Results 141 to 150 of about 2,611,781 (277)

Printing Nacre‐Mimetic MXene‐Based E‐Textile Devices for Sensing and Breathing‐Pattern Recognition Using Machine Learning

Advanced Functional Materials, EarlyView.
This study presents a Ti3C2Tx MXene/WPU nacre‐mimetic nanomaterial as a printable ink for direct‐write printing onto textiles‐based sensors. The resulting wearable device demonstrates high sensitivity, biocompatibility, and mechanical strength. Furthermore, NFC‐enabled humidity sensor produces time‐series data, which informs a machine learning ...
Lulu Xu, Wenqing Chen, Qian Li, Rohit Gupta, Biswajoy Bagchi, Laurence B. Lovat, Manish K. Tiwari   +6 more
wiley   +1 more source

A review of acupoint localization based on deep learning. [PDF]

Chin Med
Li J, Fei Z, Xie Y, Deng D, Ming X, Niu F.   +5 more
europepmc   +1 more source

Practical Classes: A Platform for Deep Learning? Overall Context in the First-Year Veterinary Curriculum

, 2009
Marion T. Ryan, Alan W. Baird, Clive W. Mulholland, Jane A. Irwin   +3 more
openalex   +1 more source

The Need for a Deeper Perspective of Education to Make Way for an Authentic Learning Experience [PDF]

, 2013
Chandana Watagodakumbura
openalex   +1 more source

Engineering Topographical Cues to Enhance Neural Regeneration in Spinal Cord Injury: Overcoming Challenges and Advancing Therapies

Advanced Functional Materials, EarlyView.
Spinal cord injury (SCI) poses significant challenges for regeneration due to a series of secondary injury mechanisms. How to use biomaterial approach to target the failed regeneration after SCI remains a critical challenge. This review systematically evaluates current strategies to optimize biomaterial topographies for neurite outgrowth, axonal ...
Wei Xu, Fenghui Wang, Joshua Stein, Siqiao Wang, Pengfei Jiang, Letao Yang, Liming Cheng, Ki‐Bum Lee   +7 more
wiley   +1 more source

Projection of ENSO using observation-informed deep learning. [PDF]

Nat Commun
Zhu Y, Zhang RH, Wang F, Cai W, Li D, Guan S, Li Y.   +6 more
europepmc   +1 more source

Do medical students who claim to be using deep learning strategies perform better at the Forensic Medicine examination?

, 2009
Kosala Marambe, Deepthi Edussuriya, P. D. Indika S. Somaratne, Chathura Piyaratne   +3 more
openalex   +2 more sources

Artificial Intelligence‐Driven Development in Rechargeable Battery Materials: Progress, Challenges, and Future Perspectives

Advanced Functional Materials, EarlyView.
AI is transforming the research paradigm of battery materials and reshaping the entire landscape of battery technology. This comprehensive review summarizes the cutting‐edge applications of AI in the advancement of battery materials, underscores the critical challenges faced in harnessing the full potential of AI, and proposes strategic guidance for ...
Qingyun Hu, Junyuan Lu, Jian Hui, Ziyuan Rao, Yang Ren, Hong Wang   +5 more
wiley   +1 more source

Deep learning for predicting the occurrence of tipping points. [PDF]

R Soc Open Sci
Zhuge C, Li J, Chen W.
europepmc   +1 more source

Experimentally Validated Design Principles of D‐Block Transition Metal Single‐Atom Non‐Dissociative Chemisorption Solid‐State Hydrogen Storage Materials

Advanced Functional Materials, EarlyView.
A novel descriptor and a bottom‐up design principle are established to enable the rational design of hydrogen storage materials based on d‐block transition metal single‐atom COFs. By modulating H₂ adsorption through d‐orbital tuning, this approach achieves both high storage capacity and fast kinetics, while revealing a volcano‐type relationship between
Qiuyan Yue, Chao Li, Yong Gao, Zhenglong Li, Wen‐Gang Cui, Xinqiang Wang, Guoquan Na, Xiaowei Wang, Yiyang Wan, Mingchang Zhang, Yanxia Liu, Fulai Qi, Chenchen Li, Xu Xue, Jian Miao, Jing Zhang, Xiao Han, Pan Wang, Chang Guo, Xiacui Liu, Mingxia Gao, Wenping Sun, Jian Chen, Zhenhai Xia, Hongge Pan   +24 more
wiley   +1 more source