cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18419/darus-3002
title: Replication data for: "NO as a Reagent for Topochemical Framework Transformation and Controlled Nitric Oxide Release in Covalent Organic Frameworks"

description: This dataset contains all data from analytical measurements including FT-IR and UV-Vis spectra, raw XRD patterns, 1H, 13C and 15N solution and ssNMR spectra, Ar, CO2, and NO sorption isotherms, pore-size distributions, TEM images, and Pawley structure refinements of the journal article mentioned under the related publication.&lt;br&gt;
Open *.cif and *.xyz files with a visualization software (see http://ww1.iucr.org/iucr-top/cif/), *.raw files with WinXPOW, *.sp files with PerkinElmer Spectrum software, *.mnova files with MestReNova, *.fq/.gr/iq/sq files with a text editor, and *.pro files with TOPAS.
DOI: 10.18419/darus-3002/6
title: UV-VIS.zip
DOI: 10.18419/darus-3105/1
title: kiemle2022a-main.tar.gz

description: Source code
DOI: 10.15468/dl.u5eey5
title: Occurrence Download

description: A dataset containing 2059 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Romulea minutiflora Klatt"
 ]
}

 The dataset includes 2059 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006780-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18419/darus-3105/2
title: README.md

description: Instructions to install and reproduce the results
DOI: 10.18419/darus-3105/3
title: docker_kiemle2022a.sh

description: Docker container startup script
DOI: 10.18419/darus-3105/4
title: install_Kiemle2022a.py

description: Installation script
DOI: 10.18419/darus-3105/5
title: Dockerfile

description: Dockerfile
DOI: 10.18419/darus-3105
title: Dumux code for modelling stable water isotopologue transport and fractionation

description: Dumux source code to reproduce the results presented in S. Kiemle, K. Heck, E. Coltman, R. Helmig (2023) Stable water isotopologue fractionation during soil-water evaporation: Analysis using a coupled soil-atmosphere model. Water Resources Research.&lt;br&gt;
The contained application allows to model stable water isotopologue transport and fractionation in soil and in the soil-atmosphere interface. The application uses a coupled porous-medium free-flow approach which allows us to derive kinetic fractionation processes without the use of further parameterization. The archive &lt;b&gt; docker_image_kiemle2022a.tar &lt;/b&gt; corresponds to the docker image. Additionally, all required files to start the corresponding docker container are included.
description: This application also requires installing some dune modules and the module dumux. The installation script 'install_Kiemle2022a.py' contains the dependencies in the correct version. For the instructions to build and execute the applications, one may check the <b>Installation</b> section in the <b>README.md</b>.

Alternatively, one may reproduce the results using the corresponding docker container. Therefore, download the archive <b> docker_image_kiemle2022a.tar </b>. The docker image can be obtained by running <code> docker load --input docker_image_kiemle2022a.tar</code>. The corresponding docker container can be started by running <code> ./docker_kiemle2022a.sh open</code>. More information is provided in the <b> Installation with Docker</b> section in <b> README.md </b>.
DOI: 10.18419/darus-3105/6
title: docker_image_kiemle2022a.tar

description: Files related to docker image
DOI: 10.18419/darus-3151
title: CSI Dataset dichasus-cf1x-part2: Distributed Antenna Setup in Industrial Environment, Day 2, Second Part
title: Radio channel measurements generated by DICHASUS

description: Dataset containing channel state information (CSI) alongside ground truth data (position tags, timestamps) of a massive MIMO-OFDM system measured with the DICHASUS channel sounder. Measurement parameters and machine-readable file format descriptions are provided in a JSON file (spec.json).

