cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.by37tf
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Gonodera metallica (Küster, 1850)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 23 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071114-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.23636/k903-md30
title: Incunabula Short Title Catalogue data release 2025

description: The Incunabula Short Title Catalogue (ISTC) is an online database of books printed with moveable type in the 15th century. It contains over 30,000 bibliographic records and holding information for incunabula collections aorund the world. This data release makes available the entirety of the ISTC data as well as additional background information on the database's history and the current standard of cataloguing. As ISTC is regularly updated, this data release reflects the state of ISTC January 2025.
description: London, UK
DOI: 10.15468/dl.86wv2t
title: Occurrence Download

description: A dataset containing 4801 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((59.31649 7.47352,178.14476 7.47352,178.14476 54.98448,59.31649 54.98448,59.31649 7.47352))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Triadica sebifera (L.) Small"
 ]
}

 The dataset includes 4801 records from 72 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071113-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18419/darus-3705
title: Parallel Lattice Boltzmann code for simulating single phase flows in porous domains

description: This dataset contains a parallelized Lattice Boltzmann code, along with an example input domain and input file containing the necessary parameters for a test run. A MATLAB script to visualize and process the simulation results is also provided.
&lt;br/&gt;&lt;br/&gt;

Among the uploaded files, Lb7mpi_281124.f90 is a computational code implementing a single phase Lattice Boltzmann (LB) model originally proposed by Guo et al. (2002). The code was developed by Prof. Andreas Yiotis (TUC) and Dr. Michael Kainourgiakis (NCSR Demokritos) based on the Fortran 95 computing language during 2005-2014. It is a highly parallel, scalable and computationally efficient code that relies on the MPI 2.0 (Message Passing Interface) protocol in order to take advantage of the computational capabilities of distributed memory supercomputers. As such, it has been thoroughly tested in terms of its efficiency and scalability in several large-scale supercomputers, including MareNostrum (BSC, Spain), IDRIS (France) and ARIS (Greece), exhibiting excellent scalability up to 2048+ cpu cores. 
&lt;br/&gt;&lt;br/&gt;
Lb7mpi is optimized for numerical simulations of single phase flows in 3D digital porous media in order to study the pore scale characteristics on the permeability of the digital porous domain. Flow is driven using a standard body force scheme and it is assumed to be periodic in all three directions in space. The digital domain is an ascii file that represents the 3D pore space as a sequence of 2D matrices. Each matrix corresponds to a fixed z value and contains the x-y conductivity of the medium. The hydraulic conductivity is denoted as zero (0) for solid lattice voxels where no flow is possible, and as one (1) for pore (void) voxels where flow takes place. 
&lt;br/&gt;&lt;br/&gt;
All computational parameters, including the name of the digital domain, the value of the body force, the LB relaxation parameters, as well as the load balancing scheme for parallel computation are declared by the user in a single input file named input.txt. The source code should be compiled using the standard mpif90 compiler wrapper that produces an executable linked to the installed mpi libraries available on your computational system. 
&lt;br/&gt;&lt;br/&gt;
The code is distributed as open-source and can be used explicitly for academic, educational and research purposes, as long as an appropriate reference to the original authors (see above) is provided. It should not be used as part of a commercial product. Furthermore, the code is distributed as is for the academic and research community without any warranty regarding the accuracy of the produced results. Very limited support can be provided by the authors. Such inquiries should be addressed to agiotis@tuc.gr (Prof. Andreas Yiotis).
description: More information can be found in the readme.txt.
DOI: 10.15468/dl.22r8kg
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Grammoptera viridipennis Pic, 1893",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071117-241126133413365/datasets/export for details.
DOI: 10.3217/vatm8-d5h15
title: Reconstruction of refractive index gradients in a reactive turbulent flow based on U-net supervised reconstruction  dataset and python code

description: This research is the result of Austrian-German joint research project, funded by the Austrian Science Fund FWF within grant FWF-I5392-N and the Deutsche Forschungsgemeinschaft DFG within grant CZ 55/50-1. This project is a Lead-Agency D-A-CH project in cooperation between Graz University of Technology, Austria and Technische Universität Dresden, Germany, named "FOUR-DIMENSIONAL MEASUREMENT OF THERMOACOUSTIC OSCILLATIONS".

The underlying hypothesis of this project claims that four-dimensional detection of local thermoacoustic oscillations, based on the combination of a (camera-based) laser interferometric vibrometer with multidirectional background-oriented schlieren method, density tagging velocimetry and deep neural networks as binding element, will reveal local and coupled information on combustion, acoustics and fluid dynamics. 

As of Jan 2025, this repository contains the Python routines and sample data from this project.

