Results 81 to 90 of about 64,828 (265)
Natural Hazards ResearchThis study employs machine learning techniques to map and predict landslide-prone areas in São Sebastião, Brazil, a region susceptible to landslides due to its steep terrain and intense rainfall.
Enner Alcântara +4 more
doaj +1 more source
Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges
Advanced Robotics Research, EarlyView.This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder +3 more
wiley +1 more source
Advanced Science, EarlyView.This study employs a nanochain engineering approach combined with an in situ oxidation strategy to fabricate self‐insulating iron‐based magnetic nanochains, addressing the challenge of balancing magnetic coupling and electrical insulation in soft magnetic materials.
Dingrong Zuo +8 more
wiley +1 more source
Song：Multiplicity of natural disasters
地震科学进展The Song Dynasty suffered the worst chain of disasters since ancient times: the third climate cold period, the millennium eruption of the Changbai volcano in 940, and the series of earthquakes and seismic floods after 1038.
Rui Feng
doaj +1 more source
Advanced Science, EarlyView.This study elucidates that β‐elemene promotes cellular uptake of L. gasseri‐derived lactate by enhancing the membrane translocation of MCT1 in a CD147‐dependent manner. Intracellular lactate, through the lactylation of RBBP4 at the K26 site, recruits EP300 to the promoter regions of downstream genes (POLD1/POLD3), catalyzing H3K27ac modification.
Jiancheng He +10 more
wiley +1 more source
Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Advanced Science, EarlyView.Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source
Advanced Science, EarlyView.The symmetry‐driven coexistence of altermagnetism and (anti)ferroelectricity in perovskites shows a strong dimensional dependence. Upon reducing the system from bulk to the two‐dimensional limit, only C‐type antiferromagnetic order retains ferroelectrically switchable altermagnetism, whereas A‐ and G‐type orders become conventional antiferromagnets ...
Zhou Cui +6 more
wiley +1 more source
Harnessing Phase Separation for the Development of High‐Performance Hydrogels
Advanced Science, EarlyView.ABSTRACT Hydrogels are indispensable for the development of next‐generation bioelectronics, soft robotics, and biomedical devices, where their mechanical properties determine performance and reliability. Among strategies to enhance hydrogel mechanics, phase separation enables controlled heterogeneity resulting in gel networks that are reinforced by ...
Yue Shao +3 more
wiley +1 more source
Advances and Perspectives in Graphene‐Based Quantum Dots Enabled Neuromorphic Devices
Advanced Science, EarlyView.Graphene‐based QDs are zero‐dimensional carbon nanomaterials with pronounced quantum confinement and tunable electronic structures. Herein, we summarize their synthesis strategies and functionalization methods, and highlight their functional roles and operating mechanisms in devices, as well as recent advances in neuromorphic electronics. We anticipate
Yulin Zhen +9 more
wiley +1 more source