cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7323527
title: Raw videos of the empirical observations performed studying large shoals of sulphur mollies (P. sulphuraria).

description: Data acquired between April 6th and April 11th 2018 in Teapa, Tabasco, Mexico. These dataset was obtained for the study of the spontaneous wave activity observed in large shoals of sulphur mollies. Details on the analysis can be found in DOI: XX.XXXX/XXX (currently under review). The file called data_ALL_clusters.csv contains four columns with the following information: cluster ID cluster area cluster volume cluster time duration cluster speed The h5 files contain the same information separated by acquisition day. In these h5 files, the areas, volumes and times are given in number of pixels and/or number of frames. Thus, they have to be re-scaled with the scaling factor dx=0.02 and dt=1/50.
DOI: 10.6073/pasta/20d8467263edceaeb44b5c4353ac8aad
title: Porewater nutrient concentrations from control plots in a Spartina alterniflora-dominated salt marsh at Goat Island, North Inlet, Georgetown, SC.

description: Porewater samples from a Spartina alterniflora-dominated salt marsh on Goat Island, North Inlet, Georgetown, SC were analyzed for ammonium, phosphate, sulfide and chloride concentrations.
DOI: 10.5281/zenodo.7323526
title: Raw videos of the empirical observations performed studying large shoals of sulphur mollies (P. sulphuraria).

description: Data acquired between April 6th and April 11th 2018 in Teapa, Tabasco, Mexico. These dataset was obtained for the study of the spontaneous wave activity observed in large shoals of sulphur mollies. Details on the analysis can be found in DOI: XX.XXXX/XXX (currently under review). The file called data_ALL_clusters.csv contains four columns with the following information: cluster ID cluster area cluster volume cluster time duration cluster speed The h5 files contain the same information separated by acquisition day. In these h5 files, the areas, volumes and times are given in number of pixels and/or number of frames. Thus, they have to be re-scaled with the scaling factor dx=0.02 and dt=1/50.
DOI: 10.5066/f7bk19mr
title: GIS Data and Tables Pertaining to the Agricultural Irrigated Land-Use Inventory for Escambia, Santa Rosa, and Okaloosa Counties in Florida, 2016

description: The GIS shapefile and spreadsheet tables show the 2016 agriculture irrigated land use for Escambia, Santa Rosa, and Okaloosa Counties developed through a cooperative project between the U.S. Geological Survey (USGS) and the Florida Department of Agriculture and Consumer Services (FDACS), Office of Agricultural Water Policy. Information provided in this layer includes crop type, irrigation system type, and primary water source for all irrigated land within these three counties.
DOI: 10.5066/f76w98bn
title: GIS data and tables associated with irrigated agricultural land use survey in Polk County, FL

description: A detailed inventory of the current irrigated crop acreage is now available to accurately estimate agricultural water use and future water demands in Polk County, Florida. A detailed digital map and summary of irrigated acreage was developed in an effort to improve the accuracy of crop acreage, type, and location for the 2016 growing season. The irrigated areas were delineated using land-use data provided by the Florida Department of Agriculture and Consumer Services (FDACS) and information obtained from the South Florida Water Management District (SFWMD) and the Southwest Florida Water Management Districts (SWFWMD) consumptive water-use permits. Each field that showed the presence of an irrigated crop or the potential for irrigation was field verified between April and December 2016. Selected attribute data were collected for each irrigated field, including crop type, primary water source, and type of irrigation system. Results and field verification of this inventory indicate that during the 2016 growing seasons (spring, summer, fall, and winter), an estimated 88,652 acres were irrigated within Polk County. Of the total field-verified crops, 83,995 acres were in citrus; 2,893 acres were in other non-citrus fruit crops (blueberries, grapes, peaches, and strawberries); 621 acres were in row crops (primarily beans and watermelons); 1,117 acres were in nursery (container and tree farms) and sod production; and 26 acres were in field crops including hay and pasture. Of the total inventoried irrigated acreage within Polk County, 98.0 percent (86,566 acres) was in the SWFWMD and the remaining 2.0 percent (2,086 acres) was in the SFWMD. About 85,788 acres (96.8 percent of the acreage inventoried) were irrigated by a microirrigation system, including drip, bubblers, and spray emitters. The remaining 3.2 percent of the irrigated acreage was irrigated using a sprinkler system (2,360 acres) or subsurface flood systems (504 acres). Groundwater was the primary source of water used to irrigate acreage (88.0 percent, or 78,050 acres); the remaining 10,602 acres (12.0 percent) used a combination of groundwater and surface water as the irrigation source.
DOI: 10.5066/f77p8xbc
title: GIS shape file and related data describing irrigated agricultural land-use in Collier County, Florida, for the growing season from October 2016 through September 2017

