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Pasameza de la Traditore I. Pars [and II. Pars] (A-Wn_Mus.Hs._18827_n01) Audio recording
No full text<h1>Audio recording of a lute piece from the E-LAUTE project</h1><h2>Overview</h2><p>This dataset contains an audio recording of the piece "Pasameza de la Traditore I. Pars [and II. Pars]", a 16th century lute music piece originally notated in lute tablature, created as part of the E-LAUTE project (<a href="https://e-laute.info/">https://e-laute.info/</a>). The recording preserves and makes historical lute music from the German-speaking regions during 1450-1550 accessible.</p><p>The recording is based on the work with the title "Pasameza de la Traditore I. Pars [and II. Pars]" and the id "A-Wn_Mus.Hs._18827_n01" in the e-lautedb. It is found on the page(s) or folio(s) 1r-2r in the source "[Lautenbuch, italienische Lautentabulatur]" with the source-id "A-Wn_Mus.Hs._18827".</p><p>The original source and multiple transcriptions of the work can be found on the E-LAUTE platform: <a href="https://edition.onb.ac.at/fedora/objects/o:lau.A-Wn_Mus.Hs._18827/methods/sdef:TEI/get?mode=n01" target="_blank">https://edition.onb.ac.at/fedora/objects/o:lau.A-Wn_Mus.Hs._18827/methods/sdef:TEI/get?mode=n01</a>.</p><p>Links to the source: <a href="http://data.onb.ac.at/rec/AC14316439" target="_blank">http://data.onb.ac.at/rec/AC14316439</a>, <a href="https://opac.rism.info/id/rismid/rism600141783" target="_blank">https://opac.rism.info/id/rismid/rism600141783</a>, .</p><h2>Dataset Contents</h2><p>This dataset includes:</p><ul><li><strong>Audio file</strong>: An audio recording of the lute piece in .wav format</li> <li><strong>Metadata file</strong>: A metadata file with detailed information about the recording in .json format</li></ul><h2>About the E-LAUTE Project</h2><p><strong>E-LAUTE: Electronic Linked Annotated Unified Tablature Edition - The Lute in the German-Speaking Area 1450-1550</strong></p><p>The E-LAUTE project creates innovative digital editions of lute tablatures from the German-speaking area between 1450 and 1550. This interdisciplinary "open knowledge platform" combines musicology, music practice, music informatics, and literary studies to transform traditional editions into collaborative research spaces.</p><p>For more information, visit the project website: <a href="https://e-laute.info/">https://e-laute.info/</a></p>
Numerical results for "Intertwined fluctuations and isotope effects in the Hubbard-Holstein model on the square lattice from functional renormalization"
No full text<div>This data repository contains the original figures, numerical (raw) data, and plot scripts to reproduce the figures from the publication "Intertwined fluctuations and isotope effects in the Hubbard-Holstein model on the square lattice from functional renormalization" in the Physical Review Research Journal. LaTeX source files of the preprint can be found on the corresponding <a href="https://arxiv.org/abs/2504.10863" target="_blank" rel="noopener">arXiv</a> page.</div>
Research data for "Bridging the gap between performance and biocompatibility: non-toxic, multifunctional aliphatic photoinitiators based on α-ketoesters for lithography-based manufacturing applications"
No full text<p><strong><span lang="EN-US">Context</span></strong></p>
<p><span lang="EN-US">This dataset was created from original work conducted in the framework of a PhD project and compiled in a publication (<em>"Bridging the gap between performance and biocompatibility: non-toxic, multifunctional aliphatic photoinitiators based on α-ketoesters for lithography-based manufacturing applications"</em>). It provides the raw data of the results presented and discussed therein.</span></p>
<p><strong><span lang="EN-US"> </span></strong></p>
<p><strong><span lang="EN-US">Technical details</span></strong></p>
<p><span lang="EN-US">Microsoft Excel file “Raw Data_Photoinitiators”:</span></p>
<p><span lang="EN-US">Tab 1 - Raw Data obtained for UV Vis measurements (KE1-4, BP)</span></p>
<p><span lang="EN-US">Tab 2 – Evaluated Data obtained for Photo-DSC measurements of KE1-4 and BP+MDEA in various monomers using a 320-500 nm broadband UV lamp</span></p>
<p><span lang="EN-US">Tab 3 – Evaluated Data obtained for Photo-DSC measurements of KE3 and co-initiators in various monomers using a 320-500 nm broadband UV lamp</span></p>
<p><span lang="EN-US">Tab 4 – Evaluated Data obtained for Photo-DSC measurements of KE1-4 and BP+MDEA in various monomers using a 385 nm LED</span></p>
<p><span lang="EN-US">Tab 5 – Raw Data obtained for Presto Blue Assay </span></p>
<p><span lang="EN-US">Tab 6 – Raw Data obtained for Presto Blue Assay – Detailed evaluation of the cytotoxicity tests</span></p>
<p><span lang="EN-US">Tab 7 – Raw Data of Plate Reader for Presto Blue Assay</span></p>
<p><span lang="EN-US">Tab 8 – Raw Data obtained for the GPC measurements of KE4 and ethoxylated pentaerythritol</span></p>
<p><span lang="EN-US">Tab 9 – Raw Data obtained for Photo-DSC measurements of KE1-4 and BP+MDEA in various monomers using a 320-500 nm broadband UV lamp</span></p>
