BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by persistent deficits in social interaction and repetitive behaviors (RBs). Therapies specifically targeting RBs have been underexplored despite advances in understanding their neurobiological basis. This study aims to evaluate whether high-definition transcranial direct current stimulation (HD-tDCS) can reduce dysfunctional RBs in autistic children and investigate… →
CONCLUSION: In patients with suspected CCS, including typical angina, atypical angina and nonangina chest pain with abnormal electrocardiogram results, the use of CCTA as a first-line diagnostic test can reduce the unnecessary incidence of ICA and hospitalization costs without increasing the incidence of MACE. A risk prediction model of obstructive CAD was established on the… →
Our study aims to investigate the effect of negative pressure wound therapy (NPWT) on microRNA-155 (miR-155) in the granulation tissue of patients suffering from diabetic foot ulcers (DFUs) and its correlation with wound healing. A total of sixty patients diagnosed with DFUs were randomly assigned to either the NPWT group (n = 40) or the… →
INTRODUCTION: Delirium, a common neuropsychiatric condition in hospitalised older adults, is associated with increased mortality, longer hospital stays and cognitive decline. The potential of melatonin to prevent delirium by improving sleep patterns and regulating circadian rhythms is promising, though existing evidence is mixed. This study aims to evaluate the efficacy of melatonin in preventing delirium… →
Efficient matrix multiplications remain a critical component in modern deep learning and high-performance computing. As models become increasingly complex, conventional approaches to General Matrix Multiplication (GEMM) often face challenges related to memory bandwidth constraints, numerical precision, and suboptimal hardware utilization. These issues are further complicated by the emerging use of mixed-precision formats, such as FP8,… →
Designing imitation learning (IL) policies involves many choices, such as selecting features, architecture, and policy representation. The field is advancing quickly, introducing many new techniques and increasing complexity, making it difficult to explore all possible designs and understand their impact. IL enables agents to learn through demonstrations rather than reward-based approaches. The increasing number of… →
Vision-language models (VLMs) have demonstrated impressive capabilities in general image understanding, but face significant challenges when processing text-rich visual content such as charts, documents, diagrams, and screenshots. These specialised images require complex reasoning that combines textual comprehension with spatial understanding—a skill set critical for analysing scientific literature, improving accessibility features, and enabling AI agents to… →