cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2bzksp
title: CCDC 2174333: Experimental Crystal Structure Determination

description: Related Article: Suman Dhara, Sanchaita Dey, Sanjib Panda, Goutam Kumar Lahiri|2022|Inorg.Chem.|61|14297|doi:10.1021/acs.inorgchem.2c01866
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.cc2bzktq
title: CCDC 2174334: Experimental Crystal Structure Determination

description: Related Article: Suman Dhara, Sanchaita Dey, Sanjib Panda, Goutam Kumar Lahiri|2022|Inorg.Chem.|61|14297|doi:10.1021/acs.inorgchem.2c01866
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.cc2bzkvr
title: CCDC 2174335: Experimental Crystal Structure Determination

description: Related Article: Suman Dhara, Sanchaita Dey, Sanjib Panda, Goutam Kumar Lahiri|2022|Inorg.Chem.|61|14297|doi:10.1021/acs.inorgchem.2c01866
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.cc2bzkws
title: CCDC 2174336: Experimental Crystal Structure Determination

description: Related Article: Suman Dhara, Sanchaita Dey, Sanjib Panda, Goutam Kumar Lahiri|2022|Inorg.Chem.|61|14297|doi:10.1021/acs.inorgchem.2c01866
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.cc2c0l88
title: CCDC 2175309: Experimental Crystal Structure Determination

description: Related Article: Zheng Zeng, Yiqiu Deng, Lanyu Li, Chungang Li, Mingli Zhong|2022|J.Org.Chem.|87|12257|doi:10.1021/acs.joc.2c01436
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.7086176
title: Table S1. Mean longevity of gamma-sterilized male Ae. aegypti post-treatment by density, temperature, and duration factors

description: This Table descibe mean longevity of gamma-sterilized male <em>Ae</em>. <em>aegypti</em> post-treatment by density, temperature, and duration factors.
DOI: 10.5281/zenodo.7086175
title: Table S1. Mean longevity of gamma-sterilized male Ae. aegypti post-treatment by density, temperature, and duration factors

description: This Table descibe mean longevity of gamma-sterilized male <em>Ae</em>. <em>aegypti</em> post-treatment by density, temperature, and duration factors.
DOI: 10.3886/e164521v1
title: Data and Code for: "The Macroeconomic Impact of Europe’s Carbon Taxes"

description: We estimate the macroeconomic impacts of carbon taxes on GDP and employment growth rates using 30 years of data on carbon taxation in various European countries. We find no evidence for a negative impact on employment or GDP growth but rather find a zero to modest positive impact. We also find a cumulative emissions reduction on the order of 4 to 6 percent for a $40/ton CO2 tax covering 30% of emissions. Reductions would likely be greater for a broad-based U.S. carbon tax since European carbon taxes typically do not cover those sectors with the lowest marginal abatement costs. <br><br><br><br><br>
description: GDP and Employment in EU countries<br>.
DOI: 10.5281/zenodo.7086186
title: IAA/CSIC Temperature and CO2 density profiles in Mars Year 34 retrieved from the 1st year of NOMAD/TGO solar occultation observations [dataset]

description: Dataset associated to manuscript 2022JE007278, "Martian atmospheric temperature and density profiles during the 1st year of NOMAD/TGO solar occultation measurements", submitted on Feb 28th, 2022, to Journal of Geophysical Research - Planets (AGU) for the Special Issue "ExoMars Trace Gas Orbiter: One Martian Year of Science". Format and Number of datafiles: 1 README.txt and 1 tar file containing 325 ASCII files, one for each retrieved NOMAD scan. Each of these files contains one vertical profile of 7 parameters: altitude (km), Temperature in the last iteration (K), atmospheric pressure (mb), Temperature of First Guess (K), pressure of First Guess (mb), Temperature retrieval error (K) and diagonal element fo the Averaging Kernel matrix at that tangent altitude (normalized to 0-1). Also, the header of each file contains extra info, like the NOMAD "internal" data filename, and the ranges in latitude, longitude, Local time, Solar Longitude, tangent heights observed, and Line-of-Sight shift needed to obtain a good fit, together with the number of altitudes in the retrieval vector (usually around 100 km). See README file for more details.<br>
DOI: 10.5281/zenodo.7075055
title: Data From: Emulation of Cardiac Mechanics using Graph Neural Networks