Distributed antenna setup with line-of-sight (LoS) and non-line-of-sight (NLoS) channels, measured in the &lt;a href="https://www.arena2036.de/"&gt;Arena2036&lt;/a&gt; research factory campus environment.
DOI: 10.18419/darus-3185/1
title: spack.yaml
DOI: 10.18419/darus-3185/2
title: COM-4.tar.gz
DOI: 10.18419/darus-3185/3
title: mirror_geokw.zip
DOI: 10.18419/darus-3185/4
title: pflotran_code.zip
DOI: 10.18419/darus-3185/5
title: README.md
DOI: 10.15468/dl.n67hca
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eriocaulon peninsulare Punekar & Lakshmin."
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006784-241107131044228/datasets/export for details.
DOI: 10.18419/darus-3185
title: COM-4 model to replicate simulation results for the GEO.KW project

description: This data repository contains the COM-4 model for the GEO.KW project. The dataset contains the PFLOTRAN and urbs simulation setup, spack build environment and spack build mirror to replicate the software build environment. A &lt;a href="https://darus.uni-stuttgart.de/file.xhtml?fileId=164419"&gt;README file&lt;/a&gt; is provided, explaining the spack building procedure and running the simulation.
DOI: 10.18419/darus-3185/6
title: LICENSE
DOI: 10.14278/rodare.3251
title: Data publication: MineNetCD: A Benchmark for Global Mining Change Detection on Remote Sensing Imagery

description: This is the full version of the MineNetCD dataset. The paper has been published in IEEE TGRS 2024 (https://ieeexplore.ieee.org/document/10744421). The dataset contains 100 sites, and the metadata can also be found in the zip archive.

The cropped version can also be found in Huggingface Hub (https://huggingface.co/datasets/HZDR-FWGEL/MineNetCD256).
description: {"references": ["W. Yu, X. Zhang, R. Gloaguen, X. X. Zhu and P. Ghamisi, \"MineNetCD: A Benchmark for Global Mining Change Detection on Remote Sensing Imagery,\" in IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2024.3491715."]}
DOI: 10.18419/darus-3195/1
title: spack.yaml
DOI: 10.14278/rodare.3250
title: Data publication: MineNetCD: A Benchmark for Global Mining Change Detection on Remote Sensing Imagery

description: This is the full version of the MineNetCD dataset. The paper has been published in IEEE TGRS 2024 (https://ieeexplore.ieee.org/document/10744421). The dataset contains 100 sites, and the metadata can also be found in the zip archive.

The cropped version can also be found in Huggingface Hub (https://huggingface.co/datasets/HZDR-FWGEL/MineNetCD256).
description: {"references": ["W. Yu, X. Zhang, R. Gloaguen, X. X. Zhu and P. Ghamisi, \"MineNetCD: A Benchmark for Global Mining Change Detection on Remote Sensing Imagery,\" in IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2024.3491715."]}
DOI: 10.18419/darus-3195/2
title: pflotran_code.zip
DOI: 10.18419/darus-3195/3
title: mirror_geokw.zip
DOI: 10.18419/darus-3195/4
title: README.md
DOI: 10.18419/darus-3195
title: REG-30 model to replicate simulation results for the GEO.KW project

description: This data repository contains the REG-30 model for the GEO.KW project. The dataset contains the PFLOTRAN and urbs software and simulation setup. Instructions for building the spack environment and running the simulation are provided in the &lt;a href="https://darus.uni-stuttgart.de/file.xhtml?fileId=164413"&gt;README&lt;/a&gt;.
DOI: 10.18419/darus-3195/5
title: REG-30.tar.gz
DOI: 10.18419/darus-3195/6
title: LICENSE
DOI: 10.18419/darus-3271
title: Data for: Measurement Campaign of Gaseous CO2 Concentrations in a Karst Cave with Aqueous Concentrations in a Stagnant Water Column 2021-2022.

