reapxdev/zenodo-scraper huggingface dataset:
Matexp source code and results
Authors: McDougall, David Alton
Type: Software
Published: 2026-06-03

<p>These archives are for the associated paper "Fast and Accurate Simulation of Ion Channels"</p>
<p>The file matexp.tar.gz contains:</p>
<ul>
<li>matexp/  - The source code for the matexp program</li>
<li>figures/  - The scripts to reproduce the figures</li>
<li>mod/   - The NMODL files which were used to test the program</li>
</ul>
<p>The file results.tar.gz contains:</p>
<ul>
<li>9950X3D2/   - Data and figures obtained on a 9950X3D2 (CPU) chipset</li>
<li>B200/   - Data and figures obtained on a B200 (GPU) chipset</li>
</ul>
Spatial Methods Workbench
Authors: Bhadury, Sagnik
Type: Software
Published: 2026-08-03
Keywords: spatial statistics, spatial biology, biostatistics, multiplex imaging, graphical models, image regression, reproducible research, R Shiny

<p>Spatial Methods Workbench is a citation-aware R Shiny environment with 12 guided workflows for spatial autocorrelation, conditional networks, spatially adjusted 2D and 3D networks, prediction, clustering, image-regression screening, mediation, and statistical shape analysis.</p><p>This corrected complete source distribution contains the installable Workbench package, Shiny application, five executable vignettes, four compact simulated datasets, complete documentation, 51 automated checks, and locally bundled package sources for the exact public ISPAT, GP-GHS, and ISPAT-3D engines. <code>install-complete.R</code> installs those local engine copies without cloning their repositories.</p><p>A curated public-source bundle also preserves license-safe regression, clustering, neural, SV-NN, STCAR, and SBLF source connected to the Workbench adaptations and related-method provenance. Exact engine calls, built-in adaptations, and related screening workflows remain explicitly distinguished. Large curriculum translations, media, demonstration datasets, Git history, and platform-specific compiled objects are omitted because they do not execute a Workbench analysis.</p><h3>Installation</h3><p>Download and extract the release, then run <code>Rscript install-complete.R</code>, <code>Rscript verify-installation.R</code>, and <code>Rscript tests/testthat.R</code>. The README contains platform prerequisites, advanced and related-engine options, verification, local launch, Docker, privacy, and troubleshooting guidance. Missing CRAN dependencies may be downloaded; the three direct method repositories do not need to be downloaded separately.</p><h3>Required attribution</h3><p>Users must cite this software release and the method-specific publications or software applicable to the workflow used. The complete bibliography is included in <code>REFERENCES.md</code> and in result bundles. Public sources are identified by repository, commit, license, retained scope, and role in <code>vendor/manifest.json</code>.</p><p>Only public, release-scoped material is included in this record.</p>
Code for: Testing density-responsive gravity at late times: cosmological dynamics with dark sector momentum transfer
Authors: Drobczyk, Martin
Type: Software
Published: 2026-08-03

<p>Supplementary material, source code and derived numerical data for reproducing all figures and the principal numerical results of  "<span class="fontstyle0">Testing density-responsive gravity at </span><span class="fontstyle0">late times: cosmological dynamics </span><span class="fontstyle0">with dark sector momentum transfer</span>"</p>
mljs/global-spectral-deconvolution: v14.2.2
Authors: Luc Patiny, mljs-bot, Jose Alejandro Bolanos Arroyave, Andres Castillo, Miguel Angel Asencio Hurtado, cheminfo-bot, Michaël Zasso, Kevin M Jablonka, Wadjih Bencheikh, tpoisseau
Type: Software
Published: 2026-08-03

<h2><a href="https://github.com/mljs/global-spectral-deconvolution/compare/v14.2.1...v14.2.2">14.2.2</a> (2026-08-03)</h2>
<h3>Bug Fixes</h3>
<ul>
<li>force shapes with <code>fwhm</code> property (<a href="https://github.com/mljs/global-spectral-deconvolution/issues/157">#157</a>) (<a href="https://github.com/mljs/global-spectral-deconvolution/commit/fc0491f5be7e68d2252999de36ec89d71cf9cedf">fc0491f</a>)</li>
</ul>
mljs/spectra-fitting: v6.2.2
Authors: Luc Patiny, Jose Alejandro Bolanos Arroyave, mljs-bot, Andres Castillo, Michaël Zasso, Aiday Marlen Kyzy, Javier Osorio M., Miguel Angel Asencio Hurtado, Wadjih Bencheikh, tpoisseau
Type: Software
Published: 2026-08-03

<h2><a href="https://github.com/mljs/spectra-fitting/compare/v6.2.1...v6.2.2">6.2.2</a> (2026-08-03)</h2>
<h3>Bug Fixes</h3>
<ul>
<li>only optimize shapes with fwhm (<a href="https://github.com/mljs/spectra-fitting/issues/132">#132</a>) (<a href="https://github.com/mljs/spectra-fitting/commit/1c7578bdd1cd61d438fc13c5d71323eb7ed5cd4a">1c7578b</a>)</li>
</ul>