description: Contains simulation results of the forward displacement from beginning to end-diastole for approximately 3000 synthetically generated left ventricle geometries. The simulation results are split into training, validation and test data. The data is described in detail in a forthcoming publication in <em>Computer Methods in Applied Mechanics and Engineering</em> - further information will be provided upon publication. A GitHub repository will also be made available, with code for processing the simulation data and training a Graph Neural Network emulator.
DOI: 10.5281/zenodo.7075054
title: Data From: Emulation of Cardiac Mechanics using Graph Neural Networks

description: Contains simulation results of the forward displacement from beginning to end-diastole for approximately 3000 synthetically generated left ventricle geometries. The simulation results are split into training, validation and test data. The data is described in detail in a forthcoming publication in <em>Computer Methods in Applied Mechanics and Engineering</em> - further information will be provided upon publication. A GitHub repository will also be made available, with code for processing the simulation data and training a Graph Neural Network emulator.
DOI: 10.6084/m9.figshare.6741431.v16
title: COCI CSV dataset of the provenance information of all the citation data

description: This dataset contains the provenance information (in CSV format) of all the citation data included in COCI, released on 31 August 2022. In particular, each line of the CSV file defines a citation, and includes the following information: <strong>[field "oci"]</strong> the Open Citation Identifier (OCI) for the citation; <strong>[field "agent"]</strong> the name of the agent that have created the citation data; <strong>[field "source"]</strong> the URL of the source dataset from where the citation data have been extracted; <strong>[field "datetime"]</strong> the creation time of the citation data. The size of the zipped archive is 19.71 GB, while the size of the unzipped CSV file is 308 GB.Additional information about COCI can be retrieved in the <sub>official webpage</sub>.
DOI: 10.34740/kaggle/dsv/4212646
title: Mahanagar Yatayat Dataset
DOI: 10.48366/r217120
title: Sports Science Motor Research Data: Subsample Power

description: Subset comparison of four studies of motor research data with participants aged 4 to 28 years on the factor power (standing long jump).
DOI: 10.5519/qd.d9mubg1w
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (31 records)
DOI: 10.5281/zenodo.6925936
title: A Survey of Electron Conics at Jupiter Utilizing the JADE-E Data During Science Orbits 01, 03-30

description: This dataset provides Figure 1 from the AGU <em>JGR: Space Physics</em> article of the same name as a PNG image. It also includes text files with the data to reproduce Figures 2-13 in the same AGU <em>JGR:Space Physics</em> article. <strong>Key Points:</strong> We surveyed the JADE-E data for science orbits 01, 03-30 and found upward, downward, and bidirectional electron conics 2.5% of the time We observed all electron conics to occur most often at altitudes of 0.3-0.4 R<sub>J</sub> and local times of 15-16h We observed all electron conic types to have energies greater than 0.7 keV below an altitude of 0.5 R<sub>J</sub> and over the main auroral region <strong>Abstract</strong> We present a survey of electron conics over Jupiter’s high latitude regions utilizing 22.6 hours of data from the Jovian Auroral Distribution Experiment electron (JADE-E) instrument aboard NASA’s Juno spacecraft during science orbits 01 and 03-30. We observed electron conics for about 2.5% of this time and characterized them into three types based on their direction of motion along Jupiter’s magnetic field lines: upward, downward, and bidirectional. We observed the upward electron conics most often and at energies of 0.057-80.1 keV, while we observed the downward electron conics least often and at energies of 0.073-1.2 keV. We observed bidirectional electron conics mostly around the same times and places as the upward electron conics having energies of 0.081-49.6 keV. We observed all electron conic types to occur mostly at altitudes 0.3-0.4 R<sub>J</sub> and local times 15-16h. Furthermore, we observed all electron conic types to have energies greater than 0.7 keV below an altitude of 0.5 R<sub>J</sub> and over the main auroral region.
DOI: 10.5281/zenodo.6925935
title: A Survey of Electron Conics at Jupiter Utilizing the JADE-E Data During Science Orbits 01, 03-30

