As the number of endangered animal species increases, their conservation requires effective methods for the surveying and monitoring of the spatial and temporal distributions of targeted species, often on a large scale. Traditional methods often fail... read more
Atomic force microscopy (AFM) enables label-free nanoscale imaging and nanomechanical profiling but remains constrained by low throughput, operator dependence, and variability in data interpretation. Artificial intelligence (AI) transforms AFM into a... read more
Journal of chemical theory and computation
Apr 23, 2026
A machine learning (ML) based, equivariant neural network for constructing distributed charge models (DCMs) of arbitrary resolution─DCM-net─is presented. DCMs efficiently and accurately model the anisotropy of the molecular electrostatic potential (E... read more
Chiral inorganic crystals, particularly semiconductors with Weyl points near the band edges or semimetals hosting Weyl points at the Fermi level, have attracted considerable interest; yet, they remain scarce in existing materials databases. This stud... read more
BACKGROUND: Speech sound disorders are common in children and are associated with an increased risk of academic reading difficulties. The COVID-19 pandemic further highlighted the need for remote and digitalized assessment tools. In South Korea, stan... read more
BACKGROUND: The integration of robots into industrial settings has rapidly advanced, aiming to reduce human involvement in demanding tasks while improving overall efficiency. As collaborative robots (cobots) become more prevalent, assessing the physi... read more
The digital mental health (DMH) industry has grown drastically over the last decade; yet, many DMH products have failed to demonstrate meaningful clinical outcomes, in large part due to lack of scientific evidence. This viewpoint paper highlights an ... read more
Reinforcement learning (RL), a key artificial intelligence technique, has been widely studied and applied over the past two decades to solve various optimization control problems. Generally speaking, there are two basic frameworks for RL-based contro... read more
IEEE transactions on neural networks and learning systems
Apr 23, 2026
Learning intractable distributions in high-dimensional spaces remains a fundamental challenge. While prevalent deep learning methods often rely on restrictive prior assumptions, we propose a novel differentiable method that approximates intractable d... read more
IEEE journal of biomedical and health informatics
Apr 23, 2026
Brain fog has raised significant public health concerns as a common neurocognitive impairment in the post-COVID-19 condition, involving memory loss, poor concentration, and language difficulties. However, their neural mechanisms remain unclear, and o... read more
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