cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5066/p9h652z8
title: Waterborne Gradient Self-potential, Temperature, and Conductivity Logging of the Upper part of the Delaware River between Hancock and Port Jervis, New York, June-July 2021

description: This data release contains waterborne gradient self-potential (SP), surface-water temperature, surface-water conductivity and specific conductance, and surface-water nitrate concentration data measured continuously in the upper part of the Delaware River along approximately 123 kilometers (km) between Hancock and Port Jervis, New York. All of the data were measured from a kayak between June 27 and July 2, 2021. Gradient self-potential data were measured along five survey segments that varied in length between 13.1 and 31.6 km. The first segment began at Hancock, N.Y. on the east branch of the Delaware River, progressed into the main stem, and ended about 13.1 river-km downstream in Lordville, N.Y. at U.S. Geological Survey (USGS) streamgage 01427207. The second segment began in Lordville, at USGS streamgage 01427207 and ended about 28.6 river-km downstream in Callicoon, N.Y. The third segment began in Callicoon, and ended about 31.5 river-km downstream in Narrowsburg, N.Y. The fourth segment began in Narrowsburg, and ended 15.3 river-km downstream in Barryville, N.Y., and the fifth segment began in Barryville, and ended 31.6 river-km downstream in Port Jervis, N.Y. Gradient SP voltage data contained in this data release were continuously logged at a period of 1 second per measurement along each of the five survey segments using an Agilent U1252B data-logging multimeter and a 0.55-meter long electric dipole comprised of two freshwater-submersible, non-polarizing copper-sulfate electrodes. Eleven separate electrode drift tests were performed to make electrode-drift corrections during data processing. At least one electrode-drift test was performed along each survey segment by leaving the kayak and the electrodes stationary in an eddy along the riverbank for 15 to 30 minutes while gradient SP voltages were continuously logged. Surface-water temperature and conductivity and specific conductance data were continuously logged along each survey segment with a YSI Pro DSS and In-Situ Aqua TROLL 500 multi-parameter water-quality sondes at a period of 5 seconds per sample. Surface-water nitrate concentration data were measured with the Aqua TROLL sonde only and are limited to the first four segments of the gradient SP survey covering a river distance of approximately 80 km. This data release includes more than 79,000 measurements of voltage from gradient SP logging in the river, 4,779 measurements of voltage logged during the electrode drift tests, 35,304 measurements each of surface-water temperature and conductivity, 20,543 measurements of surface-water nitrate concentration, and the geospatial coordinates of each measurement. Time-series of streamflow in cubic feet per second are included for five U.S. Geological Survey streamgages that are on survey reach. USGS streamflow data cover the time period between 12:00 AM eastern time on June 21, 2021 and 11:45 PM eastern time on July 3, 2021.
DOI: 10.5281/zenodo.5498369
title: Dataset for "Deep Learning with remote sensing data for image segmentation: example of rice crop mapping using Sentinel-2 images"

description: Dataset for "Deep Learning with remote sensing data for image segmentation: example of rice crop mapping using Sentinel-2 images". Contact Ricardo Dalagnol ricds@hotmail.com
DOI: 10.5281/zenodo.5498391
title: Characterizing the molecular mechanisms for flipping charged peptide flanking loops across a lipid bilayer

description: All simulation input data and analysis tools for regenerating results from the journal paper: S. J. Patel and R. C. Van Lehn. "Characterizing the Molecular Mechanisms for Flipping Charged Peptide Flanking Loops across a Lipid Bilayer." The Journal of Physical Chemistry B <strong>2018</strong> <em>122</em> (45), 10337-10348
DOI: 10.5281/zenodo.5498390
title: Characterizing the molecular mechanisms for flipping charged peptide flanking loops across a lipid bilayer

