Results 161 to 170 of about 9,252,589 (289)

Inhibition of MEKK3 Prevents Cerebral Cavernous Malformation Progression Via Restoring Endothelial Integrity and Restricting Microglial Activation

Advanced Science, EarlyView.
In this study, we demonstrate that aberrant MEKK3 signaling in endothelial cells and microglia drives the progression of cerebral cavernous malformations (CCMs). Furthermore, we identify DPDH as a potent small‐molecule MEKK3 inhibitor with substantial therapeutic potential for CCM treatment.
Weiwei Zheng, Suyun Yu, Liwenyu Chen, Jing Ma, Peiliang Shen, Chang Yu, Xiaoqing Xin, Qiuhong Shen, Jing Chen, Song Ke, Hao Liu, Xiaobing Jiang, Ruogu Qi, Juming Yan, Jia Li, Jaesung P. Choi, Yin Lu, Yang Zhao   +17 more
wiley   +1 more source

A review of full-stack autonomous obstacle avoidance for assistive robots for the disabled. [PDF]

Front Robot AI
Zhang Y, Wang S, Zhao C, Li W, Shi Z, Liu M.   +5 more
europepmc   +1 more source

Experimental Demonstration of Temporally Aware Fault‐Tolerant Sensor Fusion Using Memristive Associative Learning

Advanced Electronic Materials, EarlyView.
In dynamic driving scenarios, the proposed approach ensures only temporally aligned sensor inputs to make driving decisions, preventing false activations. By enabling selective hardware‐level learning, it achieves fast, reliable responses under noisy conditions.
Kapil Bhardwaj, Ashfak Nehal, Dmitrii Semenov, Roman Sotner, Sayani Majumdar   +4 more
wiley   +1 more source

Applications of Reinforcement Learning for Autonomous Surgical Robotics: A Systematic Review. [PDF]

Biomimetics (Basel)
Shahid M, Abdullah, Fatima Z, Feroze W, Ruiz MJT, Saldaña-Pérez M, Sánchez-Mejorada CG, Tellez RQ.   +7 more
europepmc   +1 more source

From Materials to Systems: Challenges and Solutions for Fast‐Charge/Discharge Na‐Ion Batteries

Advanced Energy Materials, EarlyView.
This review systematically analyzes the key characteristics limiting the fast‐charge/discharge capability of Na‐ion batteries (SIBs) from a multi‐scale perspective encompassing electrode materials, the electrode‐electrolyte interface, and the system. Furthermore, it presents practical solution strategies for the fundamental issues arising at each scale,
Bonyoung Ku, Sangbin Park, Sunha Hwang, Sunghyun Lim, Won‐Sub Yoon, Jongsoon Kim   +5 more
wiley   +1 more source

The Digital Transformation of Rehabilitation Medicine: A Narrative Review of Artificial Intelligence Innovations, Clinical Integration, and Future Paradigms. [PDF]

J Eval Clin Pract
Wu H, Yang Y, Wang L, Su H, Li X.
europepmc   +1 more source

Safety of Sodium‐Ion Batteries: Evaluation and Perspective from Component Materials to Cells, Modules, and Packs

Advanced Energy Materials, EarlyView.
This review provides a bottom‐up evaluation of sodium‐ion battery safety, linking material degradation mechanisms, cell engineering parameters, and module/pack assembly. It emphasizes that understanding intrinsic material stability and establishing coordinated engineering control across hierarchical levels are vital for preventing degradation coupling ...
Won‐Gwang Lim, Seoa Kim, Erik A. Wu, Darren H. S. Tan, Shawn Peng, Xiaolin Li   +5 more
wiley   +1 more source

Adaptive Task-Oriented Locomotion Control of a 2D Planar Robotic Fish Model Using Deep Reinforcement Learning and Sensory-Feedback CPG Network. [PDF]

Biomimetics (Basel)
Ozmen Koca G, Korkmaz D, Bal C, Ay M, Akpolat ZH.   +4 more
europepmc   +1 more source

Comparative Insights and Overlooked Factors of Interphase Chemistry in Alkali Metal‐Ion Batteries

Advanced Energy Materials, EarlyView.
This review presents a comparative analysis of Li‐, Na‐, and K‐ion batteries, focusing on the critical role of electrode–electrolyte interphases. It especially highlights overlooked aspects such as SEI/CEI misconceptions, binder effects, and self‐discharge relevance, emphasizing the limitations of current understanding and offering strategies for ...
Changhee Lee, Zachary T. Gossage, Shinichi Kumakura, Shinichi Komaba   +3 more
wiley   +1 more source

Safe and adaptive control of non-stationary stochastic systems via Lyapunov-constrained distributional reinforcement learning. [PDF]

Sci Rep
Khaniki MAL, Mirzaee M, Moradi E.
europepmc   +1 more source