description: The GIS shapefile and summary table provide irrigated agricultural land-use for Collier County, Florida through a cooperative project between the U.S Geological Survey (USGS) and the Florida Department of Agriculture and Consumer Services (FDACS), Office of Agricultural Water Policy. Information provided in the shapefile includes the location of irrigated land field-verified between November 2016 and September 2017, crop type, irrigation system type, and primary water source used in Collier County, Florida. A map image of the shapefile is provided in the attachment.
DOI: 10.5066/f73x85kk
title: GIS shape file and related data describing irrigated agricultural land-use in Glades County, Florida, for the growing season from October 2016 through September 2017

description: The GIS shapefile and summary table provide irrigated agricultural land-use for Glades County, Florida through a cooperative project between the U.S Geological Survey (USGS) and the Florida Department of Agriculture and Consumer Services (FDACS), Office of Agricultural Water Policy. Information provided in the shapefile includes the location of irrigated land field-verified between November 2016 and September 2017, crop type, irrigation system type, and primary water source used in Glades County, Florida. A map image of the shapefile is provided in the attachment.
DOI: 10.5066/f7cf9p1n
title: GIS shape file and related data describing irrigated agricultural land-use in Highlands County, Florida, for the growing season from October 2016 through September 2017

description: The GIS shapefile and summary table provide irrigated agricultural land-use for Highlands County, Florida through a cooperative project between the U.S Geological Survey (USGS) and the Florida Department of Agriculture and Consumer Services (FDACS), Office of Agricultural Water Policy. Information provided in the shapefile includes the location of irrigated land field-verified between November 2016 and September 2017, crop type, irrigation system type, and primary water source used in Highlands County, Florida. A map image of the shapefile is provided in the attachment.
DOI: 10.5281/zenodo.7389281
title: Ammonia Binding Energy distribution at Interstellar Icy Grains

description: Zip file containing all the structures and input obtained in our article <em>ACS Earth Space Chem.</em> 2022, 6, 6, 1514–1526, https://doi.org/10.1021/acsearthspacechem.2c00040 To easily handle all these structures an online interactive page is created: https://tinaccil.github.io/Jmol_BE_NH3_visualization/
DOI: 10.5281/zenodo.7389280
title: Ammonia Binding Energy distribution at Interstellar Icy Grains

description: Zip file containing all the structures and input obtained in our article <em>ACS Earth Space Chem.</em> 2022, 6, 6, 1514–1526, https://doi.org/10.1021/acsearthspacechem.2c00040 To easily handle all these structures an online interactive page is created: https://tinaccil.github.io/Jmol_BE_NH3_visualization/
DOI: 10.5519/qd.7wby6b35
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (13 records)
DOI: 10.5519/qd.58u7d2e4
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (130 records)
DOI: 10.13140/rg.2.2.30477.82401
title: RT_35_2022_Mihai_Abstract.pdf
DOI: 10.13140/rg.2.2.27122.38083
title: RT_35_2022_Mihai_Abstract.pdf
DOI: 10.6084/m9.figshare.21667529.v1
title: Results Summaries for Svetina and Dai, Journal of Experimental Education

description: <strong>Results</strong> related to Number of Response Categories and Sample Size Requirements in Polytomous IRT Models by Dubravka Svetina Valdivia and Shenghai Dai, published in the Journal of Experimental Education, https://doi.org/10.1080/00220973.2022.2153783
DOI: 10.6084/m9.figshare.21667268.v1
title: Deformation of the Qinling belt revealed by P-wave velocity and azimuthal anisotropy tomography

