Results 201 to 210 of about 2,422,350 (276)

Nonreciprocal Swarmalators With Reconfigurable and Controllable Formations for Robot Collectives

Advanced Robotics Research, EarlyView.
Nonreciprocal swarmalator interactions are enabled through control barrier functions to transform self‐organizing robot collectives into reconfigurable, constraint‐aware systems. Complex two‐ and three‐dimensional shapes, continuous morphing, obstacle‐aware navigation, collective splitting, and object transport emerge from modulating agent‐level ...
Kush Patel, Xinyue Xu, Wei Xiao, Steven Ceron   +3 more
wiley   +1 more source

Gradient Flow Dynamics for Cell Membranes in the Canham-Helfrich Model. [PDF]

Arch Ration Mech Anal
Rupp F, Scharrer C, Schlierf M.
europepmc   +1 more source

Microscale Mapping of Fiber Strain and Damage in Composite Wrinkled Laminates Using Computed Tomography Assisted Wide‐Angle X‐Ray Scattering

Advanced Science, EarlyView.
This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong, James Trevarthen, Igor Dolbnya, Wadwan Singhapong, Nicholas Pilato, Richard Butler, Jiraphant Srisuriyachot, Alexander J. G. Lunt   +7 more
wiley   +1 more source

A Deep Learning-Based Latent Trait Model for Forced-Choice Personality Assessment. [PDF]

Behav Sci (Basel)
Li X, Wu J, Ren Y, Guo S, Li Z, Zheng C.
europepmc   +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, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

Distortion-Constrained Minimax Data Sanitization with Multiple Adversaries. [PDF]

Entropy (Basel)
Moatazedian A, Yakimenka Y, Chou RA, Kliewer J.   +3 more
europepmc   +1 more source

Tunable Negative Thermal Expansion in Fe/Cr‐Substituted Nd2Co17 Compounds via Magnetoelastic Coupling

Advanced Science, EarlyView.
This study achieves anisotropic thermal expansion tuning in Nd2(Co1‐xFex)17‐yCry compounds via a magnetoelastic strategy. Variable‐temperature synchrotron X‐ray diffraction reveals that increased Fe content induces switchable lattice responses. Compositional control reduces the volume expansion coefficient αV by 20% (x═0.7) and modulates TC (442–625 K),
Jiayuan Li, Chenfei Qv, Haoran Tu, Qinfen Gu, Wayne D. Hutchison, Stewart J. Campbell, Zhenxiang Cheng, Wenquan Wang, Jianli Wang   +8 more
wiley   +1 more source

Anomaly Detection and Data Repair for Smart Meter Data in Smart Cities: A Comprehensive Review and Future Perspectives. [PDF]

Sensors (Basel)
Zhang B, Lin G, Zheng K, Du J.
europepmc   +1 more source

Highly Flexible and Conformable ZnO/FeGa Magnetoelectric Heterostructures for Skin wound Healing

Advanced Science, EarlyView.
The magnetic field‐induced electric field generated by a highly flexile ZnO(piezoelectric)/FeGa(magnetostrictive) magnetoelectric heterostructure embedded in the low Young's modulus elastomer PDMS has been used to stimulate the wound healing processes.
Filippos Perdikos, Laia Bagur, Cristina Vaca, Aritz Lafuente, Joaquin Llacer‐Wintle, Bojan Ambrožič, Christina Stefani, Minsoo Kim, Goran Dražić, Darja Lisjak, Jordi Sort, Xiang‐Zhong Chen, Maria Jose Esplandiu, Salvador Pané, Carme Nogués, Josep Nogués, Andreu Blanquer, Borja Sepúlveda   +17 more
wiley   +1 more source

Physics-Guided Multi-Task Learning for Small-Sample Soft Sensing: Simultaneous Prediction of Kappa Number and Viscosity in Continuous Kraft Pulping. [PDF]

Sensors (Basel)
Zhang B, Shi L, Zhang X, Xu M.
europepmc   +1 more source