Results 41 to 50 of about 691 (194)

RIPK3 Orchestrates Scar‐Associated Macrophage Dysfunction to Drive Pulmonary Fibrosis

Advanced Science, EarlyView.
Beyond signaling cell death, RIPK3 emerges as a critical metabolic regulator in pulmonary fibrosis. This research reveals that RIPK3 promotes PI3K‐AKT signaling in scar‐associated macrophages to fuel polyamine synthesis, independent of its kinase activity.
Tao Yang, Xiao Li, Shuyue Lei, Qingqing Li, Yi Zhang, Zhizhen Hui, Jinjin Ren, Xuelian Yang, Xiaoqian Yang, Chunlan Feng, Yousheng Xu, Dongxin Zhao, Wei Tang   +12 more
wiley   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Sensitivity analysis to compute advanced stochastic problems in uncertain and complex electromagnetic environments

Advanced Electromagnetics, 2012
This paper deals with the advanced integration of uncertainties in electromagnetic interferences (EMI) and electromagnetic compatibility (EMC) problems.
S. Lalléchère, B. Jannet, P. Bonnet, F. Paladian   +3 more
doaj   +1 more source

RAMS: Residual‐Based Adversarial‐Gradient Moving Sample Method for Scientific Machine Learning in Solving Partial Differential Equations

Advanced Intelligent Discovery, EarlyView.
We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang, Min Zhu, Wei Xiong, Si‐Wei Liu, Lu Lu   +4 more
wiley   +1 more source

A test of backward stochastic differential equations solver for solving semilinear parabolic differential equations in 1D and 2D

Partial Differential Equations in Applied Mathematics, 2022
Backward stochastic differential equation solver was first introduced by Han et al in 2017. A semilinear parabolic partial differential equation is converted into a stochastic differential equation, and then solved by the backward stochastic differential
Evan Davis, Guangming Yao, Elizabeth Javor, Kalani Rubasinghe, Luis Antonio Topete Galván   +4 more
doaj   +1 more source

VAE+DDPG: An Attention‐Enhanced Variational Autoencoder for Deep Reinforcement Learning‐Based Autonomous Navigation in Low‐Light Environments

Advanced Intelligent Systems, EarlyView.
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee, Chanhong Hwang, Hyunseok Kang, Yechan Park, Hangwoo Jin, Tuan Anh Nguyen, Eunmi Choi, Dugki Min   +7 more
wiley   +1 more source

Application of uncertainty design optimization based on polynomial chaos expansions and maximum entropy method in ship design

Zhongguo Jianchuan Yanjiu, 2023
ObjectivesThe key to uncertainty design optimization (UDO) is uncertainty quantification (UQ), but the traditionally used Monte Carlo (MC) method can be time-consuming and computationally expensive.
Xiao WEI, Heng LI, Chenran HUANG
doaj   +1 more source

Review of Memristors for In‐Memory Computing and Spiking Neural Networks

Advanced Intelligent Systems, EarlyView.
Memristors uniquely enable energy‐efficient, brain‐inspired computing by acting as both memory and synaptic elements. This review highlights their physical mechanisms, integration in crossbar arrays, and role in spiking neural networks. Key challenges, including variability, relaxation, and stochastic switching, are discussed, alongside emerging ...
Mostafa Shooshtari, Teresa Serrano‐Gotarredona, Bernabé Linares‐Barranco   +2 more
wiley   +1 more source

Efficient Solutions for Stochastic Fractional Differential Equations with a Neutral Delay Using Jacobi Poly-Fractonomials

Mathematics
This paper introduces a novel numerical technique for solving fractional stochastic differential equations with neutral delays. The method employs a stepwise collocation scheme with Jacobi poly-fractonomials to consider unknown stochastic processes.
Afshin Babaei, Sedigheh Banihashemi, Behrouz Parsa Moghaddam, Arman Dabiri, Alexandra Galhano   +4 more
doaj   +1 more source

Robust Trajectory Optimization of a Ski Jumper for Uncertainty Influence and Safety Quantification

Proceedings, 2018
This paper deals with the development of a robust optimal control framework for a previously developed multi-body ski jumper simulation model by the authors.
Patrick Piprek, Florian Holzapfel
doaj   +1 more source