Results 41 to 50 of about 11,954,701 (266)

Synchronization‐Dissipation in the Cardiorespiratory System

Advanced Science, EarlyView.
By modeling central nervous coupling and viscoelastic interactions in the cardiorespiratory system we show that synchronization produces a 10% gain in cardiac efficiency in humans. It is surmised that respiratory sinus arrhythmia improves cardiac pumping efficiency by reducing dynamic stress and power dissipation in the pulmonary vasculature.
Joshua R. Border, Alain Nogaret, Andrew Lefevre, Vishal Jain   +3 more
wiley   +1 more source

Construction of exponentially fitted symplectic Runge-Kutta-Nyström methods from partitioned Runge-Kutta methods [PDF]

, 2014
In this work we derive exponentially fitted symplectic Runge-Kutta-Nystr¨om (RKN) methods from symplectic exponentially fitted partitioned Runge-Kutta (PRK) methods methods.
T. E. Simos, Zacharoula Kalogiratou, Kalogiratou, Z., Theodore Monovasilis, Monovasilis, Th., E. Simos, T.   +5 more
core   +1 more source

Derivation of Three-Derivative Two-Step Runge–Kutta Methods

Mathematics
In this paper, we develop explicit three-derivative two-step Runge–Kutta (ThDTSRK) schemes, and propose a simpler general form of the order accuracy conditions (p≤7) by Albrecht’s approach, compared to the order conditions in terms of rooted trees.
Xueyu Qin, Jian Yu, Chao Yan
doaj   +1 more source

DDSurfer: A Weakly‐Supervised Dual‐Stream Deep Learning Framework for Cortical Surface Reconstruction From Diffusion MRI

Advanced Science, EarlyView.
DDSurfer reconstructs cortical surfaces directly from diffusion MRI without requiring T1‐weighted scans. By fusing complementary microstructural features and learning diffeomorphic deformations, it efficiently generates accurate white matter and pial surfaces, improving geometric fidelity and morphometric reliability across datasets for robust surface ...
Chengjin Li, Wei Zhang, Xi Zhu, Yuqian Chen, Nir A. Sochen, Jarrett Rushmore, Carl‐Fredrik Westin, Yogesh Rathi, Lauren J. O'Donnell, Ofer Pasternak, Fan Zhang   +10 more
wiley   +1 more source

Additive Runge–Kutta methods for the resolution of linear parabolic problems [PDF]

, 2002
We study the consistency for general additive Runge–Kutta methods in the integration of linear nonhomogeneous problems, obtaining necessary and sufficient conditions of order p, for arbitrary values of p.
Bujanda, B. [0000-0001-7867-8805], Jorge, J.C., Jorge, J.C. [0000-0001-5906-6125], Bujanda, B.   +3 more
core   +1 more source

Efficient numerical methods for Volterra integral equations of Hammerstein type [PDF]

, 2006
Volterra integral equations (VIEs) are the mathematical model of many evolutionary problems with memory arising from biology, chemistry, physics, engineering.
Del Prete, Ida
core   +1 more source

Continuous-Stage Runge–Kutta Approximation to Differential Problems

Axioms, 2022
In recent years, the efficient numerical solution of Hamiltonian problems has led to the definition of a class of energy-conserving Runge–Kutta methods named Hamiltonian Boundary Value Methods (HBVMs).
Pierluigi Amodio, Luigi Brugnano, Felice Iavernaro   +2 more
doaj   +1 more source

Internal Resonance Mismatch‐Controlled Dissipative Bistability Collapse in Coupled Micromechanical Oscillators

Advanced Science, EarlyView.
This paper reveals internal resonance mismatch‐controlled dissipative bistability collapse in a coupled micromechanical resonator. Tuning δIR changes both internal‐mode amplitude and phase‐dependent feedback. For negative mismatch, Duffing bistability survives.
Jianlin Chen, Xin Zhou, Takashiro Tsukamoto, Nan Wang, Shuji Tanaka   +4 more
wiley   +1 more source

Structure-preserving Runge-Kutta methods for stochastic Hamiltonian equations with additive noise [PDF]

, 2014
There has been considerable recent work on the development of energy conserving one-step methods that are not symplectic. Here we extend these ideas to stochastic Hamiltonian problems with additive noise and show that there are classes of Runge-Kutta ...
Burrage, Pamela, Burrage, Kevin
core   +1 more source

Enhanced High Dimensionality and the Information Processing Capacity in Interfered Spin Wave‐Based Reservoir Computing, Achieved With Eight Detectors

Advanced Electronic Materials, EarlyView.
Physical reservoir computing (PRC) based on spin wave interference has demonstrated high computational performance, yet room for improvement remains. In this study, we fabricated this concept PRC with eight detectors and evaluated the impact of the number of detectors using a chaotic time series prediction task.
Sota Hikasa, Wataru Namiki, Daiki Nishioka, Maki Nishimura, Ryo Iguchi, Kazuya Terabe, Takashi Tsuchiya   +6 more
wiley   +1 more source