Article
Mathematics, Interdisciplinary Applications
Ying Xu, Guodong Ren, Jun Ma
Summary: This paper investigates the electric activity in myocardial tissue and the impact of external electromagnetic radiation on its stability and wave propagation. A memristive cardiac tissue model is developed by incorporating magnetic flux variable and induction current. The results show that external electromagnetic radiation can control the wave propagation in cardiac tissue and generate specific spatial patterns.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Biology
Naoki Tomii, Masatoshi Yamazaki, Takashi Ashihara, Kazuo Nakazawa, Nitaro Shibata, Haruo Honjo, Ichiro Sakuma
Summary: Through numerical simulations, it was found that conduction blocks induce discontinuous boundaries in spatial phase maps of cardiac spiral waves, providing a more appropriate model of the wave center than phase singularities.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Biology
Youssef Belhamadia, Zeinab Rammal
Summary: This study introduces three ADI schemes for efficient solution of the nonlinear cardiac monodomain model, aiming to reduce computational time and memory consumption. The proposed methods have second order accuracy and evaluate the ionic model only once per time-step. Large-scale two- and three-dimensional simulations show higher efficiency of the proposed methods.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Physics, Multidisciplinary
Jian Gao, Changgui Gu, Huijie Yang
Summary: This study successfully eliminated spiral waves in cardiac muscle through global pulse disturbance, reducing the frequency of cardiac muscle and returning the medium to normal oscillation state, thereby preventing ventricular tachycardia and ventricular fibrillation.
Article
Physics, Fluids & Plasmas
Qi-Hao Li, Enid Van Nieuwenhuyse, Yuan-Xun Xia, Jun-Ting Pan, Mattias Duytschaever, Sebastien Knecht, Nele Vandersickel, Changsong Zhou, Alexander Panfilov, Hong Zhang
Summary: This paper presents a new method, AFV-DT, for finding the sources of cardiac excitation waves. Utilizing techniques from optical flow analysis and determinant-trace method, this approach can accurately determine different types of wave sources and is stable against low spatial resolution and noise. In clinical cases of arrhythmia, the method can correctly identify and locate the issues.
Article
Mathematics, Applied
Shahrokh Shahi, Flavio H. Fenton, Elizabeth M. Cherry
Summary: This paper introduces an integrated architecture for predicting complex signals during cardiac arrhythmias using machine learning methods. Results show that the proposed approach outperforms other methods in predicting action potentials, with smaller mean absolute errors and less sensitivity to algorithmic parameter settings.
Article
Mathematics, Interdisciplinary Applications
Yipeng Hu, Qianming Ding, Yong Wu, Ya Jia
Summary: This study investigates the effect of electric fields on spiral waves in discontinuous myocardial tissue caused by cellular structures. The research finds that a constant electric field can induce the drift of spiral waves, a polarized electric field of specific intensity and angular frequency can induce linear drift of spiral waves, and the drift of spiral waves in a predictable direction can be controlled by adjusting the phase difference of the electric field and the initial phase of the spiral wave.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Physiology
Louise Arno, Jan Quan, Nhan T. Nguyen, Maarten Vanmarcke, Elena G. Tolkacheva, Hans Dierckx
Summary: Our analysis of ventricular tachycardia in rabbit hearts shows that nearly all detected PSs were found on PDLs, but the PDLs had a significantly longer lifespan than the detected PSs. The proposed framework revisits basic building blocks of cardiac activation patterns and can become a useful tool for further theory development and experimental analysis.
FRONTIERS IN PHYSIOLOGY
(2021)
Article
Computer Science, Interdisciplinary Applications
Youssef Belhamadia, Thomas Briffard, Andre Fortin
Summary: This paper investigates the efficiency of a parallel anisotropic mesh adaptation method for solving the bidomain model in electrocardiology. The computational efficiency is evaluated by computing spiral and scroll waves in cardiac tissue.
JOURNAL OF COMPUTATIONAL SCIENCE
(2022)
Article
Physics, Multidisciplinary
Mahesh Kumar Mulimani, Soling Zimik, Rahul Pandit
Summary: This study investigates the electrophysiological factors affecting the dynamics of spiral waves in cardiac tissue. It demonstrates that changes in cellular parameters and intercellular factors can modulate the frequency of spiral waves and provides insights into the anchoring of spiral waves in fibrotic hearts.
