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Supporting Dataset for Publication: Refractive index mapping below the diffraction limit via single molecule localization microscopy
Get PDF<p><strong>Description of dataset</strong></p>
<p>This dataset includes all necessary information to reproduce<span lang="EN-US"> the analysis and </span>figures from the publication " <strong>Refractive index mapping below the diffraction limit via single molecule localization microscopy</strong>". It includes all figures from the main manuscript (Fig.1-Fig.3), as well as the supporting figures (Fig S1-S6) in high resolution. Furthermore, the dataset includes a detailed description of the used software, packages, python scripts and online repositories. Additionally, the dataset entails the localisation data files.</p>
<p><strong>Authors</strong></p>
<p>Simon Jaritz<sup>1</sup>, Lukas Velas<sup>1</sup>, Anna Gaugutz<sup>1</sup>, Manuel Rufin<sup>2</sup>, Philipp J. Thurner<sup>2</sup>, Orestis G. Andriotis<sup>2</sup>, Julian G. Maloberti<sup>3</sup>, Simon Moser<sup>3</sup>, Alexander Jesacher<sup>3</sup>, Gerhard J. Schütz<sup>1, ‡</sup></p>
<p> </p>
<p><sup>(1) </sup>Institute of Applied Physics, TU Wien, Vienna, Austria<br><sup>(2) </sup>Institute of Lightweight Design and Structural Biomechanics, TU Wien, Vienna, Austria<br><sup>(3) </sup>Institute of Biomedical Physics, Medical University of Innsbruck, Müllerstraße 44, 6020 Innsbruck, Austria</p>
<p><sup>‡</sup> <span lang="EN-US">Contact Person details</span>: <a href="mailto:[email protected]">[email protected]</a> </p>
<p><strong> </strong></p>
<p><strong><span lang="EN-US">Technical details</span></strong></p>
<p><strong><span lang="EN-US">Reproduction of the figures</span></strong><strong>: <br></strong><strong><span lang="EN-US">High Res Images:</span></strong><span lang="EN-US"> Features all Figures (Figures 1-3 and Supplementary Figures S1-S6) from the Paper, in high </span>resolution (600 dpi)<span lang="EN-US">.</span></p>
<ul>
<li><strong><span lang="EN-US">Fig 1a: </span></strong><span lang="EN-US">was created using power point</span></li>
<li><strong><span lang="EN-US">Fig 1b and c:</span></strong><span lang="EN-US"> all necessary scripts and data to create Fig 1b and Fig 1c are presented in the folder “Fig1b_and_Fig1c PSF.zip”</span></li>
<li><strong><span lang="EN-US">Fig 1d: </span></strong><span lang="EN-US">was created using the script in the folder “theoretical RI measurement.zip”</span></li>
<li><strong><span lang="EN-US">Fig 2: </span></strong><span lang="EN-US">all necessary data to create Fig 2 are presented in the data folder and in the Online Repository:<strong> “SMLM-Analysis” </strong>by Simon Jaritz. The script to create Fig2 is called: “comparing_results.ipynb“ </span></li>
<li><strong><span lang="EN-US">Fig 3: </span></strong><span lang="EN-US">all necessary scripts and data to create Fig3 are presented in the data folder and in the Online Repository:<strong> “SMLM-Analysis” </strong>by Simon Jaritz. The script to create Fig3 is called: “profile change over length of fibril.zip“</span></li>
</ul>
<ul>
<li><strong><span lang="EN-US">Fig S1: </span></strong><span lang="EN-US">was created using the script: “theoretical RI measurement.zip”</span></li>
<li><strong><span lang="EN-US">Fig S2: </span></strong><span lang="EN-US">was created using the script: “Print_STORM_AFM_Profile.ipynb.zip”</span></li>
<li><strong><span lang="EN-US">Fig S3: </span></strong><span lang="EN-US">all necessary scripts and data to create Fig 1b and Fig 1c are presented in the folder “Change along the fibril FigS3.zip”</span></li>
<li><strong><span lang="EN-US">Fig S4: </span></strong><span lang="EN-US">was created using the script in the folder “theoretical RI measurement.zip”</span></li>
<li><strong><span lang="EN-US">Fig S5:</span></strong><span lang="EN-US"> was created with a free version of AutoCAD web</span></li>
<li><strong><span lang="EN-US">Fig S6:</span></strong><span lang="EN-US"> was created using the data and scripts in the file “fibril analysis.zip”</span></li>
