This study examined the impact of a few numerical factors, such as mesh density, drag model selections, turbulence models, and bubble size descriptions on the numerical accuracy of gas-liquid (GL) flow. Multiphase flow in a vertical pipe with a diameter of 76.2 mm was simulated using the Eulerian-Eulerian (EE) model provided by ANSYS Fluent. A comparison with experimental findings shows that the two-phase

In the era of Industry 4.0, ensuring the resilience of cyber-physical systems against sophisticated cyber threats is increasingly critical. This study proposes a pioneering AI-based control framework that enhances short-term voltage stability assessments (STVSA) in power systems under complex composite cyber-attacks. First, by incorporating white-box and black-box adversarial attacks with Denial-of-Service

While network robustness is often assessed via structural connectivity, this approach does not fully capture the performance of complex systems, which also depends on information flow among internal components. In this paper, we focus on the robustness of directed networks by proposing a framework to dismantle both their information flow and connectivity. Specifically, we develop a multi-temporal information

This study proposes a Decentralized Federated Learning(DFL) framework based on population mobility networks to address the prediction challenges in multi-node dynamic systems. By incorporating an adjacency matrix constructed from population mobility networks, the framework ensures node independence while enabling dynamic information sharing and global collaborative optimization across nodes. Using

The Susceptible–Infected–Recovered (SIR) epidemic model based on a simplicial complex is investigated, incorporating higher-order network topology and nonlinear incidence rates. We derive theoretical results for the basic reproduction number, the final size, and the epidemic peak of the mean-field model. Furthermore, we provide a theoretical estimate for the peak time of an epidemic. Numerical simulations

This paper investigates Entangled Hidden Markov Models (EHMMs), with a particular focus on how entanglement influences quantum dynamics. We present a structure theorem for inhomogeneous EHMMs, which provides a foundational understanding of their behavior in complex systems. Furthermore, we compute the Ohya degree of entanglement for models with deterministic stochastic matrices, offering a precise

In this paper, we consider a delay-driven population chemotaxis model with practical significance in biology, incorporating both prey refuge and predator harvesting terms. We first prove the local-in-time existence and uniqueness of classical solutions to this model for τ=0, and the global existence and uniqueness of classical solutions to this model for τ>0. Then, using stability theory, bifurcation

While continuous coupled oscillator models, such as the Kuramoto model, have been extensively investigated, a comprehensive framework for understanding synchronization in pulse-coupled oscillator networks remains absent. In this study, we address this gap by integrating experimental and theoretical approaches. We explore synchronization dynamics through an electronic firefly system, revealing how external

Social media holds a crucial position in mitigating the proliferation of infectious diseases, as the majority of individuals rely on media coverage to enhance their awareness of prevention measures. Based on the diversity of media coverage and the heterogeneity of the audience during the epidemic period, this paper establishes an SIS infectious diseases model on networks, employing a nonlinear incidence

Neural rhythms, such as the alpha rhythm, result from spontaneous oscillatory dynamics within the brain and hold significant promise for revealing the mechanisms that drive various cognitive processes. In this study, we examine the relationship between alpha activity and cognition using the Stroop test to quantify cognitive tendencies. The Stroop Interference T-Scores (IS-values) measure the difference

Toxic gas leaks pose severe threats to public safety and societal stability, leading to large-scale casualties and social panic. This paper focuses on crowd evacuation behavior during toxic gas leak incidents, proposing an evacuation model that combines Computational Fluid Dynamics (CFD) and Agent-Based Modeling (ABM). By introducing a helping mechanism among agents with prosocial personalities, the

In this work, we experimentally observed polarization domains underlying cross-gain saturation and gain competition between the polarization modes at orthogonal directions in an L-band fiber laser. We investigated how the background noise of polarization domains be cleaned, which was demonstrated by estimating the polarization instability induced phase difference at orthogonal directions. Noise cleaning

We use the conservation laws of mass, momentum, energy, and moisture equations derived from a finite element model to assess the stability of diurnal cycles of atmospheric boundary layer flow. The results show the most accurate predictions for how temperature, pressure, and wind speed affect mesoscale flow in various domains, with isentropes remaining stable despite the dynamic influence of initial

We experimentally investigate the evolutions of the chaotic characteristics in semiconductor laser subjected to microring resonator combined with optical injection. When the experimental parameters are changed, we calculate the standard bandwidth, flatness, and time-delay signature value of the chaotic laser. By the multiple beam interference effect, linear filtering effect and nonlinear self-phase

Chimera states, a form of partial synchronization in neural networks, are characterized by the coexistence of synchronized and asynchronous regions. These states are crucial for various cognitive functions, such as learning and information processing. Conversely, abnormal synchronization—often referred to as hyper-synchronization—can lead to pathological conditions such as epilepsy and Parkinson's