description: This dataset provides Figure 1 from the AGU <em>JGR: Space Physics</em> article of the same name as a PNG image. It also includes text files with the data to reproduce Figures 2-13 in the same AGU <em>JGR:Space Physics</em> article. <strong>Key Points:</strong> We surveyed the JADE-E data for science orbits 01, 03-30 and found upward, downward, and bidirectional electron conics 2.5% of the time We observed all electron conics to occur most often at altitudes of 0.3-0.4 R<sub>J</sub> and local times of 15-16h We observed all electron conic types to have energies greater than 0.7 keV below an altitude of 0.5 R<sub>J</sub> and over the main auroral region <strong>Abstract</strong> We present a survey of electron conics over Jupiter’s high latitude regions utilizing 22.6 hours of data from the Jovian Auroral Distribution Experiment electron (JADE-E) instrument aboard NASA’s Juno spacecraft during science orbits 01 and 03-30. We observed electron conics for about 2.5% of this time and characterized them into three types based on their direction of motion along Jupiter’s magnetic field lines: upward, downward, and bidirectional. We observed the upward electron conics most often and at energies of 0.057-80.1 keV, while we observed the downward electron conics least often and at energies of 0.073-1.2 keV. We observed bidirectional electron conics mostly around the same times and places as the upward electron conics having energies of 0.081-49.6 keV. We observed all electron conic types to occur mostly at altitudes 0.3-0.4 R<sub>J</sub> and local times 15-16h. Furthermore, we observed all electron conic types to have energies greater than 0.7 keV below an altitude of 0.5 R<sub>J</sub> and over the main auroral region.
DOI: 10.48366/r217123
title: Sports Science Motor Research Data: Subsample Flexibility

description: Subset comparison of four studies of motor research data with participants aged 4 to 28 years on the factor flexibility (stand-and-reach).
DOI: 10.5281/zenodo.3754167
title: RIFIR – A Far Infrared Dataset

description: This dataset consists of sequences acquired in an urban environment with two cameras (one Far Infrared and two color cameras in stereovision) mounted on the exterior of a vehicle. Training dataset: 14788 frames (containing aprox. 19000 pedestrain bounding boxes in visible spectrum and aprox. 14000 in infrared spectrum) of 138 unique pedestrians Testing dataset: 9373 frames ( containing aprox. 7000 pedestrain bounding boxes in visible spectrum and aprox. 6000 in infrared spectrum) of 33 unique pedestrians You can cite this dataset by: Miron, Alina Dana. "Multi-modal, Multi-Domain Pedestrian Detection and Classification: Proposals and Explorations in Visible over StereoVision, FIR and SWIR." PhD diss., 2014.
DOI: 10.5281/zenodo.3754168
title: RIFIR – A Far Infrared Dataset

description: This dataset consists of sequences acquired in an urban environment with two cameras (one Far Infrared and two color cameras in stereovision) mounted on the exterior of a vehicle. Training dataset: 14788 frames (containing aprox. 19000 pedestrain bounding boxes in visible spectrum and aprox. 14000 in infrared spectrum) of 138 unique pedestrians Testing dataset: 9373 frames ( containing aprox. 7000 pedestrain bounding boxes in visible spectrum and aprox. 6000 in infrared spectrum) of 33 unique pedestrians You can cite this dataset by: Miron, Alina Dana. "Multi-modal, Multi-Domain Pedestrian Detection and Classification: Proposals and Explorations in Visible over StereoVision, FIR and SWIR." PhD diss., 2014.
DOI: 10.6084/m9.figshare.6741446.v16
title: COCI N-Triples dataset of the provenance information of all the citation data

description: This dataset contains the provenance information (in N-Triples format) of all the citation data included in COCI, released on 31 August 2022. In particular, any citation in the dataset includes the following provenance information: <strong>[citation IRI]</strong> the Open Citation Identifier (OCI) for the citation, defined in the final part of the URL identifying the citation (https://w3id.org/oc/index/coci/ci/[OCI]);; <strong>[property "prov:wasAttributedTo"]</strong> the IRI of the agent that have created the citation data; <strong>[property "prov:hadPrimarySource"]</strong> the IRI of the source dataset from where the citation data have been extracted; <strong>[property "prov:generatedAtTime"]</strong> the creation time of the citation data. The size of the zipped archive is 72.5 GB, while the size of the unzipped N-Triples file is 3.08 TB.Additional information about COCI can be retrieved in the <sub>official webpage</sub>.
DOI: 10.5281/zenodo.7072866
title: REVEL (Rare Exome Variant Ensemble Learner) Scores

