Computing speed and memory usage. by David Berling (22170661)

“…Computing time increases with increasing volume along radial (solid blue) and depth direction (dashed orange) with different slope. Original model computation time is marked with a red cross and was simulated in the same spatial volume as the first data point of the replicated model. …”

Smart contract and interface code for Nature Energy "A general form of smart contract for decentralised energy systems management" by Lee Thomas (19655773)

“…This provides the modelled electricity network cost data, the smart contract code, and the Python interface scripts described in the Nature Energy Paper  "A general form of smart contract for decentralised energy systems management." …”

Replication package for Exploring the relation between source code commit information and SonarQube issues by Liviu Marian Berciu (17797934)

Global Research Dataset on Social Media in Entrepreneurial Startup (2009–2024) by Lucky Ario (22115884)

“…Analytical outputs are organized into multiple formats: CSV files for raw bibliometric data; PNG images for thematic maps, trend topic visualizations, and research flowcharts; and CSV and PNG outputs for annual publication trajectories and polynomial regression-based modeling projections. Visualization and analysis were conducted using Microsoft Excel for summary statistics, R Biblioshiny for thematic and trend mapping, and Python for projection modeling.…”

Data Sheet 1_Establishing a real-time biomarker-to-LLM interface: a modular pipeline for HRV signal acquisition, processing, and physiological state interpretation via generative A... by Morris Gellisch (18627744)

“…</p>Discussion<p>This system represents an early prototype of bioadaptive AI, in which physiological signals are incorporated as part of the model's input context.…”

Performance Benchmark: SBMLNetwork vs. SBMLDiagrams Auto-layout. by Adel Heydarabadipour (22290905)

“…<p>Log–log plot of median wall-clock time for SBMLNetwork’s C++-based auto-layout engine (blue circles, solid fit) and SBMLDiagrams’ implementation of the pure-Python NetworkX spring_layout algorithm (red squares, dashed fit), applied to synthetic SBML models containing 20–2,000 species, with a fixed 4:1 species-to-reaction ratio. …”

MYCroplanters can quantify the interaction between pathogenic and non-pathogenic bacteria and their effects on plant health. by Melissa Y. Chen (11301882)

“…(e) Figure showing data from (d) converted into binary health/disease scores. Each dot represents a single plant. Black lines with ribbons are Bayesian model predictions with 95% prediction intervals, respectively. …”

GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios by Yang Lan (20927512)

“…Here, <i>Genus</i> represents the rodent genus, <i>GCM</i> denotes the global climate model used, <i>Year</i> specifies the projected time period, <i>SSP-RCP</i> indicates the shared socioeconomic pathway and representative concentration pathway, and <i>Statistics</i> describes the file’s data characteristics. …”

Interleg coordination in 103 adult <i>Hypsibius exemplaris</i> individuals. by Emma M. Anderson (19697573)

Overview of generalized weighted averages. by Nobuhito Manome (8882084)

“…GWA-UCB1 outperformed G-UCB1, UCB1-Tuned, and Thompson sampling in most problem settings and can be useful in many situations. The code is available at <a href="https://github.com/manome/python-mab" target="_blank">https://github.com/manome/python-mab</a>.…”

<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) by Erola Fenollosa (20977421)

“…In total, 75 % of the labelled observations were assigned to train and 25 % to test the model. To evaluate the model performance, the root mean squared root error (RMSE, the standard deviation of the residuals that represents the mean difference between the prediction and the real value for the test set) and <i>R</i>² were used, which was calculated using r2_score() from <i>Scikit-learn</i> metrics. …”

Related to Figs 1, 2 and S1. by Tyron Chang (9922533)

Overview of deep learning terminology. by Aaron E. Maxwell (8840882)

“…This paper introduces the geodl R package, which supports pixel-level classification applied to a wide range of geospatial or Earth science data that can be represented as multidimensional arrays where each channel or band holds a predictor variable. geodl is built on the torch package, which supports the implementation of DL using the R and C++ languages without the need for installing a Python/PyTorch environment. …”

R codes and curated dataset for “EnoLEX: A Diachronic Lexical Database for the Enggano Language” by Gede Primahadi Wijaya Rajeg (14592023)

Artifact for the IJCAI 2024 paper "Solving Long-run Average Reward Robust MDPs via Stochastic Games" by Krishnendu Chatterjee (15367413)

“…<br></pre></pre><h2>Structure and How to run</h2><p dir="ltr">There are four Python files in the repository.</p><pre><pre>(i) `StrategyIteration.py` is the backend code, containing the implementation of the RPPI algorithm described in the paper.…”

<b>Anthropogenic nutrient inputs cause excessive algal growth for nearly half the world’s population</b> by Richard McDowell (7311011)

“…<p dir="ltr">Contains</p><p dir="ltr">Final Analysis Output.xlsx: Current and reference concentrations of DRP, TP, NO3-N and TN along with pivot table analysis</p><p dir="ltr">Code: Python code used to implement the model in ArcGIS Pro.…”

A Hybrid Ensemble-Based Parallel Learning Framework for Multi-Omics Data Integration and Cancer Subtype Classification by Mohammed Nasser Al-Andoli (21431681)

“…<p dir="ltr">The code supports replication of results on TCGA Pan-cancer and BRCA datasets and includes data preprocessing, model training, and evaluation scripts:<br>Python scripts for data preprocessing and integration</p><ul><li>Autoencoder implementation for multimodal feature learning</li><li>Hybrid ensemble training code (DL/ML models and meta-learner)</li><li>PSO and backpropagation hybrid optimization code</li><li>Parallel execution scripts</li><li>Instructions for replicating results on TCGA Pan-cancer and BRCA datasets</li></ul><p></p>…”

<b>Algorithm Pseudocode</b> by Yibin Zhao (22425801)

“…The model generates point forecasts and forecast interval boundaries for short-term loads, providing important support for risk quantification and decision-making in power systems. The pseudo-code follows standard Python syntax specifications for functions and loops and is easy to understand and implement. …”

<b>Anonymous, runnable artifact for </b><b>Testing AI Applications Under Nondeterminism, Drift, and Resource Constraints: A Problem‑Driven Multi‑Layer Approach</b> by Nariman Mani (21380459)

“…</b> The anonymized archive includes a dependency‑free Python implementation of all five layers (oracle, coverage, drift mapping, prioritization, resource scheduling), an orchestrator, and synthetic datasets with 50 test cases per sub‑application (LLM assistant, retrieval with citation, vision calories, notification/social). …”

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

“…The only requirement for running this script is a Python 3.6+ interpreter as well as an installation of the <code>numpy</code> package. …”