MsipNet by Nan Song (22280815)

“…<h2><b>MsipNet</b></h2><p dir="ltr">This is a directory for storing the **MsipNet** model code and data. **MsipNet** is a multi-scale representation learning framework for predicting protein-RNA interactions.…”

The Transcriptional Gradient in Negative-Strand RNA Viruses Suggest a Common RNA Transcription Mechanism: Model by Jean Peccoud (275555)

“…</p><p dir="ltr">Notebook2 contains the python code for making predictions of transcriptional gradients for gene-shuffled variants.…”

SI files for "Addressing Hemolysis-Induced Loss of Sensitivity in Lateral Flow Assays of Blood Samples with Platinum-Coated Gold Nanoparticles and Machine Learning" by An Le (20473628)

“…</p><p dir="ltr">2) Model_testing.ipynb: Jupyter Notebook containing Python code for generate predictions for the 112 test strips</p><p dir="ltr">3) Best_model.keras: The final optimized machine learning model saved in Keras format.…”

ncRNA.zip by Chongyi Jiang (20987126)

“…<h3><b>ncRNA (non-coding RNA) </b><b>predicted by</b><b> CPC2 (v 0.1) and PINC for 25 </b><b>grassland plant species.…”

DCPR_V1.0 by xiao han (21405770)

“…</p><p dir="ltr"><b>DCPR_codes</b>: Source code for DCPR model.</p><p dir="ltr"><b>Visualization</b>: Scripts for data visualization, including circadian curves (cosine model fitting), sample plots (predicted and real time), model performance (CDF curves, and accuracy plots).…”

<b>Rethinking neighbourhood boundaries for urban planning: A data-driven framework for perception-based delineation</b> by Shubham Pawar (22471285)

“…</p><p dir="ltr"><b>Input:</b></p><ul><li><code>raw_data/glasgow_open_built/glasgow_open_built_areas.shp</code> - Grid defining sampling points</li></ul><p dir="ltr"><b>Command:</b></p><pre><pre>python svi_module/get_svi_data.py<br></pre></pre><p dir="ltr"><b>Output:</b></p><ul><li><code>svi_module/svi_data/svi_info.csv</code> - Image metadata (IDs, coordinates)</li><li><code>svi_module/svi_data/images/</code> - Downloaded street view images</li></ul><h3>Step 2: Predict Perceptions</h3><p dir="ltr">Use pre-trained deep learning models to predict perceptual qualities (safety, beauty, liveliness, etc.) from street view images.…”

Synthetic Mental Health Survey Dataset by Shakil Hossain (22546658)

“…Data were generated using Python code to simulate realistic patterns and scoring based on psychological constructs.This dataset was to develop a machine learning model for predicting severity of multiple mental health disorders & overall Mental Health Status based on survey responses and psychological features.…”

Monte Carlo Simulation for SAPAL Framework: AI-Augmented CI/CD Reliability by Rohit Dhawan (22457026)

“…</p><p dir="ltr">Files included: <br>- simulation.py: Python simulation code <br>- README.md: Complete documentation and methodology <br><br>This code supports the paper "AI-Augmented Reliability in Continuous Integration and Deployment: A Conceptual Framework for Predictive, Adaptive, and Self-Correcting Pipelines".…”

<b>Antibiotics in the Global River System Arising from Human Consumption</b> by Heloisa Ehalt Macedo (10319300)

“…</p><p dir="ltr">The data repository includes 3 datasets:</p><p dir="ltr">1. Python code: python project repository including the structure necessary for the model to run.…”

<b>Effects of Lifestyle and GLP-1RA based Interventions on Waist Circumference: A Systematic Review and Meta-Analysis</b> by Samit Ghosal (22024556)

“…</li><li><b>R scripts (00–06)</b> — reproducible code for primary, sensitivity, subgroup, and meta-regression analyses, forest plots, funnel plots, ROB2 templates, and prediction intervals.…”

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

“…Each folder contains the training and validation data, graph adjacency information, compiled reported energy consumption data for each city, and generated predictions.</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. …”

LGF v11 Final Archive: EWL, GMMI, LGF-EWI Metrics and Language Spacetime Specification (Dec 2025) by heojeongbeom heo (22544705)

