Results 51 to 60 of about 12,439,104 (289)
Active Oscillations of Elastic Membranes Arising from the Coupling with a Catalytic Reaction
Advanced Science, EarlyView.Coupling an elastic membrane to a catalytic reaction produces active oscillations that self‐sustain for hours: the membrane cyclically inflates and deflates as the reaction spontaneously activates and deactivates, without external power. Energy release is directly embodied in the oscillation dynamics, opening elasto‐chemical strategies for the physical
Alberto Comoretto +5 more
wiley +1 more source
Habitat‐Specific Design Strategies for Untethered Soft Robots
Advanced Science, EarlyView.Habitat shapes the design of untethered soft robots. Across land, water, air, and living tissues, environmental constraints govern viable combinations of compliant structures, actuation mechanisms, and energy delivery. This review connects these constraints with robotic performance and identifies design principles for advancing adaptable, durable, and ...
Siyang Li +3 more
wiley +1 more source
The Hybrid BFGS-CG Method in Solving Unconstrained Optimization Problems
Abstract and Applied Analysis, 2014 In solving large scale problems, the quasi-Newton method is known as the most efficient method in solving unconstrained optimization problems. Hence, a new hybrid method, known as the BFGS-CG method, has been created based on these properties, combining ...
Mohd Asrul Hery Ibrahim +2 more
doaj +1 more source
A Modified q-BFGS Algorithm for Unconstrained Optimization
Mathematics, 2023 This paper presents a modification of the q-BFGS method for nonlinear unconstrained optimization problems. For this modification, we use a simple symmetric positive definite matrix and propose a new q-quasi-Newton equation, which is close to the ordinary
Kin Keung Lai +4 more
doaj +1 more source
The Effect of SNAP Purchasing Power on Diet Quality
Applied Economic Perspectives and Policy, EarlyView.ABSTRACT The Supplemental Nutrition Assistance Program (SNAP) benefits millions of eligible low‐income Americans by increasing access to food, helping to reduce food insecurity. Previous studies have documented that the geographical variation in local food prices leads to significant differences in SNAP's purchasing power.
Farah Khan, Augustine Denteh
wiley +1 more source
Experimental and numerical study of liquid–liquid systems using the Euler–Lagrange/VOF approach
AIChE Journal, EarlyView.Abstract Achieving stable liquid–liquid dispersions with controlled droplet size remains a challenge due to the complex interplay of dispersed phase viscosity, hydrodynamic conditions and interfacial interactions. This work presents a validated computational framework for droplet breakage and coalescence in liquid–liquid dispersions with variable ...
Pavel Krýsa +3 more
wiley +1 more source
An Adaptive Lp Norm Minimization Algorithm for Direction of Arrival Estimation
Remote Sensing, 2022 In this paper, we propose a new direction of arrival (DOA) estimation algorithm, in which DOA estimation is achieved by finding the sparsest support set of multiple measurement vectors (MMV) in an over-complete dictionary. The proposed algorithm is based
Lutao Liu, Zejing Rao
doaj +1 more source
Crystal Structure Prediction of Inorganic Materials: A Benchmark and Modern Evaluation
Advanced Intelligent Discovery, EarlyView.Predicting a crystal’s structure from composition alone is a long‐standing challenge in materials discovery. The CSP180 benchmark of 180 inorganic crystals evaluates thirteen crystal structure prediction algorithms requiring no density functional theory (DFT) against DFT‐based baselines across twelve metrics.
Lai Wei +9 more
wiley +1 more source
A numerical solution of parabolic quasi-variational inequality nonlinear using Newton-multigrid method [PDF]
Iranian Journal of Numerical Analysis and OptimizationIn this article, we apply three numerical methods to study the L∞-convergence of the Newton-multigrid method for parabolic quasi-variational inequalities with a nonlinear right-hand side.
M. Bahi, M. Beggas, N. Nesba, A. Imtiaz
doaj +1 more source
Learning regularized Gauss-Newton methods
, 2022 We consider variational networks for a class of nonlinear-ill-posed least squares inverse problems. These problems are addressed by regularized Gauss-Newton type optimization algorithms where the regularization is learned by a neural network.
Francesco Colibazzi +3 more
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