cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18419/darus-3118
title: Tracer-diffusion coefficients of experimental aqueous methanol mixtures

description: In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experiment and simulation was demonstrated for two binary mixtures, methanol-water and glycerol-water, by systematically studying the dependence of densities and diffusion coefficients from water content over the whole composition range and temperatures between 278.15 and 318.15 K. Experimental data was extracted manually from literature. The same parameter space was explored by comprehensive molecular dynamics simulations, whose results were directly transferred to the analysis platform. The benefit of data integration was illustrated by assessing the transferability of the force fields, which had been developed for pure compounds to different compositions and temperatures, and by analyzing the excess mixing properties as a measure of non-ideality of methanol-water and glycerol-water mixtures. The core of the data management and analysis platform is the newly developed Python library pyThermoML, which represents metadata, the parameters and the experimentally determined or simulated properties as Python data classes. 
&lt;br&gt;&lt;/br&gt;
The feasibility of a seamless data flow from data acquisition to a comprehensive data analysis was demonstrated. &lt;a href="https://github.com/FAIRChemistry/pyThermoML"&gt;PyThermoML&lt;/a&gt; enables interoperability and reusability of the datasets. The publication of ThermoML documents on the Dataverse installation of the University of Stuttgart (DaRUS) makes thermophysical data findable and accessible, and thus FAIR.
&lt;br&gt;&lt;/br&gt;
The usage of pyThermoML is demonstrated in the following &lt;a href="https://github.com/FAIRChemistry/pyThermoML/blob/master/pyThermoML_example_workflow/templateThermoML.ipynb"&gt;example workflow&lt;/a&gt; and can be utilized to read the given ThermoML file.
DOI: 10.18419/darus-3118/1
title: exp_sdiff_meth.xml
DOI: 10.18419/darus-3119
title: Self-diffusion coefficients of experimental aqueous glycerol mixtures

description: In order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experiment and simulation was demonstrated for two binary mixtures, methanol-water and glycerol-water, by systematically studying the dependence of densities and diffusion coefficients from water content over the whole composition range and temperatures between 278.15 and 318.15 K. Experimental data was extracted manually from literature. The same parameter space was explored by comprehensive molecular dynamics simulations, whose results were directly transferred to the analysis platform. The benefit of data integration was illustrated by assessing the transferability of the force fields, which had been developed for pure compounds to different compositions and temperatures, and by analyzing the excess mixing properties as a measure of non-ideality of methanol-water and glycerol-water mixtures. The core of the data management and analysis platform is the newly developed Python library pyThermoML, which represents metadata, the parameters and the experimentally determined or simulated properties as Python data classes. 
&lt;br&gt;&lt;/br&gt;
The feasibility of a seamless data flow from data acquisition to a comprehensive data analysis was demonstrated. &lt;a href="https://github.com/FAIRChemistry/pyThermoML"&gt;PyThermoML&lt;/a&gt; enables interoperability and reusability of the datasets. The publication of ThermoML documents on the Dataverse installation of the University of Stuttgart (DaRUS) makes thermophysical data findable and accessible, and thus FAIR.
&lt;br&gt;&lt;/br&gt;
The usage of pyThermoML is demonstrated in the following &lt;a href="https://github.com/FAIRChemistry/pyThermoML/blob/master/pyThermoML_example_workflow/templateThermoML.ipynb"&gt;example workflow&lt;/a&gt; and can be utilized to read the given ThermoML file.
DOI: 10.18419/darus-3119/1
title: exp_sdiff_glyc.xml
DOI: 10.18419/darus-3860
title: Synchrotron X-ray video of full-penetration laser welding of aluminum AA1050A