This publication refers to the previous publication by

Tasmany, S., Kaiser, D., Woisetschläger, J. et al. Heterodyne background-oriented schlieren for the measurement of thermoacoustic oscillations in flames. Exp Fluids 65, 151 (2024). https://doi.org/10.1007/s00348-024-03890-1

Tasmany S, Woisetschläger J (2024) Heterodyne background-oriented schlieren for the measurement of thermoacoustic oscillations in flames. Graz Univ Technol. https://doi.org/10.3217/7k9f0-7wb03

 

repository.zip is composed of 2 subfolders:



gradient test

Neural Network code


gradient test folder contains 100 couples of numpy array files, which represents a sample of the image dataset used.

Neural network code contains the files main.py, Evaluate_model.py and net_model.pt.



main.py is the python code used to preprocess images and build and train the neural network

Evaluate_model.py is the python code used to test the network trained with main.py 

net_model.pt is a pretrained pytorch network file (trained on the full dataset of 1000 images)
DOI: 10.3217/vyf5w-yqf81
title: Reconstruction of refractive index gradients in a reactive turbulent flow based on U-net supervised reconstruction  dataset and python code

description: This research is the result of Austrian-German joint research project, funded by the Austrian Science Fund FWF within grant FWF-I5392-N and the Deutsche Forschungsgemeinschaft DFG within grant CZ 55/50-1. This project is a Lead-Agency D-A-CH project in cooperation between Graz University of Technology, Austria and Technische Universität Dresden, Germany, named "FOUR-DIMENSIONAL MEASUREMENT OF THERMOACOUSTIC OSCILLATIONS".

The underlying hypothesis of this project claims that four-dimensional detection of local thermoacoustic oscillations, based on the combination of a (camera-based) laser interferometric vibrometer with multidirectional background-oriented schlieren method, density tagging velocimetry and deep neural networks as binding element, will reveal local and coupled information on combustion, acoustics and fluid dynamics. 

As of Jan 2025, this repository contains the Python routines and sample data from this project.

This publication refers to the previous publication by

Tasmany, S., Kaiser, D., Woisetschläger, J. et al. Heterodyne background-oriented schlieren for the measurement of thermoacoustic oscillations in flames. Exp Fluids 65, 151 (2024). https://doi.org/10.1007/s00348-024-03890-1

Tasmany S, Woisetschläger J (2024) Heterodyne background-oriented schlieren for the measurement of thermoacoustic oscillations in flames. Graz Univ Technol. https://doi.org/10.3217/7k9f0-7wb03

 

repository.zip is composed of 2 subfolders:



gradient test

Neural Network code


gradient test folder contains 100 couples of numpy array files, which represents a sample of the image dataset used.

Neural network code contains the files main.py, Evaluate_model.py and net_model.pt.



main.py is the python code used to preprocess images and build and train the neural network

Evaluate_model.py is the python code used to test the network trained with main.py 

net_model.pt is a pretrained pytorch network file (trained on the full dataset of 1000 images)
DOI: 10.15468/dl.sbezys
title: Occurrence Download

description: A dataset containing 9511 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Phorcus lineatus (da Costa, 1778)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 9511 records from 123 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071116-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.45cmey
title: Occurrence Download

description: A dataset containing 386 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "GadmGid is CHN.1.5.4_1",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 386 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071120-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15131/shef.data.28046066
title: Front-facing camera data from Minicam's pipe navigation robot in concrete pipes

description: <b>This directory contains data captured by the front-facing camera of a Minicam robot navigating in</b><b> a 5-meter concrete pipe network. The network consists of two 2.5-meter concrete pipe sections. </b><b>Details for each measurement can be found in the .README file included in the folder.</b>The data was collected as efforts to address the challenges of accurate navigation, mapping and inspection within feature-sparse pipe networks.The dataset includes:Visual data captured during robot navigation.Information about the pipe network, including dimensions, material and structure.Details of the robot velocity and the camera's luminosity level.This dataset is intended to support research and development in autonomous robotics, particularly for navigation, mapping and inspection tasks in confined environments. It can be used for computer vision applications, visual odometry and algorithm development.Contributors:Dr Aristeidis Karnezis, Dr Sean Anderson, Professor Kirill Horoshenkov, Professor Lyudmila Mihaylova
DOI: 10.15131/shef.data.28046066.v2
title: Front-facing camera data from Minicam's pipe navigation robot in concrete pipes

description: <b>This directory contains data captured by the front-facing camera of a Minicam robot navigating in</b><b> a 5-meter concrete pipe network. The network consists of two 2.5-meter concrete pipe sections. </b><b>Details for each measurement can be found in the .README file included in the folder.</b>The data was collected as efforts to address the challenges of accurate navigation, mapping and inspection within feature-sparse pipe networks.The dataset includes:Visual data captured during robot navigation.Information about the pipe network, including dimensions, material and structure.Details of the robot velocity and the camera's luminosity level.This dataset is intended to support research and development in autonomous robotics, particularly for navigation, mapping and inspection tasks in confined environments. It can be used for computer vision applications, visual odometry and algorithm development.Contributors:Dr Aristeidis Karnezis, Dr Sean Anderson, Professor Kirill Horoshenkov, Professor Lyudmila Mihaylova
DOI: 10.15131/shef.data.28046066.v1
title: Front-facing camera data from Minicam's pipe navigation robot in concrete pipes

