-
61
Output datasets from ML–assisted bibliometric workflow in African phytochemical metabolomics research
Published 2025“…<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.…”
-
62
CompuCrawl: Full database and code
Published 2024“…</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.…”
-
63
Catalogue of compact radio sources in Messier-82 from e-MERLIN observations
Published 2025“…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>. …”
-
64
Smart contract and interface code for Nature Energy "A general form of smart contract for decentralised energy systems management"
Published 2024“…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." …”
-
65
R codes and curated dataset for “EnoLEX: A Diachronic Lexical Database for the Enggano Language”
Published 2025“…</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>.…”
-
66
Main parameters of braking system.
Published 2025“…<div><p>Vehicle lateral stability control under hazardous operating conditions represents a pivotal challenge in intelligent driving active safety. …”
-
67
EMB and SBW system structure.
Published 2025“…<div><p>Vehicle lateral stability control under hazardous operating conditions represents a pivotal challenge in intelligent driving active safety. …”
-
68
Raw data.
Published 2025“…<div><p>Vehicle lateral stability control under hazardous operating conditions represents a pivotal challenge in intelligent driving active safety. …”
-
69
Reward function related parameters.
Published 2025“…<div><p>Vehicle lateral stability control under hazardous operating conditions represents a pivotal challenge in intelligent driving active safety. …”
-
70
The HIL simulation data flowchart.
Published 2025“…<div><p>Vehicle lateral stability control under hazardous operating conditions represents a pivotal challenge in intelligent driving active safety. …”
-
71
Hyperparameter Configurations in PPO Training.
Published 2025“…<div><p>Vehicle lateral stability control under hazardous operating conditions represents a pivotal challenge in intelligent driving active safety. …”
-
72
Main parameters of steering system.
Published 2025“…<div><p>Vehicle lateral stability control under hazardous operating conditions represents a pivotal challenge in intelligent driving active safety. …”
-
73
Co-simulation architecture.
Published 2025“…<div><p>Vehicle lateral stability control under hazardous operating conditions represents a pivotal challenge in intelligent driving active safety. …”
-
74
Overall framework diagram of the study.
Published 2025“…<div><p>Vehicle lateral stability control under hazardous operating conditions represents a pivotal challenge in intelligent driving active safety. …”
-
75
Vehicle parameters.
Published 2025“…<div><p>Vehicle lateral stability control under hazardous operating conditions represents a pivotal challenge in intelligent driving active safety. …”
-
76
-
77
Data for "A hollow fiber membrane permeance evaluation device demonstrating outside-in and inside-out performance differences"
Published 2025“…</li><li>Plot data derived from the above data sources.</li><li>Python code to generate figures from the plot data.…”
-
78
-
79
-
80