Stable Steady State Research Articles

A Mathematical Model for Fibrous Dysplasia: The Role of the Flow of Mutant Cells.

Fibrous dysplasia (FD) is a mosaic non-inheritable genetic disorder of the skeleton in which normal bone is replaced by structurally unsound fibro-osseous tissue. There is no curative treatment for FD, partly because its pathophysiology is not yet fully known. We present a simple mathematical model of the disease incorporating its basic known biology, to gain insight on the dynamics of the involved bone-cell populations, and shed light on its pathophysiology. We develop an analytical study of the model and study its basic properties. The existence and stability of steady states are studied, an analysis of sensitivity on the model parameters is done, and different numerical simulations provide findings in agreement with the analytical results. We discuss the model dynamics match with known facts on the disease, and how some open questions could be addressed using the model.

Spatial movement with nonlocal memory and distributed delay

A single species spatial population model with nonlocal memory diffusion and distributed delay is formulated. Taking the memory delay and distributed delay as bifurcation parameters, we study the stability of the positive homogeneous steady state and bifurcation behaviors. The results show that the joint effect of distributed delay and memory delay induces the occurrence of multiple stability switches, which is impossible for the system without the distributed delay.

Dynamics of reaction–diffusion–advection system and its impact on river ecology in the presence of spatial heterogeneity

This study considers a two-species reaction–diffusion–advection (RDA) model in a heterogeneous advective environment with zero Neumann boundary conditions. We suppose that two species compete for the same food resource but have different diffusion and advection rates. The primary objective of this study is to investigate the global asymptotic stability and coexistence of steady state based on different and unequal diffusion and advection rates through theoretical and numerical analysis. We establish the local stability of two semi-trivial steady states of the competing species. Also, the non-existence of coexistence steady state is proved with the help of some non-trivial assumptions. Finally, we show the global stability with the help of monotone dynamical systems and combine the local stability and non-existence of coexistence steady state. If one species adopts a smaller diffusion and advection rate, the competition’s result depends on the advection and diffusion rate ratio. If the ratio is smaller, then the species will prevail. Also, the species with higher diffusion and smaller advection will win. Lastly, the effectiveness of the model in one and two-dimensional situations is shown by a series of numerical calculations, which is particularly important for environmental consideration.

Сравнение характеристик линий высокого и сверхвысокого напряжений при выборе параметров управляемого устройства продольной компенсации

The use of series compensation devices leads to an increase of the transmission line capacity. However, it also increases the risk of an oscillatory violation of the stability of the electric power system. Cumulative hunting and self-excitation of the system is observed in the systems with controlled series compensation devices with a high degree of capacitive compensation. It is known that automatic excitation control of generators partially eliminates the negative effect of series capacitive compensation on oscillatory stability. Therefore, when choosing the tuning parameters of controlled devices, it is necessary to consider their combined effect on the system modes. The developed methods to study steady-state stability make it possible to analyze the modes of power systems with controlled power transmission of various voltage levels. Thus, it is advisable to conduct a comparative analysis of the influence of the adjustable parameters of the series compensation device on the steady-state stability of systems of various voltage levels, considering synchronous generators automatic excitation control. Methods of mathematical modeling of the electric power system, the theory of long-distance power lines and electromechanical transients, methods of analyzing the stability of electric power systems are used. The original software in the C ++ programming language has been used as a modeling tool. The choice of controlled series compensation device and the automatic excitation control regulation laws parameters is made, provided that steady-state stability is maintained. The stability regions of the studied electric power-engineering system are constructed depending on the tuning parameters of the considered devices of various voltage levels. A comparative analysis of the characteristics of the modes of high and extra-high voltage lines has been carried out. The regulation coefficients values of controlled series compensation device and automatic excitation of generators have been determined, under which there is no violation of oscillatory stability for different voltage levels. The conducted comparative analysis of the characteristics of high and extra-high voltage power lines demonstrates the need to consider the power transmission rated voltage when comprehensively selecting the tuning parameters of the controlled series compensation device and the automatic excitation control regulator.

