Results 81 to 90 of about 1,643,808 (218)

Histidine Supplementation Stabilizes Hearing and Vision and Improves Growth in HARS1‐Related Autosomal Recessive Disorder Associated With Usher‐Like Symptoms

American Journal of Medical Genetics Part A, Volume 200, Issue 10, Page 2289-2308, October 2026.
ABSTRACT Autosomal recessive HARS1‐related disorder (originally described as Usher syndrome type 3B) caused by a homozygous Y454S variant in the histidyl‐tRNA synthetase gene (HARS1) is characterized by progressive sensorineural hearing and vision loss and respiratory deterioration with risk for sudden death following febrile illnesses.
Victoria Mok Siu, Rosan Kenana, Rana Chakrabarti, Sarah D. P. Wilhelm, Joseph Andrews, Susan J. Leat, Christina Parker, Michael Miller, Leslie A. Nangle, Wendy McCaul, Ashfia Chowdhury, Natalie Hutchings, Ryan A. Adams, Lauren Guy, Mandy Rhody, Verena Juncal, Marisa I. Mendes, Desiree E. C. Smith, Gajja S. Salomons, Angelica A. Moresco, Daphne L. McCulloch, D. Holmes Morton, Ilka U. Heinemann, C. Anthony Rupar   +23 more
wiley   +1 more source

A Probabilistic Fractional Order Physics Informed Mamba Kolmogorov‐Arnold Network for State‐of‐Charge Estimation in Grid‐Connected Battery Energy Storage Systems

Energy Science &Engineering, Volume 14, Issue 10, Page 4734-4751, October 2026.
This paper introduces the probabilistic fractional‐order Mam‐KAN (PFO‐Mam‐KAN) controller, a physics‐informed gray‐box framework for real‐time battery state‐of‐charge estimation. By unifying efficient Mamba encoders with uncertainty‐aware fractional physics, it achieves superior 0.31% RMSE accuracy and robust grid‐support operation under dynamic ...
Arun Kumar Rawat, Subhash Chandra, Vinay Kumar Deolia   +2 more
wiley   +1 more source

A RUL Prediction Method of Small Sample Equipment Based on DCNN-BiLSTM and Domain Adaptation

, 2022
To solve the problem of low accuracy of remaining useful life (RUL) prediction caused by insufficient sample data of equipment under complex operating conditions, an RUL prediction method of small sample equipment based on a deep convolutional neural ...
Yiqun Wang, Huixiang Liu, Yu Gu, Wenbai Chen, Weizhao Chen, Chunli Bi   +5 more
core   +1 more source

State‐of‐Charge Estimation of Second‐Life Batteries Using the Federated Learning

Energy Storage, Volume 8, Issue 7, October 2026.
ABSTRACT The advancement in automobile electrification has been causing concern about retired batteries. Since the battery cannot store and deliver energy for a high‐speed vehicle when its state of health (SOH) is below 80%, this battery must have another destination.
Joelton Deonei Gotz, José Rodolfo Galvão, Fernanda Cristina Corrêa, Milton Borsato, Alceu de Souza Britto Junior, Emilson Ribeiro Viana, Nathan Mendes, Alceu André Badin   +7 more
wiley   +1 more source

Integrating Machine Learning-Based Remaining Useful Life Predictions with Cost-Optimal Block Replacement for Industrial Maintenance

International Journal of Prognostics and Health Management
This study presents a preventive maintenance methodology to predict the remaining useful life (RUL) of mechanical systems and determine cost-effective replacement schedules.
Young-Suk Choo, Seung-Jun Shin
doaj   +1 more source

Prediction of Failure in Lithium‐Rich Cathode Half‐Cells Using Early‐Cycle Data

Materials Genome Engineering Advances, Volume 4, Issue 4, October 2026.
Using a dataset constructed from the performance evolution of Li‐rich cathode materials, a GBDT‐based model was developed for early half‐cell failure prediction. By using only data from the first 50 cycles, the model enables rapid identification of failure tendencies and provides an efficient tool for performance screening and evaluation.
Xiaoya Zhang, Jiayi Yao, Qi Liu, Zihao Dang, Pengfei Liu, Jingli Ren, Dongliang Peng   +6 more
wiley   +1 more source

Reliable Intelligent Diagnostics With Uncertainty Quantification for Mechanical System Condition Assessment

Quality and Reliability Engineering International, Volume 42, Issue 6, Page 2896-2916, October 2026.
ABSTRACT Health condition assessment of mechanical systems is essential to ensure their safe and reliable operation. Although AI‐driven diagnostic techniques have advanced significantly with the development of deep learning, the reliability of such techniques is often compromised due to the lack of uncertainty quantification (UQ)—particularly the ...
Guangjun Jiang, Haotian Ouyang, Zifei Xu
wiley   +1 more source

Remaining Life Prediction of Bearings Based on Improved IF-SCINet

IEEE Access
In the field of health management, predicting the remaining useful life (RUL) of a device becomes critical. However, the RUL prediction process is often affected by a various of confounding factors, resulting in reduced prediction accuracy.
Jing Zhang, Chao Zhang, Shuai Xu, Guiyi Liu, Hongbo Fei, Le Wu   +5 more
doaj   +1 more source

DCA-Based Real-Time Residual Useful Life Prediction for Critical Faulty Component

Journal of Control Science and Engineering, 2017
Residual useful life (RUL) prediction is significant for condition-based maintenance. Traditional data-driven RUL prediction method can only predict fault trend of the system rather than RUL of a specific system component.
Funa Zhou, Jiayu Wang, Yulin Gao
doaj   +1 more source

Aircraft engine turbine RUL prediction using NADINE

, 2020
RUL prediction has become a widely researched topic in recent years. This paper describes the use of the deep learning approach Neural Network with Dynamically Evolving Capability (NADINE) to overcome RUL prediction challenges used in static deep ...
Tsang, Aloysius Jin Hou
core