description: The video shows a synchrotron x-ray video of full-penetration laser welding of the aluminum alloy AA1050A (Al99.5). At the beginning of the video the transition from partial penetration welding with a keyhole which is closed at its bottom to full-penetration welding with a keyhole which is opened at its bottom can be observed. The images show that the fluctuations of the capillary’s geometry during the beginning of the process result in an excessive formation of pores. During the further progress of the process a reliable full-penetration process is achieved with an increased stability of the geometry of the keyhole. A detailed analysis of this transition and its implications on the absorptance are presented in the related publication.
description: The presented investigations were carried out in cooperation with DESY in Hamburg and with RWTH Aachen University within the framework of the Collaborative Research Centre SFB1120-236616214 “Bauteilpräzision durch Beherrschung von Schmelze und Erstarrung in Produktionsprozessen” and funded by the Deutsche Forschungsgemeinschaft e.V. (DFG, German Research Foundation). We acknowledge DESY (Hamburg, Germany), a member of the Helmholtz Association HGF, for the provision of experimental facilities. Parts of this research were carried out at PETRA III and we would like to thank F. Beckmann and J. Moosmann for assistance in using P07 EH4. Beamtime was allocated for proposal I-20191140.The sponsorship and support is gratefully acknowledged.
DOI: 10.18419/darus-3860/1
title: full_penetration_welding_aluminum.avi
DOI: 10.18419/darus-3862
title: Supplementary videos for PhD thesis: Laminar-to-turbulent transition in airfoil boundary layer flows at oscillating inflow conditions

description: &lt;p&gt;Videos from direct numerical simulations (DNS) of the laminar-to-turbulent transition under unsteady inflow conditions.&lt;/p&gt;

The flow visualizations correspond to the results of section 3.4 of the PhD thesis "Laminar-to-turbulent transition in airfoil boundary layer flows at oscillating inflow conditions", see Related Publication below.
DOI: 10.18419/darus-3862/1
title: Ohno2023c_PhDthesis_Supplementary_videos.mp4
DOI: 10.5281/zenodo.14056620
title: BOSHLANG'ICH SINFLARDA ARIFMETIK AMALLAR TUSHUNCHASI VA UNI O'RGANISH
DOI: 10.5281/zenodo.14056621
title: BOSHLANG'ICH SINFLARDA ARIFMETIK AMALLAR TUSHUNCHASI VA UNI O'RGANISH
DOI: 10.18419/darus-3679
title: OncoFEM data repository

description: In this repository the data files of OncoFEM are collected. These are in the following listed and cited where appropriate:

&lt;ul&gt;
&lt;li&gt; SRI24 atlas T1 and T2 MRI modalities (T. Rohlfing, N. M. Zahr, E. V. Sullivan, and A. Pfefferbaum, “The SRI24 multichannel atlas of normal adult human brain structure,” Human Brain Mapping, vol. 31, no. 5, pp. 798-819, 2010. &lt;a href="https://doi.org/10.1002/hbm.20906"&gt;doi: 10.1002/hbm.20906&lt;/a&gt;) &lt;/li&gt;
&lt;li&gt;Tutorial files: Because of long calculation times particular interim results are provided &lt;/li&gt; &lt;ul&gt;
&lt;li&gt;generated geometry (geometry.xdmf + geometry.h5) &lt;/li&gt;
&lt;li&gt;edema mapping (edema.xdmf + edema.h5) &lt;/li&gt;
&lt;li&gt;cerebrospinal fluid distribution file (csf.nii.gz) &lt;/li&gt;
&lt;li&gt;white matter distribution (wm.nii.gz) &lt;/li&gt;
&lt;li&gt;grey matter distribution (gm.nii.gz) &lt;/li&gt;
&lt;li&gt;Segmented tumor distribution, class 0 (tumor_class_pve_0.nii.gz) &lt;/li&gt;
&lt;li&gt;Segmented tumor distribution, class 1 (tumor_class_pve_1.nii.gz) &lt;/li&gt;
&lt;li&gt;Segmented tumor distribution, class 2 (tumor_class_pve_2.nii.gz) &lt;/li&gt;
&lt;li&gt;Folder of magnetic resonance images of first Authors head in DICOM format (T1 and Flair modality) &lt;/li&gt;
&lt;li&gt;First six datasets (T1, T1ce, T2, Flair, tumour segmentation) of BraTS 2020 collection (&lt;a href="https://www.med.upenn.edu/cbica/brats2020/data.html"&gt;https://www.med.upenn.edu/cbica/brats2020/data.html&lt;/a&gt;) &lt;/li&gt;
 &lt;/ul&gt;
 &lt;li&gt;Five different weights of tumor segmentations with different input channels. Herein, either one of T1, T1ce, T2, Flair or all of them are used. Additionally, an empty image is included for an adaptive training. &lt;/li&gt;
&lt;/ul&gt; 
The data corresponds to OncoFEM version 1.0.

