cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2bq9ft
title: CCDC 2166386: Experimental Crystal Structure Determination

description: Related Article: Mollah Rohan Ahsan, Arijit Mukherjee|2022|CrystEngComm|24|5930|doi:10.1039/D2CE00735E
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: 10.17882/73008
title: AdriFOOS Depth/Temperature profiles dataset 2012-2020

description: From 2003 to 2013, the Ancona section of CNR-IRBIM (formerly part of CNR-Institute of Marine Science) runned the “Fishery Observing System” (FOS) program aimed at using Italian fishing vessels as Vessels Of Opportunity (VOOs) for the collection of scientifically useful datasets (Falco et al. 2007). Some commercial fishing vessels, targetting small pelagic species in the northern and central Adriatic Sea, were equipped with an integrated system for the collection of information on catches, position of the fishing operation, depth and water temperature during the haul, producing a great amount of data that demonstrated to be helpful both for oceanographic and fishery biology purposes (Carpi et al. 2015; Aydoğdu et a. 2016; Sparnocchia et al. 2016; Lucchetti et al. 2018). In 2012, thanks to the participation to some national and international projects (e.g. SSD-Pesca, EU-FP7 JERICO etc.), CNR started the development of a new modular “Fishery & Oceanography Observing System” (FOOS; Patti et al. 2016). New sensors for oceanographic and meteorological data allow nowadays the FOOS to collect more parameters, with higher accuracy and to send them directly to a data center in near real time (Martinelli et al. 2016; Sparnocchia et al. 2017). Furthermore, the FOOS is a multifunction system able to collect various kind of data from the fishing operations and also to send back to the fishermen useful information (e.g. weather and sea forecasts, etc.) through an electronic logbook with an ad hoc software embedded. The new FOOS installed on various kind of fishing vessels targetting different resources, allowed a spatial extension of the monitored areas in the Mediterranean Sea (Patti et al. 2016). CNR-IRBIM implemented the “AdriFOOS” observational system, by installing the FOOS on some commercial fishing boats operating in the Adriatic Sea. Since then the datacenter based in Ancona receives daily data sets of environmental parameters collected along the water column and close to the sea bottom (eg. temperature, salinity, etc.), together with GPS haul tracks, catch amounts per haul, target species sizes and weather information. Some temperature and salinity measurements acquired by the FOOS in the Adriatic Sea from January 2014 to March 2015 were published within the JERICO project and some oxygen and fluorescence profiles obtained in 2017 within the NEXOS project. The dataset here presented contains 14810 depth (pressure)/temperature profiles collected by 10 vessels of the AdriFOOS fleet in the period 2012-2020. All the profiles were subjected to quality control.Data are flagged according the L20 (SEADATANET MEASURAND QUALIFIER FLAGS).
DOI: 10.17882/79095
title: Temperature monitoring of subtidal and intertidal microhabitats of oyster Crassostrea gigas

description: The Pacific oyster Crassostrea gigas is a marine sessile bivalve living in the coastal intertidal zone, a stressful and highly dynamic environment affected by global changes. Our work aimed at increase knowledge on the thermal environment of oyster in its intertidal habitat. Specific-pathogen-free oyster spats were produced and maintained in hatchery. On May 2nd 2018, juveniles were deployed in the intertidal zone at the experimental site in the Bay of Brest (Brittany, France, 48° 20′ 06.19″ N, 4° 19′ 06.37″ W). They were placed at three bathymetric levels (Low = 1.6 m; Middle = 3 m; High = 5 m) corresponding to the lower and upper natural limits of wild C. gigas repartition in the field. Data were acquired using SP2T probes © NKE autonomous data logger fixed in oyster bags to monitor temperature and pressure at Low, Middle and High (one logger per level). Time frequency of recording was 1 data per min. Each data available here has been averaged at a 10-min frequency and has a flagged value of 1 if taken in air or 2 if taken in sea. Our data showed that magnitude and ranges of temperature varied between vertical position on the shore. C. gigas were able to support extreme dynamic fluctuations of temperature in function of their microhabitats, driven by tidal height, day/night cycle and exposure to air. One of the main finding of our work was that oyster could support extreme ranges of temperature from -1.1 °C to 36.4°C during exposure to air during spring. The marine rocky intertidal zone thus appeared as one of the most variable and unpredictable habitats on earth.
DOI: 10.17882/92297
title: BePLi Dataset v1: Beach Plastic Litter Dataset version 1

