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Paper (Maniar and Bhattacharyay, 2021) introduces a discrete random-walk (RW) model with a site dependent waiting time and an external force i.e. a site dependent drift. The RW is compared with a Smoluchowski equation in continuous space and time with space dependent diffusivity and space dependent damping. Using numerical simulations in Maniar and Bhattacharyay (2021) it is shown that the equilibrium distribution satisfies locally the Stokes–Einstein relation i.e. there is a constant temperature in the whole system. Here we show that the result can be recovered analytically with a continuous limit in the RW master equation. Moreover, we evidence that the RW model should be carefully defined in order to satisfy locally Stokes–Einstein relation, indeed a different definition of the discrete RW process describes a system that satisfies the Smoluchowski equation with constant damping, where the temperature is not uniform. [ABSTRACT FROM AUTHOR]

Dedicated Bus Lane (DBL) is a typical strategy to ensure priority for public transportation. However, when the frequency of bus departures is low, the DBL often remains vacant, reducing the efficiency of traffic utilization. Variable bus lane (VBL) strategy allows for the provision of service to social vehicles in specific scenarios, aiming to alleviate traffic congestion and improve emission efficiency at intersections. To analyze the impact of this strategy on dynamic queuing behavior and traffic efficiency at an isolated intersection, this paper proposes a multidimensional stochastic queuing model. The model incorporates various factors such as traffic demand, signal timing, bus arrival time, and the length of the variable area at intersections. By examining the steady-state distribution of queue length and calculating performance indicators, the effectiveness of VBL in improving intersection performance is evaluated. Numerical simulations have demonstrated that the proposed model accurately describes the vehicle queuing process at intersections under different conditions. Theoretical analysis confirms that the implementation of VBL strategy can effectively improve traffic efficiency at intersections and minimize the queue length of vehicles. [ABSTRACT FROM AUTHOR]

This paper focuses on platoon control of autonomous vehicles (AVs) equipped with V2X technology and the phenomenon that the large platoons are split into multiple sub-platoons due to the communication restrictions. At the same time, with the popularity of AVs and connected human-driven vehicles (CVs), this paper also carries out the research of mixed traffic flow mixed with AV platoons, CVs and regular human-driving vehicles (RVs). According to the characteristics of the different types of vehicles, this paper extends the corresponding car-following models based on intelligent driver model (IDM), and considers the functional degradation of AVs under different car-following modes. In this paper, the AVs are classified into the second-level degenerated AV (D2AV), the first-level degenerated AV (D1AV) and the normal functioning AV (NAV) based on the differences in car-following modes. The degradation of AVs is represented via the change of communication topologies and models. Linear stability analysis is conducted. Numerical simulation shows that the higher level of AV degradation, the worse the stability of traffic flow. Under the same conditions, the more sub-platoons and the larger maximum size of sub-platoons, the better the stability of the traffic flow. The increase in communication strength of AVs is also beneficial to stability of traffic flow. In order to compensate for degradation, an adaptive gain feedback control strategy is proposed. Simulation shows that the adaptive gain feedback strategy can effectively improve the ability of the traffic flow to resist disturbances, reduce the fluctuations of velocity and acceleration, and contribute to the stability of platoon system and traffic flow. • A general car-following models are established, including eight types of vehicles. • Considering graded degradation, linear stability analysis is conducted. • Exploring the effect of the various factors of sub-platoon on traffic stability. • Proposing an adaptive gain feedback control strategy and proving its effectiveness. [ABSTRACT FROM AUTHOR]

