Background and Purpose: Depressive symptoms affect 280 million people worldwide. Although generative artificial intelligence (GenAI) tools are increasingly used in health care translation, their translation performance across languages remains unclea... read more
Plant metabolism is highly compartmentalized, sometimes even across organelles. Many participating enzymes are metalloproteins. Yet an integration of the metabolome and ionome is missing. Recently, nonaqueous fractionation (NAF) was adapted to deciph... read more
Ligand-protected metal hydride nanoclusters are crucial for applications in catalysis, luminescence, and energy technologies. However, accurately locating hydrogen atoms (hydrides) within these complex structures remains a significant challenge, hind... read more
This paper presents an AI-driven multisensor wearable system for real-time breathing pattern recognition by integrating an inertial measurement unit (IMU) and a flex sensor with wireless data connectivity. Three artificial intelligence models-transfo... read more
Collaborative learning in healthcare faces challenges, including strict regulations and fragmented data. This research introduces a federated learning framework that employs swarm intelligence to augment communication and enhance the analysis of medi... read more
International journal of oral science
May 11, 2026
Supramolecular hydrogels hold significant potential in drug delivery and tissue engineering, with standing out for their unique properties. Despite their promise, predicting nucleoside bioactivity remains challenging. This study aims to predict the b... read more
This study investigates the influence of geological characteristics and Soil-Water Characteristic Curve (SWCC) parameters on the collapse potential (CP) of unsaturated soils from loessic and lacustrine-alluvial deposits in Iran. Laboratory experiment... read more
The OncotypeDX 21-gene assay guides adjuvant chemotherapy decisions in early-stage, hormone receptor-positive, HER2-negative breast cancer, but cost and turnaround time limit access. This study presents a deep learning-based approach for predicting O... read more
Soil temperature forecasting plays a key role in agriculture, hydrology, and climate modeling; however, existing deep learning models often show degraded performance in long-term prediction due to error accumulation, insufficient physical interpretab... read more
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