</ul>
<p> </p>
<p><strong><span lang="EN-US">Required Software </span></strong></p>
<ul>
<li>Matlab (Mathworks), version <span lang="EN-US">R2023b</span></li>
<li><span lang="EN-US">Python version 3.11.5, for determining the single molecule localizations, in combination with the Matlab software provided by A.Jesacher and J.Maloberti</span></li>
<li>Python (version 3.<span lang="EN-US">9.13</span>), <span lang="EN-US">for performing the analysis and create the figures in the paper</span></li>
</ul>
<p><span lang="EN-US">All Python software requirements and packages, </span>are listed in the <span lang="EN-US">file <strong>python_requirements.txt</strong></span></p>
<p><br><strong><span lang="EN-US">Analysis Scrips and Files-Folder</span></strong></p>
<ul>
<li><strong><span lang="EN-US">File: aberration measurement.zip</span></strong><span lang="EN-US"> (from Alexander Jesacher et.al):</span></li>
<li><span lang="EN-US">Matlab Application to calculate the aberrations of the optical setup <br>for single molecule analysis</span></li>
<li><strong><span lang="EN-US">File: aberrations.mat</span></strong><span lang="EN-US"> <br>Used aberration file for the single molecule analysis, calculated using the Matlab app aberration measurement (see below)</span></li>
<li><strong><span lang="EN-US">File: theoretical RI measurement.zip</span></strong><span lang="EN-US"> (from Alexander Jesacher et.al):</span></li>
<li><span lang="EN-US">Python program for the theoretical precision determination of the refractive index, used for Fig.1d, FigS1 and FigS4<br><br></span></li>
</ul>
<p><strong><span lang="EN-US">Online Repositories</span></strong></p>
<ul>
<li><strong><span lang="EN-US">Online Repository: mlefitgpu </span></strong><span lang="EN-US">(from Julian Maloberti)</span>
<ul>
<li><span lang="EN-US">Python program to determine the fitted PSF as well as performing the GPU fit, <br>to determine the 3D position of recorded microscopy data (SMLM localisations)</span></li>
<li><span lang="EN-US">available on: </span><a href="https://github.com/jgmaloberti/mlefitgpu">https://github.com/jgmaloberti/mlefitgpu</a><br>acces to that code is restricted and is managed by Julian Maloberti</li>
</ul>
</li>
<li><strong><span lang="EN-US">Online Repository: ForceMapAnalysis</span></strong><span lang="EN-US"> (from Manuel Rufin)</span>
<ul>
<li><span lang="EN-US">Matlab program to analyze and transform AFM data </span></li>
<li><span lang="EN-US">available on: </span><a href="https://github.com/Rufman91/ForceMapAnalysis">https://github.com/Rufman91/ForceMapAnalysis</a></li>
</ul>
</li>
<li><strong><span lang="EN-US">Online Repository: SMLM-Analysis</span></strong><span lang="EN-US"> (from Simon Jaritz)</span>
<ul>
<li><span lang="EN-US">Collection of Python scripts that were used to make the fibril analysis</span></li>
<li><span lang="EN-US">available on: </span><a href="https://github.com/simonjaritz/SMLM-Analysis.git"><span lang="EN-US">https://github.com/simonjaritz/SMLM-Analysis</span></a></li>
</ul>
</li>
</ul>
<p> </p>
<p><strong><span lang="EN-US">Localization Data files</span></strong></p>
<p><span lang="EN-US">The <em>localization data</em>-folder contains the necessary Data (point clouds) to perform the fibril analysis. <br>Please note that the RAW data (tiff and jpk-files) recorded with the microscopes, is only available upon request.</span></p>
<p><span lang="EN-US"> All region of interests (ROI) contain the same file strucutre and below is an example of ROI1:</span></p>
<ul>
<li><strong><span lang="EN-US">ROI 1</span></strong><span lang="EN-US">:</span>
<ul>
<li><strong><span lang="EN-US">AFM_pointcloud_...-dry.csv</span></strong><span lang="EN-US">: AFM dry data, stored as point clouds</span></li>
<li><strong><span lang="EN-US">AFM_pointcloud_...-Qi-liquid-fit.csv: </span></strong><span lang="EN-US">AFM wet data stored as point clouds</span></li>
<li><strong><span lang="EN-US">Fibril_cutouts.pkl: </span></strong><span lang="EN-US">cutout coordinates for the fibrils</span></li>