The up-to-date Version of oncofem can be obtained from &lt;a href="https://github.com/masud-src/OncoFEM"&gt;github&lt;/a&gt; or Version 1.0 from &lt;a href="https://doi.org/10.18419/darus-3720"&gt;DaRUS&lt;/a&gt;, which comes in a pre-installed virtual box.

For usage, download and unzip file next to the oncofem folder or adjust the paths stored in the config.ini file if the files need to be somewhere else.
DOI: 10.18419/darus-3679/1
title: data.tar.gz
DOI: 10.18419/darus-3691
title: Scripts and Data for "Towards a phenomenological understanding of neural networks: data"

description: Data and scripts to reproduce the plots in the paper. Data is separated into two directories:
&lt;ul&gt;
&lt;li&gt; Surfaces: All data for rebuilding the surfaces&lt;/li&gt;
&lt;li&gt; rnd-plots: Data to reproduce the rnd plots&lt;/li&gt;
&lt;/ul&gt;
The scripts, once run, will produce the plots in the paper.
DOI: 10.18419/darus-3691/1
title: mlst_data_upload.tar.gz
DOI: 10.18419/darus-3693
title: Replication data of Kästner group for: "Understanding the Underlying Field Evaporation Mechanism of Pure Water Tips in High Electrical Fields"

description: In this dataset, all simulation data are listed. That includes all geometry optimized structures as xyz-files and all input-files for the calculations as chm-files.
DOI: 10.18419/darus-3693/1
title: publication_data.tgz
DOI: 10.18419/darus-3384
title: Replication Data for: Visual Gaze Labeling for Augmented Reality Studies

description: This .zip file contains the Unity project of the visualization tool described in the paper "Visual Gaze Labeling for Augmented Reality Studies" which was accepted at EuroVis 2023 Conference. This tool can be used to annotate gaze data from Augmented Reality (AR) scenarios to perform AOI based eye-tracking analysis. 
The visualization tool consists of a gaze replay and timeline visualization - linked together to provide spatial and image-based annotation. The project includes a dataset that we collected from an AR pilot study.
&lt;br/&gt;&lt;br/&gt;
Please install Unity 2020.3.24 to run the visualization tool. The Unity project contains two scenes (located in Assets/Scenes):

&lt;ol&gt;
&lt;li&gt;TimelineVisualization&lt;/li&gt;
&lt;li&gt;GazeReplay&lt;/li&gt;
&lt;/ol&gt;
First, drag both scenes into the hierarchy window, then unload GazeReplay. In &lt;i&gt;File/Build Settings&lt;/i&gt;, the order of the &lt;i&gt;Scenes in Build&lt;/i&gt; should be as follows: &lt;b&gt;TimelineVisualization 0, GazeReplay 1&lt;/b&gt;. When you start the active scene (TimelineVisualization), the GazeReplay scene will be loaded as well. You can work with the visualization tool in the game view.
&lt;br/&gt;&lt;br/&gt;
The project consists of an Assets, Packages and ProjectSettings folder. The Assets folder contains the necessary scripts, prefabs and data.
&lt;pre&gt;
&lt;code&gt;
Assets.
└── Scenes
 |── TimelineVisualization # Unity scene for Timeline Visualization
 |── GazeReplay # Unity scene for Gaze Replay
└── Scripts
 |── AOI_Manager # the code to create AOI cubes in gaze replay
 |── FileHandler # the code to save annotated gaze data in json file
 |── Frame # code that contains fixation information
 |── FrameAnnotator # the code to handle fixation annotation in timeline visualization
 |── dataHandler # the code to extract gaze data from the csv files
└── Streaming Assets
 |── frames # thumbnail images of the fixations for each participant
 |── study_data # fixation data of each participant
 |── RScript # R code to extract fixations from gaze data
&lt;/code&gt;
&lt;/pre&gt;