description: The Qinling belt is a transitional zone lying among three units: the North China block (NCB), the South China block (SCB) and the northeastern Tibetan Plateau (NETP). Owing to the interaction of these units, complex deformation has occurred in the Qinling belt. Although many studies have been conducted to understand the deformation mechanism, some key issues are still under debate, such as whether middle-lower crustal flow exists beneath the western Qinling belt (WQB). High-resolution images of subsurface structures are essential to shed light on the deformation mechanism. In this article, high-resolution images of the velocity structure and azimuthal anisotropy beneath the Qinling belt are obtained by using an eikonal equation-based traveltime tomography method. Our seismic tomography inverts 38,719 high-quality <em>P</em>-wave first arrivals from 1,697 regional earthquakes recorded by 387 broadband seismic stations. In the WQB, our tomography results show low-velocity anomalies but relatively weak anisotropy in the middle-lower crust. These features suggest that middle-lower crustal flow may not exist in this area. In the central Qinling belt (CQB), we find low-velocity anomalies in the middle-lower crust; however, the fast velocity directions (FVDs) no longer trend E–W but vary from NNE–SSW to N–S. These characteristics can be ascribed to the convergence and collision between the NCB and the SCB. In addition, we find strong low-velocity anomalies in the uppermost mantle beneath the CQB, which may indicate the delamination of the lower crust. In the southern Qinling belt (SQB), we observe significant high-velocity anomalies in the upper crust beneath the Hannan–Micang (HNMC) and Shennong–Huangling (SNHL) domes. These high-velocity anomalies indicate the mechanically strong upper crust, which is responsible for the arc-shaped deformation process of the Dabashan (DBS) fold. Based on the <em>P</em>-wave velocity and azimuthal anisotropic structures revealed by the inversion of the high-quality seismic data, the deformation of the Qinling belt is affected mainly by the convergence between the NCB and the SCB rather than by the middle-lower crustal flow from the Tibetan Plateau.
DOI: 10.6084/m9.figshare.21667529.v2
title: Results Files for Svetina and Dai, Journal of Experimental Education

description: <strong>Results</strong> related to Number of Response Categories and Sample Size Requirements in Polytomous IRT Models by Dubravka Svetina Valdivia and Shenghai Dai, published in the Journal of Experimental Education, https://doi.org/10.1080/00220973.2022.2153783
DOI: 10.6084/m9.figshare.21667529
title: Results Summaries for Svetina and Dai, Journal of Experimental Education

description: <strong>Results</strong> related to Number of Response Categories and Sample Size Requirements in Polytomous IRT Models by Dubravka Svetina Valdivia and Shenghai Dai, published in the Journal of Experimental Education, https://doi.org/10.1080/00220973.2022.2153783
DOI: 10.17909/e7s1-yg62
title: Spectroscopy and Imaging of the MUSE Ultra Deep Field (MUDF)

description: The MUSE Ultra Deep Field is a unique region of the sky hosting two physically-associated quasars that allow us to study the connections between galaxies and their surrounding gas using emission and absorption line spectroscopy. Using HST observations of this field, we have created custom-calibrated data products that include the following: WFC3 F140W, F125W, and F336W mosaics; 1D and 2D WFC3 G141 grism spectra, and re-calibrated archival WFPC2 F702W and F450W mosaics. We have also generated source catalogs using Source Extractor, and measured galaxy morphologies using Statmorph. We plan to provide all of the science images, point spread function models, extracted grism spectra, and source catalogs as HLSPs that can be used by the community for a variety of investigations. In the future, we plan to expand the collection to include additional data products.
DOI: 10.5281/zenodo.7379646
title: Chandra HRC-I Jupiter X-ray data set

description: Data set to supplement code scripts contained in the repository: https://github.com/SeanMcEntee/cxo_goes_disk_study
description: {"references": ["Cecconi, Baptiste, Louis, Corentin K, Lamy, Laurent, Zarka, Philippe, & Hess, S\u00e9bastien L G. (2022). LESIA-Mag_IDL: LESIA Planetary Magnetic Field IDL computing scripts (V1.1). Zenodo. https://doi.org/10.5281/zenodo.7235424"]}
DOI: 10.17909/gzj0-nr72
title: Spectroscopy and Imaging of the MUSE Ultra Deep Field (MUDF)

description: The MUSE Ultra Deep Field is a unique region of the sky hosting two physically-associated quasars that allow us to study the connections between galaxies and their surrounding gas using emission and absorption line spectroscopy. Using HST observations of this field, we have created custom-calibrated data products that include the following: WFC3 F140W, F125W, and F336W mosaics; 1D and 2D WFC3 G141 grism spectra, and re-calibrated archival WFPC2 F702W and F450W mosaics. We have also generated source catalogs using Source Extractor, and measured galaxy morphologies using Statmorph. We plan to provide all of the science images, point spread function models, extracted grism spectra, and source catalogs as HLSPs that can be used by the community for a variety of investigations. In the future, we plan to expand the collection to include additional data products.
DOI: 10.5281/zenodo.7377687
title: In situ observations of Ganymede's outflowing ionosphere

description: The file contains values for ionospheric moments from the Juno flyby of Ganymede on 7 June 2021, during the period between 16:50 to 17:00, UTC. A description of the flyby and the data set is found in Valek et al. (2022), <em>In situ ion composition observations of the Ganynmede's outflowing ionosphere</em>, GRL DOI:10.1029/2022GL100281.
description: {"references": ["Valek et al (2022), In situ ion composition observations of Ganymede's outflowing ionosphere"]}
DOI: 10.5281/zenodo.7377686
title: In situ observations of Ganymede's outflowing ionosphere

