Finites differences python code to solve CH equation with a source term and Comsol routine to solve Brusselator equation in radial domains. by Giulio Facchini (9031490)

“…<p dir="ltr"><b><i>* Cahn-Hilliard simulations *</i></b><br>Finite difference code implementing the modified Cahn Hilliard equation with a forward Euler scheme and the possibility to parallelize the solver using the numba python library.…”

Supplementary material for the paper "Conditional simulation of spatial rainfall fields using random mixing: a study that implements full control over the stochastic process". by Jieru Yan (7825607)

“…The Python script specsim_simple.py applies the method -- fast Fourier transform for regular grids -- to generate correlated Gaussian random fields. …”

Supplementary information files for When randomisation is not good enough: Matching groups in intervention studies by Francesco Sella (8391642)

“…We provide an Excel spreadsheet, as well as scripts in R, MATLAB, and Python to ease and foster the implementation of the VM procedure.…”

Data and some code used in the paper:<b>Expansion quantization network: A micro-emotion detection and annotation framework</b> by Zhou (20184816)

“…Create a directory named "28pd" to place the .csv format data files to be labeled or predicted.</p>…”

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>…”

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)

“…</li><li><code><strong>wllvm</strong></code>: The third-party library project WLLVM provides tools for building whole-program LLVM bitcode files from unmodified C or C++ source packages.</li></ul></li><li><code><strong>test</strong></code>: A few simple examples that are easy to understand and can be used to verify the installation.…”

Ambient Air Pollutant Dynamics (2010–2025) and the Exceptional Winter 2016–17 Pollution Episode: Implications for a Uranium/Arsenic Exposure Event by Thomas Clemens Carmine (19756929)

“…The full implementation is detailed in the accompanying Python script (Imputation_Air_Pollutants_NABEL.py). …”