Results 111 to 120 of about 78,313 (257)
Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design
A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram +4 more
wiley +1 more source
Using Network Science to Understand the Aging Lexicon: Linking Individuals' Experience, Semantic Networks, and Cognitive Performance. [PDF]
Wulff DU +3 more
europepmc +1 more source
Antimicrobial resistance caused by Gram‐negative bacteria remains difficult to overcome due to the protective outer membrane. To address this challenge, a multi‐condition constrained generative AI framework, GenMTAMP is proposed for de novo membrane‐targeting antimicrobial peptide design by integrating physicochemical and spatial structure descriptors.
Jingxiao Yu +5 more
wiley +1 more source
This study proposed a unified sequence‐based framework for protein binding site prediction, which adopted a tri‐track semantic multi‐source feature fusion strategy to effectively capture diverse macromolecular interaction sites and further improved the accuracy of antibody‐antigen interaction prediction.
Dongliang Hou +8 more
wiley +1 more source
Macroscale brain states support the control of semantic cognition
A crucial aim in neuroscience is to understand how the human brain adapts to varying cognitive demands. This study investigates network reconfiguration during controlled semantic retrieval in differing contexts. We analyze brain responses to two semantic
Xiuyi Wang +5 more
doaj +1 more source
This study introduces a foundation model‐based biomarker for risk stratification of pathological response in non‐small cell lung cancer. A Vision Mamba super‐resolution model standardizes heterogeneous CT images. A multi‐task Swin Transformer then fine‐tunes a pre‐trained lung foundation model to jointly optimize tumor segmentation and response ...
Yanglan Xu +10 more
wiley +1 more source
LSL-SS-Net: level set loss-guided semantic segmentation networks for landslide extraction
A landslide inventory is essential for numerous applications, including disaster prevention and mitigation. The emergence of advanced satellite technologies and the proliferation of extensive satellite imagery have greatly enhanced the role of deep ...
Yueheng Yang +4 more
doaj +1 more source
STransformer is a unified deep learning framework designed to seamlessly accommodate a comprehensive landscape of spatial data. By simultaneously capturing short‐range cellular interactions and tissue‐wide semantic patterns, it extracts robust representations to accurately dissect complex tissue heterogeneity.
Xingyi Li +9 more
wiley +1 more source
This paper illustrates a knowledge‐augmented dual‐track AI framework for advanced superalloy design. First, Large Language Models translate metallurgical heuristics into explicit rules to rapidly prune a vast compositional search space. Subsequently, LLM‐distilled priors safely guide a reinforcement learning agent during autonomous process optimization,
Jian Yao +9 more
wiley +1 more source
On the concepts of Denotation and Reference Language as a language and meta-language as a descriptive language, in fact, represents the field in which the concepts of terms emerge.
مختار درقاوي
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