Under the connected environment, connected vehicles need to resist cyber-attacks such as tampered information in an open network of the traffic system. Additionally, slope lane is frequently seen in real traffic, which means that the gravitational action of the vehicles themselves cannot be ignored. Accordingly, a novel car-following model is constructed by aggregating the tampered speed difference

Understanding and resolving cooperation dilemmas are key challenges in evolutionary game theory, which have revealed several mechanisms to address them. This paper investigates the comprehensive influence of multiple reputation-related components on public cooperation. In particular, cooperative investments in public goods game are not fixed but simultaneously depend on the reputation of group organizers

There is yet to be a unified theoretical framework for defining and solving degree correlation in evolving networks, which limits applied research in evolving networks. To address this problem, we proposed a stochastic process-based Markov chain method. The transition rules of network nodes and edges designed in this method ensure that the network topology and statistical characteristics at any time

The partially nonlocal multi-component nonlinear Schrödinger system holds significant application potential for modeling partially nonlocal nonlinear responses in multi-division multiplexing optical information systems. However, research exploring three-component systems with distinct rogue wave configurations remains notably scarce. In this study, we address this gap by investigating a variable-coefficient

Irregular dynamics (especially chaotic) is often undesirable in economics because it presents challenges for predicting and controlling the behavior of economic agents. In this paper, we used an overlapping generations (OLG) model with a control function in the form of government spending as an example, to demonstrate an effective approach to forecasting and regulating chaotic dynamics based on a combination

The performances of many-body quantum batteries strongly depend on the Hamiltonian of the battery, the initial state, and the charging protocol. In this article we derive an analytical expression for the energy stored via a double sudden quantum quench in a large class of quantum systems whose Hamiltonians can be reduced to 2x2 free fermion problems, whose initial state is thermal. Our results apply

Chlorophyll, an essential pigment for photosynthesis, is abundant in plants, algae, and cyanobacteria. Over the past few decades, research has primarily focused on its unique roles in photosynthesis, however, the nonlinear light interaction with chlorophyll is highly unexplored. We report on the nonlinear optical interplay of light with the chlorophyll solution at different concentrations. In this

We present a novel decoding approach for motor imagery electroencephalograms (MI-EEG) in Brain-Computer Interface (BCI) systems, aiming to advance neurorehabilitation and human–computer interaction. However, due to the non-stationary properties and low signal-to-noise ratio of MI-EEG, as well as significant individual variability, achieving accurate cross-subject decoding remains a challenge for real-world

Artificial neural networks (ANNs) are widely applied in fluid mechanics and engineering to model complex relationships between input and output data. They facilitate pattern recognition, process optimization, and material property prediction. This study focuses on resolving the Hall ion effect in Prandtl nanofluid using a non-Fourier double diffusion theory-based model (HIE-PNF-NFDDT). The Levenberg-Marquardt

Moran fractal (Wen, 2001) is significant in the field of Fractal Geometry. The discrete Moran sets on Z with the same expansion factor was discussed in Yao et al. (2024). This paper explores the fractal dimensions of discrete homogeneous Moran sets on Z, where each step involves a distinct expansion factor.

The inherent properties of chaos offer significant potential for information security, especially in cryptographic applications like image encryption. Therefore, a novel complex chaotic system with a memristor and complex parameters is proposed, its dynamic behaviors are investigated, and its hardware implementation is provided. Parameter-dominated attractors are identified and a precise definition

Many real-world systems comprise fundamental elements that exhibit mutual exclusion and alternating activation. Here, we develop a framework for the evolution of network structures that captures the behaviors of such systems. We define the dynamic resilience of temporal networks using variational rates to measure how the evolutionary trajectories of network structures diverge under perturbations. We

Neuron synchronization plays a crucial role in brain dynamics. Although considerable progress has been made in the understanding of synchronization, the study in neuronal models within higher-order networks remains insufficiently understood. This study explores the impact of repulsive higher-order interactions in a weighted network of coupled Huber-Braun (HB) neurons, focusing on how these interactions

This paper explores prescribed-time bipartite synchronization (PTBS) of signed networks by employing resampled interval control (RIC). With the introduction of an interval adjustment parameter sequence, the control input can be adjusted dynamically, which makes the control strategy both effective and economical. Under this control strategy, bipartite synchronization can be achieved within the prescribed

In this paper, a new type of aperiodically intermittent pinning control (AIPC) is proposed to investigate the prescribed-time stabilization (PTS) of stochastic complex dynamical networks (SCDNs). It is worth noting that the paper provides a theorem for realizing PTS for SCDNs under AIPC and affords a corollary of the relationship between the state of the nodes of the SCDNs and the control gain of AIPC

