Results 61 to 70 of about 3,578 (213)
Uncertainty‐Aware Deep Ensembles for Robust and Reliable Chemical Sensor Arrays
A reliability‐aware electronic nose is developed using photothermally anchored metal‐catalyst decorated metal oxide nanofiber sensor arrays combined with deep ensemble learning. Diverse catalytic nanofiber channels generate gas‐specific response patterns, enabling selective identification and quantification of sulfur‐containing gases.
Sungwoo Eo +5 more
wiley +1 more source
Periprosthetic joint infection establishes a sophisticated immunosuppressive network between CXCR4+ PMN‐MDSCs and Bregs, inducing profound CD8+ T cell paralysis. Alendronate effectively disrupts this CXCR4+ PMN‐MDSC–Breg axis by targeting STAT3, thereby restoring local immune surveillance.
Jintao Wu +9 more
wiley +1 more source
Automatic emotion recognition has been widely studied and applied to various computer vision tasks (e.g. health monitoring, driver state surveillance, personalized learning, and security monitoring).
Zhang, Yang
core
Mechanisms of Alkali Ionic Transport in Amorphous Oxyhalides Solid State Conductors
Large‐scale machine learning‐based molecular dynamics simulations are used to investigate isovalent amorphous oxyhalides, revealing a remarkable chemically independent ionic conductivity. A rigorous analysis of alkali residence times across different metal–anion environments identifies divalent anions as key diffusion bottlenecks.
Luca Binci +3 more
wiley +1 more source
ABSTRACT Past growth in the global organic market has been concentrated in high‐income countries, while in middle‐income countries such as Serbia the organic market remains nascent and characterized by a sparse assortment of organic products, high retail premia and limited evidence on consumer preferences and their drivers.
Milan Tatic +3 more
wiley +1 more source
The official published version of the article can be found at the link below.This paper is concerned with the robust filtering problem for a class of nonlinear stochastic systems with missing measurements and parameter uncertainties.
Zidong Wang +9 more
core +1 more source
Abstract The demand for LiOH is driven by the growth of the electric vehicle industry. Evaporative crystallization of LiOH·H2O is energy intensive, whereas ethanol‐based antisolvent crystallization has emerged as a more sustainable alternative. From a process design perspective, the crystallization yield depends on the ethanol dosage, and thermodynamic
Xiaoqi Xu +3 more
wiley +1 more source
A practical electrodialysis model for accelerating system development
Abstract Empirical optimization of electrodialysis (ED) is dependent on repetitive experiments with incremental adjustments, which is cost prohibitive at scale. While models can reduce the costs associated with optimization and scale‐up, existing ED models are limited in application to specific use cases and tend to be developed for the exploration of ...
Smith Pittman +3 more
wiley +1 more source
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley +1 more source
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin +4 more
wiley +1 more source