description: The file contains values for ionospheric moments from the Juno flyby of Ganymede on 7 June 2021, during the period between 16:50 to 17:00, UTC. A description of the flyby and the data set is found in Valek et al. (2022), <em>In situ ion composition observations of the Ganynmede's outflowing ionosphere</em>, GRL DOI:10.1029/2022GL100281.
description: {"references": ["Valek et al (2022), In situ ion composition observations of Ganymede's outflowing ionosphere"]}
DOI: 10.17909/63dw-c041
title: Spectroscopy and Imaging of the MUSE Ultra Deep Field (MUDF)
DOI: 10.5281/zenodo.7060296
title: Dataset for publication: EMPIR_19ENG02_PartialDischargeChargeEstimationInGasInsulatedSubstationsUsingElectricandMagneticAntennasData

description: Dataset for the conference paper entitled: Partial Discharge Charge Estimation In Gas-Insulated<br> Substations Using Electric and Magnetic Antennas
DOI: 10.5281/zenodo.7060297
title: Dataset for publication: EMPIR_19ENG02_PartialDischargeChargeEstimationInGasInsulatedSubstationsUsingElectricandMagneticAntennasData

description: Dataset for the conference paper entitled: Partial Discharge Charge Estimation In Gas-Insulated<br> Substations Using Electric and Magnetic Antennas
DOI: 10.17909/w8yk-3025
title: Spectroscopy and Imaging of the MUSE Ultra Deep Field (MUDF)
DOI: 10.5284/1039451
title: Nottinghamshire Historic Landscape Characterisation (HLC)

description: The Nottinghamshire Historic Landscape Characterisation project was undertaken by Nottinghamshire County Council, with funding from English Heritage. The project followed on from the county's Countryside Appraisal and aimed to produce a Historic Landscape Character map for the whole county (excluding urban areas). This was achieved by analysing and plotting a number of identifiable landscape types, as observed in modern field patterns and land use. The final product was a set of GIS files for the various landscape categories and a report describing the project and its outcome.
DOI: 10.6084/m9.figshare.21667550
title: AHA GRANT DATA Nov 2022

description: Contact authors for clarification.
DOI: 10.6084/m9.figshare.21667550.v1
title: AHA GRANT DATA Nov 2022

description: Contact authors for clarification.
DOI: 10.5066/f7057dv5
title: GIS shape file and related data describing irrigated agricultural land-use in Martin County, Florida, for the growing season from October 2016 through September 2017

description: The GIS shapefile and summary table provide irrigated agricultural land-use for Martin County, Florida through a cooperative project between the U.S Geological Survey (USGS) and the Florida Department of Agriculture and Consumer Services (FDACS), Office of Agricultural Water Policy. Information provided in the shapefile includes the location of irrigated land field-verified between November 2016 and September 2017, crop type, irrigation system type, and primary water source used in Martin County, Florida. A map image of the shapefile is provided in the attachment.
DOI: 10.5281/zenodo.7390871
title: Result LiveWDD

description: Reproduce data for paper Wigner Distribution Deconvolution Adaptation for Live<br> Ptychography Reconstruction
DOI: 10.5281/zenodo.7390870
title: Result LiveWDD

description: Reproduce data for paper Wigner Distribution Deconvolution Adaptation for Live<br> Ptychography Reconstruction
DOI: 10.13140/rg.2.2.25444.65925
title: RT_35_2022_Mihai_Abstract.pdf
DOI: 10.5066/f7vd6xcw
title: GIS shape file and related data describing irrigated agricultural land-use in Okeechobee County, Florida, for the growing season from October 2016 through September 2017

description: The GIS shapefile and summary table provide irrigated agricultural land-use for Okeechobee County, Florida through a cooperative project between the U.S Geological Survey (USGS) and the Florida Department of Agriculture and Consumer Services (FDACS), Office of Agricultural Water Policy. Information provided in the shapefile includes the location of irrigated land field-verified between November 2016 and September 2017, crop type, irrigation system type, and primary water source used in Okeechobee County, Florida. A map image of the shapefile is provided in the attachment.
DOI: 10.34740/kaggle/dsv/4638211
title: Mahanagar Yatayat Dataset
DOI: 10.5066/f7qn65p0
title: GIS shape file and related data describing irrigated agricultural land-use in St. Lucie County, Florida, for the growing season from October 2016 through September 2017