description: <b>This directory contains data captured by the front-facing camera of a Minicam robot navigating in</b><b> a 5-meter concrete pipe network. The network consists of two 2.5-meter concrete pipe sections. </b><b>Details for each measurement can be found in the .README file included in the folder.</b>The data was collected as efforts to address the challenges of accurate navigation, mapping and inspection within feature-sparse pipe networks.The dataset includes:Visual data captured during robot navigation.Information about the pipe network, including dimensions, material and structure.Details of the robot velocity and the camera's luminosity level.This dataset is intended to support research and development in autonomous robotics, particularly for navigation, mapping and inspection tasks in confined environments. It can be used for computer vision applications, visual odometry and algorithm development.Contributors:Dr Aristeidis Karnezis, Dr Sean Anderson, Professor Kirill Horoshenkov, Professor Lyudmila Mihaylova
DOI: 10.15468/dl.qg3j6h
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Graptodytes delectus (Wollaston, 1864)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 13 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071122-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17033/data.00000323
title: The impact of precipitation events on the supply and movement of fine sediment in intertidal systems

description: This is part of the data set from Pagham and Medmerry Intertidal Processes Project.
description: Remote equipment
DOI: 10.6084/m9.figshare.28091444
title: Data.xlsx

description: Mortality, Inhibition rate, Changes in liver indicators
DOI: 10.6084/m9.figshare.28091444.v2
title: Data.xlsx

description: Mortality, Inhibition rate, Changes in liver indicators
DOI: 10.6084/m9.figshare.28091444.v3
title: Data.xlsx

description: Mortality, Inhibition rate, Changes in liver indicators
DOI: 10.2908/isoc_ci_cm_pn2
title: Nutzung von Computern und dem Internet durch Beschäftigte, nach Aktivitäten der NACE Rev.2
title: Utilisation d'ordinateurs et de l'internet par les salariés, par activité de la NACE Rév. 2
title: Use of computers and the internet by employees by NACE Rev. 2 activity
DOI: 10.2908/isoc_ci_in_en2
title: Accès à l'internet, par activité de la NACE Rév. 2
title: Internet-Zugang, nach Aktivitäten der NACE Rev.2
title: Internet access by NACE Rev. 2 activity
DOI: 10.2908/isoc_ci_it_en2
title: Art der Verbindung zum Internet, nach Aktivitäten der NACE Rev.2
title: Type de connexion à l'internet, par activité de la NACE Rév. 2
title: Type of connections to the internet by NACE Rev. 2 activity
DOI: 10.2908/isoc_cismtn2
title: Types de médias sociaux utilisés, publicité sur l'internet, par activité de la NACE Rév. 2
title: Arten genutzter sozialer Medien, Werbung im Internet, nach Aktivitäten der NACE Rev.2
title: Social media use by type, internet advertising and NACE Rev. 2 activity
DOI: 10.2908/isoc_e_cvdn2
title: Impact du Covid -19 sur l'utilisation des TIC, par activité de la NACE Rév. 2
title: Auswirkungen von Covid-19 auf die IKT-Nutzung, nach Aktivitäten der NACE Rev.2
title: Covid-19 Impact on ICT usage by NACE Rev. 2 activity
DOI: 10.2908/isoc_e_diin2
title: Intensité digitale, par activité de la NACE Rév. 2
title: Digitale Intensität, nach Aktivitäten der NACE Rev.2
title: Digital Intensity by NACE Rev. 2 activity
DOI: 10.2908/isoc_cismpn2
title: Buts de l'utilisation des médias sociaux, par activité de la NACE Rév. 2
title: Einsatz von sozialen Medien, nach Aktivitäten der NACE Rev.2
title: Social media use by purpose and NACE Rev. 2 activity
DOI: 10.2908/isoc_e_envn2
title: Les TIC et l’environnement, par activité de la NACE Rév. 2
title: IKT und die Umwelt nach Tätigkeiten der NACE Rev.2
title: ICT and environment by NACE Rev. 2 activity
DOI: 10.2908/isoc_cimobe_usen2
title: Usage professionnel des connexions mobiles à l'internet, par activité de la NACE Rév. 2
title: Verwendung mobiler Verbindungen zum Internet, nach Aktivitäten der NACE Rev.2
title: Use of mobile connections to the internet by NACE Rev. 2 activity
DOI: 10.2908/isoc_ciwebn2
title: Sites web et leurs fonctionnalités, par activité de la NACE Rév. 2
title: Websites und deren Funktionalitäten, nach Aktivitäten der NACE Rev.2
title: Websites and functionalities by NACE Rev. 2 activity
DOI: 10.15468/dl.5ptshu
title: Occurrence Download

