Results 131 to 140 of about 69,954 (264)

Educational anxiety and student mental health in the era of artificial intelligence: a multi-source data fusion analysis in smart education. [PDF]

Front Public Health
Tian Q.
europepmc   +1 more source

Polysiloxane‐Based Single‐Ion Conducting Polymer Electrolyte for Sodium Batteries

Advanced Science, EarlyView.
We report a polysiloxane‐based single‐ion conducting polymer electrolyte for sodium batteries. This polymer electrolyte exhibits high Na+ ion mobility and a wide electrochemical stability window, enabling the long‐term stable cycling of various cathode chemistries – also at room temperature, elevated dis‐/charge rates and active material mass loadings,
Yixuan Guo, Hyokyeong Kang, Maider Zarrabeitia, Ludovica Roselli, Hyerim Kim, Vittorio Marangon, Jang‐Yeon Hwang, Dominic Bresser   +7 more
wiley   +1 more source

"No Fair!": Children's Perceptions of Fairness in Merit-Based Distributions. [PDF]

Behav Sci (Basel)
Yucel M, Brence M, Vaish A.
europepmc   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source

Why do experts miss AI's errors? Evidence from a randomized labeling experiment. [PDF]

PNAS Nexus
Goulas S, Megalokonomou R, Sotirakopoulos P.   +2 more
europepmc   +1 more source

Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel

Advanced Science, EarlyView.
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei, Yong Li, Chenchong Wang, Lingyu Wang, Xiang Song, Keming Mao, Yu Zhang, Wei Xu   +7 more
wiley   +1 more source

LaED: a novel lightweight, edge-aware and explainable deep learning model for privacy-preserving facial attendance tracking in resource-constrained educational environments. [PDF]

Sci Rep
Abiodun EO, Abiodun OI, Alawida M, Shawar BA, Mehmood A.   +4 more
europepmc   +1 more source

From Label‐Free Multiphoton Imaging to Pathological Reports: A Vision‐Language Breast Cancer Margin Pathological Diagnosis System

Advanced Science, EarlyView.
MarginPath is a novel vision‐language system that automates breast cancer margin assessment using a single label‐free multiphoton microscopy image. By integrating tumor‐associated collagen signatures with virtual H&E imaging, it generates accurate margin heatmaps and comprehensive diagnostic reports.
Shu Wang, Jingze Su, Xiahui Han, Deyong Kang, Xiao Zhang, Fei Xu, Changzu Liu, Junlin Pan, Xingfu Wang, Qiaohui Zhan, Aimin Wang, Feng Huang, Heping Cheng, Wenxi Liu, Ruolan Lin, Jianxin Chen   +15 more
wiley   +1 more source

Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors

Advanced Science, EarlyView.
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung, Gwang Ya Kim, Sejin Kim, Hyunjong Seo, Se Gi Lee, Sang Min Won, Dongjoon Rhee, Joohoon Kang   +7 more
wiley   +1 more source

Trustworthy artificial intelligence in predictive medicine: cancer survival analysis using ethical-by-design and explainable artificial intelligence models. [PDF]

JAMIA Open
Farahani S, Siddiqui IA, Taheri A, Fox C, Einhorn A, Helman S, Mathew J, Harshman K, Myers N, Koleck TA, Weiss KR, Lohse I, Tafti AP.   +12 more
europepmc   +1 more source