description: All simulation input data and analysis tools for regenerating results from the journal paper: S. J. Patel and R. C. Van Lehn. "Characterizing the Molecular Mechanisms for Flipping Charged Peptide Flanking Loops across a Lipid Bilayer." The Journal of Physical Chemistry B <strong>2018</strong> <em>122</em> (45), 10337-10348
DOI: 10.6073/pasta/30f58508a7b40aac0e1f3b5915ea3e32
title: Atmospheric pressure on Hog Island, Phillips Creek Marsh and Oyster, VA 2012-present

description: Barometric pressure is measured hourly at meteorological stations on the Atlantic Coast of the Delmarva Peninsula. Data is available as a long table that gives the average, minimum and maximum air pressure for each station at each time, or as a table that gives the average values for each of the stations, along with the median value across stations on each line.
DOI: 10.5517/ccdc.csd.cc28509s
title: CCDC 2090184: Experimental Crystal Structure Determination

description: Related Article: Seulgi Kim, Huiyeong Ju, Ki-Min Park, Jong Hwa Jung, Shim Sung Lee, Eunji Lee|2021|Inorg.Chem.|60|13637|doi:10.1021/acs.inorgchem.1c01943
DOI: 10.6084/m9.figshare.16592864
title: Bases de dato (sin procesar) y término de búsqueda de WoS y Scopus en Comscienciaeduspain

description: Bases de datos investigadores españoles que aparecen como autores de correspondencia en 12.680 trabajos indexados en Scopus y Wos en las áreas de Ciencias Sociales, Psicología, Arte & Humanidades, con el término de búsqueda ¨education¨, entre los años 2016-2020.<br>Se incluye operadores de búsqueda en ambos sistemas de indexación empleados.<br>Proyecto FCT-20-15761, ejecutado con la colaboración de la Fundación Española para la Ciencia y la Tecnología - Ministerio de Ciencia e Innovación. <br>Más información en: http://comscienciaeduspain.es/
DOI: 10.6084/m9.figshare.16592864.v1
title: Bases de dato (sin procesar) y término de búsqueda de WoS y Scopus en Comscienciaeduspain

description: Bases de datos investigadores españoles que aparecen como autores de correspondencia en 12.680 trabajos indexados en Scopus y Wos en las áreas de Ciencias Sociales, Psicología, Arte & Humanidades, con el término de búsqueda ¨education¨, entre los años 2016-2020.<br>Se incluye operadores de búsqueda en ambos sistemas de indexación empleados.<br>Proyecto FCT-20-15761, ejecutado con la colaboración de la Fundación Española para la Ciencia y la Tecnología - Ministerio de Ciencia e Innovación. <br>Más información en: http://comscienciaeduspain.es/
DOI: 10.6084/m9.figshare.9906200
title: A Curated ChIP-Seq Dataset of MDI-induced Differentiated Adipocytes (3T3-L1)

description: A curated dataset of publicly available ChIP-sequencing of transcription factors, chromatin remodelers and histone modifications in the 3T3-L1 pre-adipocyte cell line. The package document the data collection, pre-processing and processing of the data. In addition to the documentation, the package contains the scripts that was used to generated the data.<br>
DOI: 10.6084/m9.figshare.9906200.v1
title: A Curated ChIP-Seq Dataset of MDI-induced Differentiated Adipocytes (3T3-L1)

description: A curated dataset of publicly available ChIP-sequencing of transcription factors, chromatin remodelers and histone modifications in the 3T3-L1 pre-adipocyte cell line. The package document the data collection, pre-processing and processing of the data. In addition to the documentation, the package contains the scripts that was used to generated the data.<br>
DOI: 10.6084/m9.figshare.9906182
title: A Curated RNA-Seq Dataset of MDI-induced Differentiated Adipocytes (3T3-L1)

description: A curated dataset of RNA-Seq samples. The samples are MDI-induced pre-phagocytes (3T3-L1) at different time points/stage of differentiation. The package document the data collection, pre-processing and processing. In addition to the documentation, the package contains the scripts that was used to generated the data.
DOI: 10.5281/zenodo.5498424
title: Dataset for "Deep Learning with remote sensing data for image segmentation: example of rice crop mapping using Sentinel-2 images"