<p><span lang="EN-US">Tab 10 – Raw Data obtained for Photo-DSC measurements of KE3 and co-initiators in various monomers using a 320-500 nm broadband UV lamp</span></p>
<p><span lang="EN-US">Tab 11 - Raw Data obtained for Photo-DSC measurements of KE1-4 and BP+MDEA in various monomers using a 385 nm LED</span></p>
<p><span lang="EN-US">Tab 12 - Raw Data obtained for UV Vis measurements of IC2959 </span></p>
<p><span lang="EN-US">Tab 13 - Raw Data obtained for Photo-DSC measurements of KE3 and BP+MDEA in JRNIL cure and M286 resins</span></p>
<p><span lang="EN-US">Tab 14 - Raw Data obtained for RT-NIR measurements of KE1-3, BP+MDEA and IC2959 in various monomers using a 320-500 nm broadband UV lamp</span></p>
<p><span lang="EN-US"> </span></p>
<p><strong><span lang="EN-US">NMR file</span></strong></p>
<p><span lang="EN-US">‘1H KE2, ‘13C KE2', ‘1H KE3’, ‘13C KE3’ and ‘1H KE4’ folders:</span></p>
<p><span lang="EN-US">NMR data obtained during all synthesis steps of KE2, KE3 and KE4.</span></p>
<p><span lang="EN-US">A software to display NMR-spectra is needed, such as </span><a href="https://mestrelab.com/download/mnova/"><span lang="EN-US">MestreNova</span></a><span lang="EN-US"> or </span><a href="https://www.bruker.com/en/products-and-solutions/mr/nmr-software/topspin.html"><span lang="EN-US">Topspin</span></a><span lang="EN-US">.</span></p>
<p><strong><span lang="EN-US"> </span></strong></p>
<p><strong><span lang="EN-US">Compound descriptions</span></strong></p>
<p><span lang="EN-US">Compound descriptions in the files included herein adhere to the naming in the related publication referenced in the Related Works section, where all compounds are described in detail and drawn as structural formulas. In brief:</span></p>
<p><span lang="EN-US">KE1: Ethyl pyruvate</span></p>
<p><span lang="EN-US">KE2: 2-(Acetylcarbonyloxy)ethyl pyruvate</span></p>
<p><span lang="EN-US">KE3: 2,2-Bis[(acetylcarbonyloxy)methyl]butyl pyruvate</span></p>
<p><span lang="EN-US">KE4: Ethoxylated pentaerythritol tetrapyruvate</span></p>
<p><span lang="EN-US">BP: Benzophenone</span></p>
<p><span lang="EN-US">MDEA: Methyldiethanolamine</span></p>
<p><span lang="IT">HDDA: Hexanedioldiacrylate</span></p>
<p><span lang="EN-US">DMM: Dimethacrylate mixture (equimolar mixture of urethanedimethacrylate UDMA and decandioldimethacrylate D3MA)</span></p>
<p><span lang="EN-US">PEGDA: Poly(ethylene glycol) diacrylate Mw ~700 g/mol, 50 wt% in water</span></p>
<p><span lang="EN-US">EDB: Ethyl 4-dimethylaminobenzoate</span></p>
<p><span lang="EN-US">PEG: Poly(ethylene glycol)</span></p>
<p><span lang="EN-US">PPG: Poly(propylene glycol)</span></p>
<p><span lang="IT">IC/IC2959: Irgacure 2959</span></p>
<p><span lang="IT">Li-TPO: Lithium-phenyl-2,4,6-trimethylbenzoylphosphinat</span></p>
<p><span lang="EN-US">DMEM: Dulbecco's Modified Eagle’s medium</span></p>
<p><span lang="IT">FBS: Fetal bovine serum</span></p>
<p><span lang="IT">JRNIL cure: Decandiol diacrylat</span></p>
<p><span lang="EN-US">M286: Poly(ethylene glycol) diacrylate Mw ~700 g/mol, 50 wt% in water</span></p>
<p><strong><span lang="EN-US"> </span></strong></p>
<p><strong><span lang="EN-US">Abstract </span></strong><span lang="EN-US">(English)</span></p>
<p><span lang="EN-US">Photoinitiators (PIs) represent the key molecules within a photopolymerizable resin, due to their ability to generate the initiating species. However, the majority of state-of-the-art PIs comprise aromatic chromophores, known to produce cytotoxic photoproducts, whose migration out of the cured resin poses both environmental and human health threats. Herein, we present a set of multifunctional, aliphatic free radical photoinitiators based on the α-ketoester moiety, which exhibit low cytotoxicity even after irradiation. By systematically increasing the number of PI moieties, purely aliphatic molecules comprised of up to four radical-generating units have been synthesized. High miscibility in both organic and water-based formulations, combined with excellent photoreactivity and no discoloration upon irradiation with broadband (320-500 nm) and LED (385 nm) light sources, are demonstrated. The developed α-ketoester derivatives outperform the benchmark Norrish Type II benzophenone/amine system and can be used for advanced applications, including UV-nanoimprint lithography as well as additive manufacturing technologies (DLP 3D printing).</span></p>
Dataset for "Highly-Sensitive Integrating Optical Receiver With Large PIN Photodiode"
No full text<h1>Overview</h1>
<p>This repository provides measurement data and evaluated data related to our manuscript "Highly-Sensitive Integrating Optical Receiver With Large PIN Photodiode" by Simon Michael Laube, Christoph Gasser, Kerstin Schneider-Hornstein, and Horst Zimmerman, published in IEEE Photonics Journal, 2024, DOI: <a title="Highly-Sensitive Integrating Optical Receiver With Large PIN Photodiode" href="https://doi.org/10.1109/JPHOT.2024.3487302">10.1109/JPHOT.2024.3487302</a>.</p>
<h1>Context</h1>
