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  1. 101

    Demonstration of Isosteric Heat of Adsorption Calculation using AIFs and pyGAPs by Jack Evans (11275386)

    Published 2025
    “…The data corresponds to carbon dioxide (CO2) adsorption on the metal-organic framework CALF-20 at six different temperatures ranging from 253 K to 373 K.</p><p dir="ltr">The calculation is performed using the Clausius-Clapeyron method as implemented in the <code><strong>pyGAPS</strong></code> Python library for adsorption science. …”
  2. 102

    Leue Modulation Coefficients (LMC): A Smooth Continuum Embedding of Bounded Arithmetic Data by Jeanette Leue (22470409)

    Published 2025
    “…This Zenodo package includes: the full research paper (PDF), a complete Python implementation generating the LMC field and conductivity model, a numerical plot comparing discrete LMC values with the smoothed continuum field, a cover letter and supporting documentation. …”
  3. 103

    Probabilistic-QSR-GeoQA by Mohammad Kazemi (19442467)

    Published 2024
    “…</p><p dir="ltr">- mln: Markov Logic Network (MLN) implementation of point-based CDC and region-based RCC relations required as input for Probcog and SparQ reasoners (This obtained from the study of [Duckham, M., Gabela, J., Kealy, A., Kyprianou, R., Legg, J., Moran, B., Rumi, S. …”
  4. 104

    A Fully Configurable Open-Source Software-Defined Digital Quantized Spiking Neural Core Architecture by Nagarajan Kandasamy (8400168)

    Published 2025
    “…QUANTISENC’s software-defined hardware design methodology allows the user to train an SNN model using Python and evaluate performance of its hardware implementation, such as area, power, latency, and throughput. …”
  5. 105

    Genomic Surveillance of Pemivibart (VYD2311) Escape-Associated Mutations in SARS-CoV-2: December 2025 BioSamples (n=2) by Tahir Bhatti (20961974)

    Published 2025
    “…The samples (SRR36268464, SRR36225071) were retrieved from the NCBI Sequence Read Archive (SRA) and represent publicly available, real-world viral specimens collected during the final month of 2025, <b>the most recent temporal window available at the time of analysis.…”
  6. 106

    Accompanying data files (Melbourne, Washington DC, Singapore, and NYC-Manhattan) by Winston Yap (13771969)

    Published 2025
    “…</p><p dir="ltr">Each zipped folder consists the following files:</p><ul><li>Graph data - City object nodes (.parquet) and COO format edges (.txt)</li><li>predictions.txt (model predictions from GraphSAGE model)</li><li>final_energy.parquet (Compiled training and validation building energy data)</li></ul><p dir="ltr">The provided files are supplementary to the code repository which provides Python notebooks stepping through the data preprocessing, GNN training, and satellite imagery download processes. …”
  7. 107

    Void-Center Galaxies and the Gravity of Probability Framework: Pre-DESI Consistency with VGS 12 and NGC 6789 by Jordan Waters (21620558)

    Published 2025
    “…<br><br><br><b>ORCID ID: https://orcid.org/0009-0009-0793-8089</b><br></p><p dir="ltr"><b>Code Availability:</b></p><p dir="ltr"><b>All Python tools used for GoP simulations and predictions are available at:</b></p><p dir="ltr"><b>https://github.com/Jwaters290/GoP-Probabilistic-Curvature</b><br><br>The Gravity of Probability framework is implemented in this public Python codebase that reproduces all published GoP predictions from preexisting DESI data, using a single fixed set of global parameters. …”
  8. 108

    Contrast enhancement of digital images using dragonfly algorithm by Soumyajit Saha (19726163)

    Published 2024
    “…The Python implementation of the proposed approach is available in this <a href="https://github.com/somnath796/DA_contrast_enhancement" target="_blank">Github repository</a>.…”
  9. 109

    Compiled Global Dataset on Digital Business Model Research by Dimas Fauzan Aryadefa (22123186)

    Published 2025
    “…</p><p dir="ltr">For the modeling component, annual publication growth is projected from 2025–2034 using a logistic growth model (S-curve) implemented in Python. …”
  10. 110

    The artifacts and data for the paper "DD4AV: Detecting Atomicity Violations in Interrupt-Driven Programs with Guided Concolic Execution and Filtering" (OOPSLA 2025) by zixuan yuan (17602152)

    Published 2025
    “…</p><pre><pre>sudo apt-get install -y wget git build-essential python3 python python-pip python3-pip tmux cmake libtool libtool-bin automake autoconf autotools-dev m4 autopoint libboost-dev help2man gnulib bison flex texinfo zlib1g-dev libexpat1-dev libfreetype6 libfreetype6-dev libbz2-dev liblzo2-dev libtinfo-dev libssl-dev pkg-config libswscale-dev libarchive-dev liblzma-dev liblz4-dev doxygen libncurses5 vim intltool gcc-multilib sudo --fix-missing<br></pre></pre><pre><pre>pip install numpy && pip3 install numpy && pip3 install sysv_ipc<br></pre></pre><h4><b>Download the Code</b></h4><p dir="ltr">Download <b>DD4AV</b> from the Figshare website to your local machine and navigate to the project directory:</p><pre><pre>cd DD4AV<br></pre></pre><h4><b>Configure Environment and Install the Tool</b></h4><p dir="ltr">For convenience, we provide shell scripts to automate the installation process. …”
  11. 111