Please check the &lt;a href="https://github.com/IntCDC/AOIs-in-AR"&gt;GitHub page&lt;/a&gt; for the latest version.
description: Unity, 2020.3.24
DOI: 10.18419/darus-3384/1
title: AOIs-in-AR.zip
DOI: 10.18419/darus-3405
title: DuMux 3.7.0

description: &lt;p&gt;Release 3.7.0 of DuMux, DUNE for Multi-{Phase, Component, Scale, Physics, ...} flow and transport in porous media. DuMux is a free and open-source simulator for flow and transport processes in and around porous media. It is based on the Distributed and Unified Numerics Environment DUNE.&lt;/p&gt;

&lt;!--&lt;p&gt;The individual files correspond to the main module &lt;a href="https://git.iws.uni-stuttgart.de/dumux-repositories/dumux/-/tree/3.7.0"&gt;"dumux"&lt;/a&gt; and two dependent modules &lt;a href="https://git.iws.uni-stuttgart.de/dumux-repositories/dumux-course/-/tree/3.7.0"&gt;"dumux-course"&lt;/a&gt; and &lt;a href="https://git.iws.uni-stuttgart.de/dumux-repositories/dumux-lecture/-/tree/3.7.0"&gt;"dumux-lecture"&lt;/a&gt;.&lt;/p&gt;--&gt;
description: https://git.iws.uni-stuttgart.de/dumux-repositories/dumux/-/blob/3.7.0/CHANGELOG.md<br><br>

Use persistent identifiers from Software Heritage ( ) to cite individual files or even lines of DuMux.
DOI: 10.18419/darus-3451
title: Comparative Evaluation of Animated Scatter Plot Transitions - Supplemental Material

description: &lt;p&gt;We evaluated several animations for transitions between scatter plots in a crowd-sourcing study. We published the results in a paper and provide additional information within this supplemental material.&lt;/p&gt;
&lt;p&gt;Contents:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Tables that did not fit into the original paper, due to page limits.&lt;/li&gt;
&lt;li&gt;An anonymized print-out of the preregistration.&lt;br /&gt;
The original preregistration is available at &lt;a href="https://osf.io/3e6g4" target="_blank" rel="noopener noreferrer"&gt;OSF&lt;/a&gt; (&lt;a href="https://doi.org/10.17605/OSF.IO/3E6G4" target="_blank" rel="noopener noreferrer"&gt;DOI&lt;/a&gt;) and on the &lt;a href="https://archive.org/details/osf-registrations-3e6g4-v1" target="_blank" rel="noopener noreferrer"&gt;internet archive&lt;/a&gt;.&lt;/li&gt;
&lt;li&gt;Videos demonstrating the tasks used in the study:
&lt;ul&gt;
&lt;li&gt;used to record samples for the study,&lt;/li&gt;
&lt;li&gt;used for participant training&lt;/a&gt;,&lt;/li&gt;
&lt;li&gt;and used to detect distracted participants and bots&lt;/a&gt;.&lt;/li&gt;
&lt;/ul&gt;&lt;/li&gt;
&lt;li&gt;An interactive demonstration&lt;/a&gt; of all study tasks (including training and attention checks).&lt;br /&gt;
The source code is contained within the directory &lt;code&gt;./interactive-demo/&lt;/code&gt; of this supplemental material and also available at &lt;a href="https://github.com/NilsRodrigues/animated-scatterplot-transitions-for-comparative-study" target="_blank" rel="noopener noreferrer"&gt;GitHub&lt;/a&gt;.&lt;/li&gt;
&lt;li&gt;The animation library that we used for the study. We also include a test page for readers to use with their own data sets.&lt;br /&gt;
The source code is contained within the directory &lt;code&gt;./animation-library/&lt;/code&gt; of this supplemental material and also avialable at &lt;a href="https://github.com/NilsRodrigues/d3-scattertrans" target="_blank" rel="noopener noreferrer"&gt;GitHub&lt;/a&gt;.&lt;/li&gt;
&lt;li&gt;The list of nonsensical statements that we used for attention checks on &lt;a href="https://www.prolific.com/" target="_blank" rel="noopener noreferrer"&gt;Prolific&lt;/a&gt;.&lt;/li&gt;
&lt;li&gt;The statistical tests with the recorded study data, some of which we reported in the main paper. We also provide reports from the preliminary power analysis that we performed to determine the number of participants for the study.&lt;/li&gt;
&lt;li&gt;The recorded pseudo-anonymized study data for further analysis.&lt;/li&gt;
&lt;/ul&gt;
description: Animation source code by Vincent Brand with small adaptations by Nils Rodrigues. Test application by Vincent Brandt. Study source code by Nils Rodrigues. Study concept jointly by Nils Rodrigues, Frederik Dennig, and Daniel Weiskopf.
DOI: 10.18419/darus-3451/1
title: supplemental.zip
DOI: 10.18419/darus-3467
title: Data for Surface Immobilized Cu-1,10-Phenanthroline Complexes with α-Aminophosphonate Groups in the 5-Position as Heterogenous Catalysts for Efficient Atom-Transfer Radical Cyclizations