description: This dataset contains data generated during the measurement campaign inside the karst cave. The CO2 sensors in the cave air will continue to measure (as of Feb. 2023). 
&lt;/br&gt; For details on the site etc. see&lt;/br&gt;
&lt;a href="https://doi.org/10.3390/geosciences13020051"&gt;https://doi.org/10.3390/geosciences13020051&lt;/a&gt; &lt;/br&gt;&lt;/br&gt;
To create the graphs in the &lt;a href="https://doi.org/10.3390/geosciences13020051"&gt;Class et al. 2023&lt;/a&gt; &lt;/br&gt;
Download &lt;b&gt;cave-data.tar.xz&lt;/b&gt;, make sure you have the dependencies shown in &lt;b&gt;requirements_paper_2022.txt&lt;/b&gt;. Then one can recreate the graphs by running the jupyter-notebook in that directory.
&lt;/br&gt;&lt;/br&gt;
Structure of the dataset: 
&lt;ul&gt;
&lt;li&gt;&lt;b&gt;cave-data.tar.xz&lt;/b&gt;: contains the data produced during the measurement campaign. Additionally, all the figures of (todo: add paper doi) are created here.&lt;/li&gt;
&lt;li&gt; &lt;b&gt;grid_const.tar.gz&lt;/b&gt;: contains the data generated by the grid study with constant CO2 concentration at the top. &lt;/li&gt;
&lt;li&gt;&lt;b&gt;grid_data.tar.gz&lt;/b&gt;: contains the data generated by the grid study with measured CO2 concentration at the top &lt;/li&gt;
&lt;li&gt;&lt;b&gt;3D.tar.gz&lt;/b&gt;: contains data generated by the 2D and 3D comparison&lt;/li&gt;
&lt;li&gt;&lt;b&gt;cave_sims.tar.gz&lt;/b&gt;: contains details on the simulation of the whole column. Specifically, figures and a video on the development of vortex cascades.&lt;/li&gt;
&lt;li&gt;&lt;b&gt;requirements_paper_2022.txt&lt;/b&gt;: contains python modules for the post-processing.&lt;/li&gt;
&lt;/ul&gt;

The main focus of this dataset lies on the data generated in the cave. 
Items in &lt;b&gt;cave-data.tar.xz&lt;/b&gt; are:
&lt;ul&gt;
&lt;li&gt;&lt;b&gt;Raw_data&lt;/b&gt; contains the CO2(g) and pressure measurements in csv files.&lt;/li&gt;
&lt;li&gt;&lt;b&gt;DWD_data&lt;/b&gt; contains the pressure,temperature and precipitation data from the DWD ('Deutscher Wetterdienst'). Pressure/temperature is measured in Stötten (30km apart) and precipitation is measured in Westerheim (5km apart).&lt;/li&gt;
&lt;li&gt;&lt;b&gt;Control_data_temperature&lt;/b&gt; contains the temperature data from additional temperature sensors. This data is used for comparison only.&lt;/li&gt;
&lt;li&gt;&lt;b&gt;Control_data_CO2&lt;/b&gt; contains the CO2(g) data from additional CO2(g) sensors. This data is used for comparison only.&lt;/li&gt;
&lt;li&gt;&lt;b&gt;Sim_data&lt;/b&gt; contains results from various simulations.&lt;/li&gt;
&lt;li&gt;The script &lt;b&gt; Cave_measures_sim_plot.ipynb &lt;/b&gt; contains the code to process and visualize the data. Furthermore, the titration results are directly written into the script.&lt;/li&gt;
&lt;/ul&gt;
description: Python, 3.9
DOI: 10.18419/darus-623
title: Profile hidden Markov models of the ExED
title: Profile hidden Markov models of the Expansin Engineering Database

description: Profile hidden Markov models and their underlying multiple sequence alignments for the N- and C-terminal protein domains of expansins.
description: A profile hidden Markov model (HMM) was derived for each expansin domain from a multiple sequence alignment built from 28 representative protein sequences. The profile HMMs for the N- and C-terminal expansin domain were built by HMMER from multiple sequence alignments (structure-guided).
Based on the alignment and on annotations of secondary structures in the Pfam database (entries PF03330.17 for the N-terminal domain and PF01357.20 for the C-terminal domain), the respective domains were manually retrieved.
DOI: 10.18419/darus-623/1
title: Expansins_CterminalDomain_2.aln

