Results 91 to 100 of about 3,812 (246)

Computation of hydromagnetic tangent hyperbolic non-Newtonian flow from a rotating non-isothermal cone to a non-Darcy porous medium with thermal radiative flux

Physics Open
A theoretical and numerical study is conducted on nonlinear, steady-state thermal convection boundary layer flow of a magnetized incompressible Tangent Hyperbolic non-Newtonian fluid from a rotating cone to a non-Darcy porous medium.
S. Abdul Gaffar, O. Anwar Bég, S. Kuharat, T.A. Bég   +3 more
doaj   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

Wellposedness and regularity of second order abstract equations arising in hyperbolic-like problems with nonlinear boundary conditions

Osaka Journal of Mathematics, 1995
The paper is concerned with a class of nonlinear second-order differential equations in a Hilbert space that contains as special cases equations of nonlinear elasticity with nonlinear boundary conditions (in particular, the nonlinear Euler-Bernoulli, and von Karman plate equations).
Favini, Angelo, Lasiecka, Irena
openaire   +4 more sources

Machine‐Learning‐Assisted Onset‐Time Determination in Transient Luminescence Thermometry

Advanced Intelligent Discovery, EarlyView.
Artificial neural networks enable autonomous extraction of onset times from transient heating curves in luminescence thermometry. Using Ln3+‐doped upconverting nanoparticles as luminescent thermometers, we combine experimental transients with physically motivated synthetic curves to enhance data diversity and improve generalization.
David J. Sousa, Erving Ximendes, Luís D. Carlos, Carlos D. S. Brites   +3 more
wiley   +1 more source

A Critical Assessment of Bonding Descriptors for Predicting Materials Properties

Advanced Intelligent Discovery, EarlyView.
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik, Nidal Dhamrait, Katharina Ueltzen, Christina Ertural, Philipp Benner, Gian‐Marco Rignanese, Janine George   +6 more
wiley   +1 more source

Underexplored Catalysts as General Structures: Application of Machine Learning Techniques for Reaction‐Specific Datasets

Angewandte Chemie, EarlyView.
Bias‐aware machine learning identified an underexplored imidazolidinone catalyst with broad competitive performance in iminium‐based reactions. Experimental benchmarking shows how data‐driven prioritization can uncover overlooked catalyst scaffolds from sparse and historically biased literature data.
Jiajing Li, Isaiah O. Betinol, Junshan Lai, Soresu Juyo, Jolene P. Reid   +4 more
wiley   +2 more sources

Extending Battery Usage Time of a Heavy‐Duty Mecanum‐Wheeled Autonomous Electric Vehicle Used in Iron–Steel Industry by Considering Wheel Slippage

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
It is a fact that slippage causes tracking errors in both longitudinal and lateral directions which results to have less travel distance in tracking a reference trajectory. Less travel distance means having energy loss of the battery and carrying loads less than planned.
Gokhan Bayar, Goktug Hambarci, Ali Sezai Demirel   +2 more
wiley   +1 more source

Robust Reinforcement Learning Control Framework for a Quadrotor Unmanned Aerial Vehicle Using Critic Neural Network

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Quadrotor unmanned aerial vehicle control is critical to maintain flight safety and efficiency, especially when facing external disturbances and model uncertainties. This article presents a robust reinforcement learning control scheme to deal with these challenges.
Yu Cai, Yefeng Yang, Tao Huang, Boyang Li   +3 more
wiley   +1 more source

Microfluidic Valve‐Integrated Garment for Smooth Sequential Gradient Mechanotherapy

Advanced Intelligent Systems, EarlyView.
We present a soft wearable sleeve that delivers smooth, gap‐free compression using overlapping air‐filled actuators and tiny microfluidic valves. The system reduces bulk, lowers power needs, and uses a smartphone‐sized control box. It can provide sequential gradient compression, gradient pressure holding, and fast deflation, supporting more portable ...
Run Ze Gao, Chen Xi Huang, Drew M. Werbowski, Jacqueline Mary Kormylo, Clark R. Dickerson, Carolyn L. Ren   +5 more
wiley   +1 more source

An Integrated and Robust Deep Learning Framework for Denoising and Analyzing Single‐Cell Spatial Transcriptomics

Advanced Intelligent Systems, EarlyView.
Single‐cell Spatial Transcriptomics Analysis and Denoising Engine is introduced as a unified deep learning framework that jointly performs denoising, clustering, and gene prioritization in spatial transcriptomics. By integrating linear and nonlinear representations within a dual‐channel architecture, it improves robustness and accuracy, uncovers ...
Yaxuan Cui, Yang Cui, Ruheng Wang, Xin Zeng, Zheyong Zhu, Ding Yi, Ruihua Guo, Tetsuya Sakurai, Kenta Nakai, Xiucai Ye, Leyi Wei, Yong Chen   +11 more
wiley   +1 more source