description: The data set contains the NMR data of the new ligands and immobilized catalyst as well as examplary NMR spectra after the catalysis as used for the determination of the yield.
Additionally, it contains the UV/Vis data of the free and immobilized ligand and complex, and crystallographic data of the ligand L1.
For experimental details, see the linked publication.
DOI: 10.18419/darus-3467/1
title: Daten Darus.rar
DOI: 10.15468/dl.52qmt6
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Troglodytes troglodytes (Linnaeus, 1758)",
 "Year is 34",
 "Country is Netherlands"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003336-241107131044228/datasets/export for details.
DOI: 10.18419/darus-3230
title: MPIIGaze
title: Appearance-Based Gaze Estimation in the Wild

description: &lt;p&gt;We present the MPIIGaze dataset that contains 213,659 images we collected from 15 participants during natural everyday laptop use over more than three months. The number of images collected by each participant varied from 34,745 to 1,498. Our dataset is significantly more variable than existing ones with respect to appearance and illumination.&lt;/p&gt;

&lt;p&gt;The dataset contains three parts: “Data”, “Evaluation Subset” and “Annotation subset”.&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;The “Data” includes “Original”, “Normalized” and “Calibration” for all the 15 participants.
&lt;li&gt;The “Evaluation Subset” contains the image list that indicates the selected samples for the evaluation subset in our paper.
&lt;li&gt;The “Annotation Subset” contains the image list that indicates 10,848 samples that we manually annotated, following the annotations with (x, y) position of 6 facial landmarks (four eye corners, two mouth corners) and (x,y) position of two pupil centers for each of above images.&lt;/ul&gt;

&lt;p&gt;&lt;a href="https://www.youtube.com/watch?v=rw6LZA1USG8"&gt;Youtube video&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;&lt;a href="https://perceptualui.org/research/datasets/MPIIGaze/"&gt;More information, including FAQ&lt;/a&gt;&lt;/p&gt;
description: The data is only to be used for non-commercial scientific purposes.
DOI: 10.18419/darus-3230/1
title: MPIIGaze.zip
DOI: 10.18419/darus-3232
title: 3DGazeSim
title: 3D Gaze Estimation from 2D Pupil Positions on Monocular Head-Mounted Eye Trackers

description: Dataset of 3D gaze from eye tracking.
&lt;ul&gt;
&lt;li&gt;14 participants
&lt;li&gt;Ages 22-29 years
&lt;li&gt;PUPIL head-mounted eye tracker &lt;/ul&gt;
description: The data is only to be used for non-commercial scientific purposes.
DOI: 10.18419/darus-3232/1
title: 3DGazeSim.zip
DOI: 10.18419/darus-3247
title: DuMux 3.6.0

description: &lt;p&gt;Release 3.6.0 of DuMux, DUNE for Multi-{Phase, Component, Scale, Physics, ...} flow and transport in porous media. DuMux is a free and open-source simulator for flow and transport processes in and around porous media. It is based on the Distributed and Unified Numerics Environment DUNE.&lt;/p&gt;