    Elements: Streaming Molecular Dynamics Simulation Trajectories for Direct Analysis – Applications to Sub-Picosecond Dynamics in Microsecond Simulations by Matthias Heyden (17087794)

    Published 2025
    “…This eliminates the need for intermediate storage and allows immediate access to high-frequency fluctuations and vibrational signatures that would otherwise be inaccessible. We have implemented this streaming interface in the MD engines NAMD, LAMMPS, and GROMACS</p><p dir="ltr">On the client side, we developed the IMDClient Python package which receives the streamed data, stores into a custom buffer, and provides it to external tools as NumPy arrays, facilitating integration with scientific computing workflows. …”
  12. 112

    Bayesian Changepoint Detection via Logistic Regression and the Topological Analysis of Image Series by Andrew M. Thomas (712104)

    Published 2025
    “…The method also successfully recovers the location and nature of changes in more traditional changepoint tasks. An implementation of our method is available in the Python package bclr.…”
  13. 113

    ReaxANA: Analysis of Reactive Dynamics Trajectories for Reaction Network Generation by Hong Zhu (109912)

    Published 2025
    “…To address this challenge, we introduce a graph algorithm-based explicit denoising approach that defines user-controlled operations for removing oscillatory reaction patterns, including combination and separation, isomerization, and node contraction. This algorithm is implemented in ReaxANA, a parallel Python package designed to extract reaction mechanisms from both heterogeneous and homogeneous reactive MD trajectories. …”
  14. 114

    ReaxANA: Analysis of Reactive Dynamics Trajectories for Reaction Network Generation by Hong Zhu (109912)

    Published 2025
    “…To address this challenge, we introduce a graph algorithm-based explicit denoising approach that defines user-controlled operations for removing oscillatory reaction patterns, including combination and separation, isomerization, and node contraction. This algorithm is implemented in ReaxANA, a parallel Python package designed to extract reaction mechanisms from both heterogeneous and homogeneous reactive MD trajectories. …”
  15. 115

    High-Throughput Mass Spectral Library Searching of Small Molecules in R with NIST MSPepSearch by Andrey Samokhin (20282728)

    Published 2025
    “…High-level programming languages such as Python and R are widely used in mass spectrometry data processing, where library searching is a standard step. …”
  16. 116

    Cathode carbon block material parameters [14]. by Chenglong Gong (20629836)

    Published 2025
    “…A random aggregate model was implemented in Python and imported into finite element software to simulate sodium diffusion using Fick’s second law. …”
  17. 117

    Sodium concentration distribution cloud map. by Chenglong Gong (20629836)

    Published 2025
    “…A random aggregate model was implemented in Python and imported into finite element software to simulate sodium diffusion using Fick’s second law. …”
  18. 118

    Sodium binding coefficient R. by Chenglong Gong (20629836)

    Published 2025
    “…A random aggregate model was implemented in Python and imported into finite element software to simulate sodium diffusion using Fick’s second law. …”
  19. 119

    HCC Evaluation Dataset and Results by Jens-Rene Giesen (18461928)

    Published 2024
    “…<p dir="ltr">This archive contains the evaluation data we produced during the evaluation of our prototype implementation of HCC from our paper <i>HCC: A Language-Independent Hardening Contract Compiler for Smart Contracts</i>.…”
  20. 120

    MCCN Case Study 3 - Select optimal survey locality by Donald Hobern (21435904)

    Published 2025
    “…</p><p dir="ltr">This is a simple implementation that uses four environmental attributes imported for all Australia (or a subset like NSW) at a moderate grid scale:</p><ol><li>Digital soil maps for key soil properties over New South Wales, version 2.0 - SEED - see <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html" target="_blank">https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html</a></li><li>ANUCLIM Annual Mean Rainfall raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer</a></li><li>ANUCLIM Annual Mean Temperature raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer</a></li></ol><h4><b>Dependencies</b></h4><ul><li>This notebook requires Python 3.10 or higher</li><li>Install relevant Python libraries with: <b>pip install mccn-engine rocrate</b></li><li>Installing mccn-engine will install other dependencies</li></ul><h4><b>Overview</b></h4><ol><li>Generate STAC metadata for layers from predefined configuratiion</li><li>Load data cube and exclude nodata values</li><li>Scale all variables to a 0.0-1.0 range</li><li>Select four layers for comparison (soil organic carbon 0-30 cm, soil pH 0-30 cm, mean annual rainfall, mean annual temperature)</li><li>Select 10 random points within NSW</li><li>Generate 10 new layers representing standardised environmental distance between one of the selected points and all other points in NSW</li><li>For every point in NSW, find the lowest environmental distance to any of the selected points</li><li>Select the point in NSW that has the highest value for the lowest environmental distance to any selected point - this is the most different point</li><li>Clean up and save results to RO-Crate</li></ol><p><br></p>…”