The continuity of acceleration changes is often overlooked by existing car-following models, leading to a limitation in capturing realistic driving dynamics for emission estimation, which are essential for the application in microscopic traffic evaluations. This paper investigated and modeled the jerk-constrained acceleration stochastic process using the Markov model. A new car-following model considering the acceleration stochastic process was proposed, which incorporated two modes of unconscious following and active acceleration approaching. Additionally, a bi-objective model calibration framework was introduced to balance the trade-off between traffic-related performance and emission estimation performance. Numerical simulation was conducted to compare the performance of the new model with the conventional Wiedemann model. Results demonstrated that the proposed model provides more realistic vehicle dynamics and accurate emission estimations. Specifically, compared to the Wiedemann model, the new model reduced the root-mean-square error (RMSE) of spacing headway by 0.73 m and the RMSE of vehicle-specific power (VSP) distribution by 11.57%. • Jerk-constrained stochastic acceleration process was modeled with the Markov model. • Proposing a new car-following model considering the stochastic acceleration process. • The new model provides realistic vehicle dynamics and accurate emission estimations. • A bi-objective model calibration framework was introduced for emission estimation. [ABSTRACT FROM AUTHOR]

Abstract In this paper, how to optimize the inter-structures to enhance the synchronizability of interdependent networks is investigated. Based on a genetic algorithm (GA), combined with two fitness functions, a new method is presented that optimizes inter-structures to enhance the synchronizability of interdependent networks. For bounded and unbounded synchronous regions, when the number of inter-connections or the inter-coupling strength related to the inter-structures is changed, we apply the proposed method to optimize the two interdependent networks. The first network, namely NW–BA network, includes a small-world subnet generated by Newman–Watts algorithm and a Barabá si–Albert scale-free subnet. The second network, ST–BA network, includes a star subnet and a BA subnet. Generally, the analyses and numerical simulation results demonstrate the proposed optimization method performs well. According to the betweenness correlation defined in this paper, as the number of inter-connections increase, the optimized inter-structures experience a process that shifts a nearly positive correlation to irrelevance. However, increasing the inter-coupling strength gradually makes no difference on optimized inter-structures. Overall, the results indicate that NW–BA networks are a better choice for interdependent networks than the ST–BA networks. Highlights • A new method is presented to optimize the inter-structures. • An optimization scheme is proposed to enhance the synchronizability of interdependent networks. • The optimization scheme performs well on two kinds of interdependent networks. • The betweenness correlation is defined in this paper. [ABSTRACT FROM AUTHOR]

Abstract As for the dynamical networks which consist of some high-dimensional nonlinear systems, the problems that researchers are concerned with are usually the asymptotic convergence on some components (rather than all components) of node's state variables under certain condition. This means that partial component synchronization is more meaningful than identical synchronization in some cases. In this paper, the definition of partial component synchronization is given, and then the problem of partial component synchronization on a class of chaotic dynamical networks is investigated. By using matrix theory, stability theory and the hypothesis that several components in the solution vector of a single uncoupled node are ultimately dissipative, some sufficient conditions on partial component synchronization in the chaotic dynamical networks are derived. Finally, numerical simulations are shown to demonstrate the correctness of the theoretical results. Highlights • Partial component synchronization is a kind of group dynamics behavior weaker than identical synchronization. • In this paper, the definition of partial component synchronization is given, and the stability theory of partial variables is applied to study it. • Several sufficient conditions for partial component synchronization to be realized on the network are derived. [ABSTRACT FROM AUTHOR]

Abstract Diffusion Limited Aggregation (DLA) and Lindenmayer Systems (L-Systems) are two important fractal structures generators, whose characteristics have been often discussed in the literature. On their own, both DLA and L-Systems have been applied to model very different phenomena related to non-equilibrium growth models and self-similarity patterns generation. This paper introduces hybrid L-Systems–Diffusion Limited Aggregation schemes, as a novel combinative approach to model novel growth structures. The most intuitive possibilities for hybridizing these systems are discussed: using L-Systems to guide DLA simulations, and embedding DLA schemes into L-Systems variables. Different computational simulations illustrate the performance of some of these hybrid L-Systems–DLA schemes. Possibilities for extending the application of this hybrid proposal to alternative research fields are also discussed in the paper. Highlights • We propose hybrid L-System–DLA structures. • A DLA guided by L-Systems is first analyzed. • We also study how to embed DLAs in L-Systems structures. • Different computer simulations show the feasibility of this proposal. [ABSTRACT FROM AUTHOR]

