Results 221 to 230 of about 2,754,979 (294)

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

How do teachers' roles transform in metaverse classroom? The mechanisms of awe experience and differences across teaching stages. [PDF]

Front Psychol
Li H, Liu Y, Du J, Pan Y.
europepmc   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +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

Preparing Students to Care for Socially Excluded Patients: A Qualitative Study of Inclusion Health in Undergraduate Medical Education. [PDF]

Clin Teach
Ashwell G, Russell AM, Pope L, Williamson A.   +3 more
europepmc   +1 more source

Clinical Experience for Teaching Medical Ethics [PDF]

, 1981
Ruane, John P.
core   +1 more source

Smart Flexible Tactile Sensors: Recent Progress in Device Designs, Intelligent Algorithms, and Multidisciplinary Applications

Advanced Intelligent Discovery, EarlyView.
Flexible tactile sensors have considerable potential for broad application in healthcare monitoring, human–machine interfaces, and bioinspired robotics. This review explores recent progress in device design, performance optimization, and intelligent applications. It highlights how AI algorithms enhance environmental adaptability and perception accuracy
Siyuan Wang, Ming Dong, Rongrong Bao, Caofeng Pan   +3 more
wiley   +1 more source

Randomized, controlled study evaluating multi-disciplinary team-based learning (MDTBL) as optimal teaching paradigm for residents, comparing with problem-based learning (PBL) and lecture-based learning (LBL). [PDF]

BMC Med Educ
Tao R, Gao S, Feng J, Sun Y, Li Y, Wang Z, Liu B, Zhu X, Wang H, Jia X, Zhang G, Gao R.   +11 more
europepmc   +1 more source

Enhancing Sensitivity across Scales with Highly Sensitive Hall Effect‐Based Auxetic Tactile Sensors

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Herein, a tactile sensor based on hall‐effect sensors with an auxetic structure, called Hall effect‐based auxetic tactile sensor (HEATS), is proposed. The change in magnetism resulting from the deformation of the auxetic structure is utilized for sensing.
Youngheon Yun, Dongchan Lee, Soyeon Lee, Salvador Pané, Josep Puigmartí‐Luis, Sungwoo Chun, Bumjin Jang   +6 more
wiley   +1 more source

Script or style? Analysis of the relationship between teaching scripts and supervision style. [PDF]

PLoS One
Sader J, Bajwa NM, Lüchinger R, Fassier T, Audétat MC, Nendaz M, Junod Perron N.   +6 more
europepmc   +1 more source