Ming Yang

Abstract Multimodal fusion under smoke conditions faces the challenge of being unable to obtain clear fused images. Traditional fusion methods assume clear imaging conditions and fail to address nonlinear degradation. Existing stepwise smoke removal fusion processes are complex, prone to error accumulation, and lack lightweight solutions that balance performance and efficiency.

Abstract “Spin” refers to the manipulation of language to suggest benefits when none exist, commonly observed in randomized controlled trials (RCTs). This study investigates the extent, strategies, and reporting quality of spin in digital dental implant RCT abstracts, and explores study characteristics associated with spin. RCTs related to digital dental implants were retrieved from PubMed, Web of Science, Embase, Scopus, and the Cochrane Library.

Abstract Named entity recognition (NER) in traditional Chinese medicine (TCM) text is central to the structuring and intelligent application of TCM knowledge. TCM case texts are characterized by sparse entity distributions and limited domain-specific data. Existing methods often struggle to recognize low-frequency entities and show limited capacity for effective knowledge transfer. This paper proposes a TCM NER framework incorporating structured knowledge distillation.