description: Dataset for "Deep Learning with remote sensing data for image segmentation: example of rice crop mapping using Sentinel-2 images". Contact Ricardo Dalagnol ricds@hotmail.com
DOI: 10.17632/9m96nytkt2.1
title: Data for: Phase difference-measuring multiple correlation-based superconducting magnet quench detection method

description: The original experimental data of Figure 3 in the manuscript.
DOI: 10.17632/k4s2ty9m8w.1
title: Data for: Arc-type intraplate volcanism generated by melting of lithospheric mantle pyroxenite of the South China continental margin

description: Supplementary data table S1-7.
DOI: 10.17632/j7jhvk3dhd.1
title: Experiment Results Data Set for the Study: Animation as a Dynamic Visualization Technique to Improve Process Model Comprehension

description: This data set includes the data of the results of the experiments performed in the process model animation experiment reported in the paper titled: Animation as a Dynamic Visualization Technique to Improve Process Model Comprehension
DOI: 10.17632/tp7mhmtyxy.1
title: Data Arnqvist et al. 2021

description: Data for "Direct and indirect effects of male genital elaboration in female seed beetles" by Göran Arnqvist, Karl Grieshop, Cosima Hotzy, Johanna Rönn, Michal Polak and Locke Rowe. Proceedings of the Royal Society of London (B) (2021).
DOI: 10.17632/j7jhvk3dhd.2
title: Experiment Results Data Set for the Study: Animation as a Dynamic Visualization Technique to Improve Process Model Comprehension

description: This data set includes the data of the results of the experiments performed in the process model animation experiment reported in the paper titled: Animation as a Dynamic Visualization Technique to Improve Process Model Comprehension
DOI: 10.6084/m9.figshare.16599164
title: Supplementary data 7

description: Supplementary data 7
DOI: 10.6084/m9.figshare.16599164.v1
title: Supplementary data 7

description: Supplementary data 7
DOI: 10.6084/m9.figshare.16599161.v1
title: Supplementary data 6

description: Supplementary data 6
DOI: 10.6084/m9.figshare.16599161
title: Supplementary data 6

description: Supplementary data 6
DOI: 10.6084/m9.figshare.16599152.v1
title: Supplementary data 5

description: Supplementary data 5
DOI: 10.6084/m9.figshare.16599152
title: Supplementary data 5

description: Supplementary data 5
DOI: 10.5281/zenodo.5498479
title: Dataset for "Deep Learning with remote sensing data for image segmentation: example of rice crop mapping using Sentinel-2 images"

description: Dataset for "Deep Learning with remote sensing data for image segmentation: example of rice crop mapping using Sentinel-2 images". Contact Ricardo Dalagnol ricds@hotmail.com
DOI: 10.6084/m9.figshare.16599146
title: Supplementary data 4

description: Supplementary data 4
DOI: 10.6084/m9.figshare.16599146.v1
title: Supplementary data 4

description: Supplementary data 4
DOI: 10.6084/m9.figshare.16599140.v1
title: Supplementary data 3

description: Supplementary data 3
DOI: 10.6084/m9.figshare.16599140
title: Supplementary data 3

description: Supplementary data 3
DOI: 10.6084/m9.figshare.16599137
title: Supplementary data 2

description: Supplementary data 2
DOI: 10.6084/m9.figshare.16599137.v1
title: Supplementary data 2

description: Supplementary data 2
DOI: 10.6084/m9.figshare.16599134
title: Supplementary data 1

description: Supplementary data 1
DOI: 10.6084/m9.figshare.16599134.v1
title: Supplementary data 1

description: Supplementary data 1
DOI: 10.5281/zenodo.5498480
title: Dataset for "Deep Learning with remote sensing data for image segmentation: example of rice crop mapping using Sentinel-2 images"

