Results 101 to 110 of about 35,563 (212)
Deep Learning‐Assisted Design of Mechanical Metamaterials
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Potentials of ChatGPT in Anatomy Research: A Conversation With ChatGPT. [PDF]
Tigga SR, Saluja S.
europepmc +1 more source
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
<i>TopoCellGen</i>: Generating Histopathology Cell Topology with a Diffusion Model. [PDF]
Xu M +7 more
europepmc +1 more source
BMPCQA: Bioinspired Metaverse Point Cloud Quality Assessment Based on Large Multimodal Models
This study presents a bioinspired metaverse point cloud quality assessment metric, which simulates the human visual evaluation process to perform the point cloud quality assessment task. It first extracts rendering projection video features, normal image features, and point cloud patch features, which are then fed into a large multimodal model to ...
Huiyu Duan +7 more
wiley +1 more source
From dysphoria to anhedonia: age-related shift in the link between cognitive and affective symptoms. [PDF]
Harlev D, Vituri A, Shahar M, Wolpe N.
europepmc +1 more source
This review explores how shape‐changing structures—origami, bistable, and laminate structures—enable multifunctionality in soft robotics and metamaterials. Starting from structural design, it examines core principles, real‐world applications, and ongoing challenges.
Lingchen Kong, Yaoyao Fiona Zhao
wiley +1 more source
Beyond Euclid: an illustrated guide to modern machine learning with geometric, topological, and algebraic structures. [PDF]
Papillon M +10 more
europepmc +1 more source
The polymerase chain reaction (PCR).Perturbation Theory and Machine Learning framework integrates perturbation theory and machine learning to classify genetic sequences, distinguishing ancient DNA from modern controls and predicting tree health from soil metagenomic data.
Jose L. Rodriguez +19 more
wiley +1 more source

