Results 71 to 80 of about 7,904 (148)

Blasting effects of cross‐fault deep‐buried excavation on adjacent existing tunnel stability

Deep Underground Science and Engineering, EarlyView.
Based on the theoretical analysis of cylindrical wave propagation in a deep rock mass in the fault with a filling layer, the calculation method of peak particle velocity caused by wave propagation in the existing tunnel is established. The viscoelastic characteristics of a rock mass are examined in the analysis.
Shaobo Chai, Lianzeng Chai, Chao Meng, Kai Liu, Lang Song, Shaojie Zheng   +5 more
wiley   +1 more source

A contemporary simple risk score for prediction of severe acute kidney injury after heart transplantation

ESC Heart Failure, Volume 12, Issue 2, Page 1166-1175, April 2025.
A contemporary simple risk score for prediction of severe AKI after HT. Abstract Background The aim of this study was to develop a simple risk score to estimate severe acute kidney injury (AKI) risk based on a large contemporary heart transplantation (HT) cohort.
Shuangshuang Zhu, Weihua Qiao, Yixuan Wang, Ying Zhou, Yin Xu, Shijie Wang, Tian Xia, Guohua Wang, Si Chen, Jiawei Shi, Nianguo Dong   +10 more
wiley   +1 more source

Research on Thermal Runaway Multiphysics Coupling Simulation and Sensor Optimization Layout of Lithium Iron Phosphate Energy Storage Battery Packs

Energy Science &Engineering, EarlyView.
This study explores thermal runaway in lithium‐iron‐phosphate energy storage battery packs through multi‐physics coupling simulation. Thermal runaway evolves from battery cells (experiencing overcharge, bulging, safety valve opening, and gas venting) to battery clusters (a) and propagates within the battery pack (b). Simulation results indicate: stress
Dongliang Guo, Lei Sun, Rong Sun, Jun Jia, Peng Xiao, Hailong Ruan, Xin Jiang   +6 more
wiley   +1 more source

Machine Learning and Artificial Intelligence Techniques for Intelligent Control and Forecasting in Energy Storage‐Based Power Systems

Energy Science &Engineering, EarlyView.
A new energy paradigm assisted by AI. ABSTRACT The tremendous penetration of renewable energy sources and the integration of power electronics components increase the complexity of the operation and power system control. The advancements in Artificial Intelligence and machine learning have demonstrated proficiency in processing tasks requiring ...
Balasundaram Bharaneedharan, Suresh Panchanathan, Chan Choon Kit, Elumalai Perumal Venkatesan, Nasim Hasan   +4 more
wiley   +1 more source

Most totally real fields do not have universal forms or the Northcott property. [PDF]

Proc Natl Acad Sci U S A
Daans N, Kala V, Man SH, Widmer M, Yatsyna P.   +4 more
europepmc   +1 more source

Intelligent Control Framework of District Heating Systems Considering Waste Heat Utilization in Data Centers

Energy Science &Engineering, EarlyView.
A deep reinforcement learning–based control architecture is proposed to coordinate heat pumps, thermal storage, renewable energy, and demand response in data center waste heat recovery systems. The agent learns optimal control actions from system states and reward feedback to achieve electrical–thermal co‐optimization under realistic operational ...
Rendong Shen, Ruifan Zheng, Shengyuan Zhong, Lei Gu, Dongfang Yang, Jun Zhao   +5 more
wiley   +1 more source

On Algebraic Properties of Primitive Eisenstein Integers with Applications in Coding Theory. [PDF]

Entropy (Basel)
Hadi A, Isnaini U, Wijayanti IE, Ezerman MF.   +3 more
europepmc   +1 more source

A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios

Journal of Forecasting, EarlyView.
ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley   +1 more source

On Quantum Ergodicity for Higher Dimensional Cat Maps. [PDF]

Commun Math Phys
Kurlberg P, Ostafe A, Rudnick Z, Shparlinski IE.   +3 more
europepmc   +1 more source

Forecasting Count Data With Varying Dispersion: A Latent‐Variable Approach

Journal of Forecasting, EarlyView.
ABSTRACT Count data, such as product sales and disease case counts, are common in business forecasting and many areas of science. Although the Poisson distribution is the best known model for such data, its use is severely limited by its assumption that the dispersion is a fixed function of the mean, which rarely holds in real‐world scenarios.
Easton Huch, Candace Berrett, Mason Ferlic, Kimberly F. Sellers   +3 more
wiley   +1 more source