description: Dataset for "Deep Learning with remote sensing data for image segmentation: example of rice crop mapping using Sentinel-2 images". Contact Ricardo Dalagnol ricds@hotmail.com
DOI: 10.5281/zenodo.5498488
title: Dataset for "Deep Learning with remote sensing data for image segmentation: example of rice crop mapping using Sentinel-2 images"

description: Dataset for "Deep Learning with remote sensing data for image segmentation: example of rice crop mapping using Sentinel-2 images". Contact Ricardo Dalagnol ricds@hotmail.com
DOI: 10.18112/openneuro.ds002799.v1.0.4
title: Human es-fMRI Resource: Concurrent deep-brain stimulation and whole-brain functional MRI
DOI: 10.5281/zenodo.5498489
title: CoVaxxy Tweet IDs data set

description: A collection of Tweet IDs related to Covid-19 Vaccines, gathered from Twitter since Jan 4, 2021. Please see https://arxiv.org/abs/2101.07694 for more information.
DOI: 10.5281/zenodo.5498695
title: Model data

description: The model data from three microphysics schemes (MORR, MY2, THOM) in the Meiyu Case
DOI: 10.5281/zenodo.5498694
title: Model data

description: The model data from three microphysics schemes (MORR, MY2, THOM) in the Meiyu Case
DOI: 10.6084/m9.figshare.13621169.v14
title: Speedtest Open Data - Four International cities - MEL, BKK, SHG, LAX

description: This dataset compares four cities broadband internet speeds:- Melbourne, AU- Bangkok, TH- Shanghai, CN- Los Angeles, US<br>ERRATA:1.Data is for Q3 2020, but some files are labelled incorrectly as 02-20 of June 20. They all should read Sept 20, or 09-20 as Q3 20, rather than Q2. Will rename and reload.Amended in v7.<br>2. LAX file named 0320, when should be Q320.Amended in v8.<br><br>*lines of data for each geojson file; a line equates to a 600m^2 location, inc total tests, devices used, and average upload and download speed- MEL 16181 locations/lines =&gt; 0.85M speedtests (16.7 tests per 100people)- SHG 31745 lines =&gt; 0.65M speedtests (2.5/100pp)- BKK 29296 lines =&gt; 1.5M speedtests (14.3/100pp)- LAX 15899 lines =&gt; 1.3M speedtests (10.4/100pp)<br>Geojsons of these 2* by 2* extracts for MEL, BKK, SHG now added, and LAX added v6.<br>This dataset unpacks, geospatially, data summaries provided in Speedtest Global Index (linked below). See Jupyter Notebook (*.ipynb) to interrogate geo data. See link to install Jupyter.<br>** To DoWill add Google Map versions so everyone can see without installing Jupyter.- Link to Google Map (BKK) added below. Key:Green &gt; 100Mbps(Superfast). Black &gt; 500Mbps (Ultrafast). CSV provided. Code in Speedtestv1.1.ipynb Jupyter Notebook.<br>** Pythonmelb = au_tiles.cx[144:146 , -39:-37] #Lat/Lon extract<br>shg = tiles.cx[120:122 , 30:32] #Lat/Lon extract<br>bkk = tiles.cx[100:102 , 13:15] #Lat/Lon extract<br>lax = tiles.cx[-118:-120, 33:35] #lat/Lon extract<br>Histograms (v9), and data visualisations (v3,5,9,11) will be provided.Data Sourced from - This is an extract of Speedtest Open data available at Amazon WS (link below - opendata.aws).<br>**VERSIONSv15. Load Melb Q1 2021 data - csv.V14. Added Melb Q1 2021 data - geojson.v13. Added Twitter link to pics.v12 Add Line-Compare pic (fastest 1000 locations) inc Jupyter (nbn-intl-v1.2.ipynb).v11 Add Line-Compare pic, plotting Four Cities on a graph.v10 Add Four Histograms in one pic.v9 Add Histogram for Four Cities. Add NBN-Intl.v1.1.ipynb (Jupyter Notebook).v8 Renamed LAX file to Q3, rather than 03.v7 Amended file names of BKK files to correctly label as Q3, not Q2 or 06.v6 Added LAX file.v5 Add screenshot of BKK Google Map.v4 Add BKK Google map(link below), and BKK csv mapping files. v3 replaced MEL map with big key version. Prev key was very tiny in top right corner.v2 Uploaded MEL, SHG, BKK data and Jupyter Notebookv1 Metadata record<br>** LICENCEAWS data licence on Speedtest data is "CC BY-NC-SA 4.0", so use of this data must be:- non-commercial (NC)- reuse must be share-alike (SA)(add same licence).This restricts the standard CC-BY Figshare licence.<br>** Other uses of Speedtest Open Data;- see link at Speedtest below.<br>
DOI: 10.5517/ccdc.csd.cc26ztnp
title: CCDC 2055413: Experimental Crystal Structure Determination

