Results 131 to 140 of about 385,428 (250)

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

Student experiences and learning outcomes of an interprofessional and international service-learning program: an exploratory study. [PDF]

BMC Med Educ
Kor PPK, Tan HZ, Tsang APL, Cheung K, Cheung SP, Montayre JRG, Ko KY, Triastuti IA, Widagdo TMM, Prasetyo YC, Amnatsatsue K, Kittiteerasack P.   +11 more
europepmc   +1 more source

Personalized Network‐Guided Neuromodulation Enhances Human Working Memory

Advanced Science, EarlyView.
A personalized neuromodulation framework combining individualized functional brain network targeting with real‐time neural decoding is introduced. Using concurrent TMS–fMRI, participant‐specific stimulation targets and optimal frequencies are identified. Only optimal‐frequency stimulation improves working memory across sessions.
Ahsan Khan, Hongming Li, Camille Blaine, Julie Grier, Ethan Hammett, Almaris Figueroa‐Gonzalez, Sarai Garcia, Romain Duprat, Justin Reber, Joseph Deluisi, Christos Davatzikos, Theodore D. Satterthwaite, Yong Fan, Desmond J. Oathes   +13 more
wiley   +1 more source

Inclusive service learning: contributions from an acrosport programme for university students with and without intellectual disabilities. [PDF]

Front Psychol
Aguado-Gómez R, Calle-Molina MT, Sanz-Arribas I.   +2 more
europepmc   +1 more source

Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers

Advanced Science, EarlyView.
FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao, Misheng Cai, Zhenghong Wang, Yan Wang, Yuqi Li, Bo Dong, Hewu Wang, Andrew F. Burke, Simona Onori, Stephen J. Harris   +9 more
wiley   +1 more source

Effects of an intergenerational service-learning program on prosocial behaviors and perception of physical education in primary education students. [PDF]

Front Psychol
Ruiz-Montero EE, Sánchez-Trigo H, Chiva-Bartoll O, Ruiz-Montero PJ.   +3 more
europepmc   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Multistakeholder Assessment of Project-Based Service-Learning in Medical Education: A Comparative Evaluation. [PDF]

Adv Med Educ Pract
Liao SC, Hung YN, Chang CR, Ting YX.
europepmc   +1 more source

Magnetoelectric Nanoparticle‐Based Wireless Brain–Computer Interface: Underlying Physics and Projected Technology Pathway

Advanced Science, EarlyView.
Magnetoelectric nanoparticles (MENPs) enable fully wireless, minutely invasive neuromodulation, and potentially neural recording, by converting magnetic into electric and, conversely, electric into magnetic fields, respectively, at high spatiotemporal resolution.
Elric Zhang, Max Shotbolt, Mostafa Abdel‐Mottaleb, Shawnus Chen, Victoria Andre, Jieyuan Tian, Jonathan Shulgach, Max Murphy, Brian Noga, Ping Liang, Darcy Griffin, Douglas Weber, Marta Pardo, Salvador Pane, Sakhrat Khizroev   +14 more
wiley   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source