Results 151 to 160 of about 15,714,929 (285)

Causal‐Guided Ultra‐Long‐Term Time Series Forecasting Via Anticipated Covariates

Advanced Science, EarlyView.
Often treated as unknown, information from the future remains underutilized.We demonstrate that in a coupled dynamical system, providing the future state of the effect enables accurate forecasting of the cause for a long timesteps. A time series forecasting paradigm that introduces anticipated covariates to represent such known future states is ...
Jintong Zhao, Yufei Liu, Ruixi Huang, Zhongxue Gan, Siyang Leng   +4 more
wiley   +1 more source

Exact Discrete Stochastic Simulation With Deep‐Learning‐Scale Gradient Optimization

Advanced Science, EarlyView.
A 203,796‐parameter gene regulatory network classifies handwritten digits with 98.4% accuracy using exact stochastic dynamics. The framework decouples forward simulation from backward differentiation, making continuous‐time Markov chain models compatible with deep‐learning optimization.
Jose M. G. Vilar, Leonor Saiz
wiley   +1 more source

Deep Learning Network‐Tailored Microenvironment Matching of 4D Bioprinting Bioactive Scaffolds for Bone Regeneration

Advanced Science, EarlyView.
A DLN dataset was built to analyze MABS composition versus in vitro/in vivo osteogenesis and angiogenesis. An MLP neural network, taking BG morphological parameters as input, extracts bioactive features from these datasets. A rabbit tibial defect model then validates 4D‐printed MABS for adaptability and bone regeneration in critical defects.
Xiongjie Liang, Yuechi Zhang, Weifeng Hu, Shiyan Lv, Fan Jia, Yan Zhang, Feng Wu, Changjiang Yang, Guanqi Zhen, Jinglong Yan, Xu Cui, Wei Zhao, Guanghua Chen   +12 more
wiley   +1 more source

Study on Finite Element Model Updating in Highway Bridge Static Loading Test Using Spatially-Distributed Optical Fiber Sensors. [PDF]

Sensors (Basel), 2017
Wu B, Lu H, Chen B, Gao Z.
europepmc   +1 more source

Discovering Early‐Stage Gas Generation Kinetics Enables Thermal Runaway Early Warning in Lithium‐Ion Batteries

Advanced Science, EarlyView.
Operando gas diagnostics reveal a previously unrecognized chemical activation (CA) stage during thermal runaway in lithium‐ion batteries. A physics‐informed gas generation kinetics network (GGKNet) is developed to reconstruct reaction pathways and physical models automatically.
Jiabo Zhang, Qianzhen Guo, Shuaiqi Liu, Shuai Li, Xianghao Kong, Dong Han, Zhen Huang   +6 more
wiley   +1 more source

Finite Element Model Updating for a Continuous Beam-Arch Composite Bridge Based on the RSM and a Nutcracker Optimization Algorithm. [PDF]

Sensors (Basel)
Zhou W, Yang H, Hao J, Zhai M, Cao H, Liu Z, Wang K.   +6 more
europepmc   +1 more source

Finite element model updating of aerospace structures

, 2017
Model updating methods can be used to obtain more accurate mathematical models. Results of linear finite element models which can be assumed as mathematical models for structural dynamics studies almost never match with the real test results.
DOĞUŞ ÜNLÜ
core  

Time Resolved DNA Barcodes for Information Encoding and Dynamic Encryption

Advanced Science, EarlyView.
This study establishes a molecular information platform based on DNA Temporal Barcodes. Information is encoded through combinations of DNA tags with distinct retention times, while dynamic encryption is achieved through a key‐triggered DNA ligation.
Likang Chu, Haixia Wang, Haiyan Gao, Sixian Chen, Zilong Li, Zhanyihao Hao, Lei He, Da Han   +7 more
wiley   +1 more source

Characterising Through-Thickness Shear Anisotropy Using the Double-Bridge Shear Test and Finite Element Model Updating. [PDF]

Materials (Basel)
Starman B, Chen B, Maček A, Zhang Y, Halilovič M, Coppieters S.   +5 more
europepmc   +1 more source

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