description: Clustal alignment for the C-terminal expansin domain
DOI: 10.15468/dl.cqwq4n
title: Occurrence Download

description: A dataset containing 23164 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Germany",
 "PublishingOrg is one of (c8d737e0-2ff8-42e8-b8fc-6b805d26fc5f, 28eb1a3f-1c15-4a95-931a-4af90ecb574d)",
 "TaxonKey is Squamata",
 "Year 2018-2022"
 ]
}

 The dataset includes 23164 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006782-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18419/darus-623/2
title: Expansins_CterminalDomain_2.hmm

description: Profile hidden Markov model in HMMER format for the C-terminal expansin domain
DOI: 10.18419/darus-623/3
title: Expansins_CterminalDomain_2.sto

description: Stockholm alignment for the C-terminal expansin domain
DOI: 10.15468/dl.csp4jk
title: Occurrence Download

description: A dataset containing 9533 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Calotis cuneifolia R.Br."
 ]
}

 The dataset includes 9533 records from 70 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006783-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18419/darus-623/4
title: Expansins_NterminalDomain_9.aln

description: Clustal alignment for the N-terminal expansin domain
DOI: 10.18419/darus-623/5
title: Expansins_NterminalDomain_9.hmm

description: Profile hidden Markov model in HMMER format for the N-terminal expansin domain
DOI: 10.18419/darus-623/6
title: Expansins_NterminalDomain_9.sto

description: Stockholm alignment for the N-terminal expansin domain
DOI: 10.18419/darus-628
title: Deep enzymology data related to Adam et al.: DNA sequence-dependent activity and base flipping mechanisms of DNMT1 regulate genome-wide DNA methylation
title: Data Set 2 related to enzyme assays with random flank substrate methylation

description: Methylation of random flank substrates: Libraries of double stranded DNA substrates with unmethylated or hemimethylated CpG sites in randomized sequence context were methlyated by DNMT1. Reactions were stopped by shock freezing in liquid nitrogen, then treated with proteinase K for 2 hours. Afterwards, the DNA was digested with the BsaI-HFv2 enzyme and a hairpin was ligated using T4 DNA ligase (NEB). The DNA was bisulfite converted using EZ DNA Methylation-Lightning kit (ZYMO RESEARCH) according to the manufacturer protocol, purified and eluted with 10 µL ddH2O. Libraries for Illumina Next Generation Sequencing (NGS) were produced with the two-step PCR approach. In the first PCR, 2 µL of bisulfite-converted DNA were amplified with the HotStartTaq DNA Polymerase (QIAGEN) and primers containing internal barcodes using following conditions: 15 min at 95 °C, 10 cycles of 30 sec at 94 °C, 30 sec at 50 °C, 1 min and 30 sec at 72 °C, and final 5 min at 72 °C; using a mixture containing 1x PCR Buffer, 1x Q-Solution, 0.2 mM dNTPs, 0.05 U/µL HotStartTaq DNA Polymerase, 0.4 µM forward and 0.4 µM reverse primers in a total volume of 20 µL. In the second PCR, 1 µL of obtained products were amplified by Phusion Polymerase (Thermo) with another set of primers to introduce adapters and indices needed for NGS (30 sec at 98 °C, 10 cycles - 10 sec at 98 °C, 40 sec at 72 °C, and 5 min at 72 °C). PCRII was carried out in 1x Phusion HF Buffer, 0.2 mM dNTPs, 0.02 U/µL Phusion HF DNA Polymerase, 0.4 µM forward and 0.4 µM reverse primers in a total volume of 20 µL. Obtained libraries were pooled in equimolar amounts and purified using NucleoSpin® Gel and PCR Clean-up kit (Macherey-Nagel), followed by a second purification step of gel extraction and size exclusion with AMPure XP magnetic beads (Beckman Coulter). Sequencing was performed at the Max Planck Genome Centre Cologne.
description: pmid: 32709850
DOI: 10.18419/darus-628/1
title: unmethylated with enzyme.txt
DOI: 10.18419/darus-628/2
title: readme_random_flank_substrate.pdf