description: Related Article: Minghui Cui, Linpo Yang, Fengcai Li, Liming Zhou, Yinglin Song, Shao-Ming Fang, Cai-Ming Liu, Xi-Li Li|2021|Inorg.Chem.|60|13366|doi:10.1021/acs.inorgchem.1c01682
DOI: 10.5517/ccdc.csd.cc289b0y
title: CCDC 2094329: Experimental Crystal Structure Determination

description: Related Article: Hiroshige Yamaura, Koji Yamamoto, Tetsuro Murahashi|2021|Chem.Commun.|57|9120|doi:10.1039/D1CC03719F
DOI: 10.5517/ccdc.csd.cc289b1z
title: CCDC 2094330: Experimental Crystal Structure Determination

description: Related Article: Hiroshige Yamaura, Koji Yamamoto, Tetsuro Murahashi|2021|Chem.Commun.|57|9120|doi:10.1039/D1CC03719F
DOI: 10.5517/ccdc.csd.cc289b20
title: CCDC 2094331: Experimental Crystal Structure Determination

description: Related Article: Hiroshige Yamaura, Koji Yamamoto, Tetsuro Murahashi|2021|Chem.Commun.|57|9120|doi:10.1039/D1CC03719F
DOI: 10.5517/ccdc.csd.cc289b31
title: CCDC 2094332: Experimental Crystal Structure Determination

description: Related Article: Hiroshige Yamaura, Koji Yamamoto, Tetsuro Murahashi|2021|Chem.Commun.|57|9120|doi:10.1039/D1CC03719F
DOI: 10.5517/ccdc.csd.cc28b6c6
title: CCDC 2095177: Experimental Crystal Structure Determination

description: Related Article: Beatrice L. Chinen, Jakub Hyvl, Daniel F. Brayton, Matthew M. Riek, Wesley Y. Yoshida, Timothy W. Chapp, Arnold L. Rheingold, Matthew F. Cain|2021|RSC Advances|11|28602|doi:10.1039/D1RA05926B
DOI: 10.5517/ccdc.csd.cc28b6d7
title: CCDC 2095178: Experimental Crystal Structure Determination

description: Related Article: Beatrice L. Chinen, Jakub Hyvl, Daniel F. Brayton, Matthew M. Riek, Wesley Y. Yoshida, Timothy W. Chapp, Arnold L. Rheingold, Matthew F. Cain|2021|RSC Advances|11|28602|doi:10.1039/D1RA05926B
DOI: 10.5517/ccdc.csd.cc28b6f8
title: CCDC 2095179: Experimental Crystal Structure Determination

description: Related Article: Beatrice L. Chinen, Jakub Hyvl, Daniel F. Brayton, Matthew M. Riek, Wesley Y. Yoshida, Timothy W. Chapp, Arnold L. Rheingold, Matthew F. Cain|2021|RSC Advances|11|28602|doi:10.1039/D1RA05926B
DOI: 10.5517/ccdc.csd.cc28b6g9
title: CCDC 2095180: Experimental Crystal Structure Determination

