A novel 4D dual-memristor chaotic system (4D-DMCS) is constructed by concurrently introducing two types of memristors: an ideal quadratic smooth memristor and a memristor with an absolute term, into a newly designed jerk chaotic system. The excellent nonlinear properties of the system are investigated by analyzing the Lyapunov exponent spectrum, and bifurcation diagram. The 4D-DMCS retains some characteristics of the original jerk chaotic system, such as the offset boosting in the x-axis direction. Simultaneously, the integration of the two memristors significantly enriches the dynamic behavior of the system, notably augmenting its transitional behaviors, fostering greater multistability, and elevating both spectral entropy and C complexity. This augmentation underscores the profound impact of the memristors on the system's overall performance and complexity. The system is implemented through the STM32 microcontroller, further proving the physical realizability of the system. Ultimately, the 4D-DMCS exhibits remarkable performance when applied to image encryption, demonstrating its significant potential and effectiveness in this domain.
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http://dx.doi.org/10.1038/s41598-024-80445-8 | DOI Listing |
Int J Drug Policy
January 2025
MGH Institute for Technology Assessment, Harvard Medical School, Boston, MA, 02144, USA. Electronic address:
The overdose epidemic in the United States is evolving, with a rise in stimulant (cocaine and/or methamphetamine)-only and opioid and stimulant-involved overdose deaths for reasons that remain unclear. We conducted interviews and group model building workshops in Massachusetts and South Dakota. Building on these data and extant research, we identified six dynamic hypotheses, explaining changes in stimulant-involved overdose trends, visualized using causal loop diagrams.
View Article and Find Full Text PDFChaos
January 2025
Physics Institute, University of São Paulo, 05508-090 São Paulo, SP, Brazil.
In this work, we investigate the dynamics of a discrete-time prey-predator model considering a prey reproductive response as a function of the predation risk, with the prey population growth factor governed by two parameters. The system can evolve toward scenarios of mutual or only of predators extinction, or species coexistence. We analytically show all different types of equilibrium points depending on the ranges of growth parameters.
View Article and Find Full Text PDFChaos
January 2025
School of Mathematics and Statistics, University College Dublin, Dublin 4 D04 V1W8, Ireland.
Synaptic plasticity plays a fundamental role in neuronal dynamics, governing how connections between neurons evolve in response to experience. In this study, we extend a network model of θ-neuron oscillators to include a realistic form of adaptive plasticity. In place of the less tractable spike-timing-dependent plasticity, we employ recently validated phase-difference-dependent plasticity rules, which adjust coupling strengths based on the relative phases of θ-neuron oscillators.
View Article and Find Full Text PDFChaos
January 2025
Department of Chemistry, Indian Institute of Technology Guwahati, Guwahati 781039, Assam, India.
Spirals are a special class of excitable waves that have its significance in the understanding of cardiac arrests and neuronal transduction. In a theoretical model of the chemical Belousov-Zhabotinsky reaction system, we explore the dynamics of the spatiotemporal patterns that emerge out of competing reaction and diffusion phenomena. By modifying the existing mathematical models of the reaction kinetics, we have been able to explore the explicit effect of hydrogen ion concentration in the system, so as to achieve various regimes of wave activity, from stable spirals to oscillation death.
View Article and Find Full Text PDFBiomimetics (Basel)
January 2025
Group of Biomechatronics, Fachgebiet Biomechatronik, Technische Universität Ilmenau, D-98693 Ilmenau, Germany.
Anguilliform locomotion, an efficient aquatic locomotion mode where the whole body is engaged in fluid-body interaction, contains sophisticated physics. We hypothesized that data-driven modeling techniques may extract models or patterns of the swimmers' dynamics without implicitly measuring the hydrodynamic variables. This work proposes empirical kinematic control and data-driven modeling of a soft swimming robot.
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