Abstract This paper addresses the group-delay consensus of second-order nonlinear multi-agent systems by piecewise adaptive pinning control in part of time interval. The topology of the networked system is assumed to be directed and weakly connected. The agents in each group can be classified into three subsets, which are inter-act agent, intra-act agent with zero in-degree and the other agents. According to the agents' property and intrinsic dynamics, the protocol is designed to guarantee that agents in the same group reach consensus, and the agents in different groups reach group-delay consensus. By using Lyapunov stability theory, graph theory and matrix theory, some consensus criteria are derived in the form of matrix inequalities. At last, a numerical simulation is also given to verify the correctness of theoretical analysis. Highlights • We classify the agents in each group into three subsets, and take different control for different agent to derive the sufficient condition of consensus. • Pinning control is also taken into account, and we only choose some of agents to control. Both of them can effectively reduce the cost of control. • The group-delay consensus this paper is under directed and weakly connected network topology. Compared to the existing result that needs a directed spanning tree, it reduces the requirement of topology. [ABSTRACT FROM AUTHOR]

The Full velocity difference (FVD) model considers the velocity difference, but it cannot capture the acceleration/deceleration asymmetric characteristic. This paper points out that the response of drivers to the velocity difference is influenced by the space gap (which is the space headway minus the vehicle length), and improves the FVD model based on this view. The improved model indicates that the reason why the asymmetric characteristic exists in the car-following behavior is that the response of drivers to the velocity difference is in negative correlation to the space gap. Neutral stability curves of the improved model are asymmetry. And the stability analysis indicates that the visual angle model (one of the improved FVD models) is a special case of the improved model proposed in this paper. Results of numerical computer simulations confirm that the improved model can capture the asymmetric characteristic, and further indicate that the asymmetric characteristic is caused by the influence of space gap to the drivers’ response. And finally, parameters of the improved car-following model are calibrated by real traffic flow data. [ABSTRACT FROM AUTHOR]

Rumor spreading is an important form of social communication, and it will cause unnecessary panic and conflict to society. This paper aims to investigate the combined impact of the internal and external factors on the efficiency of rumor spreading over the social networks. In this paper, firstly, a modified I S R rumor spreading model on heterogeneous networks by taking into account the activity and infectivity of nodes and propagation environment was introduced. Then, through theoretical analysis, we derive the mean field equations with considering nonlinear spreading rate and active network nodes. Next, we calculate the basic reproduction number ℜ 0 based on the next generation matrix method whose results reveal that if ℜ 0 < 1 , the rumor-free equilibrium is global asymptotically stable, the rumors will disappear. If ℜ 0 > 1 , the rumor-endemic equilibrium is global attractivity, then the number of spreaders will remain stable and the rumors will become endemic. Further, some numerical simulations are performed, which is consistent with the deterministic mean-field approach. Our results show that it is very important to consider the internal and external factors to control the spread of the rumors. [ABSTRACT FROM AUTHOR]

