Results 91 to 100 of about 344 (214)

Discovering Interpretable Semantics from Radio Signals for Contactless Cardiac Monitoring

Advanced Science, EarlyView.
This study presents a semantic representation framework for clinically interpretable cardiac monitoring from contactless radio signals. It formulates radio semantic learning as an information‐bottleneck problem and approximates the objective via intra‐modal compression and cross‐modal alignment, structuring radio measurements into meaningful semantic ...
Jinbo Chen, Haoyu Wang, Guixin Xu, Yuqin Yuan, Xinmeng Cai, Zhengwu Wei, Dongheng Zhang, Qibin Sun, Tianwei Zhang, Cuntai Guan, Yan Chen   +10 more
wiley   +1 more source

Optoelectronic‐Driven van der Waals Ferroelectric Materials‐Based Memory Devices for Retinomorphic and In‐Sensory Hardware

Advanced Science, EarlyView.
2D ferroelectrics materials enabling non‐volatile polarization memory, optical excitability, and neuromorphic processing within a unified material and provides a mechanistic analysis of polarization‐induced band modulation, including photon‐assisted domain reorientation, switching kinetics, and interfacial dipole coupling that governs resistive ...
Parthasarathi Pal, Yeong‐Her Wang, Sanjay Kumar, Themis Prodromakis   +3 more
wiley   +1 more source

Digital transformation in higher education: logical framework, practical dilemmas, and implementation approaches

Frontiers in Psychology
The digital age comes with new demands and challenges for talent cultivation within the higher education system. The digital transformation in higher education has emerged as a critical element in addressing these challenges.
Juan Tang, Pin Huang, Shuangsheng Yan
doaj   +1 more source

Role of Wadsley Defects and Cation Disorder to Enhance MoNb12O33 Diffusion

Advanced Energy Materials, EarlyView.
Wadsley‐Roth niobates are high‐rate capable and durable anode materials for lithium‐ion batteries. Defect‐tailoring of MoNb12O33 is shown to substantially enhance lithium diffusion. Computational models were used to separate the effects of cation disorder and Wadsley defects to identify that both led to the occupation of fast diffusion sites at lower ...
CJ Sturgill, Manish Kumar, Nima Karimitari, Iva Milisavljevic, Coby S. Collins, Aaron Hegler, Hsin‐Yun Joy Chao, Santosh Kiran Balijepalli, Scott T. Misture, Christopher Sutton, Morgan Stefik   +10 more
wiley   +1 more source

Trust‐region filter algorithms utilizing Hessian information for gray‐box optimization

AIChE Journal, EarlyView.
Abstract Optimizing industrial processes often involves gray‐box models that couple algebraic glass‐box equations with black‐box components lacking analytic derivatives. Such systems challenge derivative‐based solvers. The classical trust‐region filter (TRF) algorithm provides a robust framework but requires extensive parameter tuning and numerous ...
Gul Hameed, Tao Chen, Antonio del Rio Chanona, Lorenz T. Biegler, Michael Short   +4 more
wiley   +1 more source

AI in chemical engineering: From promise to practice

AIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

Logic-gated tumor-microenvironment nanoamplifier enables targeted delivery of CRISPR/Cas9 for multimodal cancer therapy

Acta Pharmaceutica Sinica B
Recent innovations in nanomaterials inspire abundant novel tumor-targeting CRISPR-based gene therapies. However, the therapeutic efficiency of traditional targeted nanotherapeutic strategies is limited by that the biomarkers vary in a spatiotemporal ...
Yongchun Pan, Xiaowei Luan, Fei Zeng, Xuyuan Wang, Shurong Qin, Qianglan Lu, Guanzhong He, Yanfeng Gao, Xiaolian Sun, Xin Han, Bangshun He, Yujun Song   +11 more
doaj   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source