“…This was confirmed by the final $\mathbf{\Psi}$ Operator simulation: the Python code returned <b>$\text{nan}$</b><b> (Not a Number)</b> due to the runaway divergence of the Language Potential ($\mathbf{\Phi_L}$), serving as the <b>computational proof of the </b><b>$\mathbf{T=0}$</b><b> structural failure.…”

Leveraging explainable causal artificial intelligence to study forest gross primary productivity dynamics in China's protected areas by Pedro Cabral (18947566)

“…<p dir="ltr">A Python script used for modeling forest GPP in China´s Protected Areas, including mean encoding of the categorical variable climate zone (CZ), multicollinearity testing using Variance Inflation Factor (VIF), implementation of four machine learning models to predict forest GPP, XAI and causality analysis.…”

Seattle Demo Accompanying Files by Winston Yap (13771969)

“…<p dir="ltr">We release the data, code, and prepared city graph objects to facilitate city scale building operating energy prediction with Seattle as a case study. …”

IGD-cyberbullying-detection-AI by Bryan James (19921044)

“…</p><h2>Requirements</h2><p dir="ltr">To run this code, you'll need the following dependencies:</p><ul><li>Python 3.x</li><li>TensorFlow</li><li>scikit-learn</li><li>pandas</li><li>numpy</li><li>matplotlib</li><li>imbalanced-learn</li></ul><p dir="ltr">You can install the required dependencies using the provided <code>requirements.txt</code> file.…”

Harmonic Shell Structures in MaDCoWS2 Clusters: Empirical Validation of Oscillatory Field Genesis (OFG) by Drippy Stone (21218843)

“…Analyzing 22,971 galaxy clusters from MaDCoWS2 DR2, we demonstrate: - **Harmonic shell spacings** (λ = 2π/|∇Φ·∇Θ|) in high-z clusters (z ≥ 1.5) - **Phase-locked redshift distributions** via Lomb-Scargle periodograms - **Predictive templates** for LSST void lensing (Δκ ≥ 0.5) and SPHEREx spectral harmonics Includes: - Cluster spacing histograms (`Cluster_Spacing_Histogram.csv`) - Redshift-phase coherence data (`theta_oscillation_peaks.csv`) - High-z cluster catalog (`High-Redshift_Cluster_z.csv`) - Full analysis code (Python/Jupyter) </p><p><br></p><p><br></p><p dir="ltr">Related Publications**: - Gonzalez et al. (2024) MaDCoWS2 DR2 Catalog (ApJ, 967, 123) - OFG Theoretical Framework (J.D.S. 2025, DeepSeek-verified) - **Tools Required**: Python 3.10+, NumPy, Pandas, Astropy - **Experiment Type**: Observational/Cosmological Simulation </p>…”

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

“…</p><h2><b>Included Files</b></h2><h3><b>1. </b><code><strong>GenosophusV2.py</strong></code></h3><p dir="ltr">Executable Python implementation of the Genosophus Engine.…”

<b>MSLU-100K: A multi-source land use dataset of Chinese major cities</b> by Yao Yao (7903457)

“…</li><li>The Manual Filtering.py-Based Multilevel Model Classification Method includes code to perform multilevel model predictions.</li></ul><h3>5.requirements.txt</h3><ul><li>Lists environment configurations and version specifications, including Python 3.7 and Pytorch 2.2.…”

Bayesian Neural Network-Based Ground Motion Model for Horizontal and V/H spectral ordinate with Epistemic Uncertainty for the European Region by jyothi yedulla (18319545)

“…<p dir="ltr">The Python code provides the computation of 100 predictions using the proposed BNN model for the given input parameters which includes Moment magnitude (M_w), Joyner-Boore distance (R_JB), Shear wave velocity (V_s30), focal depth (d) and focal mechanism.…”

LNP drug delivery image data by Philip Harrison (8899735)

“…</div><div><br></div><div><u>Python code:</u></div><div><a href="https://github.com/pharmbio/phil_LNP_modelling">https://github.com/pharmbio/phil_LNP_modelling</a><br></div><div><br></div><div><br></div><div><br></div><div><br></div><div><br></div><p></p>…”