with the Sun Angles : 85, 75, 65, 55, 45, 35, 25, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 09, 08, 07, 06, 05, 04, 03, 02, 01, 00, -1, -10

The 29 simulation runs for Testing Data were all seeded at 5000 respectively
DOI: 10.5281/zenodo.10511421
title: CARLA Simulation Datasets for Training, Validation, and Test Data of the project "Out-Of-Domain Data Detection using Uncertainty Quantification in End-to-End Driving Algorithms"

description: These are CARLA Simulation Datasets of the project "Out-Of-Domain Data Detection using Uncertainty Quantification in End-to-End Driving Algorithms". The simulations are generated in CARLA Town 02 for different sun angles (in degrees).  You will find image frames, command labels, and steering control values in the respective 'xxxx_files_data' folder. You will find videos of each simulation run in the 'xxxx_files_visualizations' folder.

 

The 8 simulation runs for Training Data, are with the Sun Angles : 90, 80, 70, 60, 50, 40, 30, 20 

The 8 simulation runs for Training Data were seeded at 0000, 1000, 2000, 3000, 4000, 5000, 6000, 7000 respectively

 

The 4 simulation runs for Validation Data, are with the Sun Angles : 87, 67, 47, 23

The 4 simulation runs for Validation Data were seeded at 0000, 2000, 4000, 7000 respectively

 

The 29 simulation runs for Testing Data, are with the Sun Angles : 85, 75, 65, 55, 45, 35, 25, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 09, 08, 07, 06, 05, 04, 03, 02, 01, 00, -1, -10

The 29 simulation runs for Testing Data were all seeded at 5000 respectively
DOI: 10.5281/zenodo.10515889
title: CoderEval

description: Dataset for CoderEval
DOI: 10.5281/zenodo.10515890
title: CoderEval

description: Dataset for CoderEval
DOI: 10.5281/zenodo.10515913
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Joan Dingley, http://www.wikidata.org/entity/Q6205005. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q6205005
DOI: 10.5281/zenodo.8288216
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Joan Dingley, http://www.wikidata.org/entity/Q6205005. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q6205005
DOI: 10.5281/zenodo.8288217
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Joan Dingley, http://www.wikidata.org/entity/Q6205005. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q6205005
DOI: 10.5281/zenodo.10515917
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Betty Molesworth Allen, http://www.wikidata.org/entity/Q16537579. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q16537579