description: The BePLi Dataset v1 (Beach Plastic Litter Dataset version 1) comprised 3708 original images taken in various coastal environments and the corresponding instance-based and pixel-level annotations for all plastic litter objects in the images are compiled in MSCOCO (Microsoft Common Objects in Context) Object Detection Task format. The format is partially intendedly modified from the original MSCOCO format.
DOI: 10.17882/85472
title: The BeachLitter Dataset v2022

description: 8-class segmentation masks by high-quality manual pixel-by-pixel annotations, corresponding 3500 beach litter images from 2011 to 2019 in Yamagata Prefecture, Japan. (papers are under review)
DOI: 10.17882/83294
title: Transcriptomic, lipidomic, biometric and physiological rate data for the determination of the reaction norm of the Pacific oyster to ocean acidification.

description: Data & R scripts. For each figure in the paper, the dataset and corresponding R script are provided.
DOI: 10.17882/96076
title: Daily-average estimates of turbulent kinetic energy dissipation rate in Celtic Sea (49.4N -8.6E) from June 19th 2014 to September 1st 2014

description: Estimates of turbulent kinetic energy dissipation rate (ε) were derived from velocity measurements made by three Teledyne RDI WorkHorse Sentinel 600kHz Acoustic Doppler Current Profiler (ADCP) instruments mounted inline on a buoyancy tensioned mooring (location shown in figure 1). The upper ADCP (S/N 7301) was installed upward-looking in a syntactic buoy at a nominal depth of 23m based on an overall water depth of 145m; the middle ADCP (S/N 3725) was downward-looking in an open frame at a nominal depth of 36m; and the lower instrument (S/N 4015) was again upward-looking in a syntactic buoy at a nominal 54m.
DOI: 10.17882/96290
title: Location of mode-1 and mode-2 internal solitary waves off the Amazon shelf

description: Location of the leading wave of mode-1 and mode-2 internal solitary wave (ISW) packet off the Amazon shelf from 2005 to 2021 visible in MODIS-Terra images. Each mapped ISW signature is associated with one ID number and has 12 points of latitude and longitude to describe the location of its crest.
DOI: 10.17882/96296
title: Seismic data and analog modeling results supporting the brittle-viscous dynamic evolution of the Barbados accretionary prism

description: In a study to be published in the AGU journal "Tectonics", seismic data and analog modeling results revealed that a system of elongated extensional trenches (of the "basin-&-range" type) developed in the thickest zone of the Barbados accretionary prism. Synchronous with this extension, compression occurred at the front of the accretionary prism (frontal accretion zone), and compression was also active at the inner edge of the prism (characterized by back-thrusting). The interpretation proposed in this study involves a spreading of the superficial part of the accretionary prism due to a viscous response associated with tectonic thickening of the deepest parts of the prism. This interpretation is consistent with the fact that extension is limited to the axial part of the prism and coincides with the zone where the prism is thickest. The deep zone of viscous behavior is interpreted as shale-rich sedimentary domains intensely deformed by penetrative deformation. Analog sand-silicone models controlled by X-ray scanner were used to simulate the deformation distribution compared to the Barbados accretionary prism, as observed on available seismic reflection data. A bilayer model with an upper brittle zone and a lower ductile part is best suited to account for the observed deformation. We present here the data on which this study is based: (1) seismic data acquired as part of an industrial consortium under the auspices of the “Comité d'Etudes Pétrolières et Marines” (CEPM), and (2) raw data from analog modeling experiments made at IFPEN. The seismic data comprise time-migrated data from CEPM's CRV128 and AN107 profiles, and a depth conversion of the AN107 profile. Raw 2D tomography data from analog experiments 1385_214, 1385_114 and 01258. 3D serial sections of experiment 01258 are also shown.
DOI: 10.17882/77207
title: Deep Chlorophyll Maximum global database from BioGeoChemical-Argo floats

