cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10867805
title: Data for EBP-Nor workshop in 2024

description: This repository hosts data used for a workshop given by EBP-Nor (https://www.ebpnor.org/) in spring 2024. The workshop itself is hosted at GitHub (https://github.com/ebp-nor/workshop-2024). 

The PacBio reads were downloaded like this:



wget ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR654/000/ERR6548410/ERR6548410.fastq.gz


and subsampled like this:



seqtk sample ERR6548410.fastq.gz  420000 |gzip > ERR6548410_30x.fastq.gz

seqtk sample ERR6548410.fastq.gz  300000 |gzip > ERR6548410_22x.fastq.gz

seqtk sample ERR6548410.fastq.gz  360000 |gzip > ERR6548410_26x.fastq.gz


 

The Hi-C reads were downloaded like this:



wget ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR605/001/ERR6054981/ERR6054981_1.fastq.gz

wget ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR605/001/ERR6054981/ERR6054981_2.fastq.gz


and subsampled like this:



seqtk sample ERR6054981_1.fastq.gz 30000000 |gzip > ERR6054981_1_60x.fastq.gz

seqtk sample ERR6054981_2.fastq.gz 30000000 |gzip > ERR6054981_2_60x.fastq.gz

seqtk sample ERR6054981_1.fastq.gz 25000000 |gzip > ERR6054981_1_50x.fastq.gz

seqtk sample ERR6054981_2.fastq.gz 25000000 |gzip > ERR6054981_2_50x.fastq.gz
DOI: 10.15468/dl.9k87ff
title: Occurrence Download

description: A dataset containing 149 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhododendron goyozanense (M.Kikuchi) Craven"
 ]
}

 The dataset includes 149 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091698-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n2nmv6
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Agropyron fragile (Roth) P.Candargy",
 "HasCoordinate is true",
 "Country is Iceland",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000",
 "CoordinateUncertaintyInMeters is less than 10000"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091699-240321170329656/datasets/export for details.
DOI: 10.25666/dataubfc-2023-04-11-02
title: Execution times and results of instances of an FPMAS epidemiological model
title: Temps d'exécution et résultats d'instances d'un modèle épidémiologique FPMAS

description: This dataset contains fpmas-virus (https://github.com/FPMAS/fpmas-virus) execution times and model results obtained with the FPMAS platform (https://github.com/FPMAS/) in the context of the Paul Breugnot's Ph.D. thesis (Distribution and synchronisation of Multi-Agent System simulations).
description: Ce jeu de données contient des temps d'exécution et des résultats du modèle fpmas-virus (https://github.com/FPMAS/fpmas-virus) obtenus avec la plateforme FPMAS (https://github.com/FPMAS/) dans le contexte de la thèse de doctorat de Paul Breugnot (Distribution et synchronisation des simulations de Systèmes Multi-Agents).
description: Audience: Research
description: UpdatePeriodicity: no update
description: AdditionnalInformation: Data collected as part of a Ph.D. thesis in computer science, by Paul Breugnot, co-supervised by Laurent-Philippe (Professor), Christophe Lang (Associate Professor) et Bénédicte Herrmann (Research Professor), FEMTO-ST.
description: AdditionnalInformation: Données collectées dans le cadre de la thèse en informatique de Paul Breugnot, co-encadrée par Laurent-Philippe (Professeur), Christophe Lang (Maître de conférence HDR) et Bénédicte Herrmann (Enseignant-Chercheur) au laboratoire FEMTO-ST.
description: Project: FPMAS, EIPHI Graduate School (contrat ANR-17-EURE-0002) (French National Agency for Research), SYMPAMA (contrat CRBFC:2019-Y-09120) (Region Bourgogne Franche-Comté)
description: Label: Mésocentre(s) UBFC (Mésocentre(s) UBFC)
description: Simulation or computational data: Raw data have been obtained from simulations of the fpmas-virus with the FPMAS platform, executed on the Mésocentre de calcul de Franche-Comté. See the README.md file included in the dataset for detailed explanations.
description: Données computationnelles ou de simulation: Les données brutes ont été obtenues par des simulations du modèle fpmas-virus grâce à la plateforme FPMAS, exécutées sur le Mésocentre de calcul de Franche-Comté. Voir le fichier README.md inclus dans le jeu de données pour des explications détaillées.
DOI: 10.25666/dataubfc-2023-04-11-03
title: Detailed execution times of several FPMAS Meta-model instances
title: Temps d'exécution détaillés de plusieurs instances du Meta-modèle FPMAS

