TU Wien Research Data
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Real-World Escape Route Models in IFC format
No full text<h2>Description</h2>
<p>The published data are digital building models (BIM models) in the IFC format (Industry Foundation Classes).<br>The IFC models represent escape route models containing the geometry of escape routes and additional characteristics as properties. The models were generated from the escape route analysis results of a real-world test model by researchers from the TU Wien Research Unit Digital Building Process.</p>
<h3>Context and methodology</h3>
<ul>
<li>The IFC models were generated by software prototypes developed with the programming languages Python (IfcOpenShell) and JavaScript (web-ifc). The required information is given by the attached JSON file including the model structure as well as coordinates and properties of the escape routes.</li>
<li>The escape route results were generated from a real-world test model for escape route analysis (see related works). </li>
<li>The Real-World Escape Route Models correspond to the IFC4 and IFC4X3_ADD2 schema.</li>
</ul>
<h3>Technical details</h3>
<ul>
<li>The dataset includes five BIM models in the IFC format (.ifc) and one dataset in the JSON format.</li>
<li>The models can be used in any software that supports the IFC format.</li>
</ul>
Dataset to: Electro-Tuned Catalysts - Voltage-Controlled Activity Selection of Bimetallic Exsolution Particles
No full text<h2>Context and methodology</h2><ul><li>Data was recorded at TU Wien, Research Unit of Technical Electrochemistry</li><li>The purpose of this dataset is to provide the data behind the figures in the paper entitled "Electro-Tuned Catalysts: Voltage-Controlled Activity Selection of Bimetallic Exsolution Particles" by Summerer et al. (J.Mat.Chem.A, 2024).</li></ul><h2>Technical details</h2><p>The folder structure of the dataset is as follows:</p><h3>Data</h3><ul><li>Data for each figures in various file formats (.csv, .xlsx, .txt, .dat, …)</li></ul><h3>Helpers</h3><ul><li>Various .py-Files necessary for equilibrium calculations</li><li>Style and colour file for plots</li></ul><h3>Plotting</h3><ul><li>.py-Files for each plot including a brief figure description</li></ul><h3> </h3>
Dataset to: "Fermi and Luttinger arcs: two concepts, realized on one surface"
No full text<p>The data repository 'Data_FermiLutArc' contains the original figures, numerical (raw) data, and plot scripts to reproduce the figures from the publication "Fermi and Luttinger arcs: two concepts, realized on one surface" at Physical Review Letters. The preprint and LaTeX source files are available on <a href="https://doi.org/10.48550/arXiv.2312.17700">arXiv</a>. Additional information can be found in the README. A detailed list of the used python packages provides the file 'python_versions.txt'.</p>
<h3><strong>License</strong></h3>
<p>The CC-BY license applies to all the data, png and pdf files. All distributed code is under the MIT license.</p>
dcTCO - Fluorescence microscopy data
No full text<p>The provided data includes all fluorescence microscopy images (embedded in a pptx-file) as published in <a href="https://doi.org/10.1002/chem.202203069">10.1002/chem.202203069</a> (freely accessible). The images are arranged according to the performed experiments and fluorescence channels and can be exported from the pptx-file in 2048x2048px resolution to external tools. The chemical structures of all compounds are specified in <a href="https://doi.org/10.1002/chem.202203069">10.1002/chem.202203069</a>.</p>
<p> </p>
<h2>Technical information</h2>
<p>HT1080 cells were seeded into a 96-well plate at 10,000 cells per well and allowed to grow overnight. The medium was removed, and the cells were treated with a 50 nM solution of sulfo-dcTCO-DMEDA-CA4 (compound 15) in media. <em>In situ</em> click-to-release was initiated by addition of DMT (compound 9) at a final concentration of 10 µM. As controls, cells were left untreated or incubated with either the parent drug CA4 (50 nM) or 10 µM DMT (compound 9). After an incubation time of 6 h cells were stained with SiR-tubulin (a fluorogenic, cell permeable and highly specific probe for microtubules). An 11X stock solution of the probe was directly added to the growth medium to obtain a final concentration of 1 µM and incubation was carried out for 1 h. Subsequently, the medium was removed, and cells were stained with Hoechst 33342 nuclear dye (Invitrogen, 5 µM in growth medium) for 10 minutes and washed once with PBS. Multichannel imaging of the cells was carried out in FluoroBrite DMEM medium (Gibco) on an Olympus IX82 microscope.</p>
<p> </p>
<h2>Summary of results</h2>