<li><strong><span lang="EN-US">List_of_val.csv:</span></strong><span lang="EN-US"> defocus value and middle layer thickness for each fibril</span></li>
<li><strong><span lang="EN-US">Overlay_table.pkl</span></strong><span lang="EN-US">: transformation parameters for the overlay </span></li>
<li><strong><span lang="EN-US">ROI 1 overview.png</span></strong><span lang="EN-US">: shows which fibril is which in an overview image</span></li>
<li><strong><span lang="EN-US">ROI 1 SMLM files folder</span></strong><span lang="EN-US">:</span>
<ul>
<li><strong><span lang="EN-US">Single molecule Localization files, drift corrected<br></span></strong><span lang="EN-US">These files contain the localizations that were analyzed using the Script<strong> mlefitgpu</strong> from Julian Maloberti (see below), with the following code example: “results_def_579_mid_138_n133_n1.4_n1518.csv”<br><br></span><span lang="EN-US">objective defocus = 579 nm<br></span><span lang="EN-US">middle layer thickness (AFM fibril height) = 138 nm<br></span><span lang="EN-US">refractive index surrounding medium = 1.33<br></span><span lang="EN-US">refractive index collagen = 1.40<br></span><span lang="EN-US">refractive index glass coverslip = 1.518</span></li>
</ul>
</li>
</ul>
</li>
</ul>
<p> </p><p>Single molecule localization microscopy (SMLM) is a powerful method to image biological samples in three dimensions below the diffraction limit of light microscopy. Beyond the position of the emitter, the shape of the single molecule point spread function provides additional information, for example about the refractive properties of the sample between the emitter and the glass coverslip. Here, we show that combination of SMLM with atomic force microscopy (AFM) allows to map the refractive index of a biological sample at sub-diffraction resolution and at a precision only limited by measurement errors of SMLM and AFM. We showcase the new method by the determination of the refractive index of isolated single collagen fibrils. Variabilities both in refractive index and the swelling behavior of single fibrils upon drying and rehydration exposed deviations from the ensemble behavior, demonstrating differential hydration of single collagen fibrils. Mapping the refractive index along single collagen fibrils revealed substantial fluctuations at characteristic length scales below 500 nm, which indicates structural heterogeneity of collagen fibrils at the length scale of single collagen molecules.</p>
Bauverhandlung in Wien mittels Augmented Reality (Projekt BRISE-Vienna)
No full text<p>This video shows the process of Augmented Reality supported building hearing in Vienna.</p>
<p>This process was developed as part of the <a href="https://digitales.wien.gv.at/en/projekt/brise-vienna/">BRISE-Vienna</a> research project. The aim was to develop a new process for building negotiations using new technologies.</p>
<p>For this purpose, a web-based platform was developed at the Vienna University of Technology (TU Wien), which enables the evaluation of submission models using augmented reality.</p>
Data for "Two-particle calculations with quantics tensor trains -- solving the parquet equations"
No full text<p>This data repository contains the original figures, numerical (raw) data and plot scripts to reproduce the figures from the publication "Two-particle calculations with quantics tensor trains -- solving the parquet equations" at Physical Review Research. The preprint is available on arXiv. Additional information can be found in the README.</p>
<h3>License</h3>
<ul>
<li>The CC-BY license applies to all the data and pdf files. All distributed code is under the MIT license.</li>
</ul>
<h3>Technical details</h3>
<ul>
<li>The dataset was created among others using the publicly available <a title="tensor4all" href="https://github.com/tensor4all" target="_blank" rel="noopener">tensor4all</a> libraries and <a title="ITensors" href="https://github.com/ITensor/ITensors.jl" target="_blank" rel="noopener">ITensors</a>.</li>
