Results 61 to 70 of about 80,955 (158)
Recent advances in TiO2 modification strategies: structure regulation and composite engineering for improved activity and functionality. TiO2 has emerged as a pivotal catalyst for enhancing MgH2, a high‐capacity solid‐state hydrogen storage material, owing to its structural versatility.
Xiaopeng Chu +10 more
wiley +1 more source
Large Language Model‐Based Chatbots in Higher Education
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci +4 more
wiley +1 more source
Global trends and thematic evolution in online consultation with digital health technologies: Implications for future implementation and policy development. [PDF]
Liu J +5 more
europepmc +1 more source
A schema‐first alignment framework builds compact, executable domain‐specific language models under data scarcity. Large‐scale synthetic question‐answer generation instills domain knowledge, and a code‐centric IR‐to‐DPO pipeline aligns generation with tool‐executable syntax.
Di Wang +4 more
wiley +1 more source
Real-Time Influenza Surveillance Using DeepSeek-Augmented BERT Classification on Chinese Social Media: Infodemiology Study. [PDF]
Chen S +6 more
europepmc +1 more source
An large language model‐powered multimodal framework is developed for robotic endoscope control. It integrates speech recognition and real‐time instrument tracking, achieving 89.47% command accuracy with ~1s latency for natural human–robot interaction in minimally invasive surgery.
Yisen Huang +7 more
wiley +1 more source
Non-pharmacological traditional Chinese medicine interventions for depression: bibliometric mapping of Chinese databases and WoSCC, 2000-2025. [PDF]
Dong S +6 more
europepmc +1 more source
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
Mapping Brain-Computer Interface Research in Depression (1995-2026): A Bibliometric Analysis. [PDF]
Jiang Y, Duan X.
europepmc +1 more source