Steady state stability assessment of voltage source converter in a DC microgrid under weak grid conditions

Traditionally, steady-state assessment involves analyzing numerous variables using Eigen analysis. This paper presents a decision support application for diagnosing the steady-state assessment of droop-controlled voltage source inverters in islanded microgrid operations or weak grid operations with reduced input attributes. This paper proposes an approach using feature extraction from the state space variables of the droop-controlled voltage source inverter (VSI). Photovoltaic (PV) and wind energy sources are considered with their stipulated power-delivering capability considered. To improve the generalization of the predictive model, preprocessing techniques are employed to eliminate data distortions. Dimensionality reduction is achieved through principal component analysis (PCA) applied to the steady-state variables. The evaluation of the VSI's steady-state stability is conducted utilizing support vector classification algorithm. To ascertain the reliability of the steady-state stability classification, an assessment of the support vector machine (SVM) model's performance is carried out, which includes the examination of metrics like the area under the curve (AUC) and the receiver operating characteristics (ROC) curve. The findings from the assessment of VSI's steady-state stability indicate a commendable level of performance, achieving an accuracy rate of 93.5%.

Small‐signal rotor angle stability of multi‐virtual synchronous machine (n‐VISMA) microgrid

AbstractAutonomous microgrid is known to lack appropriate inertia and damping for grid stabilization. Due to this, virtual synchronous machine (VISMA) has been introduced to provide necessary ancillary services through control of power converters. In a multi‐VISMA (n‐VISMA) microgrid, relative rotor angle stability of the power system is dependent on the active power balance after small perturbation. Thus, the use of relevant analytical models are essential issues for microgrid stability analysis. This paper presents a comprehensive small‐signal stability analysis to study inherent electromechanical oscillations in the virtual rotors. The subsystems of the microgrid consisting of VISMA, network, load and the outer power control were all modelled in Synchronous Reference Frame. The small‐signal model (SSM) was tested on IEEE‐9 bus system with VISMA replacing electromechanical synchronous machines on the network. To validate the developed numerical analytics, dynamic responses of the SSM are compared with those of the non‐linear (NL) system dynamics and the results reveal that the developed linearized SSM is sufficient to accurately characterize behaviour of the VISMA microgrid when operated in autonomous mode. Eigenvalues analysis and parameter sensitivities of the critical modes were investigated. Oscillatory participations of the VISMAs and steady state stability limit of the microgrid have also been investigated.

Dynamical Modeling and Qualitative Analysis of a Delayed Model for CD8 T Cells in Response to Viral Antigens.

Although the immune effector CD8 T cells play a crucial role in clearance of viruses, the mechanisms underlying the dynamics of how CD8 T cells respond to viral infection remain largely unexplored. Here, we develop a delayed model that incorporates CD8 T cells and infected cells to investigate the functional role of CD8 T cells in persistent virus infection. Bifurcation analysis reveals that the model has four steady states that can finely divide the progressions of viral infection into four states, and endows the model with bistability that has ability to achieve the switch from one state to another. Furthermore, analytical and numerical methods find that the time delay resulting from incubation period of virus can induce a stable low-infection steady state to be oscillatory, coexisting with a stable high-infection steady state in phase space. In particular, a novel mechanism to achieve the switch between two stable steady states, time-delay-based switch, is proposed, where the initial conditions and other parameters of the model remain unchanged. Moreover, our model predicts that, for a certain range of initial antigen load: 1) under a longer incubation period, the lower the initial antigen load, the easier the virus infection will evolve into severe state; while the higher the initial antigen load, the easier it is for the virus infection to be effectively controlled and 2) only when the incubation period is small, the lower the initial antigen load, the easier it is to effectively control the infection progression. Our results are consistent with multiple experimental observations, which may facilitate the understanding of the dynamical and physiological mechanisms of CD8 T cells in response to viral infections.