description: Related Article: Beatrice L. Chinen, Jakub Hyvl, Daniel F. Brayton, Matthew M. Riek, Wesley Y. Yoshida, Timothy W. Chapp, Arnold L. Rheingold, Matthew F. Cain|2021|RSC Advances|11|28602|doi:10.1039/D1RA05926B
DOI: 10.5517/ccdc.csd.cc28b6hb
title: CCDC 2095181: Experimental Crystal Structure Determination

description: Related Article: Beatrice L. Chinen, Jakub Hyvl, Daniel F. Brayton, Matthew M. Riek, Wesley Y. Yoshida, Timothy W. Chapp, Arnold L. Rheingold, Matthew F. Cain|2021|RSC Advances|11|28602|doi:10.1039/D1RA05926B
DOI: 10.5517/ccdc.csd.cc279lz4
title: CCDC 2064816: Experimental Crystal Structure Determination

description: Related Article: Hua Chen, Laura Voigt, Mariusz Kubus, Dmytro Mihrin, Susanne Mossin, René W. Larsen, Sren Kegnæs, Stergios Piligkos, Kasper S. Pedersen|2021|J.Am.Chem.Soc.|143|14041|doi:10.1021/jacs.1c05057
DOI: 10.5517/ccdc.csd.cc279ly3
title: CCDC 2064815: Experimental Crystal Structure Determination

description: Related Article: Hua Chen, Laura Voigt, Mariusz Kubus, Dmytro Mihrin, Susanne Mossin, René W. Larsen, Sren Kegnæs, Stergios Piligkos, Kasper S. Pedersen|2021|J.Am.Chem.Soc.|143|14041|doi:10.1021/jacs.1c05057
DOI: 10.5517/ccdc.csd.cc279lx2
title: CCDC 2064814: Experimental Crystal Structure Determination

description: Related Article: Hua Chen, Laura Voigt, Mariusz Kubus, Dmytro Mihrin, Susanne Mossin, René W. Larsen, Sren Kegnæs, Stergios Piligkos, Kasper S. Pedersen|2021|J.Am.Chem.Soc.|143|14041|doi:10.1021/jacs.1c05057
DOI: 10.5517/ccdc.csd.cc2850cv
title: CCDC 2090186: Experimental Crystal Structure Determination

description: Related Article: Seulgi Kim, Huiyeong Ju, Ki-Min Park, Jong Hwa Jung, Shim Sung Lee, Eunji Lee|2021|Inorg.Chem.|60|13637|doi:10.1021/acs.inorgchem.1c01943
DOI: 10.6084/m9.figshare.16529640.v22
title: Ensemble of Nucleic Acid Absolute Quantitation Modules for Accurate Copy Number Variation Detection and Targeted RNA Profiling

description: NGS data of the publication. Check sample_list.xlsx for sample information.
DOI: 10.6084/m9.figshare.16590359.v2
title: Supplementary material for "Prophage Encoded Human Immune Evasion Cluster Genes are Enriched in Staphylococcus aureus Isolated from Chronic Rhinosinusitis Patients with Nasal Polyps"

description: Supplementary material for "Prophage Encoded Human Immune Evasion Cluster Genes are Enriched in Staphylococcus aureus Isolated from Chronic Rhinosinusitis Patients with Nasal Polyps"
DOI: 10.6084/m9.figshare.16590359
title: Supplementary material for "Prophage Encoded Human Immune Evasion Cluster Genes are Enriched in Staphylococcus aureus Isolated from Chronic Rhinosinusitis Patients with Nasal Polyps"

description: Supplementary material for "Prophage Encoded Human Immune Evasion Cluster Genes are Enriched in Staphylococcus aureus Isolated from Chronic Rhinosinusitis Patients with Nasal Polyps"
DOI: 10.15156/bio/sh0895724.10fu
title: SH0895724.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0895725.10fu
title: SH0895725.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.