Results 121 to 130 of about 239,048,002 (311)

LLMs as Representation Generators for Gradient‐Free Scientific Optimization: A Case Study in Battery Fast Charging

open access: yesAdvanced Science, EarlyView.
Large language models serve as representation generators for gradient‐free scientific optimization. Two complementary approaches produce executable battery‐charging policies either directly or through LLM‐designed neural representations coupled to Bayesian optimization.
Ge Lei   +3 more
wiley   +1 more source

An Expertise Transfer Framework For Autonomous Surgical Assistance

open access: yesAdvanced Science, EarlyView.
This study introduces an expertise transfer framework for procedure‐spanning autonomous surgical assistance. By emulating expert logic through hierarchical perception, attention modeling, and knowledge graph‐based decision‐making, the system provides near‐expert surgical view assistance.
Yuan Gao   +12 more
wiley   +1 more source

A Hybrid Intuitionistic Logic: Semantics and Decidability

open access: yes, 2005
An intuitionistic, hybrid modal logic suitable for reasoning about distribution of resources was introduced by Jia and Walker. The modalities of the logic allow validation of properties in a particular place, in some place and in all places.
Damiano Macedonio   +5 more
core  

The Morpho-Semantics of Spanish Indefinites [PDF]

open access: yes, 2016
I analyze the Spanish indefinites algún and algunos as a paucal and a greater paucal determiner, respectively, contrary to the common assumption that views the former as singular and the latter as plural.
Semantics and Linguistic Theory   +2 more
core   +1 more source

Bridging Chemical Literature and Molecular Graphs: LLM‐Augmented Enantioselectivity Prediction for Iridium‐Catalyzed Asymmetric C–H Borylation

open access: yesAdvanced Science, EarlyView.
A machine‐learning framework for asymmetric C–H borylation bridges multi‐entity 3D molecular graphs and chemical literature. Atom‐resolved mechanistic annotations extracted by large language models augment three‐component graph encoding of catalyst, substrate, and product. The model predicts enantioselectivity with high accuracy on unseen scaffolds and
Zhe Wang   +4 more
wiley   +1 more source

Toward A Working Theory For Human-Data Interaction In The Built Environment

open access: yes
Human-Data Interaction is central to the dynamic nature of the construction industry and its growing reliance on substantial data sets. In this paper, we evaluate literature on the topic of Human-Data Interaction across several technologies and concepts ...
Msawil, Mahir   +14 more
core   +1 more source

Mechanism‐Informed Language Modeling and Oxygenated 3D Screening Identify Berberine–Enzalutamide Synergy in Prostate Cancer Models

open access: yesAdvanced Science, EarlyView.
By integrating knowledge‐augmented artificial intelligence with an oxygen‐supplemented 3D screening platform, a synergistic interaction between berberine and enzalutamide is identified. The framework integrates compound mechanisms of action with disease‐relevant signaling context to prioritize candidate combinations and generate testable pathway‐based ...
Chih‐Hui Lo   +15 more
wiley   +1 more source

Integrative Reduction, Confirmation, and the Syntax-Semantics Map [PDF]

open access: yes, 2011
Different pairs of scientific theories stand in different relations. The present paper identifies a new type of intertheoretic relation, Integrative Reduction, that is instantiated in the relation between linguistic syntax and semantics.
Hartmann, Stephan, Liefke, Kristina
core  

Pseudo‐Haptic Feedback: Multi‐Modal Approaches to Stiffness Perception and User Experience

open access: yesAdvanced Science, EarlyView.
Can visual deformation substitute for physical haptic feedback? In immersive VR, deformation‐based pseudo‐haptics enables stiffness discrimination comparable to wearable force feedback, while their combination yields the highest performance and presence without increasing workload.
Mehmet Ege Cansev   +4 more
wiley   +1 more source

Symptom‐Driven Prediction of Chronic Multimorbidity with a Macro–Micro Heterogeneous Graph Neural Network

open access: yesAdvanced Science, EarlyView.
Clinical symptoms offer a window into multimorbidity. A macro‐micro heterogeneous graph neural network integrates clinical records with biomedical knowledge to improve patient‐level symptom‐disease association learning and visit‐level multimorbidity completion.
Yiheng Ye   +15 more
wiley   +1 more source

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