description: This dataset contains detailed fpmas-metamodel (https://github.com/FPMAS/fpmas-metamodel) execution time data obtained with the FPMAS platform (https://github.com/FPMAS/) in the context of Paul Breugnot's PhD thesis (Distribution and synchronisation of Multi-Agent Systems simulations), that proposes aggregated and selected views and analysis of the complex raw data contained in this dataset.
description: Ce jeu de données contient des temps d'exécution détaillés du fpmas-metamodel (https://github.com/FPMAS/fpmas-metamodel) obtenus avec la plateforme FPMAS (https://github.com/FPMAS/) dans le contexte de la thèse de doctorat de Paul Breugnot (Distribution et synchronisation des simulations de Systèmes Multi-Agents), qui proposent des vues et analyses agrégées et choisies des données brutes complexes contenues dans ce jeu de données.
description: Audience: Research
description: UpdatePeriodicity: no update
description: AdditionnalInformation: Data collected as part of a Ph.D. thesis in computer science, by Paul Breugnot, co-supervised by Laurent-Philippe (Professor), Christophe Lang (Associate Professor) et Bénédicte Herrmann (Research Professor), FEMTO-ST.
description: AdditionnalInformation: Données collectées dans le cadre de la thèse en informatique de Paul Breugnot, co-encadrée par Laurent-Philippe (Professeur), Christophe Lang (Maître de conférence HDR) et Bénédicte Herrmann (Enseignant-Chercheur) au laboratoire FEMTO-ST.
description: Project: FPMAS, EIPHI Graduate School (contrat ANR-17-EURE-0002) (French National Agency for Research), SYMPAMA (contrat CRBFC:2019-Y-09120) (Region Bourgogne Franche-Comté)
description: Label: Mésocentre(s) UBFC (Mésocentre(s) UBFC)
description: Simulation or computational data: Raw data have been obtained from simulations of the fpmas-metamodel with the FPMAS platform, executed on the Mésocentre de calcul de Franche-Comté. See the README.md file included in the dataset for detailed explanations.
description: Données computationnelles ou de simulation: Les données brutes ont été obtenues par des simulations du modèle fpmas-metamodel grâce à la plateforme FPMAS, exécutées sur le Mésocentre de calcul de Franche-Comté. Voir le fichier README.md inclus dans le jeu de données pour des explications détaillées.
DOI: 10.15468/dl.dn2wwf
title: Occurrence Download

description: A dataset containing 764 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Conioselinum anthriscoides (H.Boissieu) Pimenov & Kljuykov",
 "Country is China",
 "Year is greater than or equal to 1900",
 "HasCoordinate is true"
 ]
}

 The dataset includes 764 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091700-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w7urmh
title: Occurrence Download

description: A dataset containing 274 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhynchosia sordida (E.Mey.) Schinz"
 ]
}

 The dataset includes 274 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091701-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7uhju4
title: Occurrence Download

description: A dataset containing 281 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Quercus acrodonta Seemen"
 ]
}

 The dataset includes 281 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091704-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hsx6b5
title: Occurrence Download

description: A dataset containing 85 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ranunculus pollinensis (N.Terracc.) Chiov."
 ]
}

 The dataset includes 85 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091705-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5nxjw2
title: Occurrence Download

description: A dataset containing 263 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((42.75429 -20.47626,41.14791 -26.18767,52.90544 -26.8859,60.84507 -20.13462,52.93583 -11.13321,47.39475 -10.90021,42.75429 -10.90021,42.75429 -20.47626))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Sanzinia madagascariensis (Duméril & Bibron, 1844)"
 ]
}

 The dataset includes 263 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091703-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5ecjxt
title: Occurrence Download

description: A dataset containing 134 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhododendron gracilentum F.Muell."
 ]
}

 The dataset includes 134 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091707-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.57mzkt
title: Occurrence Download

description: A dataset containing 142 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Country is one of (Portugal, Spain)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Ceratocapnos claviculata subsp. claviculata",
 "Year 1950-2025"
 ]
}