</ul>
Dataset for "Fractional Skyrmion Tubes in 3D Magnetic Nanowires"
No full text<h2>About the dataset</h2>
<p>This dataset supports a study where fractional skyrmion tubes were observed in double-helical nanowires fabricated by 3D nano-printing using focused electron beam-induced deposition. </p>
<p>The dataset includes code, images and processed data for reproducing the figures from the associated paper, and is intended to support researchers interested in reproducing the data of the scientific article, including simulations and experiments. For more information about the code and data, please refer to the <code>readme.txt</code> file.</p>
<p>The published preprint can be found here: <a href="https://arxiv.org/abs/2412.14069">https://arxiv.org/abs/2412.14069</a></p>
<p> </p>
<h2>Data & File Overview</h2>
<div>
<p><em>1) Micromagnetic Simulations</em><br>Contains Mumax3 files and scripts used to generate simulated data for the publication:</p>
<ul>
<li>shape.go: Modified Mumax3 source file enabling double-helix geometry.</li>
<li>Double_Helix_Phase_Diagram.mx3: Script for calculating the energetic phase diagram (Fig. 1d), run with varying Msat, arm_Separation, and nm_per_turn_d.</li>
<li>Double_Helix_Two_Vortex_State_Hysteresis_Loop.mx3 + .ovf: Script and initial state for hysteresis loop simulations (Figs. 2e/f/k).</li>
<li>Double_Helix_Two_Vortex_State_Minor_Hysteresis_Loop.mx3 + Hybrid_Vortex-AP_State_MinorLoop.ovf: For minor loop simulations starting from hybrid vortex–AP states (Fig. 3c + Supplementary).</li>
<li>Double_Helix_Two_Vortex_State_Topological_Charge_Variation.mx3 + .ovf: For topological charge variation in two-vortex state (Figs. 4c/d).</li>
<li>Double_Helix_Fractional_Skyrmion_State_Topological_Charge_Variation.mx3 + .ovf: For topological charge variation in fractional Skyrmion state (Figs. 4e/f/g/h).</li>
</ul>
<p><em>2) XMCD</em><br>Contains original ptychographic XMCD data from SOLEIL (beamtime 20210958, June 2022), processed from CL and CR reconstructions, aligned and normalized. Data saved as .dat arrays and .png images with field values in filenames. Includes metadata in [figure_name]_data_list.csv.</p>
<ul>
<li>Fig2: Data for Fig. 2; includes Fig2_fitparameters.dat (linecut fit results for experimental loops in Fig. 2j).</li>
<li>SFig4: Data for Fig. 2 and Supplementary Fig. 4.</li>
<li>SFig5-major: Data for Fig. 3 and Supplementary Fig. 5.</li>
<li>SFig5-minor: Data for Fig. 3 and Supplementary Figs. 5 & 6.</li>
<li>SFig9: Data for Supplementary Fig. 9.</li>
</ul>
<p><em>3) SEM</em><br>Contains an original SEM image of the fabricated double-helix structures used in Fig. 1.</p>
<p><em>4) TEM</em><br>Contains original TEM images of the FEBID Co nanostructure, used in Supplementary Fig. 7.</p>
</div>
<h2>Requirements</h2>
<p>The code can be executed using <a href="https://www.python.org/" target="_blank" rel="noopener">Python</a>, <a href="https://www.mathworks.com/products/matlab.html" target="_blank" rel="noopener">MATLAB</a>, <a href="https://www.paraview.org/" target="_blank" rel="noopener">Paraview</a> and <a href="https://mumax.github.io/" target="_blank" rel="noopener">Mumax3</a>, depending on the file.</p>
<p>The images can be opened with any standard image software.</p>
<h2>Licenses</h2>
<p>The data is licensed under CC-BY, the code is licensed under MIT.</p>
Atmospheric excitation of length of day inferred from 21st century climate projections (CMIP6 multi-model ensemble results)
No full text<h2>Results of the study "Atmospheric excitation of length of day inferred from 21st century climate projections"</h2>
<p>This dataset contains the results of a study presented in the scientific article "Atmospheric excitation of length of day inferred from 21st century climate projections", which is published in Journal of Geophysical Research: Atmospheres.</p>
<h3>Context and methodology</h3>
<ul>
<li>The study investigates trends in atmospheric angular momentum in historical and 21st century simulations using a CMIP6 multi-model ensemble.</li>