description: REVEL is an ensemble method for predicting the pathogenicity of missense variants in the human genome. For more information, see https://sites.google.com/site/revelgenomics/ and https://dx.doi.org/10.1016/j.ajhg.2016.08.016.
description: {"references": ["Ioannidis NM, Rothstein JH, Pejaver V, Middha S, McDonnell SK, Baheti S, Musolf A, Li Q, Holzinger E, Karyadi D, Cannon-Albright LA, Teerlink CC, Stanford JL, Isaacs WB, Xu J, Cooney KA, Lange EM, Schleutker J, Carpten JD, Powell IJ, Cussenot O, Cancel-Tassin G, Giles GG, MacInnis RJ, Maier C, Hsieh CL, Wiklund F, Catalona WJ, Foulkes WD, Mandal D, Eeles RA, Kote-Jarai Z, Bustamante CD, Schaid DJ, Hastie T, Ostrander EA, Bailey-Wilson JE, Radivojac P, Thibodeau SN, Whittemore AS, and Sieh W. \"REVEL: An ensemble method for predicting the pathogenicity of rare missense variants.\" American Journal of Human Genetics 2016; 99(4):877-885"]}
DOI: 10.5281/zenodo.7072865
title: REVEL (Rare Exome Variant Ensemble Learner) Scores

description: REVEL is an ensemble method for predicting the pathogenicity of missense variants in the human genome. For more information, see https://sites.google.com/site/revelgenomics/ and https://dx.doi.org/10.1016/j.ajhg.2016.08.016.
description: {"references": ["Ioannidis NM, Rothstein JH, Pejaver V, Middha S, McDonnell SK, Baheti S, Musolf A, Li Q, Holzinger E, Karyadi D, Cannon-Albright LA, Teerlink CC, Stanford JL, Isaacs WB, Xu J, Cooney KA, Lange EM, Schleutker J, Carpten JD, Powell IJ, Cussenot O, Cancel-Tassin G, Giles GG, MacInnis RJ, Maier C, Hsieh CL, Wiklund F, Catalona WJ, Foulkes WD, Mandal D, Eeles RA, Kote-Jarai Z, Bustamante CD, Schaid DJ, Hastie T, Ostrander EA, Bailey-Wilson JE, Radivojac P, Thibodeau SN, Whittemore AS, and Sieh W. \"REVEL: An ensemble method for predicting the pathogenicity of rare missense variants.\" American Journal of Human Genetics 2016; 99(4):877-885"]}
DOI: 10.5517/ccdc.csd.cc2cjs5w
title: CCDC 2190868: Experimental Crystal Structure Determination

description: Related Article: Li-Juan Wang, Sha Bai, Ying-Feng Han|2022|J.Am.Chem.Soc.|144|16191|doi:10.1021/jacs.2c07586
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.7086487
title: Incorporating Human Dimensions Improves Wildlife Translocation Outcomes

description: Raw dataset used for manuscript currently under review.
DOI: 10.5281/zenodo.7086486
title: Incorporating Human Dimensions Improves Wildlife Translocation Outcomes

description: Raw dataset used for manuscript currently under review.
DOI: 10.5287/bodleian:0zwddm7qm
title: Magmatic, Metamorphic and Structural History of the Variscan Lizard Ophiolite, Cornwall, UK, and its Metamorphic Sole
DOI: 10.6084/m9.figshare.21133570
title: actinopyga_echinites_zanfona_1.fasta.gz

description: ......
DOI: 10.6084/m9.figshare.21133570.v1
title: actinopyga_echinites_zanfona_1.fasta.gz

description: ......
DOI: 10.6084/m9.figshare.14776242
title: Geographic records of Anas bahamensis rubrirostris from mainland Ecuador

description: Occurrence data of Anas bahamesas rubrirostris from mainland Ecuador from different sources. Published records were synthesised based on a literature review, not limited by study type, study design, or language, conducted in Google Scholar™ scholarly text search (https://scholar.google.com) by online searches. We gathered relevant references using the search terms ‘<i>Anas bahamensis</i>’. Open metadata for all occurrences from mainland Ecuador were downloaded from eBird (https://ebird.org) by Cornell Lab of Ornithology (eBird 2020) and iNaturalist (https://www.inaturalist.org) by California Academy of Science and National Geographic (GBIF 2021). Data search and extraction from all sources were conducted in March 2020 and updated in April 2021. For each occurrence point, we compiled geographic data and all other associated information. Protocol for data curation and mining included validation of localities and duplicate detection. All localities were reviewed and validated individually, and coordinates were amended when incorrectly georeferenced in the source.
DOI: 10.6084/m9.figshare.14776242.v1
title: Geographic records of Anas bahamensis rubrirostris from mainland Ecuador