<p>In our study, we present the design and experimental verification of three optoelectronic integrated circuits (OEICs). The main difference between the OEICs is the integrated photodiode. The three photodiodes are:</p>
<ol>
<li>7WPD, a 7-dot honeycomb PIN photodiode</li>
<li>3X3PD, a 3-by-3 matrix PIN photodiode</li>
<li>6X6PD, a 6-by-6 matrix PIN photodiode</li>
</ol>
<p>We measured the responsivity and capacitance of the photodiodes. Moreover, we measured the transient output voltage of the OEICs across optical input power with an oscilloscope, and stored the waveforms in HDF5 files. The bit error probability (BER) was evaluated from the transient measurements using post-processing in Python, as explained in our manuscript. A data rate of 20 Mb/s with 80% return-to-zero (RZ) on-off keying (OOK) modulation was used for all BER measurements.</p>
<h1>File structure</h1>
<p>All measurement data is provided separately for each of the three photodiodes. Please note that the OEIC samples have individual sample identifiers that are part of the file names. The sample identifiers are:</p>
<ol>
<li>7WPD: H6_1</li>
<li>3X3PD: D3_7</li>
<li>6X6PD: E6_6</li>
</ol>
<p>The main folders <code>/BER</code>, <code>/powermeter</code>, <code>/responsivity</code>, and <code>/waveforms</code> are provided.</p>
<h2>Waveforms</h2>
<p><code>/waveforms</code> contains raw waveform (transient measurement) data. Waveforms are stored as HDF5 files (.h5 file ending) that contain an internal file system with metadata and data, generated by the oscilloscope. HDF5 files can be read using the free HDFView program, h5py Python library, or other software.</p>
<p>The internal file system within our HDF5 files has the following structure:<br><code>/FileType/KeysightH5FileType</code><br><code>/Frame/TheFrame</code><br><code>/Waveforms</code><br><code> /Channel 1/Channel 1 Data</code><br><code> /Channel 2/Channel 2 Data</code></p>
<p><code>KeysightH5FileType</code> and <code>TheFrame</code> are oscilloscope metadata. The<code> Channel 1</code> sub-folder contains metadata and <code>Channel 1 Data</code>. <code>Channel 1 Data</code> is the raw waveform data of the pseudo-random bit sequence (PRBS) that was used as the input signal of our OEICs. The <code>Channel 2</code> sub-folder contains metadata and <code>Channel 2 Data</code>. <code>Channel 2 Data</code> is the raw waveform data of the OEIC output voltage.</p>
<p>The file name structure of the HDF5 files is<br> <code><sample identifier>_<measurement identifier>x1x<optical power identifier>x<vG identifier>.h5</code></p>
<p>Here, the sample identifier is the same as explained above; the measurement identifier is an arbitrary text/number; the optical power identifier connects the power measurement (see below) with the corresponding waveform; and the vG identifier connects the reference voltage setting (see below) with the corresponding waveform. For example, the file "<code>E6_6_01Hx1x10x5.h5</code>" is the raw waveform of the 6X6PD OEIC, measurement "01H", recorded for the 10th optical power setting and 5th vG setting. Note that the vG settings are not coherent across measurements, e.g. setting number 5 is not always the same voltage.</p>
<h2>Optical Power</h2>
<p><code>/powermeter</code> contains the raw optical power measurement results, as well as the calibration factor that was used to calculate the power incident on the chip. In other words,<br> chip power=raw power * calibration factor.</p>
<p>The optical power measurements are provided in CSV files (.csv file ending), separately for each OEIC and measurement. Within the CSV files, the first column is the optical power identifier of the measurement (see above), and the second column is the respective raw optical power. The file name structure of the CSV files is<br> <code>power_<sample identifier>_<measurement identifier>.csv</code></p>
<p>The calibration factor is provided in a TXT file (.txt file ending), separately for each OEIC and measurment. The TXT file contains only a single floating point number that is the calibration factor. The file name structure of the TXT file is<br> <code>calibration_<sample identifier>_<measurement identifier>.txt</code></p>
<p>Here, the sample identifier and measurement identifier are the same as for the waveform files, as explained above. For example, the files "<code>calibration_E6_6_01H.txt</code>" and "<code>power_E6_6_01H.csv</code>" correspond to all waveforms with the prefix "E6_6_01H", such as the abovementioned "<code>E6_6_01Hx1x10x5.h5</code>".</p>
<h2>Bit error probability</h2>
<p><code>/BER</code> contains the evaluated bit error probability of the OEICs. All files within this folder are generated from the raw data provided in <code>/waveforms</code> and<code> /powermeter</code>, using our Python script. Three file types are provided for each photodiode:</p>
<ol>
<li>Log files (.log file ending) that document the result of the evaluation. These log files were used to plot Fig. 9 in our manuscript.</li>
<li>Image files (.png file ending) that illustrate the result of the evaluation, similar to Fig. 10 in our manuscript.</li>
