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>.…”

Minami_etal_2025 by Keiichi Mochida (4670800)

“…<h2>Code files related to Minami et al (2025)</h2><p dir="ltr">accession_plot.py:Python script used to generate Fig4a.…”

Satellite monitoring of Greenland wintertime buried lake drainage by Jianing Wei (22400896)

“…Buried_lake_drainage_code</p><p dir="ltr">This folder contains two Python Jupyter Notebooks for detecting wintertime buried lake drainages (BLDs). …”

JASPEX model by Olugbenga OLUWAGBEMI (21403187)

“…</p><p dir="ltr">We wrote new sets of python codes and developed python programming codes to rework on the map to generate the coloured map of Southwest Nigeria from the map of Nigeria (which represented the region of our study). …”

CNG-ARCO-RADAR.pdf by Alfonso Ladino (21447002)

“…This approach uses a suite of Python libraries, including Xarray (Xarray-Datatree), Xradar, and Zarr, to implement a hierarchical tree-like data model. …”

Multisession fNIRS-EEG data of Post-Stroke Motor Recovery: Recordings During Intact and Paretic Hand Movements by Aleksandra Medvedeva (21221383)

“…The fNIRS .snirf files are accompanied by event files as .txt tables, containing arrays of event timestamps and corresponding event codes. The code for signal reading, preprocessing, and epoching is provided with the dataset in the “Preprocessing” file. …”

GeoGraphNetworks: Shapefile-Derived Datasets for Accurate and Scalable Graphical Representations by Harish Sharma (18881935)

“…<br></p><p dir="ltr">Visual representation of each network along with the code to use these networks (in Notebooks) are hosted on the Github Profile: <a href="https://github.com/Harsh9650/GeoGraphNetworks" rel="noreferrer" target="_blank">https://github.com/Harsh9650/GeoGraphNetworks</a></p>…”

Building footprtints from 1970s Hexagon spy satellite images for four global urban growth hotspots by Franz Schug (10165159)

“…</p> <p><strong>Processing environment</strong></p> <p>This research has been conducted using Python for ESRI ArcGIS Pro version 3.2.1 and the TensorFlow package. …”

<b>Dataset for manuscript: </b><b>Phylogenetic and genomic insights into the evolution of terpenoid biosynthesis genes in diverse plant lineages</b> by Puguang Zhao (19023065)

“…</p><p dir="ltr"> 'boxplot.py': This script is executed in Visual Studio Code, using Python 3.10.4 as the runtime environment.…”

(A) Sampling locations and ranges of <i>I. feisthamelii</i> (purple) and <i>I. podalirius</i> (teal) butterflies. by Sam Ebdon (21072525)

“…(B) Sampling locations of butterflies from the <i>Iphiclides</i> HZ. The dashed line represents the approximate HZ center, based on samples collected by Lafranchis et al. …”

Iterative Methods for Vecchia-Laplace Approximations for Latent Gaussian Process Models by Pascal Kündig (19824557)

“…All methods are implemented in a free C++ software library with high-level Python and R packages. …”

Oka et al., Supplementary Data for "Development of a battery emulator using deep learning model to predict the charge–discharge voltage profile of lithium-ion batteries" by Kanato Oka (20132185)

“…(<b>DOI:</b> 10.1038/s41598-024-80371-9 )<br><br>A zip file contains following data and codes.</p><p dir="ltr"><br></p><p dir="ltr">01_lstm_model_making.py</p><p dir="ltr">This file is a Python script for reading battery charge-discharge data and training an LSTM model. …”

Data&Codes.zip by Zer0 Star (20545655)

“…</p><p dir="ltr">To facilitate the widespread use of the proposed framework, we have implemented it as the <b><i>ESLocalIndi</i></b> open-source package in Python, making it easily accessible to geographers. …”

Supplementary file 1_ParaDeep: sequence-based deep learning for residue-level paratope prediction using chain-aware BiLSTM-CNN models.docx by Piyachat Udomwong (22563212)

“…The implementation is freely available at https://github.com/PiyachatU/ParaDeep, with Python (PyTorch) code and a Google Colab interface for ease of use.…”

Bacterial persistence modulates the speed, magnitude and onset of antibiotic resistance evolution by Giorgio Boccarella (22810952)

“…This file can be used together with the analysis code (link to be added upon publication) to generate all figures.…”

<b>Engineered Muscle-Derived Extracellular Vesicles Boost Insulin Sensitivity and Glucose Regulation</b> by Hagit Shoyhet (21090650)

“…</p><p dir="ltr"><b>miR_path_target_enrichment.csv</b></p><p dir="ltr"><b>Description:</b> KEGG pathway enrichment analysis results of shared mRNA targets of miRNAs miR-16-5p, miR-122-5p and miR-486-5p ranked by their interaction score defined in our paper. this includes the pathway name, the enrichment p-value, number of genes found in the term and number of miRNAs targeting these genes</p><p dir="ltr"><b>Code/software</b></p><p dir="ltr">Data were analyzed using R-V4.0.4, Python-V3.9.2 and GraphPad software. miRNA analyses were run in R-V4.0.4 Differential expression analysis was conducted using the “DEseq2” package and corrected for multiple hypotheses by FDR. …”

Tracking when the number of individuals in the video frame changes. by Hirotsugu Azechi (20700528)

“…The removal of unnecessary keypoint data is achieved through a Python code that allows specified ranges of tracking data obtained from DeepLabCut to be rewritten as NaN (no data) (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003002#pbio.3003002.s019" target="_blank">S1 Protocol</a> and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003002#pbio.3003002.s010" target="_blank">S10C Fig</a>). …”

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>…”

Data Sheet 1_Nationwide epidemiological study of subarachnoid hemorrhage: trends in admissions, mortality, seasonality, costs, clipping, embolization, and the impact of COVID-19.pd... by Thiago Oscar Goulart (22485604)

“…</p>Methods<p>This retrospective study analyzed secondary data from the Brazilian public health system (DataSUS) using ICD-10 code I60 for aSAH. Key metrics included the evaluation of admissions with time-series in Python, and mortality rates, procedures, and costs.…”

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>realworld_AV</strong></code>: 18 real-world embedded interrupt-driven programs, all written in C, including control software, firmware, and device drivers.…”