FRONTIERS IN PHYSICS
(2022)
Article
Engineering, Multidisciplinary
Sumit Kumar Vishwakarma, Rupinderjit Kaur
Summary: This article investigates the propagation behavior of SV-wave, SH-wave, and P-wave in continuously inhomogeneous cross-anisotropic material. Mathematical expressions for displacement components and quasi-wave velocities have been derived, and numerical examples illustrate the dependency of phase velocity on phase angle and inhomogeneity coefficients. The study observes that changes in material anisotropy greatly affect the magnitude of phase velocity.
APPLIED MATHEMATICAL MODELLING
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Verena Brandt, Raffi Bekeredjian, U. Joseph Schoepf, Akos Varga-Szemes, Tilman Emrich, Gilberto J. Aquino, Josua Decker, Richard R. Bayer, Lauren Ellis, Ullrich Ebersberger, Christian Tesche
Summary: This study aimed to determine the prognostic implication of EAT volume, CCTA-derived plaque quantification, and CT-FFR for major adverse cardiac events (MACE) and found that a combination of these parameters significantly improved the prediction performance. EAT volume, CCTA >= 50% stenosis, and CT-FFR were significantly different in patients who developed MACE, highlighting their potential as predictors for adverse cardiac events.
EUROPEAN JOURNAL OF RADIOLOGY
(2022)
Article
Physics, Multidisciplinary
H. Y. Huang, A. Singh, C. Y. Mou, S. Johnston, A. F. Kemper, J. van den Brink, P. J. Chen, T. K. Lee, J. Okamoto, Y. Y. Chu, J. H. Li, S. Komiya, A. C. Komarek, A. Fujimori, C. T. Chen, D. J. Huang
Summary: Quantum phase transitions are crucial in shaping the phase diagram of high-temperature cuprate superconductors, with evidence found for the role of charge order in the compound La2-xSrxCuO4 (LSCO) impacting phonon softening. These results provide insight into the quantum critical scaling and discommensurations associated with charge order in LSCO.
Article
Physics, Fluids & Plasmas
Kritsana Khaothong, Jarin Osaklung, Malee Sutthiopad, Jiraporn Luengviriya, Kenneth Showalter, Chaiya Luengviriya
Summary: This study investigates the effects of excitability on the dynamics of partially pinned scroll waves in three-dimensional Belousov-Zhabotinsky excitable media. The study reveals that increasing excitability leads to a faster transition to a twisted wave structure and a higher development speed. In addition, the study finds a correlation between the average speed and twist rate of the scroll waves and the difference in initial frequency.
Article
Mathematics, Applied
Karthikeyan Rajagopal, Sajad Jafari, Anitha Karthikeyan, Ashokkumar Srinivasan
Summary: Master stability functions are significant tools for identifying the synchronizability of nonlinear dynamical systems. By studying the MSF in a network of coupled oscillators, synchronization can be achieved, with magnetic flux coupling increasing synchronization of coupled neurons.
Article
Mathematics, Applied
Feifei Yang, Ying Xu, Jun Ma
Summary: Connecting memristors enhances potential controllability; magnetic flux-controlled memristor estimates electromagnetic induction effect; charge-controlled memristor estimates external electric field effect.