<li>A CSV file that contains a results summary (.csv file ending).</li>
</ol>
<p>The log file contains metadata about the evaluation process, the evaluation result (BER), as well as the the input file (waveform) and output files of the evaluation. Note that the .tab output files are not provided because they were only used for debugging of our Python script. While most of the log file contents should be self-explanatory, some require special attention:</p>
<ul>
<li>In the "User settings" section we provide settings for the evaluation of the reference PRBS (<code>Channel 1 Data</code> in the HDF5 files). The boolean flag "PRBS inverted" shows whether the PRBS waveform was processed as is, or was logically inverted. The "PRBS detection threshold" is the threshold voltage that was used to digitize the (analog) PRBS waveform. Because the SNR of the PRBS is very high, the threshold itself is uncritical and was auto-detected by our Python script. The "PRBS detection offset" marks the start of the PRBS with respect to the recorded waveform. This is necessary because the recording may start at an arbitrary time, so the first recorded bit is incomplete. The start of the PRBS was auto-detected by our Python script by rising edge detection. The "PRBS detection delay" shows at which time instant each PRBS bit is sampled, with respect to the start of a bit. Typically, the bit should be sampled at the center. For 20 Mb/s with 80% RZ modulation, the center is 20 ns (=PRBS detection delay) after the start of the bit.</li>
<li>In the "Results" section, the result and the optimized settings for the evaluation of the chip output (<code>Channel 2 Data</code> in the HDF5 files) are provided. "Decision threshold" is the threshold (voltage) for bit decision. "CDS delta time" is the time between the two sample instants of correlated double sampling (CDS). "Best BER" is the BER result. The "Static delay" is the coarse delay between PRBS and chip output waveform, given in multiples of the bit period (50 ns at 20 Mb/s). The "Inter-bit delay" is the fine delay between PRBS and chip output waveform, that is always less than the bit period. The sum of static delay and inter-bit delay are the total delay between PRBS and chip output waveform.</li>
</ul>
<p>The file name structure of the log files is<br> <code><sample identifier>_<measurement identifier>x1x<optical power identifier>x<vG identifier>.log</code><br>The file name structure of the image files is<br> <code><sample identifier>_<measurement identifier>x1x<optical power identifier>x<vG identifier>.png</code></p>
<p>The results summary CSV contains all optical power and vG settings, the BER results, and the underlying dataset file names. For the meaning of vG, please refer to Fig. 4 of our manuscript.</p>
<p>The file name structure of the CSV is<br> <code>BER_<photodiode>_20Mbps_80RZ.csv</code><br>where the photodiode is 7WPD, 3X3PD, or 6X6PD, as defined above.</p>
<h2>Responsivity</h2>
<p><code>/responsivity</code> contains the raw spectral responsivity data of the photodiodes, that is plotted in Fig. 6 of our manuscript. A single CSV file (.csv file ending) is provided for each photodiode. The first column of the CSV file is the optical wavelength (lambda); the second column is the measured responsivity (R).</p>
<p>The file name structure of the CSV files is<br> <code>responsivity_<photodiode>.csv</code><br>where the photodiode is 7WPD, 3X3PD, or 6X6PD, as defined above.</p>
<h2>Capacitance</h2>
<p>Because the raw photodiode capacitance data is given in the manuscript, no data is provided in this dataset.</p>
<h1><br>Licensing</h1>
<p>The dataset consists of raw measurement data and processed data.<br>Raw data is licensed under the <strong>Creative Commons Zero 1.0 Universal (CC0)</strong> license.<br>Processed data is copyrighted and licensed under the <strong>Creative Commons Attribution 4.0 International (CC-BY)</strong> license.<br>All metadata is licensed under the <strong>Creative Commons Attribution 4.0 International (CC-BY)</strong> license.</p>
<p>The following list shows the license attached to the individual files:</p>
<ul>
<li>All files and sub-folders within <code>/waveforms</code>: <strong>CC0</strong> license</li>
<li>All files and sub-folders within<code> /powermeter</code>: <strong>CC0</strong> license</li>
<li>All files and sub-folders within <code>/BER</code>: <strong>CC-BY</strong> license</li>
<li>All files and sub-folders within <code>/responsivity</code>: <strong>CC0</strong> license</li>
<li><code>/README.txt</code>: <strong>CC-BY</strong> license</li>
</ul>
Data related to article "CD4+ T-cells create a stable mechanical environment for force-sensitive TCR:pMHC interactions"
No full text<p><a href="https://doi.org/10.48436/y5yw4-ggn77">This record</a> contains all data, artwork, and code used to create figures and tables in the article <em>Schrangl et al. (2025): “CD4+ T-cells create a stable mechanical environment for force-sensitive TCR:pMHC interactions”</em>.</p>
<h1>Dataset structure</h1>
<ul>
<li><em>schrangl2025_force_v1.zip</em> contains source code for data file handling, high-level analysis, and figure generation</li>