description: A dataset containing 1513 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Grynocharis oblonga (Linnaeus, 1758)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1513 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071125-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15131/shef.data.28046630
title: Front-facing camera data from Minicam's pipe navigation robot in plastic pipes

description: <b>This directory contains data captured by the front-facing camera of a Minicam robot navigating in</b><b> multiple plastic pipe networks. The first network includes two 3-meter plastic pipe sections, the second network includes four 3-meter plastic pipe sections, and the third network includes six 3-meter plastic pipes and one 2-meter plastic pipe section. Detailed measurement information can be found </b><b>in the .README file included in each folder.</b>The data was collected as efforts to address the challenges of accurate navigation, mapping and inspection within feature-sparse pipe networks.The dataset includes:Visual data captured during robot navigation.Information about the pipe network, including dimensions, material and structure.Details of the robot velocity and the camera's luminosity level.This dataset is intended to support research and development in autonomous robotics, particularly for navigation, mapping and inspection tasks in confined environments. It can be used for computer vision applications, visual odometry and algorithm development.Contributors:Dr Aristeidis Karnezis, Dr Sean Anderson, Professor Kirill Horoshenkov, Professor Lyudmila Mihaylova
DOI: 10.15131/shef.data.28046630.v1
title: Front-facing camera data from Minicam's pipe navigation robot in plastic pipes

description: <b>This directory contains data captured by the front-facing camera of a Minicam robot navigating in</b><b> multiple plastic pipe networks. The first network includes two 3-meter plastic pipe sections, the second network includes four 3-meter plastic pipe sections, and the third network includes six 3-meter plastic pipes and one 2-meter plastic pipe section. Detailed measurement information can be found </b><b>in the .README file included in each folder.</b>The data was collected as efforts to address the challenges of accurate navigation, mapping and inspection within feature-sparse pipe networks.The dataset includes:Visual data captured during robot navigation.Information about the pipe network, including dimensions, material and structure.Details of the robot velocity and the camera's luminosity level.This dataset is intended to support research and development in autonomous robotics, particularly for navigation, mapping and inspection tasks in confined environments. It can be used for computer vision applications, visual odometry and algorithm development.Contributors:Dr Aristeidis Karnezis, Dr Sean Anderson, Professor Kirill Horoshenkov, Professor Lyudmila Mihaylova
DOI: 10.60520/ieda/113644
title: Sr-Nd-Pb isotopic compositions of ocean island basalts from the Marquesas archipelago

description: Sr-Nd-Pb dataset for ocean island basalts from three islands of the Marquesas Archipelago. Data complements and extends those of Castillo et al. (2007 Chem. Geol.) for the same samples. High-precision data for the short-lived 142Nd radiogenic system are included. The purpose of the dataset is to evaluate the time-integrated relationship between different geochemical components of volcanism (FOZO, HIMU, EM) present in the isotopic compositions of Marquesas lavas.
DOI: 10.15468/dl.wr82aw
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Prunus laurocerasus",
 "Country is Belgium"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071127-241126133413365/datasets/export for details.
DOI: 10.7483/opendata.cms.7kmx.g5bk
title: /TprimeBToTH_THad_Hbb_LH_MT800_MH250_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.9ggm.fc7w
title: /TprimeBToTH_THad_Hbb_LH_MT800_MH25_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.byu3.1s5a
title: /TprimeBToTH_THad_Hbb_LH_MT800_MH25_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.15468/dl.739x5g
title: Occurrence Download

description: A dataset containing 976 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Gymnopleurus sturmii MacLeay, 1821",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 976 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071129-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7483/opendata.cms.fjon.ddd3
title: /TprimeBToTH_THad_Hbb_LH_MT800_MH350_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.gkno.2p88
title: /TprimeBToTH_THad_Hbb_LH_MT800_MH350_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.jb81.4w31
title: /TprimeBToTH_THad_Hbb_LH_MT800_MH450_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.12t3.gff3
title: /TprimeBToTH_THad_Hbb_LH_MT800_MH450_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM
DOI: 10.7483/opendata.cms.yz2q.nghv
title: /TprimeBToTH_THad_Hbb_LH_MT800_MH500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16MiniAODv2-106X_mcRun2_asymptotic_v17-v2/MINIAODSIM
DOI: 10.7483/opendata.cms.rwzy.q96s
title: /TprimeBToTH_THad_Hbb_LH_MT800_MH500_TuneCP5_13TeV-madgraph-pythia8/RunIISummer20UL16NanoAODv9-106X_mcRun2_asymptotic_v17-v1/NANOAODSIM