Secure Python Code Manager: A Tool for Protected Python Code Distribution and Management by Pavel Izosimov (20096259)

“…</li><li><b>Commercial Distribution</b>: Safely share Python code with clients or customers, implementing advanced <b>Python code protection tools</b> for sales or rentals.…”

Comparison of BlueRecording with existing tools by Joseph James Tharayil (21416715)

“…<div><p>As the size and complexity of network simulations accessible to computational neuroscience grows, new avenues open for research into extracellularly recorded electric signals. …”

Exploring the integration of metaverse technologies in engineering education through the SAMR model by Snezhana Dineva (22444471)

“…It demonstrates the successful implementation of the model in practice and provides examples of effective practices in the context of the CAVE (Cave Automatic Virtual Environment) metaverse. …”

Simple implementation examples of agent AI on free energy calculation and phase-field simulation by Toshiyuki Koyama (22828581)

“…</p> <p>Using Gibbs energy calculations and diffusion simulations as examples, we demonstrated the implementation method and usefulness of simple agent AI, where sample python codes are distributed as supplemental materials.…”

Memory monitoring recognition test workflow. by Pedro C. Martínez-Suárez (21192459)

“…The computerization of technical resources that allow the monitoring of reality offers a new tool to evaluate the attribution process, in an effective and agile way and with easy understanding of cognitive deficits in a friendly environment.…”

Voice recognition workflow. by Pedro C. Martínez-Suárez (21192459)

“…The computerization of technical resources that allow the monitoring of reality offers a new tool to evaluate the attribution process, in an effective and agile way and with easy understanding of cognitive deficits in a friendly environment.…”

Memory monitoring recognition test main screen. by Pedro C. Martínez-Suárez (21192459)

“…The computerization of technical resources that allow the monitoring of reality offers a new tool to evaluate the attribution process, in an effective and agile way and with easy understanding of cognitive deficits in a friendly environment.…”

Task descriptions. by Pedro C. Martínez-Suárez (21192459)

“…The computerization of technical resources that allow the monitoring of reality offers a new tool to evaluate the attribution process, in an effective and agile way and with easy understanding of cognitive deficits in a friendly environment.…”

The format of the electrode csv file by Joseph James Tharayil (21416715)

“…<div><p>As the size and complexity of network simulations accessible to computational neuroscience grows, new avenues open for research into extracellularly recorded electric signals. …”

The format of the simulation reports by Joseph James Tharayil (21416715)

“…<div><p>As the size and complexity of network simulations accessible to computational neuroscience grows, new avenues open for research into extracellularly recorded electric signals. …”

The format of the weights file by Joseph James Tharayil (21416715)

“…<div><p>As the size and complexity of network simulations accessible to computational neuroscience grows, new avenues open for research into extracellularly recorded electric signals. …”

Genosophus: A Dynamical-Systems Diagnostic Engine for Neural Representation Analysis by Alan Glanz (22109698)

“…</b><code><strong>GenosophusV2.py</strong></code></h3><p dir="ltr">Executable Python implementation of the Genosophus Engine.</p><h3><b>2. …”

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)

“…Run the following commands to configure the environment and install the necessary tools:</p><pre><p dir="ltr"><i># Install LLVM and clang</i><br>tool/install_llvm.sh<br><br><i># Set up the environment</i><br>source tool/init_env.sh<br><br><i># Install SVF</i><br>$ROOT_DIR/tool/install_SVF.sh<br><br><i># Install the static analysis tool</i><br>$ROOT_DIR/tool/install_staticAnalysis.sh<br><br><i># Install wllvm</i><br>sudo pip install -e $ROOT_DIR/tool/wllvm/<br></p></pre><h4><b>Note</b></h4><p dir="ltr">Each time you open a new terminal, you will need to set the environment variables to ensure proper execution of the tool:</p><pre><pre><i># set up environment</i><br>source tool/init_env.sh</pre></pre><h2><b>Quick Start for Simple Test</b></h2><p dir="ltr">Before using DD4AV, we recommend starting with the simple examples provided to ensure that the tool functions correctly. …”

Globus Compute: Federated FaaS for Integrated Research Solutions by eRNZ Admin (6438486)

“…</p><p dir="ltr">Globus Compute [2] is a Function-as-a-Service platform designed to provide a scalable, secure, and simple interface to HPC resources. Globus Compute implements a federated model via which users may deploy endpoints on arbitrary remote computers, from the edge to high performance computing (HPC) cluster, and they may then invoke Python functions on those endpoints via a reliable cloud-hosted service. …”

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>…”

Fast, FAIR, and Scalable: Managing Big Data in HPC with Zarr by Alfonso Ladino (21447002)

“…(NEXRAD), using open-source tools from the Python ecosystem such as Xarray, Xradar, and Dask to enable efficient parallel processing and scalable analysis. …”

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. …”

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

“…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. …”

Code by Baoqiang Chen (21099509)

“…DynaRDS (MRD-diff) was calculated by subtracting the old mRNA MRD from the new mRNA MRD. Similarly, DynaRDS (AUC-diff) was calculated by subtracting the old mRNA AUC from the new mRNA AUC, for both gene-level and isoform-level analyses.…”

Core data by Baoqiang Chen (21099509)

“…DynaRDS (MRD-diff) was calculated by subtracting the old mRNA MRD from the new mRNA MRD. Similarly, DynaRDS (AUC-diff) was calculated by subtracting the old mRNA AUC from the new mRNA AUC, for both gene-level and isoform-level analyses.…”