<li>The dataset serves as a public resource in the sense of open research; it provides all results of the above-mentioned study. </li>
<li>The dataset has been created using standard functions of MATLAB R2023b.</li>
</ul>
<h3>Technical details</h3>
<ul>
<li>The zip file contains five MATLAB files Boehm_Salstein_aamwind_lod.mat, Boehm_Salstein_aampressure_lod.mat, Boehm_Salstein_aamtotal_lod.mat, Boehm_Salstein_surface_temperature.mat, Boehm_Salstein_zonalmean_zonalwind.mat, Boehm_Salstein_aam2D_preslat_ring.mat that host five MATLAB structure arrays described in the following. Each structure has six fields for each simulation type: <em>historical, ssp119, ssp126, ssp245, ssp370, ssp585</em>; some also have a field <em>times</em> with the epochs of the time series or amplitudes given inside the fields. The simulation type fields have one line per model used in the study (11+1 for the multi-model mean). For each model different sets of parameters or results are present.<br>
<ul>
<li>aamwind_lod, aampressure_lod, aamtotal_lod: atmospheric angular momentum (AAM) in equivalent length of day (LOD) units (ms). Provided are ensemble means, arrays of ensemble member AAM results, base values for calculating anomalies with respect to 1976-2014, smoothed anomalies, centennial trends including standard deviations and p-values, mean annual amplitudes, and time dependent annual amplitudes.</li>
<li>surftemp: time series of global surface temperature in degree Celsius, provided are ensemble means and ensemble member results and the same for annual averages.</li>
<li>zmzonalwind: trends in zonal mean zonal wind speed (m s^-1 cy^-1) as a function of latitude and pressure. Latitude and pressure levels are provided as well as the trends interpolated to the coarsest grid and the intermodel standard deviation and model agreement.</li>
<li>aam2D_preslat: same parameters as for zmzonalwind but in terms of angular momentum per pressure/latitude ring (kg m^2 s^-1 cy^-1).</li>
</ul>
</li>
<li>The data can be accessed with MATLAB, but there are also Python functions to load MATLAB structure arrays (not tested in this case).</li>
</ul>
Stochastic Inversion of Transient Electromagnetic Data to Derive Aquifer Geometry and associated Uncertainties
No full text<h2>Context</h2>
<p dir="auto">This repository contains all the data, scripts, and libraries needed to reproduce the results (except for the QGIS map) from the article "Stochastic Inversion of Transient Electromagnetic Data to Derive Aquifer Geometry and Associated Uncertainties" by Lukas Aigner, Hadrien Michel, Thomas Hermans, and Adrián Flores Orozco.</p>
<h2>Reuse instructions</h2>
<p dir="auto">Functions and classes needed to run the scripts are located in the modules subfolder. Please find the scripts to reproduce the figures of the manuscript within the project folder. The scripts are configured to add a relative import path to <code>os.sys</code></p>
<p dir="auto">To build the Python environments:<br>There are several Conda environments (<code>*.yml</code>) provided; the correct environment to use depends on the use case (i.e. which parts of the provided code to execute).<br>For everything related to pyBEL1D please use the <code>bel1d</code> environment, for the sensitivity analysis please use the <code>salib_tem.yml</code> file, while all the other scripts can be run using the <code>empypg.yml</code>.</p>
<h2>Special thanks</h2>
<p dir="auto">This work would not have been possible without many other open-source libraries, so please also have a look at the following repositories and consider citing the corresponding articles:</p>
<ul>
<li><a href="https://github.com/gimli-org/gimli">https://github.com/hadrienmichel/pyBEL1D</a></li>
<li><a href="https://github.com/emsig/empymod">https://github.com/emsig/empymod</a></li>
<li><a href="https://github.com/gimli-org/gimli">https://github.com/gimli-org/gimli</a></li>
<li><a href="https://github.com/zperzan/pyDGSA">https://github.com/zperzan/pyDGSA</a></li>
</ul>
<h2>Licenses</h2>