 The dataset includes 142 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021930-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25574/00107
title: Chandra X-ray Observatory ObsId 00107

description: HETG OBSERVATIONS OF X-RAY BINARIES
DOI: 10.21227/2xsm-8r59
title: Goose Surface Temperature Monitoring System Based on Deep Learning Using Visible and Infrared Thermal Image Integration

description: Owing to increased biosecurity and industrial demands, the poultry houses in Taiwan are generally nonopen and closed types, with automatic environmental control and sensor equipment gradually being installed in such houses. Environmental sensors and poultry health monitoring systems are necessary to improve poultry feeding efficiency and safety. In this work, we developed a goose surface temperature monitoring system based on deep learning using visible and infrared thermal images. The goose images were first collected in a poultry house to form the deep learning training data set. The Mask R-convolutional neural network algorithm was then employed to train the goose detection model. The developed goose surface temperature monitoring system consisted of an embedded system with the trained goose detection model, a visible camera, and an infrared thermal camera. The visible camera captured visible images in the poultry house, in which the geese could be identified by the trained goose detection model. The individual surface temperatures of the geese were obtained through integration of the visible and infrared thermal images. The developed monitoring systems were installed in the land and pool areas of a commercial goose house to monitor the surface temperature of the geese and achieved a precision of 97.1% and recall of 95.1%. In addition, the goose surface temperature of the pool area was observed to be lower than that of the land area.
DOI: 10.5281/zenodo.3327313
title: Slip model and Relative Source Time Functions for the 2013 Mw 3.3 St. Gallen earthquake

description: Slip model and Relative Source Time Functions for the the 2013 Mw 3.3 St. Gallen earthquake Király‐Proag, E., Satriano, C., Bernard, P., & Wiemer, S. (2019). Rupture process of the Mw 3.3 earthquake in the St. Gallen 2013 geothermal reservoir, Switzerland. Geophysical Research Letters, 46, doi: 10.1029/2019GL082911
DOI: 10.5281/zenodo.3245487
title: Slip model and Relative Source Time Functions for the 2013 Mw 3.3 St. Gallen earthquake

description: Slip model and Relative Source Time Functions for the the 2013 Mw 3.3 St. Gallen earthquake Király‐Proag, E., Satriano, C., Bernard, P., & Wiemer, S. (2019). Rupture process of the Mw 3.3 earthquake in the St. Gallen 2013 geothermal reservoir, Switzerland. Geophysical Research Letters, 46, doi: 10.1029/2019GL082911
DOI: 10.6084/m9.figshare.14539971.v1
title: Personal monitoring data and interview results regarding dosimeters worn by medical workers in Japan

description: Misuse (inappropriate positioning) of personal dosimeters by health professionals leads to erroneous readings. This dataset include information on 670 pairs of the dose equivalent Hp(10) readings of medical workers at the Hiroshima University Hospital and the positions of the dosimeters used for monitoring. The data are presented in ‘Original_readings_included_interviews.csv’.
DOI: 10.25534/tudatalib-166.2
title: RailDriVE February 2019 - Data Set for Rail Vehicle Positioning Experiments

description: <strong>Key facts</strong> <strong>Fields of application:</strong><br> railway positioning, sensor fusion, sensor models <strong>Available data:</strong><br> 2x GNSS, 2x IMU, 1x odometer, 2x speed sensors, camera images <strong>Available reference data:</strong><br> Open GNSS/IMU EKF-fusion solution (loosely coupled), Proprietary GNSS/IMU EKF-fusion solution (tightly coupled), Track-Map <strong>Structure:</strong><br> This data set follows the data sharing principles of the LRT (localization reference train) initiative that are available at lrt-initiative.org. <strong>About</strong> We provide a data set that can be used for various rail vehicle positioning experiments. The data were collected using the German Aerospace Center (DLR) research vehicle RailDriVE on a segment of the Braunschweig harbor railway in February 2019. Several sensors of the RailDriVE equipment and an additional self-sufficient system provided by Technische Universität Darmstadt (TU Darmstadt) were employed, including two GNSS receivers, two inertial measurement units (IMU), and several speed and distance sensors (radar, optical, odometer). Front-facing camera data has been included for documentation purposes. In order to simplify its use, some pre-processing steps were applied to the data, mainly to have common time and coordinate frames. Furthermore, example and reference positioning solutions as well as a track map have been included. The data can be used as a starting point for research work or student theses. Novel and established algorithms for many different sub-problems can be tested on the data, in order to facilitate their comparison and make results and insights more accessible. <strong>Companion paper</strong> For reference to the data set in your research, please cite the companion paper: M. Roth and H. Winter, "An Open Data Set for Rail Vehicle Positioning Experiments," 23rd International Conference on Intelligent Transportation Systems (ITSC), Sep. 2020
DOI: 10.25534/tudatalib-260
title: Supplementary information to 'Radiogenic heat production of crystalline rocks in the Gonghe Basin Complex (Northeastern Qinghai-Tibet plateau, China)'