description: Occurrence data of Anas bahamesas rubrirostris from mainland Ecuador from different sources. Published records were synthesised based on a literature review, not limited by study type, study design, or language, conducted in Google Scholar™ scholarly text search (https://scholar.google.com) by online searches. We gathered relevant references using the search terms ‘<i>Anas bahamensis</i>’. Open metadata for all occurrences from mainland Ecuador were downloaded from eBird (https://ebird.org) by Cornell Lab of Ornithology (eBird 2020) and iNaturalist (https://www.inaturalist.org) by California Academy of Science and National Geographic (GBIF 2021). Data search and extraction from all sources were conducted in March 2020 and updated in April 2021. For each occurrence point, we compiled geographic data and all other associated information. Protocol for data curation and mining included validation of localities and duplicate detection. All localities were reviewed and validated individually, and coordinates were amended when incorrectly georeferenced in the source.
DOI: 10.5287/bodleian:2rq4mk50e
title: Contribution of Education to Economic Development
DOI: 10.5281/zenodo.7086557
title: Van de Ven et al 2022_Mitigation_DATASET

description: This dataset contains the underlying scenario protocol, input (socioeconomic assumptions), and output (model results) for the study by Van de Ven et al. on post-Glasgow climate action and feasibility gap
DOI: 10.5281/zenodo.7086556
title: Van de Ven et al 2022_Mitigation_DATASET

description: This dataset contains the underlying scenario protocol, input (socioeconomic assumptions), and output (model results) for the study by Van de Ven et al. on post-Glasgow climate action and feasibility gap
DOI: 10.34740/kaggle/dsv/4212962
title: Tales from the Pizza Guy
DOI: 10.17861/883889ef-8083-4550-93fb-3f9184d1a562
title: Data and code which can be used to recreate results from the paper: "Can root systems redistribute soil water to mitigate the effects of drought?"

description: Data and code will be made available on publication of the paper.
DOI: 10.6084/m9.figshare.21126169
title: Deposit thickness data for select model runs

description: We utilize thickness maps to measure rugosity of the simulated submarine fans. The maps are interpolated onto a Cartesian grid from raw data that is stored initially on a triangular irregular network (TIN). The grid transformation from TIN to a Cartesian grid is achieved using standard and publically available algorithms. We provide public access to four model runs that cover different corners of the regime diagram and contains subcritical, transcritical, and supercritical simulations. We subsample the number of thickness maps due to size limitations as an average model output data exceeds 1 terabyte. The processed maps are stored as 3D arrays that are structured in space (x-location) by space (y-location) by time (elevations). We also provide a Matlab script along with thickness data that can measure rugosity of the simulated submarine fans.
DOI: 10.6084/m9.figshare.21126169.v1
title: Deposit thickness data for select model runs

description: We utilize thickness maps to measure rugosity of the simulated submarine fans. The maps are interpolated onto a Cartesian grid from raw data that is stored initially on a triangular irregular network (TIN). The grid transformation from TIN to a Cartesian grid is achieved using standard and publically available algorithms. We provide public access to four model runs that cover different corners of the regime diagram and contains subcritical, transcritical, and supercritical simulations. We subsample the number of thickness maps due to size limitations as an average model output data exceeds 1 terabyte. The processed maps are stored as 3D arrays that are structured in space (x-location) by space (y-location) by time (elevations). We also provide a Matlab script along with thickness data that can measure rugosity of the simulated submarine fans.
DOI: 10.5281/zenodo.7086627
title: Example of data for 01 Knapsack problem

description: <strong>ks01</strong> is a set of 42 weights and profits for a knapsack of capacity 120. ks01_c.txt, the knapsack capacity. ks01_w.txt, the weights of the objects. ks01_p.txt, the profits of each object. ks01_s.txt, the optimal selection of weights.