<p>Cell imaging via fluorescence microscopy (scale bars: 50 µm) upon staining with Hoechst 33342 (blue, nuclei) and SiR-tubulin (red, microtubules) shows comparable depletion of tubulin signals after 6 h treatment with CA4 (50 nM) or bioorthogonal activation of prodrug 15 (50 nM) by in situ reaction with DMT (compound 9). No significant change (compared to untreated cells) was observed after treatment with DMT (compound 9) or prodrug 15.</p>
A Statistical Approach to Monte Carlo Denoising: Result Images in Lossless PFM Format
No full text<p>This dataset contains the result images (inputs and denoiser outputs) in lossless <a href="https://netpbm.sourceforge.net/doc/pfm.html">PFM format</a> (compatible with <a href="https://www.gimp.org/">GIMP 2.10</a> among others) for our paper “A Statistical Approach to Monte Carlo Denoising” (<a href="https://doi.org/10.1145/3680528.3687591">https://doi.org/10.1145/3680528.3687591</a>). The directory names for the images correspond to the figure numbers in the paper and the supplementary document.</p>
<p>Furthermore, we provide additional materials (e.g., source code to reproduce the results) for our paper at <a href="https://www.cg.tuwien.ac.at/StatMC">https://www.cg.tuwien.ac.at/StatMC</a>.</p>
<h1>Acknowledgments</h1>
<p>We would like to thank the creators of the scenes we have used: <a href="https://blendswap.com/profile/130393">Wig42</a> for “Wooden Staircase” (Fig. 1), “Grey and White Room” (Fig. S6), and “Modern Living Room” (Fig. S8); <a href="https://www.blendswap.com/profile/72536">nacimus</a> for “Bathroom” (Fig. 3, S5); NovaZeeke for “Japanese Classroom” (Fig. 4, 6); <a href="https://www.beeple-crap.com/">Beeple</a> for “Zero-Day” (Fig. 8); <a href="https://blendswap.com/profile/1574">Jay-Artist</a> for “White Room” (Fig. S7); <a href="https://www.blendswap.com/profile/53736">Mareck</a> for “Contemporary Bathroom” (Fig. 2); Christian Freude for “Glass Caustics” (Fig. S10); and <a href="https://benedikt-bitterli.me/">Benedikt Bitterli</a> for “Veach Ajar” (Fig. 7, S2), “Veach MIS” (Fig. S4), and “Fur Ball” (Fig. S11). This work has received funding from the Vienna Science and Technology Fund (WWTF) project ICT22-028 (“Toward Optimal Path Guiding for Photorealistic Rendering”) and the Austrian Science Fund (FWF) project F 77 (SFB “Advanced Computational Design”).</p>
Sentinel-1 Flood Maps Using Exponential Filter as No-Flood Reference
No full text<h2>Background</h2><p>The TU Wien flood mapping algorithm is a Sentinel-1-based workflow using Bayes Inference at the pixel level. The algorithm is currently deployed in global operations under the Copernicus <a href="https://global-flood.emergency.copernicus.eu/technical-information/glofas-gfm/">GFM</a> project and have been shown to work generally well. However, the current approach has overestimation issues related to imperfect no-flood probability modeling. In a recent study, we proposed and compared an Exponential Filter derived from no-flood references versus the original Harmonic Model. We have conducted experiments on seven study sites for flooded and no-flood scenarios. A full description and discussion are found in the paper: <strong>Assessment of Time-Series-Derived No-Flood Reference for SAR-based Bayesian Flood Mapping.</strong></p><h3>Methodology</h3><ul><li>We generated no-flood references using the Exponential Filter at various T-parameter values and the original Harmonic Model as a baseline.</li><li>Flood maps were generated using the Bayes Inference-based SAR Flood mapping algorithm implemented in Python using <a href="https://github.com/TUW-GEO/yeoda">the Yeoda</a> software package. Flood maps using the various no-flood references for all available Sentinel-1 image acquisitions for a selected relative orbit per study site.</li><li>Each flood map is compared with the reference <a href="https://emergency.copernicus.eu/mapping/list-of-activations-rapid">CEMS</a> Rapid Mapping or <a href="https://sentinel-asia.org/event/Event.html">Sentinel Asia</a> reference dataset to generate validation/confusion maps.</li></ul><h3>Technical details</h3><ul><li>Datasets are stored in GeoTiff format using LZW Compression.</li><li>Files are compressed in two bundles: 1) flood maps, 2) false positive count maps, and 3) validation results.</li><li>Files are organized and tiled following the T3 <a href="https://github.com/TUW-GEO/Equi7Grid">Equi7Grid</a> tilling system at 20m x 20m resolution.<ul><li>Folder structure: dataset/map product>(continental)subgrid>tile>files.</li><li>The study covers the following study sites:<ul><li>EU E039N027T: Scotland</li><li>AS E054N015T3: Vietnam</li><li>EU E054N006T3: Greece</li><li>EU E051N012T3: Slovenia</li><li>AS E024N027T3: India</li><li>OC E057N117T3: Philippines</li><li>EU E057N024T3: Latvia</li></ul></li></ul></li><li>Files are named following the <a href="https://github.com/TUW-GEO/geopathfinder/blob/master/src/geopathfinder/naming_conventions/yeoda_naming.py">Yeoda</a> file naming convention.</li><li>Summary Accuracy Assessment Metrics are in CSV format.