description: The Gonghe Basin Complex (GBC), is a pull-apart basin located in the Northeastern Qinghai-Tibet plateau (Qinghai, China) displaying various geothermal features such as elevated geothermal gradients and hot springs, whose origin has not been conclusively determined so far. The adjacent mountain ranges and the basement are comprised of granitoidic rock, which, at sufficient depth and temperature, are suitable for deep enhanced geothermal systems. This study aims to investigate if the radiogenic heat production of these plutonic rocks is the heat source for the surface geothermal features. Therefore, 30 newly sampled Triassic, Silurian, Ordovician and Devonian intrusive rocks were extracted from outcrops in the surroundings and within the GBC, of which one sample was retrieved from exploration well DR2 at c. 1800 m. Samples were geochemically discriminated using the results of XRF measurements and radiogenic heat productions were subsequently calculated. Additionally, analysis of 341 intrusive, 105 extrusive, 155 sedimentary and 76 metamorphic rocks of the Qinling-Qilianshan-Kunlunshan were comprised from literature and compared to the data sampled in the GBC. As evidenced in the presented research, the radiogenic heat production measured in the GBC are within the highest calculated for the Qinling-Qilianshan-Kunlunshan. Although, radiogenic heat production rates in the GBC only range from &lt; 1 µW m^-3 in tonalites to &gt; 5 µW m^-3 in two-mica granites and syenogranites. Nonetheless, average heat productions analyzed do not evidence large intrusions of HHP (high heat producing) granitoids as source of the geothermal features in the GBC pull-apart basin.
DOI: 10.25534/tudatalib-69
title: One Dimensional Magnetic Resonance Microscopy with Micrometer Resolution in Static Field Gradients : secondary data
DOI: 10.25534/tudatalib-57
title: Unsplit VoF review data and tables

description: Tabular data of the reconstruction and advection errors from reviewed unsplit Volume-of-Fluid methods.
DOI: 10.25534/tudatalib-58
title: Contact Line Advection using the Level Set Method : Data and C++ Implementations

description: Solving the contact line advection problem with the level set method.
DOI: 10.25534/tudatalib-62
title: Results of the SAAMPLE algorithm

description: Curvature approximation and force-balance errors of the SAAMPLE algorithm.
DOI: 10.25534/tudatalib-61
title: Convergence of the OpenFOAM fvc::reconstruct operator

description: Convergence of the OpenFOAM fvc::reconstruct operator error in the L_inf norm for the reconstruction of explicit velocity fields given by the single vortex case (2D shear) model and the Hadamard-Rybczynsky model.
DOI: 10.25534/tudatalib-73
title: geophase: Consecutive Cubic Spline positioning results

description: Tabular data, diagrams and processing script for the Newton Cubic Spline and Consecutive Cubic Spline iterative positioning algorithms used for the Volume-of-Fluid PLIC in generalized polyhedron that can be non-convex (star shaped) and have non-planar faces.
DOI: 10.25534/tudatalib-75
title: Plant growth speed (trees)

description: Large set of data related to plats, or not.
DOI: 10.25534/tudatalib-113.2
title: MRV data of a pulsating flow through a generic aneurysm