description: Additional information
DOI: 10.18419/darus-628/3
title: hemimethylated Repeat 1.txt
DOI: 10.18419/darus-628/4
title: hemimethylated without enzyme.txt
DOI: 10.18419/darus-628/5
title: hemimethylated Repeat 2.txt
DOI: 10.18419/darus-628/6
title: unmethylated without enzyme.txt
DOI: 10.18419/darus-680/1
title: Reticulite-01_AxMF01.rar

description: micro-XRCT data set in *.rek and *.tif file format of a dry cubic reticulite sample with about 10 mm side length. 1520 x 1520 x 1480 voxels by a uniform voxel size of 16.01 µm.
DOI: 10.18419/darus-680/2
title: Reticulite_03_AxMF01.rar

description: micro-XRCT data set in *.rek and *.tif file format of a dry cubic reticulite sample with about 5 mm side length. 1520 x 1520 x 1522 voxels by a uniform voxel size of 4.49 µm.
DOI: 10.18419/darus-680/3
title: Reticulite-AxHP_wet_1ml.rar

description: micro-XRCT data set in *.rek and *.tif file format of a cubic reticulite sample with about 12 mm side length saturated with 1 ml distilled water. 1520 x 1520 x 1554 voxels by a uniform voxel size of 12.85 µm.
DOI: 10.18419/darus-680/4
title: Reticulite-AxHP_wet_500ul.rar

description: micro-XRCT data set in *.rek and *.tif file format of a cubic reticulite sample with about 12 mm side length saturated with 500 µl distilled water. 1520 x 1520 x 1554 voxels by a uniform voxel size of 12.85 µm.
DOI: 10.18419/darus-680/5
title: Reticulite-AxHP_wet_750ul.rar

description: micro-XRCT data set in *.rek and *.tif file format of a cubic reticulite sample with about 12 mm side length saturated with 750 µl distilled water. 1520 x 1520 x 1554 voxels by a uniform voxel size of 12.85 µm.
DOI: 10.18419/darus-680/6
title: Segmented_subsamples.rar

description: Binarized subsamples of 400 x 400 x 400 voxels of "Reticulite-01_AxMF01" and "Reticulite_03_AxMF01" data sets in *.raw file format. A MATLAB script "ReadCTDataToMATLAB_simple.m" to read the data is attached.
DOI: 10.18419/darus-803/1
title: Reference_alignment_CHITs.aln

description: Clustal alignment for the profile hidden Markov model of the chitinase superfamily
DOI: 10.18419/darus-803/2
title: ELYSs.hmm

description: Profile hidden Markov model in HMMER format for the endolysin superfamily
DOI: 10.18419/darus-803/3
title: Reference_alignment_CHITs.stockholm

description: Stockholm alignment for the profile hidden Markov model of the chitinase superfamily
DOI: 10.18419/darus-803/4
title: Reference_alignment_ELYSs.aln

description: Clustal alignment for the profile hidden Markov model of the endolysin superfamily
DOI: 10.18419/darus-803/5
title: Reference_alignment_ELYSs.stockholm

description: Stockholm alignment for the profile hidden Markov model of the endolysin superfamily
DOI: 10.18419/darus-803/6
title: CHITs.hmm

description: Profile hidden Markov model in HMMER format for the chitinase superfamily
DOI: 10.18419/darus-1144/1
title: User_Manual_EHTM_v_3.2.04.pdf

description: User manual for EHTM version 3.2.04
DOI: 10.18419/darus-1144/2
title: EHTM_v3.2.04.f