In this work, we introduce a new Painlevé integrable fifth–order equation. We employ the Painlevé integrability test to examine the compatibility conditions for this newly established system. We use the dispersion relation, the phase shift, and the Hirota’s method to derive multiple soliton solutions for this equation. We also derive several other solutions of distinct physical structures. The obtained

With the growing integration of Advanced Driver Assistance Systems (ADAS) in modern vehicles, cybersecurity threats present substantial risks to traffic stability and safety. This study introduces an advanced car-following model that accounts for the effects of passing, driver attention, and information delays caused by cyberattacks, and investigates their impact on traffic dynamics within ADAS systems

Schizophrenia diagnosis remains challenging due to the reliance on subjective clinical assessments and the lack of robust, objective biomarkers. Current neuroimaging methods are often expensive, time-consuming, and may lack specificity, highlighting the need for the development of scalable and accurate diagnostic tools. This study investigates the feasibility of using electroencephalogram (EEG) frequency

The FitzHugh–Nagumo (FHN) model is an efficient and biologically plausible model for simulating neuronal dynamics. However, it lacks any inherent capability to appropriately integrate memory effects. In this study, a non-Markov stochastic neuron model is formulated as an extension of the FHN model by incorporating Gamma distributed delay kernel as the form of memory in a recovery variable. Additionally

Memristors have been extensively integrated into neurons as key elements for emulating electromagnetic radiation (EMR). The complex firing patterns triggered by external magnetic field is a hot topic in neuronal dynamics. By integrating a specially designed memristor into a complex-valued FitzHugh–Nagumo (CV-FHN) neuron model to emulate external magnetic induction current, we have developed a novel

Stochastic processes with renewal properties, or semi-Markovian processes, have emerged as powerful tools for modeling phenomena where the assumption of complete independence between temporally spaced events is unrealistic. These processes find applications across diverse disciplines, including biology, neuroscience, health sciences, social sciences, ecology, climatology, geophysics, oceanography,

In this paper, we are concerned with a class of McKean–Vlasov stochastic differential equations with Markovian regime-switching driven by fractional Brownian motions with Hurst parameter H>12. We first obtain the existence and uniqueness theorem for solutions of the concerned equations under the non-Lipschitz conditions. Second, we establish the propagation of chaos for the associated mean-field interaction

Wildfires are a recurrent and devastating phenomenon that has expanded in Chile and various places worldwide, with complex propagation patterns influenced by environmental, climatic, and anthropogenic factors. In this study, we employ a complex network framework to analyze the temporal and spatial dynamics of fire propagation throughout Chile. Using publicly available data on wildfires, including their

It was demonstrated that the herd behavior in prey, described by a square root functional response, induces a Hopf bifurcation in the Leslie-type predator–prey model. This paper is devoted to discussing bifurcations of the same model, but with constant-rate predator harvesting. We show that the system exhibits complicated bifurcations driven by the predator harvesting. More concretely, we first prove

This study explores the connections between fractional calculus, a field that has recently garnered significant research interest, and multiplicative analysis. The introduction provides a comprehensive overview of the historical development and foundational concepts of these areas. The preliminary section outlines key definitions and illustrative examples from multiplicative analysis. The research

Infectious diseases rarely spread in isolation, and the competing spreading of multiple diseases widely exists. However, existing studies on the dynamics of competing infectious diseases typically rely on networked populations, lacking systematic research on specific metropolitan areas. This study proposes a competing infectious disease model to describe two competing infectious diseases spreading

This work aims to investigate the dynamic behavior of the carbon fiber oscillator in the winding process of the novel multi-filament fiber winding equipment for high-pressure vessels, employing an improved fractional-order controller. Specifically, a coupling suppression fractional-order PD (CS-FOPD) control strategy is proposed for the two-degree-of-freedom carbon fiber oscillator. The multiple-scales

Nanomaterials exhibiting broadband nonlinear optical responses have garnered considerable interest in the field of ultrafast photonics. These materials have been extensively validated as effective saturable absorbers (SAs), demonstrating their capability to facilitate the generation of broadband optical pulses. In this study, strontium ferrite nanoparticles (SrFeO-NPs), were synthesized using the sol-gel

With the continuous increase of road traffic flow, traffic congestion is becoming increasingly severe. To reduce traffic jam, cooperative driving of vehicles under the environment of Internet of Vehicles is an effective method. Aiming at the difference of cognition and utilization of the target vehicle for its preceding and following traffic information, a novel lattice hydrodynamic model by considering

Identifying key influential nodes in complex networks is crucial for applications such as social network analysis, epidemiology, and recommendation systems. This paper proposes SE_GCN (Structural Equivalence with Graph Convolutional Network), a method that combines structural equivalence with Graph Convolutional Networks (GCNs) to identify key nodes in complex networks. SE_GCN leverages structural

