Full‐Stack Architectures for Intelligent Brain‐Computer Interfaces
System‐level overview of brain–computer interfaces (BCIs), illustrating the integration of neural signal acquisition, wireless transmission, and adaptive decoding. Advanced electrode, tissue interfaces, energy‐efficient communication, and robust algorithms collectively enable stable signal quality, real‐time processing, and closed‐loop operation ...
Hee Kyu Lee +9 more
wiley +1 more source
CeO2‐x/Pt single‐atom nano‐island is constructed via low‐temperature reduction, featuring abundant oxygen vacancies and an island–sea structure. It delivers outstanding multi‐enzyme‐mimetic activity and ROS‐scavenging efficiency. Density functional theory reveals optimized electronic structures and reaction pathways.
Yang Zhu +12 more
wiley +1 more source
Myanmar XNLI: building a dataset and exploring low-resource approaches to natural language inference with Myanmar [PDF]
Aung Kyaw Htet, Mark Dras
openalex +1 more source
Improving Natural Language Inference in Arabic using Transformer Models and Linguistically Informed Pre-Training [PDF]
Mohammad Majd Saad Al Deen +4 more
openalex +1 more source
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
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
AI‐Physics‐Experiment Trinity for Integrated Protein Dynamics Modeling
This review unites experiments, physics‐based simulations, and AI as a synergistic triad for protein dynamics modeling. It highlights integrative strategies, resolves sampling and forcefield bottlenecks, and outlines challenges and future directions for accurate, interpretable conformational ensemble prediction.
Chen Shi +4 more
wiley +1 more source
Recent Advances in Natural Language Inference: A Survey of Benchmarks,\n Resources, and Approaches [PDF]
Shane Storks, Qiaozi Gao, Joyce Chai
openalex +1 more source
CauFinder: Steering Cell‐State and Phenotype Transitions by Causal Disentanglement Learning
CauFinder combines causal disentanglement modeling and network control to prioritize causal drivers of cell‐state transitions from observational transcriptomic data. The framework separates transition‐relevant signals from spurious associations, nominates intervention targets across biological and disease contexts, and identifies DAAM1 as an actionable
Chengming Zhang +11 more
wiley +1 more source
Causal‐Guided Ultra‐Long‐Term Time Series Forecasting Via Anticipated Covariates
Often treated as unknown, information from the future remains underutilized.We demonstrate that in a coupled dynamical system, providing the future state of the effect enables accurate forecasting of the cause for a long timesteps. A time series forecasting paradigm that introduces anticipated covariates to represent such known future states is ...
Jintong Zhao +4 more
wiley +1 more source