description: This dataset is intended to serve as an input for different WSS estimators and has been discussed in the publication of: Bauer, A.; Bopp, M.; Jakirlic, S.; Tropea, C.; Krafft, A. J.; Shokina, N. & Hennig, J. Analysis of the wall shear stress in a generic aneurysm under pulsating and transitional flow conditions Experiments in Fluids, 2020, under review. We provide the data in two different file formats: The raw data, directly from the MRI scanner in the DICOM format, and converted files suitable for Matlab. For each format a separate ReadMe file is provided with additional information within the respective folder. The data was acquired within the DFG project under Grants TR 194/56-1, EG 331/1-1 and HE 1875/30-1.
DOI: 10.25534/tudatalib-104
title: Umfragedaten zu "NFDI4Ing - Rückmeldung aus den Forschungscommunities"

description: Die Online-Umfrage "NFDI4Ing - Rückmeldung aus den Forschungscommunities" wurde vom Konsortium NFDI4Ing (Nationale Forschungsdateninfrastruktur für die Ingenieurwissenschaften, https://nfdi4ing.de) vom 21.08.2019 bis einschließlich 16.09.2019 durchgeführt. <br> Zielgruppe waren die Leiter von ingenieurwissenschaftlichen Forschungsgruppen, im Sinne von Lehrstühlen / Professurenn / Fachgebieten an Hochschulen und Universitäten sowie Verbundprojekte (z.B. SFBs) und einzelne Forschungsabteilungen außeruniversitärer Forschungseinrichtungen (z.B. Forschungsbereiche eines Fraunhofer-Instituts). <br> Es wurden alle ingenieurwissenschaftlichen Forschungseinrichtungen Deutschlands angeschrieben (Fachbereiche von Universitäten und Hochschulen, Verbundprojekte (SFBs, GRKs, Exzellenzcluster), Fraunhofer-, Leibniz-, Max-Planck-Institute, Helmholtz-Zentren, Ressortforschungseinrichtungen, Fachgesellschaften- und verbände). <br> Insgesamt wurden 701 Fragebögen ausgefüllt, davon 618 vollständig.
DOI: 10.25534/tudatalib-127
title: Simultaneous imbibition and evaporation of liquids on grooved substrates: Secondary Data

description: The enclosed „Simultaneous_Imbibition_Evaporation.xlsx” file contains the data used to generate the plots in Figs. 5, 7-10 of the publication “Simultaneous imbibition and evaporation of liquids on grooved substrates“ by Tatiana Gambaryan-Roisman. The file contains tables labeled “Fig 5 data”, “Fig 7 data”, …, “Fig 9 10 data”, in which the data are organized in columns. The labels of columns correspond to the axes labels in the figures. For the figures containing more than one curve, additional information is provided in order to establish a one-to-one correspondence between the data and the plots published in the paper. This is done by describing the line type and color as well as the data item attribute mentioned in the paper. The file contains, in addition, the plots generated from the data. These plots are labeled “Fig 5 plot”, …, “Fig 10 plot”.
DOI: 10.25534/tudatalib-136
title: Validation of the LENT-SAAMPLE method with the large amplitude droplet oscillation experiments conducted by Trinh and Wang

description: The LENT-SAAMPLE method is validated using oscillations of droplets for which the amplitude cannot be considered small compared to the equivalent radius of the droplet. For the experiments, single silicone oil drops are suspended in water. Each drop is kept at a stable position using acoustic radiation pressure generated by an ultrasonic transducer. A second transducer is used to drive the droplet oscillations. Besides forced oscillations, the authors investigate the damping of free large amplitude oscillations (section 5 in (https://doi.org/10.1017/S0022112082002237)). In the following, we examine to what degree our LENT-SAAMPLE method is able to reproduce Trinh and Wang’s experimental results.
DOI: 10.25534/tudatalib-140
title: Numerical investigation of the aeration process in the MBR system equipped with a flat sheet membrane module

description: New solver (InterSolidFoam) development <br> Combing the interDyMFoam and the driftFluxFoam, interSolidFoam is developed within the framework OpenFOAM to investigate the effect of activated sludge on bubble dynamics. <br> OpenFOAM simulations <br> Simulations are performed to quantify the hydrodynamic characteristics in MBRs ( the flat sheet membrane module), i.e. shear stress on the membrane surfaces under different operational and constructional conditions. The critical parameters are bubble size, liquid velocity, membrane channel distance, and activated sludge concentration. They are investigated both for single bubbles and bubble swarms in the membrane channel numerically. Besides, simulations on air flow rate, aerator geometry, aerator position and aeration intensity are performed.