<li><em>data_force_raw.part1.zip</em> and <em>data_force_raw.part2.zip</em> contain raw single-molecule fluorescence microscopy data from force sensor experiments</li>
<li><em>data_force.zip</em> contains per-experiment single-molecule FRET tracking datasets derived from the above using the <a href="https://github.com/schuetzgroup/fret-analysis">fret-analysis</a> software</li>
<li><em>data_lifetime_raw.zip</em> contains raw single-molecule fluorescence microscopy data from TCR:pMHC bond lifetime measurements</li>
<li><em>data_lifetime.zip</em> contains per-experiment single-molecule FRET tracking data derived from the above using the <a href="https://github.com/schuetzgroup/smfret-bondtime">smfret-bondtime</a> software</li>
<li><em>data_supplementary_raw.zip</em> contains raw data for supplementary figures</li>
<li><em>data_supplementary.zip</em> contains analysis data for supplementary figures</li>
</ul>
<h1>Installation</h1>
<ul>
<li>
<p>Install the <a href="https://docs.astral.sh/uv/">uv</a> Python package and project manager. Note that many Linux distributions provide packages for easy installation. Version 0.7.13 was used to produce the published figures.</p>
</li>
<li>
<p>Create a new folder and download the data archives (<em>data_force.zip</em>, <em>data_force_raw.part1.zip</em>, <em>data_force_raw.part2.zip</em>, <em>data_lifetime.zip</em>, <em>data_lifetime_raw.zip</em>, <em>data_supplementary.zip</em>, <em>data_supplementary_raw.zip</em>) into that folder.</p>
</li>
<li>
<p>Download and unpack <em>schrangl2025_force_v1.zip</em> somewhere on your hard drive.</p>
</li>
<li>
<p>Using a terminal, navigate into the unpacked folder and execute</p>
<p><code>uv sync</code></p>
<p>to obtain required Python packages.</p>
</li>
<li>
<p>Execute</p>
<pre><code>uv run python data_utils/unpack.py --input-dir <download_folder> --output-dir data</code></pre>
<p>where <em><download_folder></em> is the folder into which the data archives were downloaded. Note that this will unpack all files with extension <em>.zip</em>, so make sure that only downloaded files are present in the folder.</p>
<p>Alternatively, any application supporting zstd-compressed zip archives (such as <code>7z</code>) can be used.</p>
<p>After unpacking, the <em>data</em> folder should contain subfolders <em>force</em>, <em>force_raw</em>, <em>lifetime</em>, <em>lifetime_raw</em>, <em>supplementary</em>, and <em>supplementary_raw</em> consisting of the data files.</p>
</li>
<li>
<p>Optionally delete the folder containing the downloaded data archives to free disk space.</p>
</li>
</ul>
<h1>Generation of figures and tables</h1>
<p>The <a href="https://scons.org/">SCons</a> software construction tool is used to execute Python scripts for data analysis and figure/table generation. SCons keeps track of dependencies and only reruns Python scripts if either the inputs or the scripts themselves change.</p>
<p>To build figures and tables, execute</p>
<pre><code>uv run scons</code></pre>
<p>This will</p>
<ul>
<li>generate a cache of single-molecule force data to speed up subsequent analysis</li>
<li>analyze cached force data and lifetime data</li>
<li>generate figures and tables from analysis results</li>
</ul>
<p>All created files are placed in the <em>output</em> subfolder. On a current PC, this takes about 15 minutes to complete.</p>
<p>To clear the <em>output</em> subfolder, run</p>
<p><code>uv run scons --clean</code></p>
<p>For further information, consult the <a href="https://scons.org/documentation.html">SCons documentation</a> and inspect the <em>SConscript</em> file.</p>
<h1>Licensing</h1>
<p>Each file in <em>schrangl2025_force_v1.zip</em> and <em>data_force.zip</em> either contains a header or is accompinied by a file with additional extension <em>.license</em> providing licensing information according to the <a href="https://reuse.software/">REUSE</a> specfication. As a rule of thumb,</p>
<ul>
<li>code is subject to the <a href="https://spdx.org/licenses/BSD-3-Clause.html">BSD 3-Clause license</a>,</li>
<li>minor helper files are put into the public domain,</li>
<li>other files (this README, illustrations, data) are subject to the <a href="https://spdx.org/licenses/CC-BY-4.0.html">Creative Commons Attribution 4.0 International license</a>,</li>
</ul>
<p>but there some exceptions, e.g. due to reuse of work created by third parties.</p>
<p><em>data_force_raw.part1.zip</em>, <em>data_force_raw.part2.zip</em>, <em>data_lifetime_raw.zip</em>, <em>data_lifetime.zip</em>, <em>data_supplementary.zip</em> and <em>data_supplementary_raw.zip</em> contain</p>
<ul>
<li>Jupyter notebooks subject to the <a href="https://spdx.org/licenses/BSD-3-Clause.html">BSD 3-Clause license</a> and</li>
<li>other files (mainly data) subject to the <a href="https://spdx.org/licenses/CC-BY-4.0.html">Creative Commons Attribution 4.0 International license</a>.</li>
</ul>
<p><em>data_supplementary_raw.zip</em> additionally contains ImageJ macros, which are <a href="https://spdx.org/licenses/BSD-3-Clause.html">BSD 3-Clause</a>-licensed.</p>
