EEG-DBNet: a dual-branch framework for temporal-spectral representation learning of motor imagery electroencephalography See

Purpose: Motor imagery electroencephalography (MI-EEG) decoding remains challenging due to low signal-to-noise ratio and complex temporal-spectral characteristics. This study aims to develop a robust deep learning framework for effective EEG representation learning. Methods: We propos...

A cross-sectional study of category fluency serial recall order in Italian individuals with amnestic mild cognitive impairment from the TREDEM registry: The role of word length See

Category Fluency (CF) “item-level” scoring methodologies identify neurocognitive processes that are distinct from those of standard quantitative scoring. One of these accounts for words’ serial recall order (SRO) and calculates the correlation between SRO and item-level complexity to operationalise th...

Binding Affinity Ranking at the Molecular Initiating Event (BARMIE): An open-source computational pipeline for the rapid screening of chemical interactions with steroid receptors from many species See

A challenge in ecological risk assessment is identifying the chemicals that pose the greatest threat and determining which species are most vulnerable to them. To help address this, this study has developed an in-silico open-source tool called BARMIE (Binding Affinity Ranking at the...

Comprehensive analysis of pseudogene expression in human and macaque brains compared with other tissues See

Although gene expression in the brain has been extensively investigated and compared to other tissues, the activity of pseudogenes has not been comprehensively surveyed. Here, leveraging large-scale RNA-seq data, we construct consistent pseudogene expression profiles in human and macaque brains a...

Spatiotemporal graph neural networks reveal conformational binding signature in protein dynamics See

Biomolecular function is often controlled by structural and dynamical adaptations to binding events. Although molecular dynamics (MD) simulations can capture these events at atomic resolution, separating functional signatures from stochastic noise remains challenging. Traditional methods often struggle to ...

Methodological advances in injury surveillance and injury inciting event analysis in elite UK netball See

Injury remains a persistent challenge in netball across all levels of participation, yet limitations in how injuries are defined, captured and described have constrained injury prevention efforts. To address these limitations, this thesis aimed to develop and apply robust methods...

“I’m a bit of a Snowflake. I Can’t Meet the Male Expectations.” How Adolescent Boys’ Perceived Competency Shapes Their Motivation for Physical Activity. See

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Biosensing in the Internet of Medical Things: A System Architecture and Design-Oriented Survey See

Diseases and healthcare concerns have become more prevalent in our society. As a result, more individuals are turning towards wearable technology as a way to keep track of their well-being. In addition, the introduction of the Internet of Medical Things will allow for continuous&#x...

AI‑Driven Student Performance Prediction in Higher Education Using Multi‑Source Educational Data See

Predicting how students will perform remains a central challenge in educational data mining and learning analytics. Anticipating difficulties early allows instructors to refine feedback and plan interventions to keep learners on track. Our study describes an AI driven framework for predicting...