&lt;!--&lt;p&gt;The individual files correspond to the main module &lt;a href="https://git.iws.uni-stuttgart.de/dumux-repositories/dumux/-/tree/3.6.0"&gt;"dumux"&lt;/a&gt; and two dependent modules &lt;a href="https://git.iws.uni-stuttgart.de/dumux-repositories/dumux-course/-/tree/3.6.0"&gt;"dumux-course"&lt;/a&gt; and &lt;a href="https://git.iws.uni-stuttgart.de/dumux-repositories/dumux-lecture/-/tree/3.6.0"&gt;"dumux-lecture"&lt;/a&gt;.&lt;/p&gt;--&gt;
description: https://git.iws.uni-stuttgart.de/dumux-repositories/dumux/-/blob/3.6.0/CHANGELOG.md<br><br>

Use persistent identifiers from Software Heritage (
 
) to cite individual files or even lines of DuMux.
DOI: 10.18419/darus-3247/3
title: dumux-3.6.0.tar.gz
DOI: 10.18419/darus-3259/1
title: Calculations_Klostermann.tar.gz

description: The simulation dataset includes all geometry optimizations and single-point energy calculations. It is organized as follows: The file includes separate folders sorted by structure. Each sturcture contains a folder "Opt" that includes the Geometry Optimization and a folder "SP" that includes the Single-point energy calculation.
DOI: 10.15468/dl.by24pg
title: Occurrence Download

description: A dataset containing 133 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Widdringtonia whytei Rendle"
 ]
}

 The dataset includes 133 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003335-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18419/darus-4338/1
title: data.json
DOI: 10.18419/darus-4339/1
title: model.keras
DOI: 10.18419/darus-4346
title: Data Supplement (PhD Thesis Cicac-Hudi, Mario)
title: Datenanhang (Dissertation Cicac-Hudi, Mario)

description: The document contains the Data supplement to the PhD Thesis of Cicac-Hudi, Mario. The document contains representations of processed spectroscopic data (NMR spectra, FTIR spectra, mass spectra, UV-VIS spectra) and results of computational studies (atomic coordinates, calculated energies).
DOI: 10.18419/darus-4346/1
title: PhD Thesis Mario Cicac-Hudi (Supplement).pdf

description: Data Supplement to PhD Thesis
DOI: 10.18419/darus-4348
title: Setup for High-Speed Synchrotron X-Ray Imaging of Laser Drilling at the DESY

description: &lt;p&gt;The image shows the High-Speed Synchrotron X-Ray Imaging setup at the Deutsches Elektronen Synchrotron (DESY) in Hamburg. &lt;/p&gt;

&lt;p&gt;It is used to capture X-ray imaging sequences of a laser drilling process with an ultrafast Yb:YAG laser with an output wavelength of 1030 nm. The polarization could be adjusted by two λ/4 and λ/2 waveplates which were placed between the laser source and the focusing f-theta lens. &lt;/p&gt;

&lt;p&gt;A sample of thickness t is transmitted by the X-ray beam of diameter about 2 mm in y-direction. At a distance of about 3.5 m behind the sample, a scintillator converts the X-ray beam into visible light, which is captured by a high-speed camera at a frame rate of 1000 fps and a spatial resolution of 856 pixels/mm.&lt;/p&gt;

&lt;p&gt;In addition, the measurement beam of an optical coherence tomography (OCT) is aligned coaxially with the processing laser beam using a dichroitic mirror.&lt;/p&gt;
DOI: 10.18419/darus-4348/1
title: setup_desy_darus.png

description: The image shows the High-Speed Synchrotron X-Ray Imaging setup at the Deutsches Elektronen Synchrotron (DESY) in Hamburg.
DOI: 10.18419/darus-4351
title: DuMux 3.9.0

description: Release 3.9.0 of DuMux, DUNE for Multi-{Phase, Component, Scale, Physics, ...} flow and transport in porous media. DuMux is a free and open-source simulator for flow and transport processes in and around porous media. It is based on the Distributed and Unified Numerics Environment DUNE.
description: https://git.iws.uni-stuttgart.de/dumux-repositories/dumux/-/blob/3.9.0/CHANGELOG.md
 <br> Use persistent identifiers from Software Heritage ( ) to cite individual files or even lines of DuMux.
DOI: 10.18419/darus-4351/1
title: dumux-3.9.0.tar.gz