description: Fortran code for EHTM version 3.2.04
DOI: 10.18419/darus-1144/3
title: EHTM_v3.2.04.f

description: Fortran code for EHTM version 3.2.04
DOI: 10.18419/darus-1144/4
title: User_Manual_EHTM_v_3.2.04.pdf

description: User manual for EHTM version 3.2.04
DOI: 10.18419/darus-1144/5
title: EHTM_v_4.0.00.f

description: Fortran code for EHTM version 4.0.00
DOI: 10.18419/darus-1144/6
title: User_Manual_EHTM_v_4.0.00.pdf

description: User manual for EHTM version 4.0.00
DOI: 10.18419/darus-1151/1
title: 2d_microstructures.h5

description: file containing all the data
DOI: 10.18419/darus-1151/2
title: example_data_access.py

description: accessing and plotting of microstructures
DOI: 10.18419/darus-1151/3
title: compute_regression_data.py

description: code to recompute/reproduce the data used for the regression problem
DOI: 10.18419/darus-1151/4
title: processing_functions.py

description: dependency file for 'compute_regression_data.py'
DOI: 10.18419/darus-1151/5
title: 2d_microstructures.h5

description: hdf5 file containing all the data
DOI: 10.18419/darus-1151
title: 2d microstructure data

description: The hdf5 file contains image data of inclusion based microstructured material and the homogenized effective heat conductivity thereof. The microstructure is defined with a representative volume element with periodic boundary conditions.
30.000 images are contained and split into two inclusion subclasses of circular and rectangular inclusions.
Features computed via the 2-point correlation function can be found. The features and effective properties have been used for a regression problem in the related paper. Example code to access the data and recreate the features is attached.
DOI: 10.18419/darus-1151/6
title: example_data_access.py

description: an example on how to access data stored in the hdf5 file
DOI: 10.18419/darus-1155/1
title: umat_2d_softening_test.tar.gz

description: This archive contains the material model used to describe the softening behavior and a test simulation run with a single finite element. Run the test with `make tests`.

The fortran compiler must be correctly configured in Abaqus in order to compile the user subroutine. If you use Linux, instructions are in the README file or just running `make fortran`. If you are using Windows, good luck! :) .
DOI: 10.18419/darus-1155/2
title: model_usage_example.tar.gz

description: This archive contains an example of how to use the model. The example consists on the analysis presented using the Database B (see Section 8.1 in the dissertation).
DOI: 10.18419/darus-1155/3
title: S3GluM_finite_element.tar.gz

description: Python package that defines classes and functions to run the Montecarlo finite element simulations of the glulam model.
DOI: 10.18419/darus-1155/4
title: S3GluM_material_simulation.tar.gz

description: Python package that defines classes and functions used to generate the material properties used in the stochastic finite element simulations.
DOI: 10.18419/darus-1155/5
title: S3GluM_data_analysis.tar.gz

description: Python package that defines functions used for the post-processing of the results obtained from the stochastic finite element simulations for the bending strength of glulam.
DOI: 10.18419/darus-1155
title: Source code for: Stuttgart Stochastic Strength Glulam Model (S3GluM)

description: This repository contains the stochastic finite element model developed to study the stiffness and strength variation of glulam beams.&lt;br&gt;
The S3GluM model was developed during the PhD thesis of Cristóbal Tapia Camú.
DOI: 10.18419/darus-1155/6
title: Python_Libs_for_Abaqus_2017.md

description: Instructions to install additional python dependencies in the Abaqus 2017 environment. This is required to run the model.
DOI: 10.18419/darus-1213/1
title: 00004002.JPG
DOI: 10.18419/darus-1213/2
title: 00004003.JPG
DOI: 10.18419/darus-1213/3
title: 00004006.JPG
DOI: 10.18419/darus-1213/4
title: 00004005.JPG
DOI: 10.18419/darus-1213/5
title: 00004001.JPG