Results 171 to 180 of about 858,800 (318)
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
Reduced cloud cover errors in a hybrid AI-climate model through equation discovery and automatic tuning. [PDF]
Grundner A +5 more
europepmc +1 more source
Has northern Indian Ocean Cloud cover changed due to increasing anthropogenic aerosol?
J. Norris
semanticscholar +1 more source
Modeling High-Resolution 3-D Cloud Fields for Earth-Space Communication Systems
L. Luini, C. Capsoni
semanticscholar +1 more source
Temperature‐Tunable Cholesteric Liquid Crystal Optical Combiners for Extended Reality Applications
Recent advancements in extended reality highlight their potential to enhance traditional displays like liquid crystal displays and organic light‐emitting diode screens. This article introduces an innovative cholesteric liquid crystal‐based optical combiner for head‐mounted displays, enabling seamless transitions between augmented reality, virtual ...
Yuanjie Xia +6 more
wiley +1 more source
An all-sky light pollution model for global-scale applications that embraces a full range of cloud distributions. [PDF]
Kocifaj M, Falchi F, Kundracik F.
europepmc +1 more source
SuperResNET is a powerful integrated software that reconstructs network architecture and molecular distribution of subcellular structures from single molecule localization microscopy datasets. SuperResNET segments the nuclear pore complex and corners, extracts size, shape, and network features of all segmented nuclear pores and uses modularity analysis
Yahongyang Lydia Li +6 more
wiley +1 more source
Integrating Phenological Features with Time Series Transformer for Accurate Rice Field Mapping in Fragmented and Cloud-Prone Areas. [PDF]
Xu T, Cai P, Wei H, He H, Wang H.
europepmc +1 more source