<p>The data in this repository is licensed under CC-BY, the majority of the code is licensed under the apache 2.0 license, with the exception of everything related to pyBEL1D which uses the BSD-2-clause.</p>
<h2>Citation</h2>
<p dir="auto">If you find this work useful and consider publishing related work, please consider citing our article ("Stochastic Inversion of Transient Electromagnetic Data to Derive Aquifer Geometry and Associated Uncertainties") that is accepted with minor revisions in GJI.</p>
Businessmodelle für RDM-Tools und Services
Get PDF<p>Poster zu den Betriebsmodelle des Projekts Shared RDM im Zuge der Expo 2025.</p>
Adieu mes amours (Ger_1533-1_n38) 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 "Adieu mes amours", 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 "Adieu mes amours" and the id "Ger_1533-1_n38" in the e-lautedb. It is found on the page(s) or folio(s) XXXIXr-XLr in the source "Tabulatur auff die Laudten" with the source-id "Ger_1533-1".</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.Ger_1533-1/methods/sdef:TEI/get?mode=n38" target="_blank">https://edition.onb.ac.at/fedora/objects/o:lau.Ger_1533-1/methods/sdef:TEI/get?mode=n38</a>.</p><p>Links to the source: <a href="http://resolver.staatsbibliothek-berlin.de/SBB0001F5B500000000" target="_blank">http://resolver.staatsbibliothek-berlin.de/SBB0001F5B500000000</a>, <a href="https://opac.rism.info/rism/Record/rism993104093" target="_blank">https://opac.rism.info/rism/Record/rism993104093</a>, <a href="https://gateway-bayern.de/VD16+G+1578" target="_blank">https://gateway-bayern.de/VD16+G+1578</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>
Statistical Error Reduction for Monte Carlo Rendering: Result Images in Lossless PFM Format
No full text<p>This dataset contains the main 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 3.0.4</a> among others) for our paper “Statistical Error Reduction for Monte Carlo Rendering” (<a href="https://doi.org/10.1145/3757377.3763995">https://doi.org/10.1145/3757377.3763995</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/StatER">https://www.cg.tuwien.ac.at/StatER</a>.</p>
<h1>Acknowledgments</h1>
<p>We thank <a href="https://auzinger.name/">Thomas Auzinger</a> for providing LaTeX plugins, <a href="https://ciencia.iscte-iul.pt/authors/jose-joaquim-dias-curto/cv">José Dias Curto</a> for support with confidence intervals, and <a href="https://www.cg.tuwien.ac.at/staff/MarkusSch%C3%BCtz">Markus Schütz</a> for assistance with the CUDA implementation. We also thank the creators of the scenes we used: <a href="https://benedikt-bitterli.me/">Benedikt Bitterli</a> for <a href="https://benedikt-bitterli.me/resources/">“Veach, Bidir Room”</a> (Figs. 1, S12), <a href="https://benedikt-bitterli.me/resources/">“Cornell Box”</a> (Fig. 2), and <a href="https://benedikt-bitterli.me/resources/">“Fur Ball”</a> (Fig. 12); <a href="https://blendswap.com/profile/1574">Jay-Artist</a> for <a href="https://blendswap.com/blend/5156">“Country Kitchen”</a> (Figs. 4, 5, 10, S2, S10, S16); <a href="https://www.blendswap.com/profile/53736">Mareck</a> for <a href="https://blendswap.com/blend/13303">“Contemporary Bathroom”</a> (Figs. 7, 14, S13); <a href="https://blendswap.com/profile/215428">thecali</a> for <a href="https://blendswap.com/blend/13489">“4060.b Spaceship”</a> (Fig. 9); <a href="https://blendswap.com/profile/10550">piopis</a> for <a href="https://blendswap.com/blend/14205">“Old Vintage Car”</a> (Fig. 13); <a href="http://www.cemyuksel.com/">Cem Yuksel</a> for <a href="http://www.cemyuksel.com/research/hairmodels/">“Straight Hair”</a> (Fig. S4) and <a href="http://www.cemyuksel.com/research/hairmodels/">“Curly Hair”</a> (Fig. S5); <a href="https://blendswap.com/profile/4758">UP3D</a> for <a href="https://blendswap.com/blend/6885">“Little Lamp”</a> (Fig. S6); <a href="https://blendswap.com/profile/945886">axel</a> for <a href="https://blendswap.com/blend/3915">“Glass of Water”</a> (Fig. S7); <a href="https://blendswap.com/profile/10069">MrChimp2313</a> for <a