Results 191 to 200 of about 2,283,484 (302)
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
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 +4 more
wiley +1 more source
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 +3 more
wiley +1 more source
This review aims to provide a broad understanding for interdisciplinary researchers in engineering and clinical applications. It addresses the development and control of magnetic actuation systems (MASs) in clinical surgeries and their revolutionary effects in multiple clinical applications.
Yingxin Huo +3 more
wiley +1 more source
Western Adults' Neural Responses to an Ambiguous Rhythm: Effects of Priming With and Without Active Attention. [PDF]
Flaten E, Carrillo C, Trainor L.
europepmc +1 more source
This article introduces a computer vision‐assisted control strategy for light‐driven liquid crystal elastomer actuators. Through negative feedback regulation, the liquid crystal elastomer actuator exhibits accurate and stable bending deformation in complex environments.
Wei Zhang +6 more
wiley +1 more source
Experience-driven Predictability Does Not Influence Neural Entrainment to the Beat. [PDF]
Hoddinott JD, Henry MJ, Grahn JA.
europepmc +1 more source
Impact of Biomimetic Pinna Shape Variation on Clutter Echoes: A Machine Learning Approach
Bats with dynamic ear structures navigate dense, echo‐rich environments, yet the echoes they receive are highly random. This study shows that machine learning can reliably detect structural signatures in these seemingly chaotic biosonar signals. The results open new directions for biologically inspired sensing, where time‐varying receiver shapes ...
Ibrahim Eshera +2 more
wiley +1 more source
Securing Generative Artificial Intelligence with Parallel Magnetic Tunnel Junction True Randomness
True random numbers can protect generative artificial intelligence (GAI) models from attacks. A highly parallel, spin‐transfer torque magnetic tunnel junction‐based system is demonstrated that generates high‐quality, energy‐efficient random numbers.
Youwei Bao, Shuhan Yang, Hyunsoo Yang
wiley +1 more source
Cardiovascular diseases are leading death causes; electrocardiogram (ECG) analysis is slow, motivating machine learning and deep learning. This study compares deep convolutional generative adversarial network, conditional GAN, and Wasserstein GAN with gradient penalty (WGAN‐GP) for synthetic ECG spectrograms; Fréchet Inception Distance (FID) and ...
Giovanny Barbosa‐Casanova +3 more
wiley +1 more source