A decade ago, Josephson “flying qubits” based on adiabatic superconducting logic cells showed promise as quantum data buses, but their development stalled due to the incompatibility of traditional qubit control methods with their design. We revisit this concept by exploring the control of the inductively shunted two-junction superconducting interferometer (adiabatic quantum flux parametron, AQFP) in

To overcome the limitations of conventional designs for memristive multi-scroll chaotic systems, this paper introduces a novel memristor that relies solely on a single memristor function and a single state variable function to generate both odd and even numbers of double-scroll attractors. This design not only simplifies the memristor structure but also offers a new approach to constructing multi-scroll

We investigated multifractality of temporal series of daily mean air temperature anomalies over the entire European continent by applying the method Multifractal detrended fluctuation analysis (MFDFA) on high resolution E-OBSv26.0e dataset. The spatial resolution is 0.10 which corresponds to 120,866 grid cells, and the time span of daily temperature series is from 1961 to 2020, which permits to compare

Microscale electric field-induced vortical structures, arising from spatial accumulation of induced charges, demonstrate significant potential for augmenting mixing performance in low Reynolds number (Re) laminar flows. This investigation establishes a computational framework incorporating an asymmetric conductive plate with hybrid linear-curvilinear edges to systematically elucidate the coupling mechanisms

Binary-state dynamics are prevalent in nature, from societal dynamics to dynamical systems in physics. Reconstructing a network structure behind interacting binary-state dynamical systems is essential, as it can facilitate understanding of these dynamical systems and improve the accuracy of predicting dynamical behavior. So far, few works have focused on correlation information in binary-state temporal

In this study, we utilize the PV iteration method to generate Mandelbrot and Julia sets for the function G(z)=zk+c. We establish escape criterion conditions for the PV iteration and provide a variety of graphical examples for different parameter settings. We also compare the graphs with those generated by other well-known iterations, such as the Picard-Mann and M iterations. Furthermore, we investigate

Remote synchronization (RS) is an emerging focus in nonlinear dynamics and complex networks, as it provides insights into how functional connections in the brain arise from its structural network. While previous studies have extensively explored RS under intrinsic coupling conditions, the combined influence of external stimuli and coupling strength, a critical factor in real-world systems, remains

Aging, understood as the tendency to remain in a given state the longer the persistence time in that state, plays a crucial role in the dynamics of complex systems. In this paper, we explore the influence of aging on coevolution models, that is, models in which the dynamics of the states of the nodes in a complex network is coupled to the dynamics of the structure of the network. In particular we consider

We propose a stochastic model of the Hepatitis B Virus (HBV) and investigate viral extinction, persistence, and average residence time. To predict whether HBV will persist in the long term, we construct a crucial stochastic threshold. The establishment of this threshold faces some challenges due to the coexistence of predation and competition mechanisms in the model. To overcome this challenge, we

The Born–Infeld type fluid, which obeys the pressure–density relation where the pressure is positive, is introduced into the nonhomogeneous Euler equations of compressible fluid flow. It is discovered for the first time that, for the positive pressure, the delta-shock with Dirac delta function in density develops in the solutions, even though the considered system is strictly hyperbolic with two genuinely

Dangerous cardiac arrhythmias occur often due to ischemic heart disease. One of the most important methods for removing an arrhythmia is low-voltage electrotherapy, in particular overdrive pacing, that is stimulation from an implanted cardioverter with a period slightly less than the arrhythmia period. The main aim of this paper is to study how ischemia can affect overdrive pacing of arrhythmias caused

Vaccine coverage and non-pharmaceutical interventions have great importance relative to public health in the current scenario of pandemic throughout the world. A compartmental model for assessing the vaccine and community contact rate (in light of social-distancing and isolation) coverage in symptomatic and asymptomatic public. In most biological phenomena, particularly infectious diseases, fractional

This study investigates the intricate dynamics of different types of solitons and their interactions within the framework of the Landau-Ginzburg-Higgs model as applied to nonlinear fiber optics. Employing the Hirota bilinear transformation technique, we derive a range of analytical soliton solutions, and demonstrating their rich and diverse behaviors. The proposed methodology provides a more comprehensive

Continuous-variable quantum key distribution (CVQKD) is one of the promising ways to ensure information security. In this paper, we propose a high-rate scheme for discretely-modulated (DM) CVQKD using quantum machine learning technologies, which divides the whole CVQKD system into three parts, i.e., the initialization part that is used for training and estimating quantum classifier, the prediction

This study aims to develop a new electronic realization of a neuron. We based our work on a previously constructed circuit and modified it to reduce the number of elements. All modeling was done using ngSPICE circuit simulator. For the new developed circuit current–voltage characteristics were constructed, then dependence of signal amplitude on resistance of potentiometer was measured. In this way