<p>© 2017–2025 Lukas Schrangl <[email protected]>, Florian Kellner <[email protected]>, Vanessa Mühlgrabner <[email protected]>, Janett Göhring <[email protected]></p>
Proof of Concept: JUNON Digital Twin (v1.4d)
No full text<h2>Proof of Concept: JUNON Digital Twin (v1.4)</h2>
<h3>Context and methodology</h3>
<p><a href="https://www.junon-cvl.fr/fr" target="_blank" rel="noopener">JUNON</a> is an ambitious research programme to develop a digital research cluster on the continental environment (agricultural, urban, forestry and river) in the Centre-Val de Loire region, France. This cluster aims to design digital services to improve the monitoring and understanding of the environment, for better management of natural resources.</p>
<p>This repository contains a proof of concept (PoC) of the JUNON Digital Twin. It tests some planned parts of DT, data exchange protocols, communication processes and services. The PoC is built on dockerized modules that can be executed on a single machine. It is formed by a <a href="https://www.fiware.org/" target="_blank" rel="noopener">FIWARE</a> network that includes the following components: Data Manager, Scheduler, Web Application, MongoDB, Orion Context Manager, Cygnus, and STH-Comet. External repositories (<a href="https://donneespubliques.meteofrance.fr/?fond=produit&id_produit=230&id_rubrique=40" target="_blank" rel="noopener">MétéoFrance-Safran</a>, <a href="https://hubeau.eaufrance.fr/page/api-piezometrie" target="_blank" rel="noopener">Hubeau-ADEs</a> and <a href="https://python-visualization.github.io/folium/latest/" target="_blank" rel="noopener">Folium</a>) are connected through official APIs. The developed PoC serves a use case in which the DT collects and manipulates data related to 53 piezometric sensors from strategic locations in the Centre-Val de Loire selected by expert hydrologists. They collect data of aquifer water levels (<a href="https://hubeau.eaufrance.fr/page/api-piezometrie" target="_blank" rel="noopener">Hubeau-ADEs</a>). Additionally, this information is combined with weather/climate measurements and estimations (<a href="https://donneespubliques.meteofrance.fr/?fond=produit&id_produit=230&id_rubrique=40" target="_blank" rel="noopener">MétéoFrance-Safran</a>). <a href="https://python-visualization.github.io/folium/latest/" target="_blank" rel="noopener">Folium</a> repositories are accessed to obtain interactive geographic maps.</p>
<p>The database contains data from January 2020 to July 2025 by default, although users can easily extend or reduce the temporal coverage. The DT prototype provides services for: (a) historical data visualization, (b) time series forecasting with or without exogenous inputs, (c) clustering of multivariate time series, and (d) spatial interpolation of two-dimensional water-level maps. Users access the PoC services through a Flask/Dash application.</p>
<h3>Technical details</h3>
<ul>
<li>[docker] contains the Dockerfile and docker-compose.yml to build the FIWARE network with the MongoDB, Orion Context Manager, Cygnus, and STH-Comet components as well as a debian-based system component with Python to run the Data Manager, Scheduler and Web Application components.</li>
<li>[db] contains the default MongoDB with data from 2020 to 2025.</li>
<li>[data_manager] contains scripts to run the Data Manager.</li>
<li>[scheduled] contains scripts to run the Scheduler.</li>
<li>[webapp] contains scripts to run the Web Application.</li>
<li>"README.md" contains documentation and instructions.</li>
<li>*metadata.json*: description of data assets stored in the MongoDB database by default in this repository in compliance with *Open Access and ISO-compliant metadata* requirements.</li>
</ul>
<p>All data files are licensed under CC BY 4.0, all software is licensed under MIT License.</p>
<h3>Supplementary repository</h3>
<p>The following repository complements this one by providing a precompiled Docker image of the project and references to external Docker images pinned with SHA-256 digests. This ensures long-term use and accurate replicability (use the prebuilt version in case of compilation problems or compatibility issues with future versions of external modules and dependencies).</p>
<blockquote>
<p>Iglesias Vazquez, F. (2025). Proof of Concept: JUNON Digital Twin (v1.4) -- Prebuilt Image (1.4). TU Wien. <a href="https://doi.org/10.48436/rpkgp-d3b15" target="_blank" rel="noopener">https://doi.org/10.48436/rpkgp-d3b15</a></p>
</blockquote>
K23-1284
No full text<h2>Related work</h2>
<p>This dataset is part of the digital documentation of the Tomb of Meret Neith, Umm el Qaab, Abydos, Egypt about 3000BC, its artefacts, and the reconstruction of the tomb. For an overview of the related work, please visit <a href="https://researchdata.tuwien.at/communities/meretneith/">https://researchdata.tuwien.at/communities/meretneith/</a>.</p>
<h2>Archaeological information</h2>
<h3>Object name</h3>
<p>Decorated vessel</p>
<h3>Object number(s)</h3>
<p>K23-1284; LN2215</p>
<h3>Description</h3>
<p>decorated vessel fragment, ivory</p>