Analysis of steady-state dynamics and stability of particle dampers considering the friction effect

This study analyzes the steady-state dynamics and stability of a structure with a particle damper considering the friction effect between the particle and container, with a focus on whether the system can maintain stable-state motion for an extended period. The determination of friction’s contribution and the maximum allowable gap clearance for steady-state motion is demonstrated through the solution of motion of the primary structure with a particle damper subjected to low-frequency vibration conditions. Additionally, stability analysis is conducted to assess if initial disturbances cause deviations from the original stable state and identify necessary parameters for stability when the system parameters are uncertain. Analytical descriptions for the stability of the system are derived. The effects of friction on the dynamics and stability regions of the particle dampers are systematically revealed, where the theoretical and numerical models are mutually verified and supported by the cases of previous studies. Results show that the inclusion of the rolling friction effect will disrupt the steady-state motion as gap clearance approaches the optimal value. As the coefficient of rolling friction increases, the stability region’s area gradually decreases with a notable leftward shift of its right boundary. This shift ultimately leads to a leftward shift in the optimal vibration reduction curve. In the range of gap clearance variation allowing for steady-state motion with two symmetrical impacts per cycle, the relative velocity of the particle is more effective and intuitive to reveal the vibration reduction mechanism of particle dampers than other perspectives such as momentum, energy, and phase.

Stability analysis and numerical simulations of the infection spread of epidemics as a reaction–diffusion model

This paper presents a spatiotemporal reaction–diffusion model for epidemics to predict how the infection spreads in a given space. The model is based on a system of partial differential equations with the Neumann boundary conditions. First, we study the existence and uniqueness of the solution of the model using the semigroup theory and demonstrate the boundedness of solutions. Further, the proposed model's basic reproduction number is calculated using the eigenvalue problem. Moreover, the dynamic behavior of the disease‐free steady states of the model for is investigated. The uniform persistence of the model is also discussed. In addition, the global asymptotic stability of the endemic steady state is examined. Finally, the numerical simulations validate the theoretical results.

Nonlinear dynamics and optimal control strategies of a novel fractional-order lumpy skin disease model

Fractional order differential equations are often employed to better and accurately model several natural and physical processes with memory characteristics than the integer-order models. In this work, a proposed fractional-order model is presented to simulate one of the most dangerous viral cattle diseases. The present fractional-order Lumpy Skin Disease model considers the interactions between different compartments of cattle and virus vectors. The solution of the model is examined in terms of existence, uniqueness, positivity and boundedness. Then, the stability analysis of the different equilibrium points in the model is carried out. The basic reproduction number, R0, has been obtained too. The dependence of stability regions on the values of key parameters is demonstrated and the sensitivity of R0 to different parameters in the system is also investigated. Finally, a proposed optimal control scheme is adopted to successfully diminish the disease spread. It is found that the stability of disease-free equilibrium point is verified at small values of the infection rate of cattle caused by infected cattle or insects. In addition, the disease-free equilibrium point maintains its stability in cases where the recovery rate of cattle or the vaccination rate of cattle are increased. Moreover, the high-efficiency vaccination program helps in stabilizing the disease-free equilibrium point. Also, the fractional-order parameter is found to provide additional degree of freedom in the model to represent different scenarios of evolution for solution orbits. The optimal control parameters of the model are examined in different scenarios to limit or suppress the spread of the disease. It is demonstrated that two control parameters are sufficient to achieve the goals of disease elimination and stabilization of an infection-free steady state. Numerical simulations are verified to confirm our theoretical findings and estimations.

Turing Instability and Spatial Pattern Formation in a Model of Urban Crime

A nonlinear crime model is generalized by introducing self- and cross-diffusion terms. The effect of diffusion on the stability of non-negative constant steady states is applied. In particular, the cross-diffusion-driven instability, called Turing instability, is analyzed by linear stability analysis, and several Turing patterns driven by the cross-diffusion are studied through numerical investigations. When the Turing–Hopf conditions are satisfied, the type of instability highlighted in the ODE model persists in the PDE system, still showing an oscillatory behavior.