description: The dataset dcm_dtb.txt contains bio-optical measurements and environmental parameters associated with Deep Chlorophyll Maxima (DCM) acquired by BGC-Argo profiling floats. For each BGC-Argo profile the data files includes the World Meteorological Organization (WMO) and profile numbers, the Data Assembly Center (DAC), the geographical position (LON and LAT), the date of the profile in Julian Day (JULD) and in YYYY-MM-DD format; the region of the profile (REGION, acronyms detailed in the region.txt file), the DCM zonal attribution (ZONE, acronyms detailed in the zone.txt file), the vertical resolution of measurements of the concentration of the chlorophyll a [Chla] and of the backscattering coefficient (bbp) within the 250 first meters, the Mixed Layer Depth (MLD, m), the qualification of the vertical profile (DCM_TYPE) as Deep Biomass Maximum (3), Deep photoAcclimation Maximum (2), or presenting no DCM (1); the depth of the DCM (DCM_DEPTH); the chlorophyll a concentration (CHLA_DCM, mg chla m-3 ) the backscattering coefficient (BBP_DCM, m-1), and the Brunt-Vaisala frequency (N2_DCM) at the DCM depth; the nitracline depth (NCLINE_DEPTH, m) and steepness (NCLINE_STEEP, µmol NO3 m-3 m-1), the mean nitrate concentration within the Mixed Layer (NO3_MEAN_MLD, µmol NO3 m-3), the mean daily Photosynthetically Available Radiation in the Mixed Layer (MEAN_IPAR_MLD, E m -1 d -1), the daily Photosynthetically Available Radiation at the nitracline depth (IPAR_NCLINE, E m-2 d-1); and the [Chla] measured by satellite (CHLA_SAT, mg chla m-3). The dataset shape_NASTG_ASEW.txt contains the seasonal median, the first and third quartiles of the [Chla] and of the bbp profiles for the North Atlantic Subtropical Gyre and Atlantic SubEquatorial Waters regions. The dataset climato_NASTG_ASEW.txt contains the monthly mean and standard deviations of the DCM depth (DCM_depth), the isolume depth of daily Photosynthetically Available Radiation of 20 E m-2 d-1 (iPAR_20), the nitracline depth, and the Mixed Layer Depth (MLD) for the profiles within the North Atlantic Subtropical Gyre and Atlantic SubEquatorial Waters regions. The qualification and processing of the BGC-Argo profiles, as well as the DCM detection (DCM_TYPE) and the estimation of the environmental parameters, were applied as described from Cornec, M., Claustre, H., Mignot, A., Guidi, L., Lacour, L., Poteau, A., D’Ortenzio, F.,Gentili, B., Schmechtig, C., (to be updated.) Deep Chlorophyll Maxima in the global ocean: occurrences, drivers and characteristics. Global Biogeochemical Cycles, to be updated The [Chla] satellite variable was obtained by the match of each BGC-Argo profile with a L3S [Chla] product from the Ocean Colour-Climate Change Initiative v4.0 database merging observations from MERIS, MODIS, VIIRS and SeaWiFs, at a monthly and 4x4-km-pixel resolution, up to December 31, 2019 (ftp://oc-cci-data:ELaiWai8ae@oceancolour.org/occci-v4.2/).
DOI: 10.6084/m9.figshare.24057120.v1
title: China Inorganic Nitrogen deposition database1.0

description: The atmospheric IN deposition fluxes database consists of three files (Fig. 1). The ‘data file’ provides yearly data on the dry, wet and total IN deposition fluxes. Specifically, dry deposition is the sum of two forms, gaseous and particulate, including NO<sub>2</sub>，HNO<sub>3</sub>，NH<sub>3</sub>，NO<sub>3</sub><sup>-</sup>，NH<sub>4</sub><sup>+</sup>.Wet deposition is the sum of both NO<sub>3</sub><sup>-</sup>-N and NH<sub>4</sub><sup>+</sup>-N. The ‘readme file’ describes the ‘data file’ and the units of all variables included. The ‘source file’ includes the full references used in the database, which comprise satellite data and precipitation data.
DOI: 10.34740/kaggle/dsv/6547105
title: Meteorological Data
DOI: 10.5281/zenodo.8380576
title: Genetic diversity, population structure, and linkage disequilibrium among tropical quality protein maize (QPM) lines assessed with high-density SNP markers

