Intrinsically disordered proteins are ubiquitous in biological systems and play essential roles in a wide range of biological processes and diseases. Despite recent advances in high-resolution structural biology techniques and breakthroughs in deep l... read more
Controlling protein solubility is critical yet challenging for food and pharmaceutical applications. This review dissects the molecular and environmental determinants governing solubility behavior. It integrates traditional modification strategies wi... read more
This paper presents an open-access telemetry dataset designed to support research and training in intelligent fixed-wing unmanned aerial systems. The dataset contains 240 fully annotated autonomous missions flown outdoors over repeatable, waypoint-ba... read more
Accurate segmentation and classification of brain tumors from Magnetic Resonance Imaging (MRI) remain key challenges in medical image analysis, primarily due to the lack of high-quality, balanced, and diverse datasets with expert annotations. In this... read more
This study explored the value of nonlinear features extracted from EEG signals to facilitate the assessment of patients with disorders of consciousness (DOC) with limited communication capacity. We utilized a dataset comprising 104 participants, 56 w... read more
Artificial intelligence-driven educational systems have largely prioritised cognitive adaptation, often neglecting the critical role of learners' emotional states in shaping engagement and learning outcomes. To address this limitation, this study pro... read more
Accurate assessment of cognitive load is vital in cognitive research and human-machine interaction. This study investigates a multimodal approach for classifying graded cognitive load levels using cardiovascular signals derived from photoplethysmogra... read more
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.