Study of a cannibalistic prey–predator model with Allee effect in prey under the presence of diffusion

In this study, we have investigated the temporal and spatio-temporal behavior of a prey–predator model with weak Allee effect in prey and the quality of being cannibalistic in a specialist predator. The parameters responsible for the Allee effect and cannibalism impact both the existence and stability of coexistence steady states of the temporal system. The temporal system exhibits various kinds of local bifurcations such as saddle–node, Hopf, Generalized Hopf (Bautin), Bogdanov–Takens, and global bifurcation like homoclinic, saddle–node bifurcation of limit cycles. For the model with self-diffusion, we establish the non-negativity and prior bounds of the solution. Subsequently, we derive the theoretical conditions in which self-diffusion leads to the destabilization of the interior equilibrium. Additionally, we explore the conditions under which cross-diffusion induces the Turing-instability where self-diffusion fails to do so. Further, we present different kinds of stationary and dynamic patterns on varying the values of diffusion coefficients to depict the spatio-temporal model’s rich dynamics. It has been found that the addition of self and cross-diffusion in a prey–predator model with the Allee effect in prey and cannibalistic predator play essential roles in comprehending the pattern formation of a distributed population model. It is expected that the comprehensive mathematical analysis and extensive numerical simulations used in investigating the global dynamics of the proposed model can facilitate researchers in studying the temporal and spatial aspects of prey–predator models in more significant detail.

Folding State within a Hysteresis Loop: Hidden Multistability in Nonlinear Physical Systems.

Identifying hidden states in nonlinear physical systems that evade direct experimental detection is important as disturbances and noises can place the system in a hidden state with detrimental consequences. We study a cavity magnonic system whose main physics is photon and magnon Kerr effects. Sweeping a bifurcation parameter in numerical experiments (as would be done in actual experiments) leads to a hysteresis loop with two distinct stable steady states, but analytic calculation gives a third folded steady state "hidden" in the loop, which gives rise to the phenomenon of hidden multistability. We propose an experimentally feasible control method to drive the system into the folded hidden state. We demonstrate, through a ternary cavity magnonic system and a gene regulatory network, that such hidden multistability is in fact quite common. Our findings shed light on hidden dynamical states in nonlinear physical systems which are not directly observable but can present challenges and opportunities in applications.

Spatiotemporal patterns in a diffusive resource–consumer model with distributed memory and maturation delay

In this paper, we propose a diffusive consumer–resource model in which the consumer is involved with spatiotemporal memory and the resource has maturation delay. Firstly, for the case without maturation delay, the influence of the spatiotemporal distributed memory on the stability of the positive steady state is investigated. It has been shown that memory delay can induce Turing bifurcation for the negative memory-based diffusion coefficient and induce Hopf bifurcation for the positive memory-based diffusion coefficient. Then the joint effect of the memory delay and the maturation delay on the stability of the positive steady state is investigated and it has been shown that the joint effect of the memory delay and the maturation delay can induce more complicated spatiotemporal dynamics via Turing–Hopf bifurcation and double Hopf bifurcation. Finally, we apply our theoretical analysis results to a consumer–resource model with Holling-II type functional response to illustrate the existence of the different spatiotemporal patterns.

Unraveling the forces shaping foraging dynamics in harvester ant colonies: Recruitment efficiency and environmental variability

The collective foraging behavior of ant colonies is a central focus in behavioral ecology. This paper enhances the classical model of foraging dynamics in harvester ant colonies by introducing a nonlinear recruitment rate and considering environmental variability. Initially, we analyze the existence and stability of steady states in the deterministic model. The results suggest that an increase in mean recruitment time can reduce the foraging threshold, leading to both forward and backward bifurcations. Furthermore, both average recruitment time and the interference intensity of recruiters impact the number of workers in each subgroup. Subsequently, we conduct an analysis of the long-term and transient dynamics of collective foraging in random environments, providing sufficient conditions for the colony to sustain foraging activity. The findings emphasize the scene-dependent impact of environmental stochasticity on foraging dynamics. When ant colonies deterministically cease foraging, environmental stochasticity may unexpectedly prolong the foraging state. Conversely, when colonies deterministically persist in foraging, environmental stochasticity may disrupt this continuity. Additionally, the effect of environmental stochasticity on foraging status varies with the initial worker size. Sizes near the boundary of the basin of attraction between non-foraging and foraging states exhibit greater sensitivity to environmental stochasticity, and sufficiently large stochasticity can impact foraging dynamics across a broader range of initial worker sizes. These findings underscore the intricate interplay between intrinsic factors (e.g., recruitment efficiency and interference intensity) and extrinsic factors (e.g., environmental stochasticity) in shaping the collective foraging dynamics of ant colonies.

