Results 111 to 120 of about 51,507 (261)

A Closed‐Loop Framework for Inverse Design: Dynamic Training and Intelligent Optimization for Heterostructured Materials

Advanced Science, EarlyView.
To accelerate the inverse design of heterostructured metal matrix composites, a closed‐loop scientific machine learning framework integrates continual learning prediction with NSGA‐II‐PMCP optimization. The framework maps microstructural descriptors to strength, toughness, and modulus, expands high‐quality Pareto solutions, and guides experimentally ...
Zhiyan Zhong, Xueru Zheng, Xiao Zhou, Zhengheng Tao, Wan Han, Jingyi Pan, Dian Wu, Ning Gao, Lei Liu, Zhongyang Wang, Fanchao Meng, Tongxiang Fan   +11 more
wiley   +1 more source

Deep‐Learning‐Driven High‐Fidelity In Vivo Hyperspectral Fluorescence Imaging Under Extreme Photon‐Limited Conditions

Advanced Science, EarlyView.
Highly overlapping fluorescent signals become distinguishable in photon‐limited living organisms via advanced imaging with intelligent reconstruction. The resulting in vivo hyperspectral imaging capability reveals nanoplastic uptake and circulation in live zebrafish, providing a new approach for studying complex biological and environmental processes ...
Renjian Li, Shutao Wu, Kaixiang Li, Zhenyu An, Yuwen Ben, Guiye LI, Sunil Kumar, James Mcginty, Tawfique Hasan, Songnian Fu, Meng Zhang, LingLing Chen   +11 more
wiley   +1 more source

Bayesian Neural Network-Assisted Parameter Estimation of the Transmuted Teissier Distribution for Environmental Data Modeling

IEEE Access
Machine learning has evolved into a potent tool for analysing patterns and making predictions from complex data. In this machine learning era, we employed neural network techniques to estimate the parameters of statistical distributions.
P. T. Amrutha, C. S. Rajitha
doaj   +1 more source

Employment of Self-Adaptive Bayesian Neural Network for Systematic Antenna Design: Improving Wireless Networks Functionalities. [PDF]

Micromachines (Basel), 2023
Aliqab K, Sohaib MA, Ali F, Armghan A, Alsharari M.   +4 more
europepmc   +1 more source

Systematic Multi‐Level Analyses Decode the Arthritis‐Neurodegeneration Axis With In Vivo Validation

Advanced Science, EarlyView.
Arthritis and neurodegeneration are usually studied as separate disorders, but this study connects them through population evidence, genetic inference, transcriptomic mapping, and mouse models. It highlights RNF40 as a context‐dependent joint‐brain candidate, induced in inflammatory joints yet functionally linked to dopamine‐neuron vulnerability ...
Jinwen Wang, Wenhui Xie, Lei Yang, Zhengrong Wang, Yi Huang, Peng Huang, Yuan Liu, Jun Hu   +7 more
wiley   +1 more source

Modelling daily plant growth response to environmental conditions in Chinese solar greenhouse using Bayesian neural network. [PDF]

Sci Rep, 2023
Mohmed G, Heynes X, Naser A, Sun W, Hardy K, Grundy S, Lu C.   +6 more
europepmc   +1 more source

Livestock Multi‐Omics Integration: A Systematic Framework From Statistical Association to Causal Interpretation

Advanced Science, EarlyView.
A three‐tier livestock multi‐omics framework resolves four typical analytical pitfalls. Moving from statistical association through machine learning preprocessing to triple‐modal causal inference, it converts omics results into genomic selection and gene editing strategies to achieve One Health, underpinned by multi‐omics data, multimodal sequencing ...
Jiying Wen, Zhongyu Wang, Jieping Huang, Fen Li, Ningbo Chen, Yun Ma   +5 more
wiley   +1 more source

Accelerating Stellar Photometric Distance Estimates with Neural Networks

The Astronomical Journal
Building on the Bayesian approach to estimating stellar distances from broadband photometry, we show that the computation can be accelerated by about an order of magnitude by using neural networks. Focusing on the case of the ugrizy filter complement for
Karlo Mrakovčić, Željko Ivezić, Lovro Palaversa   +2 more
doaj   +1 more source

EpICC: A Bayesian neural network model with uncertainty correction for a more accurate classification of cancer. [PDF]

Sci Rep, 2022
Joshi P, Dhar R.
europepmc   +1 more source

Unveiling the Uncharted Potential of 2D Materials in Li/Na–S Batteries: A Paradigm Shift From Graphene

Advanced Science, EarlyView.
This review explores emerging 2D materials beyond graphene, including graphdiyne, phosphorene, borophene, siloxene, MBene, antimonene, and germanene for Li/Na–S batteries. It analyzes their roles as sulfur hosts, metallic anode protectors, separators, and electrolyte fillers, emphasizing polysulfide suppression, dendrite inhibition, and interfacial ...
Naveen Kumar T. R, Xuebing Zhu, Yao‐Jie Lei, Lei Zhang, Hua Kun Liu, Weihong Lai, Guoxiu Wang, Yun‐Xiao Wang   +7 more
wiley   +1 more source