<h3>Location of object at time of photographs</h3>
<p>MoTA storage</p>
<h3>Find location</h3>
<p>Tomb Y; context L177 S2</p>
<h3>Bibliography</h3>
<p>Köhler, E. C., Ferschin, P., Hood, A., Junge, F., Kovács, B. I., & Minotti, M. (2023). A PRELIMINARY REPORT OF NEW ARCHAEOLOGICAL FIELDWORK AT THE TOMB OF QUEEN MERET-NEITH OF THE 1ST DYNASTY AT ABYDOS, UMM EL-QAAB. Ägypten Und Levante / Egypt and the Levant, 33, p. 128, fig. 71.4.</p>
<h2>Technical Information</h2>
<p>For imaging, Canon RAW and Apple RAW images were captured.</p>
<h3>Physical properties</h3>
<table>
<tbody>
<tr>
<td>Length (cm)</td>
<td>N/A</td>
</tr>
<tr>
<td>Width (cm)</td>
<td>N/A</td>
</tr>
<tr>
<td>Height (cm)</td>
<td>N/A</td>
</tr>
<tr>
<td>Weight (g)</td>
<td>N/A</td>
</tr>
<tr>
<td>Volume (cm3)</td>
<td>N/A</td>
</tr>
<tr>
<td>Density (g/cm3)</td>
<td>N/A</td>
</tr>
</tbody>
</table>
<h3>Comments</h3>
<p>not processed, scale is missing</p>
<h3>Files overview</h3>
<ul>
<li><b>images_videos.zip</b> contains photographs of the real object in RAW format.</li>
<li>[optional] <b>exports_{H,M,L}Q.zip</b> archives contain the scanned object as 3D model in OBJ format including MTL and texture files. HQ, MQ, and LQ refer to high, medium and low quality versions of the model.</li>
<li>[optional] <b>{objectName}_report.pdf</b> contains further technical information of the reconstruction process.</li>
</ul>
Research data for "Investigation of sputtering and erosion phenomena in radio-frequency quadrupoles"
No full text<p><strong>Summary</strong></p>
<p>This data repository contains the sputtering yield measurement data and atomic force microscopy (AFM) files used in the following publication:<br>Emmanouil Trachanas, Luca Bellan, Gyula Nagy, Antonio Palmieri, Andrea Bignami, Richard Arthur Wilhelm, Francesco Grespan, and Nikolaos Gazis, Phys. Rev. Accel. Beams 28, 104501 (2025).</p>
<p> </p>
<p><strong>Technical details</strong></p>
<p>The raw measurement files presented here are all human-readable ASCII files.</p>
<p>For the sputter yield measurements, the files contain the term "QCM_data". These files contain the recorded quartz crystal microbalance (QCM) frequencies together with a time-stamp, in a 2-column format. Although within one such file there are recorded data for multiple incidence angles (for practical reasons, i.e. one file is one un-interrupted angle scan measurement), the file name itself indicates the order of the different angles. The 4 datasets represent 4 measurements using different beam energies and species, also indicated in the file name. An example is shown in Figure 5 of the published paper, with visual explanation of the data interpretation.</p>
<p>For calculating absolute sputter yields from QCM measurements, one needs the intensity of the incident beam, and the constants of the quartz crystal microbalance. Incident beam intensity is calculated from the beam profiles, found in the files starting with a name "BeamProfile" for each beam energy and species. For the 2 keV H+, 2 keV Ar+ and 36 keV Ar6+ irradiation, the average beam intensity was calculated from the profiles taken before and after. For the 6 keV H+, there are 5 more beam profiles recorded in addition to the before and after ones. These intermediate beam profiles were recorded evenly distributed during the whole measurement. The QCM constants used for the experiment can be found in the file "QCM_constants.txt".</p>
<p>The files starting with "25Cu1" (which is the sample ID that is used for the study), are AFM data. For each AFM measurement, both the raw microscopy data file converted to a human-readable ASCII file, and a visual representation in png format are available. The ones containing the term "before" were taken before the sputter yield measurement, while those with the term "after" were taken after the ion irradiations.</p><p>The performance and stability of radio-frequency quadrupoles (RFQs) depend critically on the structural integrity of their electrodes (vanes or rods), which are subjected to high-intensity ion beam exposure during accelerator operation. This study investigates the sputtering induced vane erosion on the European Spallation Source (ESS) RFQ, a critical component of the ESS linear accelerator. Particle tracking simulations for the determination of RFQ beam loss profiles were coupled to <span>sdt</span>rim<span>sp</span> software (static-dynamic transport of ions in matter sequential-parallel processing) modeling to estimate the sputtering yield distribution and the resulting erosion rates under nominal operating conditions. Methodology validation and benchmarking was performed using quartz crystal microbalance (QCM) measurements employing proton (2, 6 keV) and argon (Ar⁺ 2 keV, Ar⁶⁺ 36 keV) ion beams with incident angles of 0°–70°. The QCM experiments were used to benchmark <span>sdt</span>rim<span>sp</span> software simulation parameters for the calculation of sputtering yields and total electrode erosion rates across the energy and angular ranges relevant to the ESS RFQ. The results and conclusions are extended to RFQs employed for heavy-ion acceleration providing insights into long-term stability and performance degradation. The results indicate that heavy-ion irradiation leads to significantly higher sputtering yields and erosion rates compared to protons. It is estimated that the increased erosion rates result in critical frequency perturbations in RFQ cavities especially in high current or cw configurations that need to be effectively compensated.</p>
