6. Motif Code Theory by William Terry (22279591)

“…<p dir="ltr">The Motif Code Theory (MCT) simulation code, mct_unified_code.py, is a Python 3.9 script that models the universe as a time-dependent directed multigraph G(t) = (V(t), E(t)) with N=10^7 vertices (representing quantum fields/particles) and edges (interactions). …”

Tracking module training details. by Khelina Fedorchuk (19130089)

Modeling lung cancer AST network and its perturbation with a SOX2 degrader. (A) Lung Cancer AST Network and the corresponding stochastic equations. Parameters are , , , , , , , , w... by Ziyan Jin (21021976)

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

“…Evaluation of the original model for different spatial volumes was not possible due to hard coding of these parameters in the published application. …”

Comparison of tools with features similar to <i>bmdrc,</i> and a descriptions of the modules within the <i>bmdrc</i> package.  by David J. Degnan (13886280)

“…The smaller boxes within the larger boxes represent individual functions within the <i><i>bmdrc</i></i> Python library.…”

CompuCrawl: Full database and code by Richard Haans (6324669)

“…</li><li><i>08 Word2Vec work with aligned models.py</i>: Python script which loads the trained Word2Vec models to trace the development of the embeddings for the terms “sustainability” and “profitability” over time.…”

Differences in compartment weights explain differences between EEG and ECoG. by Joseph James Tharayil (21416715)

Simplified calculation methods produce inaccurate signals. by Joseph James Tharayil (21416715)

BlueRecording simulates whisker-flick EEG. by Joseph James Tharayil (21416715)

BlueRecording simulates hippocampal LFP. by Joseph James Tharayil (21416715)

Output datasets from ML–assisted bibliometric workflow in African phytochemical metabolomics research by Temitope Omogbene (18615415)

“…<p dir="ltr">This collection contains supplementary datasets generated during the machine learning–assisted bibliometric workflow for metabolomics and phytochemical research. The datasets represent sequential outputs derived from the integration and harmonisation of bibliographic metadata from <b>Scopus</b>, <b>Web of Science (WoS)</b>, and <b>Dimensions</b>, processed via R and Python environments.…”

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

“…</p><p>Method</p><p>The MMRT was developed using Python and Kivy, facilitating the creation of cross-platform user interfaces. …”

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

“…</p><p>Method</p><p>The MMRT was developed using Python and Kivy, facilitating the creation of cross-platform user interfaces. …”

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

“…</p><p>Method</p><p>The MMRT was developed using Python and Kivy, facilitating the creation of cross-platform user interfaces. …”

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

“…</p><p>Method</p><p>The MMRT was developed using Python and Kivy, facilitating the creation of cross-platform user interfaces. …”

Catalogue of compact radio sources in Messier-82 from e-MERLIN observations by Sibongumusa Shungube (21197363)

“…Source finding was initially performed using Python Blob Detection and Source Finder (PyBDSF).</p><p dir="ltr">The dataset includes two tables detailing the properties of these 36 sources:</p><p dir="ltr"><b>Table 3.1: CASA </b><code><strong>imfit</strong></code><b> Source Catalogue</b></p><p dir="ltr">This table contains source parameters derived using the CASA task <code>imfit</code>. …”

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." …”

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.…”

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

“…</p><blockquote><b><i>EnoLEX</i></b><i> represents a network of independent research materials consisting of a </i><a href="https://doi.org/10.25446/oxford.28295648.v1" rel="noreferrer" target="_blank"><i>source dataset</i></a><i>, this repository of source R codes and the curated data, the </i><a href="https://enggano.shinyapps.io/enolex/" rel="noreferrer" target="_blank"><i>online database</i></a><i>, and a conference </i><a href="https://doi.org/10.25446/oxford.27013864.v1" rel="noreferrer" target="_blank"><i>paper</i></a><i>.…”

A comparison between the static Python-based visualizations of the p65 activity in activated fibroblasts and the dynamic, HTML-based visualizations that use these same reduction me... by Hector Torres (11708207)

“…<p><b>(a)</b> UMAP, t-SNE, PCA, and Diffmap were first generated using the Python libraries Scikit-learn, UMAP, and PyDiffmap within Jupyter to generate static graphs as a starting point. …”