Comparison data 6 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

“…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”

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)

“…</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. …”

Comprehensive Fluid and Gravitational Dynamics Script for General Symbolic Navier-Stokes Calculations and Validation by Stylianos Touloumidis (19938747)

“…It provides a flexible foundation on which theoretical assumptions can be validated, and practical calculations performed. Implemented in Python with symbolic calculations, the script facilitates in-depth analysis of complex flow patterns and makes advanced mathematical computations more accessible. …”

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

“…</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>…”

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

“…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.…”

Table 1_Analysis of distribution equilibrium and influencing factors for older adult meal service facilities in mainland China.xlsx by Feng Wang (44414)

“…Objective<p>Analyze the distribution equilibrium of older adult meal service facilities in mainland China and explore the factors influencing their distribution.</p>Methods<p>Use Python to obtain data on older adult meal service facilities, and analyze the equity of older adult meal services using descriptive statistics, the Lorenz curve, the Gini coefficient, and the Spatial Mismatch Index (SMI). …”

Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

“…<p dir="ltr">Spatially Offset Raman Spectroscopy (SORS) has emerged as a potential tool for non-invasive biomedical diagnostics, enabling molecularly specific probing of subsurface tissues. …”

Methodological Approach Based on Structural Parameters, Vibrational Frequencies, and MMFF94 Bond Charge Increments for Platinum-Based Compounds by Gloria Castañeda-Valencia (20758502)

“…The developed bci optimization tool, based on MMFF94, was implemented using a Python code made available at https://github.com/molmodcs/bci_solver. …”

Table 3_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

“…</p>Conclusions<p>This study demonstrates that integrating deep learning with multi-sequence breast MRI and clinical data provides a highly effective and reliable tool for predicting HER2 expression in breast cancer. …”

Table 2_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

“…</p>Conclusions<p>This study demonstrates that integrating deep learning with multi-sequence breast MRI and clinical data provides a highly effective and reliable tool for predicting HER2 expression in breast cancer. …”

Table 1_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

“…</p>Conclusions<p>This study demonstrates that integrating deep learning with multi-sequence breast MRI and clinical data provides a highly effective and reliable tool for predicting HER2 expression in breast cancer. …”

Data Sheet 1_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx by Shi Qiu (425335)

“…</p>Conclusions<p>This study demonstrates that integrating deep learning with multi-sequence breast MRI and clinical data provides a highly effective and reliable tool for predicting HER2 expression in breast cancer. …”

World Heritage documents reveal persistent gaps between climate awareness and local action by Yang Chen (20756166)

“…The analysis section includes a GLM model implemented in R, along with evaluation tools such as correlation heatmaps, ICC agreement analysis, and MCC-based binary classification assessment. …”

Advancing Solar Magnetic Field Modeling by Carlos António (21257432)

“…<br><br>We developed a significantly faster Python code built upon a functional optimization framework previously proposed and implemented by our team. …”

Knowledge Graph validation using SHACL Shapes by Ángel Iglesias Préstamo (19745767)

“…Leveraging Rust’s performance and safety features, rudof provides efficient validation tools and Python bindings for integration with data science workflows. …”

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

“…The pipeline integrates established open-source tools (fastp, BWA-MEM, samtools, iVar, bcftools) and implements <b>codon-aware mutation calling</b> at five canonical RBD positions (R346, S371, K444, F456, F486) relative to NC_045512.2. …”

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

“…<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. …”

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

“…Comparisons with state-of-art methods ensure the superiority of the proposed algorithm. 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>.…”

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

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

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

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