href="https://blendswap.com/blend/12687">“Victorian Style House”</a> (Fig. S8); <a href="https://blendswap.com/profile/135376">NovaAshbell</a> for <a href="https://blendswap.com/blend/13632">“Japanese Classroom”</a> (Fig. S9); and <a href="https://www.beeple-crap.com/">Beeple</a> for <a href="https://www.beeple-crap.com/resources">“Zero-Day”</a> (Fig. S11). Statistical simulation studies were conducted using the <a href="https://asc.ac.at/">Austrian Scientific Computing (ASC)</a> infrastructure. This work has been funded by the Vienna Science and Technology Fund (WWTF) [Grant ID: 1047379/ICT22028]. This research was funded in whole or in part by the Austrian Science Fund (FWF) [<a href="https://doi.org/10.55776/F77">10.55776/F77</a>]. For open-access purposes, the author has applied a CC BY public copyright license to any author-accepted manuscript version arising from this submission. The authors acknowledge TU Wien Bibliothek for financial support through its Open Access Funding Programme.</p>
Wanilla: Sound Noninterference Analysis for WebAssembly (artifacts)
No full text<p>This dataset contains the software and benchmarks accompanying the paper "Wanilla: Sound Noninterference Analysis for WebAssembly" (to be published at the ACM Conference on Computer and Communications Security (CCS) 2025). Additionally, we provided build instructions for the tools we compare against (RAPID [1], wassail [3]) and the benchmarks used (RAPID [1], EOSFuzzer [2]) in the form of a nix flake.</p>
<p><code>wanilla-artifact-sources.zip</code> contains the sources for our prototype noninterference analyzer Wanilla (<code>./wanilla</code>) and its dependencies (<code>./horst</code>, <code>./wparser</code>). It furthermore contains the code of our prototype abstract interpretation for constrained Horn clause programs (<code>./asmt</code>). The build instructions and patches for the software we compare with (RAPID, wassail) are stored in the respective subdirectories (<code>./rapid</code>, <code>./wassail</code>). The scripts to filter out trivial examples and generate test specifications from the EOSFuzzer benchmark are stored in ./eosfuzzer-benchmark-data, while the code used in the figures of the paper (including the test specifications) is stored in <code>./figures-benchmark-data</code>. <code>stats.py</code> is a script to calculate statistics on the benchmark. The flake files (<code>flake.nix</code>, <code>flake.lock</code>) contain code to build the different components separately or <br>bundle them in a Docker container. <code>README</code>.md contains exact build/reproduction instructions.</p>
<p><code>wanilla-artifacts-docker-container.tar.gz</code> is a Docker container image that realizes the sources in <code>wanilla-artifact-sources.zip</code>. It contains all executables (in the versions we evaluated, with our patches applied) and all benchmark data in a form that Wanilla can understand.</p>
<p><code>smt-lib-files.zip</code> contains the outputs of Wanilla when applied to the benchmark inputs (our own benchmarks + the EOSFuzzer benchmark + the RAPID benchmarks) as constrained Horn clause programs (in the z3 dialect of SMT-LIB). The outputs are supplied for convenience (as the files can take some time to generate) and because Wanilla has some nondeterminism in its output, which (while producing semantically equivalent programs) can impact solver performance.</p>
<p>[1] G. Barthe, R. Eilers, P. Georgiou, B. Gleiss, L. Kovács, and M. Maffei. Verifying Relational Properties using Trace Logic. In Formal Methods in Computer Aided Design (FMCAD). IEEE, 2019.<br>[2] Y. Huang, B. Jiang, and W. K. Chan. Eosfuzzer: Fuzzing EOSIO smart contracts for vulnerability detection. In Internetware’20: 12th Asia-Pacific Symposium on Internetware, Singapore, November 1-3, 2020, pages 99–109. ACM, 2020.<br>[3] Q. Stiévenart and C. De Roover. Compositional Information Flow Analysis for WebAssembly Programs. In International Working Conference on Source Code Analysis and Manipulation (SCAM). IEEE, 2020.</p>