</li></ul><h3>Datasets:</h3><ul><li>Flood: <i>flood maps</i> generated using different parameterizations of no-flood reference.</li><li>FP_Count: false positive count maps.</li><li>Validation results include:<ul><li><i>Confusion maps</i> were generated from the difference between the flood maps and the rasterized <a href="https://emergency.copernicus.eu/mapping/list-of-activations-rapid">CEMS</a> Rapid Mapping reference or <a href="https://sentinel-asia.org/event/Event.html">Sentinel Asia</a> datasets. <i>Summary Accuracy Assessment Metrics</i> in CSV format.</li><li><i>ERA5-LAND daily aggregates </i>in CSV format.</li><li><i>Root Mean Square Error</i> time-series analysis in CSV format.</li><li><i>False Positive Rate</i> time-series analysis in CSV format.</li></ul></li><li>*Due to storage constraints, no flood reference is available upon request.</li></ul>
Field observations reveal how plunging mixing and sediment resuspension affect the pathway of a dense river inflow into a deep stratified lake - Dataset
No full text<p>This dataset is part of the manuscript "Field observations reveal how plunging mixing and sediment resuspension affect the pathway of a dense river inflow into a deep stratified lake" submitted to Water Resources Research in 2024. It contains measurements of a river intrusion and underflow event in Lake Geneva, Switzerland, from 2016.09.23 to 2017.01.23.</p><p>This dataset contains the following files:</p><ul><li>Current and echo measurements from an upward and a downward looking Acoustic Doppler Current Profile (ADCP), Teledyne RDI Workhorse 300 kHz.</li><li>Bottom water temperature measurements from a line of eight Seabird SBE56 thermistor nodes.</li><li>Vertical profiles of depth, temperature and conductivity from a CTD (ME OTS Sonde) obtained on 2016.12.12. The profile numbering corresponds to the positions given in the 20161212_CTD_Deployment_Figure.png file.</li></ul>
Calculation models: The LT-bridge construction method for the material-saving and fast construction of post-tensioned concrete bridges
No full text<p>Calculation models behind the paper on the LT-bridge construction method for the material-saving and fast construction of post-tensioned concrete bridges (https://doi.org/10.1002/best.202400007). </p><p>The calculation models on the basis of which the formwork, reinforcement, and tendon plans were created are provided here.<br>The *.sofistik and *.dwg files can be opened with the Sofistik 2022 software.<br>The *.inc files can be opened with the INCA2 software (https://www.u-pfeiffer.de/inca2/inca2-09.html).<br><br>If any further information is needed please contact [email protected]</p><p> </p>
Inventory of hazardous substance concentrations in different environmental compartments in the Danube river basin
No full text<h2>Description of the dataset</h2><p>The data set contains an SQL-dump of a PostgreSQL data base. This data base contains concentrations of hazardous substances and other water quality parameters in different environmental compartments:</p><ul><li>river water (water and suspended sediments)</li><li>ground water</li><li>waste water (treated and untreated) and sewage sludge</li><li>storm water runoff from combined and separate sewer systems</li><li>atmospheric deposition</li><li>soil</li></ul><p>Data from many different data sources were collected, cheked and combined and meta data were harmonized to allow for a combined data evaluation.</p><h3>Technical specifications</h3><p>The SQL-file was exported from a PostgreSQL 15.2 data base and compressed using 7zip into a zip-file (dhm3c<i>inventory</i>V2.zip).</p><p>Text-encoding is UTF-8.</p><h3>Supplementary files</h3><p>A short documentation (documentation_inventory_db_V2.0.pdf) and a listof known issues with the data which could not be resolved before publication (List_of_known_issues_V2.0.pdf) are enclosed as PDF files.</p><h2>Versions</h2><h3>Version 2.0.1</h3><p>During creation of Version 1.0.0 and 2.0.0 there was an processing error in the coordinates of atmospheric deposition and soil sampling sites leading to identical values for latitude and longitude for some sites. This was fixed in version 2.0.1.</p><h3>Version 2.0.0</h3><p>This Version 2.0.0 of the database contains more data as for further data sets a publication agreement was reached and some data were reimported to resolve some errors created during data preparation for import. The database structure was extended and corrected at different points, leading to an improved data model.</p>
3D pointcloud model Karlskirche, Vienna Austria
No full text<p>pointcloud model [e57] of the interior and exterior of Karlskirche, Vienna Austria</p>
<p>please contact <strong>[email protected]</strong> for access</p><p>captured with terrestrial laserscanner Riegl VZ-400i with Nikon D810 planted on top for RGB coloring of scans; positioning with GNSS antenna (no correction data)</p><p>coordinate system WGS84_EPSG 4978</p>