description: The GIS shapefile and summary table provide irrigated agricultural land-use for St Lucie County, Florida through a cooperative project between the U.S Geological Survey (USGS) and the Florida Department of Agriculture and Consumer Services (FDACS), Office of Agricultural Water Policy. Information provided in the shapefile includes the location of irrigated land field-verified between November 2016 and September 2017, crop type, irrigation system type, and primary water source used in St Lucie County, Florida. A map image of the shapefile is provided in the attachment.
DOI: 10.13140/rg.2.2.15378.32962
title: RT_35_2022_Mihai_Abstract.pdf
DOI: 10.13140/rg.2.2.28800.10241
title: RT_35_2022_Mihai_Abstract.pdf
DOI: 10.5281/zenodo.7391143
title: ArEmotive

description: Dataset for ArEmotive along with datasets for supporting ontologies used in the frameworke
DOI: 10.5281/zenodo.7391142
title: ArEmotive

description: Dataset for ArEmotive along with datasets for supporting ontologies used in the frameworke
DOI: 10.15454/v70zst/mph4ef
title: ECOPICS_FR_Monolith Aboveground Biomass.tab

description: :unav
DOI: 10.57745/gnvp26
title: ECOPICS_FR_Monolith Aboveground Biomass-1.tab

description: :unav
DOI: 10.7303/syn47028493
title: mr-extract_transform.ipynb
DOI: 10.18434/mds2-2556
title: Serum proteomics of coronavirus shedding in vampire bats (Desmodus rotundus)
DOI: 10.7303/syn47194116
title: mr-municipalities.csv
DOI: 10.7303/syn47028485
title: mr_load.ipynb
DOI: 10.5281/zenodo.7390567
title: Appendix of the thesis "Acquisition of new genetic knowledge on Mycobacterium bovis strains, circulating in France, by the whole genome sequencing approach", part "4. Sequencing of new complete genomes", Ciriac CHARLES

description: Annex S1: Sequencing metric of the 10 new genomes and obtained with fastqc. A: Metric provide to Illumina metric. B: metric provide to MinION metric. Annex S2: Pan-genomic study performed on 12 <em>M. bovis</em> complete genomes. The table indicates the genes accessory. “1” shows the presence of CDS and “0” his absence. Annex S3: Indels between the ten new complete genomes and Mb3601 using progressiveMauve. Annotation of these indels was performed with reference genome comparison for gap or with the annotation (with Prokka) of the new complete genome studied for insertion. IS<em>6110</em> is marked in green. "Indel distribution" sheet shows the indel distribution on the <em>M. bovis</em> genome for the ten new complete genomes. Black arrows show the genomic region with the most of indel found. Annex S4: WgSNP analysis performed on 98 <em>M. bovis</em>. SNPs were annotated and selected according to their specificity to an <em>M. bovis</em> group described in Fig 5. The last common give information on the genetic impact of the SNP. The last sheet presents a graph of SNP number in genomic position. Annex S5: Alignments of the 12 <em>M. bovis </em>complete genomes.
DOI: 10.5281/zenodo.7390566
title: Appendix of the thesis "Acquisition of new genetic knowledge on Mycobacterium bovis strains, circulating in France, by the whole genome sequencing approach", part "4. Sequencing of new complete genomes", Ciriac CHARLES

description: Annex S1: Sequencing metric of the 10 new genomes and obtained with fastqc. A: Metric provide to Illumina metric. B: metric provide to MinION metric. Annex S2: Pan-genomic study performed on 12 <em>M. bovis</em> complete genomes. The table indicates the genes accessory. “1” shows the presence of CDS and “0” his absence. Annex S3: Indels between the ten new complete genomes and Mb3601 using progressiveMauve. Annotation of these indels was performed with reference genome comparison for gap or with the annotation (with Prokka) of the new complete genome studied for insertion. IS<em>6110</em> is marked in green. "Indel distribution" sheet shows the indel distribution on the <em>M. bovis</em> genome for the ten new complete genomes. Black arrows show the genomic region with the most of indel found. Annex S4: WgSNP analysis performed on 98 <em>M. bovis</em>. SNPs were annotated and selected according to their specificity to an <em>M. bovis</em> group described in Fig 5. The last common give information on the genetic impact of the SNP. The last sheet presents a graph of SNP number in genomic position. Annex S5: Alignments of the 12 <em>M. bovis </em>complete genomes.
DOI: 10.7303/syn47199024
title: mr_utils.py
DOI: 10.7303/syn47194124
title: mr-federation_units.csv
DOI: 10.13140/rg.2.2.26283.52008
title: RT_35_2022_Mihai_Abstract.pdf
DOI: 10.7303/syn47199836
title: mr-mortality_rates.csv
DOI: 10.7303/syn47193617
title: mr-dict.csv