Article
Mathematics, Interdisciplinary Applications
Ying Xu, Guodong Ren, Jun Ma
Summary: This paper investigates the electric activity in myocardial tissue and the impact of external electromagnetic radiation on its stability and wave propagation. A memristive cardiac tissue model is developed by incorporating magnetic flux variable and induction current. The results show that external electromagnetic radiation can control the wave propagation in cardiac tissue and generate specific spatial patterns.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Mathematics, Interdisciplinary Applications
Lei Ren, Ming-Hung Lin, Abdulkareem Abdulwahab, Jun Ma, Hassan Saberi-Nik
Summary: In this paper, the dynamical behavior of the integer and fractional 4D hyperchaotic Rabinovich system is investigated. An optimization problem is solved analytically using the Lagrange coefficient method to find an accurate ultimate bound set (UBS) for the system. The bifurcation diagrams, Lyapunov exponents, global attractive sets, and positive invariant sets of the fractional-order system are also studied. Furthermore, the Mittag-Leffler GAS and Mittag-Leffler PIS of the proposed system are estimated using the Mittag-Leffler function and Lyapunov function method.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Mathematics, Interdisciplinary Applications
Ping Zhou, Jun Ma, Ying Xu
Summary: In this paper, the use of a voltage-controlled resistor to connect two neural circuits and the activation of a hybrid synapse to control synchronization stability and mode transition in neurons under phase lock are investigated. It is demonstrated that realistic stimuli consisting of mixed signals within a specific frequency band can induce multiple firing modes in neurons. The effectiveness of a hybrid synapse in preventing bursting synchronization between neurons driven by filtered chaotic signals is confirmed. The results suggest that activation of this hybrid synapse can help prevent seizure occurrence in the nervous system.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Mathematics, Applied
Feifei Yang, Ya Wang, Jun Ma
Summary: The field energy in neuron can be changed under shape deformation due to external energy injection. Stimulating neurons in the same region enables energy pumping through electromagnetic field superposition, and synaptic connection can be created for local energy balance. Neurons in the network maintain energy balance through continuous energy propagation and exchange, with identical neurons forming a homogeneous state and non-identical ones supporting gradient spatial patterns. This study improves the Fitzhugh-Nagumo neural circuit by adding a thermistor and a phototube, making the neuron sensitive to light and temperature. The energy diversity between neurons controls heterogeneity and defects in the network, and local energy injection regulates the firing patterns by modulating wave propagation.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2023)
Article
Physics, Multidisciplinary
Bo Hou, Ping Zhou, Guodong Ren, Jun Ma
Summary: External stimulus and noisy disturbance can inject energy into nonlinear systems and regulate the energy propagation between different circuits to control the oscillatory states. In this study, memristive synapse is activated under energy diversity to control the coupling channels between Chua circuits. The local energy balance helps develop regular spatial patterns and the memristive channel plays a role in increasing synchronization factor.
EUROPEAN PHYSICAL JOURNAL PLUS
(2023)
Article
Automation & Control Systems
Han Bao, Mengjie Hua, Jun Ma, Mo Chen, Bocheng Bao
Summary: In this article, a Memristor synapse with activated synaptic plasticity is introduced as an adaptive connection synaptic weight. An improved Hopfield neural network with two memristive self-connection synaptic weights is presented to demonstrate its kinetic effects. The stability distributions of the network are analyzed by analyzing the two nonzero roots of the eigenvalue polynomial. Bifurcation behaviors and phase portraits are used to investigate the parameter-related behaviors. Furthermore, the kinetic effects of memristor synapses are demonstrated by taking the memristor initial conditions as two invariant measures.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Physics, Multidisciplinary
Yitong Guo, Ying Xie, Jun Ma
Summary: This paper investigates the energy exchange and synchronization patterns of memristive neurons controlled by magnetic flux under spatial radiation. By using field coupling instead of synaptic coupling, the development of complete synchronization and regular patterns is hindered by introducing noise and spatial disturbances.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
Article
Physics, Multidisciplinary
Bo Hou, Xikui Hu, Yitong Guo, Jun Ma
Summary: This paper presents two kinds of memristors used as memristive channels to build a new neural circuit that can sense both external magnetic and electric fields. The energy proportion of the memristive channels is controlled to achieve mode selection and transition in the firing patterns. Noisy disturbance is applied to identify the occurrence of stochastic resonance in this memristive neuron.
Article
Engineering, Multidisciplinary
Han Bao, KeXin Li, Jun Ma, ZhongYun Hua, Quan Xu, BoCheng Bao
Summary: This paper presents an improved ID-Rulkov neuron model by coupling a memristor with a discrete Rulkov neuron model, and investigates the dynamic effects of the memristor on the neuron model. The experimental results demonstrate that the memristor enhances the diversity of the neuron model and generates hyperchaotic attractors.
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2023)
Article
Engineering, Multidisciplinary
FuQiang Wu, YiTong Guo, Jun Ma
Summary: In the presence of external stimuli and electromagnetic radiation, biological neurons can exhibit different firing patterns and switch to appropriate firing modes due to intrinsic self-adaption. Memristive synapses coupled to neurons can discern the effect of electromagnetic radiation and can be effectively regulated by external physical fields. Moreover, the energy flow in the memristive channel plays a crucial role in controlling the growth and enhancement of memristive synapses. The findings contribute to the understanding of why and how multiple firing modes are induced and controlled, as well as the self-adaption property of memristive neurons.
