Results 111 to 120 of about 14,345,702 (255)
Asymmetry in Skipping Enhances Viability Against Control Input Noise
Quadruped animals use asymmetric galloping gaits at high speeds, yet the functional role of this asymmetry remains unclear. This study shows that left–right asymmetry in touchdown angles enhances robustness to control noise. Using a simple two‐legged locomotion model and viability theory, it demonstrates that asymmetric skipping substantially enlarges ...
Yuichi Ambe, Alvin So, Shinya Aoi
wiley +1 more source
Projections for world maps can only be a compromise between different requirements as it is impossible to construct a projection that preserves distances, areas, and angles.
Franz-Benjamin Mocnik
doaj +1 more source
Autonomous field robots equipped with ISFET‐based sensors enable rapid, spatially resolved soil nutrient analysis directly in the field. An automated system based on the BoniRob platform is presented for standardized on‐site extraction and measurement of key macronutrients and soil pH.
Vadim Riedel +3 more
wiley +1 more source
Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges
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
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 +7 more
wiley +1 more source
Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia +7 more
wiley +1 more source
Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
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
Rhombic triacontahedron-based hexagonal discrete global grid systems (RTHDGGS) exhibit desirable geometric properties; however, their practical application is constrained by expensive cross-face computations and incongruent hierarchical subdivisions.
QiShuang Liang +5 more
doaj +1 more source
Semiregular Degenerate Refinement for 3D Discrete Global Grid Systems
Recent technological advancements have led to unprecedented amounts of 3D data becoming available about the Earth. With this, technologies that facilitate the efficient integration and management of geospatial data are becoming increasingly important.
openaire +2 more sources
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source