description: The study of genetic diversity (GD), population structure, and linkage disequilibrium (LD) provides a better understanding of the genetic relationships between individuals in a population which can be utilized in crop research and improvement. Genotyping-by-sequencing (GBS) was used to detect and genotype single nucleotide polymorphisms (SNPs) in a collection of 74 quality protein maize (QPM) lines and further to characterize their genetic diversity, population structure, and linkage disequilibrium. A total of 235,214 high-quality SNPs were used for different genetic analyses except for structure analysis where 11,950 SNPs were used. Analysis of molecular variance (AMOVA) based on these SNPs revealed high genetic heterozygosity among the five populations with 1% of the total genetic variation present among the subpopulations and 99% of the variation among individuals within the populations. Population structure analysis using Bayesian-based clustering revealed that the 74 lines could be clustered into four groups. However, neighbor-joining trees indicate the lines are grouped into three major clusters. Further analysis using principal component analyses (PCA) clustered the genotypes into five groups which are concordant with the groups based on pedigree information. Higher genetic diversity was detected in population 1 with a GD value of 0.484 and the lowest in population 5 (0.396) and overall, with a mean of 0.434. The LD pattern in the quality protein maize was investigated and we observed a relatively rapid LD decay of 3.53kb and 10.66kb at r<sup>2</sup> =0.2 and r<sup>2</sup>= 0.1, respectively. Our findings provide important information for future Linkage mapping studies, genome-wide association analyses, and marker-assisted selective breeding of maize as well as genomic prediction-based selection in tropical germplasm.
DOI: 10.5281/zenodo.8380575
title: Genetic diversity, population structure, and linkage disequilibrium among tropical quality protein maize (QPM) lines assessed with high-density SNP markers

description: The study of genetic diversity (GD), population structure, and linkage disequilibrium (LD) provides a better understanding of the genetic relationships between individuals in a population which can be utilized in crop research and improvement. Genotyping-by-sequencing (GBS) was used to detect and genotype single nucleotide polymorphisms (SNPs) in a collection of 74 quality protein maize (QPM) lines and further to characterize their genetic diversity, population structure, and linkage disequilibrium. A total of 235,214 high-quality SNPs were used for different genetic analyses except for structure analysis where 11,950 SNPs were used. Analysis of molecular variance (AMOVA) based on these SNPs revealed high genetic heterozygosity among the five populations with 1% of the total genetic variation present among the subpopulations and 99% of the variation among individuals within the populations. Population structure analysis using Bayesian-based clustering revealed that the 74 lines could be clustered into four groups. However, neighbor-joining trees indicate the lines are grouped into three major clusters. Further analysis using principal component analyses (PCA) clustered the genotypes into five groups which are concordant with the groups based on pedigree information. Higher genetic diversity was detected in population 1 with a GD value of 0.484 and the lowest in population 5 (0.396) and overall, with a mean of 0.434. The LD pattern in the quality protein maize was investigated and we observed a relatively rapid LD decay of 3.53kb and 10.66kb at r<sup>2</sup> =0.2 and r<sup>2</sup>= 0.1, respectively. Our findings provide important information for future Linkage mapping studies, genome-wide association analyses, and marker-assisted selective breeding of maize as well as genomic prediction-based selection in tropical germplasm.
DOI: 10.5281/zenodo.8380392
title: CSS-2: GW analysis January 2006

description: S3D analyses of simulated temperature retrievals; Jan 2006
DOI: 10.5281/zenodo.8380140
title: CSS-2: Temperature retrieval January 2006

description: Simulated CAIRT retrieval results for temperatures from ECMWF-IFS 36h forward integration initilaized by ERA-5; Jan 2006
DOI: 10.5281/zenodo.8380141
title: CSS-2: Temperature retrieval January 2006

description: Simulated CAIRT retrieval results for temperatures from ECMWF-IFS 36h forward integration initilaized by ERA-5; Jan 2006
DOI: 10.5281/zenodo.8380391
title: CSS-2: GW analysis January 2006