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2023)
Article
Physics, Multidisciplinary
Feifei Yang, Jun Ma
Summary: In this study, a neural circuit was rebuilt using a thermistor and a photocell, making it sensitive to external temperature and illumination. A magnetic flux-controlled memristor was used to connect the neural circuits, with its coupling channel adaptively controlled by energy diversity. The involvement of memristive synapses activated the ability for energy pumping and storage via magnetic field, allowing for controlled energy propagation along the memristive channel. It was found that by enhancing the magnetic field coupling via memristor, neurons could achieve complete synchronization and energy balance.
PRAMANA-JOURNAL OF PHYSICS
(2023)
Article
Computer Science, Artificial Intelligence
D. Vignesh, Jun Ma, Santo Banerjee
Summary: In this article, a discrete fractional Hopfield neural network model is proposed to investigate the influence of external stimuli in the presence of electromagnetic induction and radiation. The network model exhibits chaotic dynamics and coexisting behavior. The study also explores the generation of multi-scroll attractors by varying the level of the pulse function introduced to electromagnetic induction. The findings contribute to our understanding of discrete fractional memristors and shed light on the dynamical behavior of neurons and their electrical activity in the brain.
Article
Computer Science, Artificial Intelligence
Fuqiang Wu, Hao Meng, Jun Ma
Summary: Employing electronic components such as memristor and Josephson junction to imitate biological neurons and synapses has been a popular research topic in recent years. This paper revisits a previous work on memristive Josephson junction and proposes a new model called inductive memristive Josephson junction (L-MJJ) by adding an inductor with internal resistor. The L-MJJ model can reproduce the square-wave bursting behavior of classical neuronal models and achieve bursting synchronization similar to nonlinear coupling neurons. This research aims to build a bridge between superconducting physics and theoretical neuroscience, and demonstrates the potential feasibility of using this junction in designing neuron-inspired computations for larger-scale neuromorphic networks.
Article
Mathematics, Applied
Jun Ma
Summary: Continuous dynamical systems with different nonlinear terms can exhibit rich dynamical characteristics. In this study, reliable algorithms for discretization and equivalent maps are proposed to reproduce similar dynamics as the nonlinear oscillators. The application of scale transformation helps convert maps into equivalent nonlinear oscillators and define energy function. Additionally, a generic memristive term is introduced into the map, which can be used to develop memristive oscillators and clarify the energy function and oscillatory characteristics.
APPLIED MATHEMATICS AND COMPUTATION
(2024)
Article
Physics, Multidisciplinary
Xiaoyu Shi, Jian Zhang, Xia Jiang, Juan Chen, Wei Hao, Bo Wang
Summary: This study presents a novel framework using offline reinforcement learning to improve energy consumption in road transportation. By leveraging real-world human driving trajectories, the proposed method achieves significant improvements in energy consumption. The offline learning approach demonstrates generalizability across different scenarios.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Junhyuk Woo, Soon Ho Kim, Hyeongmo Kim, Kyungreem Han
Summary: Reservoir computing (RC) is a new machine-learning framework that uses an abstract neural network model to process information from complex dynamical systems. This study investigates the neuronal and network dynamics of liquid state machines (LSMs) using numerical simulations and classification tasks. The findings suggest that the computational performance of LSMs is closely related to the dynamic range, with a larger dynamic range resulting in higher performance.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Yuwei Yang, Zhuoxuan Li, Jun Chen, Zhiyuan Liu, Jinde Cao
Summary: This paper proposes an extreme learning machine (ELM) algorithm based on residual correction and Tent chaos sequence (TRELM-DROP) for accurate prediction of traffic flow. The algorithm reduces the impact of randomness in traffic flow through the Tent chaos strategy and residual correction method, and avoids weight optimization using the iterative method. A DROP strategy is introduced to improve the algorithm's ability to predict traffic flow under varying conditions.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Chengwei Dong, Min Yang, Lian Jia, Zirun Li
Summary: This work presents a novel three-dimensional system with multiple types of coexisting attractors, and investigates its dynamics using various methods. The mechanism of chaos emergence is explored, and the periodic orbits in the system are studied using the variational method. A symbolic coding method is successfully established to classify the short cycles. The flexibility and validity of the system are demonstrated through analogous circuit implementation. Various chaos-based applications are also presented to show the system's feasibility.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Viorel Badescu