Data Set: The Dark Side of Metal Exsolution: A Combined In-Situ Surface Spectroscopic and Electrochemical Study on Perovskite-Type Cathodes for High-Temperature CO2 Electrolysis
No full text<h2>Primer on the dataset</h2>
<p>This dataset was created as part of research on high-temperature CO₂ electrolysis, specifically investigating the impact of Fe metal exsolution on the performance of perovskite-type oxide electrodes. It is aligned with the field of solid oxide electrochemistry and catalysis.</p>
<h3>Context and methodology</h3>
<ul>
<li>
<p><strong>Research domain or project:</strong> High-temperature CO₂ electrolysis, solid oxide electrochemistry, and catalysis.</p>
</li>
<li>
<p><strong>Purpose:</strong> Supports findings on surface chemistry and catalytic activity for CO₂ splitting.</p>
</li>
<li>
<p><strong>Creation:</strong> Generated using NAP-XPS (Near Ambient Pressure X-ray Photoelectron Spectroscopy), impedance and DC (direct current) measurements.</p>
</li>
</ul>
<h3>Technical details</h3>
<ul>
<li>
<p><strong>Structure:</strong> Organized by measurement technique (Impedance, XPS, DC) with clear file names.</p>
</li>
<li>
<p><strong>Software required:</strong> Standard formats, no special software requiered. </p>
</li>
</ul>
Normalization of Anomaly Detection Scores Based on Antagonistic Fuzzy-sets - Evaluation Tests
No full text<h2>Normalization of Anomaly Detection Scores Based on Antagonistic Fuzzy-sets - Evaluation Tests</h2>
<p>conducted for the paper: <strong>Interpreting and Unifying Anomaly Scores with Antagonistic Fuzzy Sets</strong> by Félix Iglesias, Tanja Zseby and Arthur Zimek. <em>2025 IEEE International Conference on Fuzzy Systems</em>.</p>
<h3>Context and methodology</h3>
<p>Beyond or in addition to binary labels (expressing anomalous and non-anomalous), most anomaly detection algorithms generate scores associated with the anomaly quality of each data point. Raw scores are often difficult to interpret directly, as they depend on the specific data and the analysis algorithm used. To overcome this drawback, traditionally these scores are normalized using the probabilistic interpretation proposed by Kriegel et al [1]. Such approach has obvious benefits, but also presents conceptual issues and some loss of information. A normalization based on antagonistic fuzzy-sets is more natural with the measurements provided by field algorithms while minimizing the possible loss of information. The advantages of fuzzy normalization vs. probabilistic normalization are explored and evaluated with the experiments provided in this repository. </p>
<h3>Technical details</h3>
<p>Experiments are in Python 3 (tested with v3.9.6). Provided scripts process all data and generate results. We keep paper-results in the repo for the sake of comparability and replicability. The file and folder structure is as follows:</p>
<ul>
<li><em>[datasets], </em>folder with datasets in .npz format.</li>
<li>[LICENSES], folder with third-party licences.</li>
<li>[results], folder with results as shown in the paper.</li>
<li><em>ensemble.py</em> runs evaluation experiments.</li>
<li><em>extract_tables.py</em> extracts .tex tables and .pdf plots as shown in the paper.</li>
<li><em>indices.py</em> implement different accuracy performance metrics commonly used in anomaly detection.</li>
<li><em>perf.csv</em> contains experiment results in tabular format as shown in the paper.</li>
<li><em>requirements.txt</em> lists Python package dependencies.</li>
<li><em>LICENSE</em> contains the GNU GPL license text.</li>
<li><em>README.md</em> provides explanations and step by step instructions for replication.</li>
</ul>
<h3>References</h3>
<p>[1] H. Kriegel, P. Kröger, E. Schubert, and A. Zimek, “Interpreting and unifying outlier scores,” in Proceedings of the 11th SIAM International Conference on Data Mining, SDM 2011, B. Liu, H. Liu, C. Clifton, T. Washio, and C. Kamath, Eds. United States: Society for Industrial and Applied Mathematics, Dec. 2011, pp. 13–24.</p>
<h3>Licenses</h3>
<p>All distributed code is under the GNU GPL license.</p>
<p>As for the datasets, they were originally published in the repository: <strong>ADBench</strong> (<a href="https://github.com/Minqi824/ADBench/tree/main">https://github.com/Minqi824/ADBench/tree/main</a>), In particular, the <strong>Classical collection</strong> (<a href="https://github.com/Minqi824/ADBench/tree/main/adbench/datasets/Classical">https://github.com/Minqi824/ADBench/tree/main/adbench/datasets/Classical</a>)</p>
<p>These datasets are © the original authors and are licensed under the BSD 2-Clause "Simplified" License. No endorsement by the original authors is implied.</p>