Mathematical modeling and dynamic analysis for cancer resistance incorporating persister cells

Drug resistance is a key impediment to cancer treatment, however, the resistance mechanism remains controversial. Experiment evidence indicated that persister cells, a subpopulation in a transient pseudo-dormant state, are posited to play a potential role in the emergence of resistance. In this study, we propose a novel mathematical model for describing the interactions among sensitive, persister, and resistant cells to qualitatively and quantitatively analyze how persister cells affect cancer evolution and unravel the underlying resistance mechanisms. The proposed model is validated by theoretical analysis and fitting of actual human CT scan and mice data. Theoretical analysis demonstrates the existence and stability of the multiple steady states, as well as the global asymptotical stability of a unique steady state. Furthermore, bifurcation analysis reveals that the key factors, including the apoptotic rate of sensitive cells and the transformation rate between sensitive and persister cells, induce bistable phenomenon and are characterized by double saddle–node and transcritical bifurcations. The bistable region indicates that persister cells under high stable steady state as a reservoir could promote the emergence of resistant cells conferring a proliferative advantage and conversely when they are in lower stable steady state, the source of resistant cells and resistance process will be controlled. Therefore, the first transcritical bifurcation point can be viewed as an early indicator to detect critical transitions from low resistance to high resistance. Together, the proposed model and quantitative results would provide new insights for searching for strategies in modulating and decreasing the risk of drug resistance.

The Spatial Solow Model with Capital and Labor Diffusion

Spatial economics has become a prominent part of economic sciences over the past decades. One of its goals is to explain the flow and distribution of production factors in space. One possible way to do that is by employing theoretical economic models, such as the Solow model. This article aims to analyze the impact of including a labor diffusion term in the capital equation upon the steady state stability of the spatial Solow model, thereby bridging a gap in the literature. The results indicate that the diffusion coefficient has a profound effect on stability. Namely, high values of the coefficient can make the model unstable, but only if labor reacts to the density of capital.

Dynamical analysis of healthcare policy effects in an integrated economic-epidemiological model

We study the static and dynamical properties of a model that describes the interaction between the economic and epidemiological domains. The epidemiological sphere is represented by a susceptible–infected–susceptible model, while the economic domain consists of an overlapping generations model in which the workers correspond to the non-infected population of adults. The productivity of the firms and the propensity to save for retirement of the households are negatively affected by the disease spread. A capital tax is levied and the collected resources are used to curb the spread of the outbreak. We show that multiple endemic steady states can arise from the interaction between the two domains, and different stable endemic attractors can coexist with the stable disease free steady state. We study analytically and numerically the complex dynamics and the evolution of the basins of attraction in the case of multistability. We show that the effect of taxation can be beneficial from both the epidemiological and the economic points of view, as it can give rise to new steady states characterized by reduced shares of infected people and increased capital level, it can simplify the dynamical behaviors and reduce the size of the basins of attraction of those outcomes in which large shares of infected people and low capital levels are observed.

Analyzing grid connected shaded photovoltaic systems with steady state stability and crow search MPPT control

Analyzing grid connected shaded photovoltaic systems with steady state stability and crow search MPPT control

Dynamic Analysis of a Ratio-Dependent Food Chain Model with Prey-Taxis

In this paper, we consider a food chain model with ratio-dependent functional response and prey-taxis. We first investigate the global existence and boundedness of the unique positive classical solutions of the system in a bounded domain with smooth boundary and Neumann boundary conditions. Then, we analyze the local stability of the system and the existence of Hopf bifurcation. In addition, we prove the global asymptotic stability of steady states under some conditions by constructing a Lyapunov functional, and investigate convergence rates. Finally, we present several numerical simulations to illustrate the results.