Summary: This article discusses the maximum work extraction from confined particles energy, considering both reversible and irreversible processes. The results vary for different types of particles and conditions. The concept of exergy cannot be defined for particles that undergo spontaneous creation and annihilation. It is also noted that the Carnot efficiency is not applicable to the conversion of confined thermal radiation into work.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
P. M. Centres, D. J. Perez-Morelo, R. Guzman, L. Reinaudi, M. C. Gimenez
Summary: In this study, a phenomenological investigation of epidemic spread was conducted using a model of agent diffusion over a square region based on the SIR model. Two possible contagion mechanisms were considered, and it was observed that the number of secondary infections produced by an individual during its infectious period depended on various factors.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zuan Jin, Minghui Ma, Shidong Liang, Hongguang Yao
Summary: This study proposes a differential variable speed limit (DVSL) control strategy considering lane assignment, which sets dynamic speed limits for each lane to attract vehicle lane-changing behaviors before the bottleneck and reduce the impact of traffic capacity drop. Experimental results show that the proposed DVSL control strategy can alleviate traffic congestion and improve efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Matthew Dicks, Andrew Paskaramoorthy, Tim Gebbie
Summary: In this study, we investigate the learning dynamics of a single reinforcement learning optimal execution trading agent when it interacts with an event-driven agent-based financial market model. The results show that the agents with smaller state spaces converge faster and are able to intuitively learn to trade using spread and volume states. The introduction of the learning agent has a robust impact on the moments of the model, except for the Hurst exponent, which decreases, and it can increase the micro-price volatility as trading volumes increase.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zhouzhou Yao, Xianyu Wu, Yang Yang, Ning Li
Summary: This paper developed a cooperative lane-changing decision system based on digital technology and indirect reciprocity. By introducing image scoring and a Q-learning based reinforcement learning algorithm, drivers can continuously evaluate gains and adjust their strategies. The study shows that this decision system can improve driver cooperation and traffic efficiency, achieving over 50% cooperation probability under any connected vehicles penetration and traffic density, and reaching 100% cooperation probability under high penetration and medium to high traffic density.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Josephine Nanyondo, Henry Kasumba
Summary: This paper presents a multi-class Aw-Rascle (AR) model with area occupancy expressed in terms of vehicle class proportions. The qualitative properties of the proposed equilibrium velocity and the stability conditions of the model are established. The numerical results show the effect of proportional densities on the flow of vehicle classes, indicating the realism of the proposed model.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Oliver Smirnov
Summary: This study proposes a new method for simultaneously estimating the parameters of the 2D Ising model. The method solves a constrained optimization problem, where the objective function is a pseudo-log-likelihood and the constraint is the Hamiltonian of the external field. Monte Carlo simulations were conducted using models of different shapes and sizes to evaluate the performance of the method with and without the Hamiltonian constraint. The results demonstrate that the proposed estimation method yields lower variance across all model shapes and sizes compared to a simple pseudo-maximum likelihood.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Przemyslaw Chelminiak
Summary: The study investigates the first-passage properties of a non-linear diffusion equation with diffusivity dependent on the concentration/probability density through a power-law relationship. The survival probability and first-passage time distribution are determined based on the power-law exponent, and both exact and approximate expressions are derived, along with their asymptotic representations. The results pertain to diffusing particles that are either freely or harmonically trapped. The mean first-passage time is finite for the harmonically trapped particle, while it is divergent for the freely diffusing particle.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Hidemaro Suwa
Summary: The choice of transition kernel is crucial for the performance of the Markov chain Monte Carlo method. A one-parameter rejection control transition kernel is proposed, and it is shown that the rejection process plays a significant role in determining the sampling efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Xudong Wang, Yao Chen
Summary: This article investigates the joint influence of expanding medium and constant force on particle diffusion. By starting from the Langevin picture and introducing the effect of external force in two different ways, two models with different force terms are obtained. Detailed analysis and derivation yield the Fokker-Planck equations and moments for the two models. The sustained force behaves as a decoupled force, while the intermittent force changes the diffusion behavior with specific effects depending on the expanding rate of the medium.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
