Results 131 to 140 of about 13,618 (231)

A Review of Vagus Nerve Stimulation for Disease: Comprehensive Theory and Evidence for Mechanisms of Action

Comprehensive Physiology, Volume 16, Issue 2, April 2026.
Vagus nerve stimulation (VNS) effects span central and peripheral organ systems through diverse mechanistic pathways. This comprehensive review provides a unified synthesis of these mechanisms across neurological, cardiovascular, immunological, metabolic, and gastrointestinal domains, filling a critical gap and serving as a foundational resource for ...
Yifeng Bu, Alex Liang, Benjamin U. Hoffman, Dawn M. Schiehser, Oliver Case, Alan Simmons, Ruth Klaming, Andres Gottfried‐Blackmore, Ravinder K. Mittal, Christopher Puleo, Hubert Lim, Imanuel Lerman   +11 more
wiley   +1 more source

Endemic Mediterranean seagrasses poised to survive climate change challenges

Ecological Applications, Volume 36, Issue 3, April 2026.
Abstract Understanding the current and future trajectories of critical habitats is essential for biodiversity conservation and ecosystem management, especially in semi‐enclosed environments such as the Mediterranean Sea. Endemic habitats in the Mediterranean, such as Posidonia meadows, are crucial for marine biodiversity, nutrient cycling, oxygen ...
Francesco Paolo Mancuso, Mar Bosch‐Belmar, Mario Francesco Tantillo, Martina Russi, Viviana Piermattei, Marco Marcelli, Gianluca Sarà   +6 more
wiley   +1 more source

Non-autonomous Koopman operator family spectrum

, 2018
Poincar e at the beginning of XX-th century, and then Carleman, Koopman and von Neumann in the 1920-is made their visionary contributions to the analysis of dynamical systems behavior through the analysis of the spectral properties of the associated Koopman operator.
Maćešić, Senka, Črnjarić-Žic, Nelida, Mezić, Igor   +2 more
openaire   +2 more sources

A deep Koopman operator‐based modelling approach for long‐term prediction of dynamics with pixel‐level measurements

CAAI Transactions on Intelligence Technology
Although previous studies have made some clear leap in learning latent dynamics from high‐dimensional representations, the performances in terms of accuracy and inference time of long‐term model prediction still need to be improved. In this study, a deep
Yongqian Xiao, Zixin Tang, Xin Xu, Xinglong Zhang, Yifei Shi   +4 more
doaj   +1 more source

Optimal Control of Entity-Based Systems via Koopman Representations With Product Density Observables

IEEE Open Journal of Control Systems
The Koopman operator, which describes a dynamical system via a linear representation that can be approximately learned from data, allows application of linear control techniques to nonlinear systems.
Madeline Blischke, Joao P. Hespanha
doaj   +1 more source

Optimality Deviation using the Koopman Operator

This paper investigates the impact of approximation error in data-driven optimal control problem of nonlinear systems while using the Koopman operator. While the Koopman operator enables a simplified representation of nonlinear dynamics through a lifted state space, the presence of approximation error inevitably leads to deviations in the computed ...
Lin, Yicheng, Wu, Bingxian, Bai, Nan, Ren, Yunxiao, Duan, Zhisheng   +4 more
openaire   +2 more sources

Electronic Correlation Effects in the Response of Graphene and MoS2 Monolayers to the Impact of Highly‐Charged Ions

physica status solidi (b), Volume 263, Issue 4, April 2026.
The response of graphene and MoS2 monolayers to highly‐charged impinging ions is investigated using nonequilibrium Green functions theory. Electronic correlations are found to have a significantly stronger influence on the ultrafast ion‐induced electron dynamics in MoS2 than in graphene.
Giorgio Lovato, Michael Bonitz, Karsten Balzer, Fabio Caruso, Jan‐Philip Joost   +4 more
wiley   +1 more source

Koopman Spectral Linearization vs. Carleman Linearization: A Computational Comparison Study

Mathematics
Nonlinearity presents a significant challenge in developing quantum algorithms involving differential equations, prompting the exploration of various linearization techniques, including the well-known Carleman Linearization.
Dongwei Shi, Xiu Yang
doaj   +1 more source

The distributional Koopman operator for random dynamical systems

Mathematics of Control, Signals, and Systems
The Distributional Koopman Operator (DKO) is introduced as a way to perform Koopman analysis on random dynamical systems where only aggregate distribution data is available, thereby eliminating the need for particle tracking or detailed trajectory data.
Oprea, Maria, Townsend, Alex, Yang, Yunan   +2 more
openaire   +2 more sources

Toward an Analytical Solution of the Liouville Equation via Data‐Driven Methods: Applications to Ensemble Forecasting

Journal of Advances in Modeling Earth Systems, Volume 18, Issue 4, April 2026.
Abstract Solving probabilistic weather forecasts is challenging due to computational constraints and the nonlinear nature of Earth atmosphere. This study proposes a proof‐of‐concept to address these challenges by solving the Liouville equation, that is, the analytical solution for probabilistic forecasts, with data‐driven method.
Kai‐Chih Tseng, Ray Kuo, Yi‐An Feng
wiley   +1 more source