description: S3D analyses of simulated temperature retrievals; Jan 2006
DOI: 10.5519/qd.02khcukk
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1387522 records)
DOI: 10.6084/m9.figshare.24057120
title: A database of atmospheric inorganic nitrogen deposition fluxes in China from satellite monitoring

description: The atmospheric IN deposition fluxes database consists of three files. The ‘data file’ provides yearly data on the dry, wet and total IN deposition fluxes. Specifically, dry deposition is the sum of two forms, gaseous and particulate, including NO<sub>2</sub>，HNO<sub>3</sub>，NH<sub>3</sub>，NO<sub>3</sub><sup>-</sup>，NH<sub>4</sub><sup>+</sup>.Wet deposition is the sum of both NO<sub>3</sub><sup>-</sup>-N and NH<sub>4</sub><sup>+</sup>-N. The ‘readme file’ describes the ‘data file’ and the units of all variables included. The ‘source file’ includes the full references used in the database, which comprise satellite data and precipitation data.
DOI: 10.5281/zenodo.8003198
title: Data and code for Seasonal variation in dragonfly assemblage colouration suggests a link between thermal melanism and phenology

description: Data and code for the manuscript entitled: "Seasonal variation in dragonfly assemblage colouration suggests a link between thermal melanism and phenology" by Roberto Novella-Fernandez, Roland Brandl, Stefan Pinkert, Dirk Zeuss, Christian Hof.
DOI: 10.5281/zenodo.8377714
title: Edición 77 Revista Varona

description: Artículos correspondientes a la edición número 77 de la Revista Científico metodológica Varona, perteneciente a la Universidad de Ciencias Pedagógicas, en La Habana Cuba.
DOI: 10.5281/zenodo.8377713
title: Edición 77 Revista Varona

description: Artículos correspondientes a la edición número 77 de la Revista Científico metodológica Varona, perteneciente a la Universidad de Ciencias Pedagógicas, en La Habana Cuba.
DOI: 10.6084/m9.figshare.24199533
title: 20230927_starrydata2

description: All data on Starrydata2, a database of experimental properties in the field of inorganic materials
DOI: 10.6084/m9.figshare.24199533.v1
title: 20230927_starrydata2

description: All data on Starrydata2, a database of experimental properties in the field of inorganic materials
DOI: 10.5285/3659eca2afe54ab9ae437bf25fec1c2e
title: Chapter 2 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 2.26 (v20230523)

description: Data for Figure 2.26 from Chapter 2 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 2.26 shows changes in ocean heat content (OHC). --------------------------------------------------- How to cite this dataset --------------------------------------------------- When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates: Gulev, S.K., P.W. Thorne, J. Ahn, F.J. Dentener, C.M. Domingues, S. Gerland, D. Gong, D.S. Kaufman, H.C. Nnamchi, J. Quaas, J.A. Rivera, S. Sathyendranath, S.L. Smith, B. Trewin, K. von Schuckmann, and R.S. Vose, 2021: Changing State of the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change[Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 287–422, doi:10.1017/9781009157896.004. --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Data provided in relation to Figure 2.26: - AR6 FGD assessment timeseries OHC These data files are from data for Cross-Chapter Box 9.1, Figure 1. The link to this dataset is provided in the Related Documents section of this catalogue record. --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the figure on the IPCC AR6 website - Link to the report component containing the figure (Chapter 2) - Link to the Supplementary Material for Chapter 2, which contains details on the input data used in Table 2.SM.1 - Link to Cross-Chapter Box 9.1, Figure 1
DOI: 10.6084/m9.figshare.24199527
title: SWA Data for Walking and Running

description: The datasets are for 20 participants who underwent walking and ran at various intensities to compare the SenseWear Armband to indirect calorimetry.
DOI: 10.6084/m9.figshare.24199572
title: Proteomics data processed by Sanger

description: Proteomics data processed by Sanger: The metadata is downloaded from https://cellmodelpassports.sanger.ac.uk/downloads, Proteomics_20221214.zip, proteomics_all_20221214.csv
DOI: 10.6084/m9.figshare.24199542
title: FASTA file of the 654 OTUs

description: This .fasta file contains all 654 OTU sequences.
DOI: 10.6084/m9.figshare.24199542.v1
title: FASTA file of the 654 OTUs

description: This .fasta file contains all 654 OTU sequences.