Abstract Shareholders of listed companies can be divided into institutional and non-institutional shareholders. Both groups are important to their listed companies. Many scholars have conducted research on institutional shareholders, some research on non-institutional shareholders, and some scholars have researched similarities of the two shareholder types to reveal co-holding relationships at the shareholder level. However, there are seldom studies of the similarity of the co-shareholder relationship at the listed company level. What are the similarities between the co-shareholder relationships from these two perspectives? In this paper, we apply the complex network theory, which is often used in the financial markets to conduct research, and divide the data of ten major circulating shareholders of the listed companies in China into two parts. We then construct two projected networks that are a common institutional shareholder relationship network and a common non-institutional shareholder relationship network based on the bipartite networks using the decreasing-mode method, in which the shareholders are mediate elements. We analyze the evolutionary similarity of the two co-shareholder relationship networks from three angles, including the contribution rate of the common institutional shareholder relationship network and the common non-institutional shareholder relationship network to the whole network, the behavior intensity of the co-shareholder in the two networks, and the similarity of the two networks. The results indicate that (1) The evolution of the contribution rate of the listed companies with the co-shareholder relationship was influenced by different factors in two projected networks. The evolution of the contribution rate of the co-shareholder relationship in the whole network is consistent with that of the common institutional shareholder relationship network. (2) The intensity of co-shareholder behavior in the common institutional shareholder relationship network is stronger than that in the common non-institutional shareholder relationship network, and the trend in the whole network is the same as the former. (3) The similarity of the co-shareholder networks is consistent with the change of the co-shareholder relationship and is influenced by the stock market and the difference in the number of co-shareholder relationships. In this paper, we analyze the evolutionary similarity of the co-shareholder relationship between the common institutional shareholder relationship network and the common non-institutional shareholder relationship network and the influence factor of the two networks. This provides a new perspective for analyzing relationships among the listed companies. Highlights • Dividing different sets of shareholders and simulating heterogeneous networks of different shareholders holding listed companies. • Constructing one-mode derivative co-shareholder relationship networks based on the primitive two-mode network. • Providing similarity analysis of different co-shareholder relationship networks. • Providing a new perspective for analyzing relationships among the listed companies. [ABSTRACT FROM AUTHOR]

Abstract Based on the cellular automaton model and the concept of ant pheromone, this paper proposes a new route guidance strategy, called the ant pheromone route guidance strategy, in which the vehicles are regarded as special types of ants and their traffic information is regarded as the ant pheromone. To evaluate its performance, the new route guidance strategy was applied and compared with other three typical route guidance strategies under three different route scenarios, respectively, with open boundary conditions based on the Nagel–Schreckenberg cellular automaton model. First, in a symmetrical two-route scenario with two exits, results showed that the new route guidance strategy and vacancy length route guidance strategy were optimal. They outperformed the other strategies in terms of the value, stability, and balance of vehicle number, and the average speed and average flux on each route. To understand the impact of the strategy on traffic states, flux–density evolution process was studied. In addition, the influence of evaporation rate was also investigated. Second, in an asymmetrical two-route scenario with one exit, the simulation results also proved that ant pheromone route guidance strategy and vacancy length route guidance strategy were the best. Finally, in a symmetrical two-route scenario with a traffic accident, we compared the new route guidance strategy with the vacancy length route guidance strategy. Results indicated that the new route guidance strategy has distinct advantages. In short, in all three route scenarios we investigated, the ant pheromone route guidance strategy performed best. Highlights • This paper proposes the ant pheromone route guidance strategy based on CA model. • The new strategy takes vehicles as ants and vehicles' data as ant pheromones. • Adopting the NS model, this strategy is applied to three two-route scenarios. • Results indicate that the new strategy outperforms other route guidance strategies. • In traffic accident, the new strategy can reduce congestion and save recovery time. [ABSTRACT FROM AUTHOR]

Time series could be mapped into complex networks through the visibility or horizontal visibility algorithms, and the properties of the constructed network reflect the nonlinear dynamics of the time series. When horizontal visibility algorithm is directly applied to climate anomaly time series, in which both local maximum and local minimum are equally important, local minimum might be "overlooked". In this paper, we propose a new method that maps climate anomaly time series into signed networks. Positive and negative data values of climate anomaly time series are classified into two types and mapped as nodes of signed networks. Links connecting nodes of the same type are assigned positive signs, while links connecting neighboring nodes of different types are assigned negative signs. This method is also applicable to time series those are assumed to be "stationary" or with no significant trends. Four kinds of degree as well as the degree distributions of the signed networks have been defined. Specifically, the degree and degree distribution could be partly derived analytically for periodic and uncorrelated random time series. The theoretical predictions for periodic and uncorrelated random time series have also been verified by extensive numerical simulations. Based on the entropy of the distribution of net degree, we propose a new complexity measure for chaotic time series. Compared to some previous complexity measures, the new complexity measure is an objective measure without transforming continuous values into discrete probability distributions but still has higher accuracy and sensitivity. Moreover, correlation information of stochastic time series can also be extracted via a topological parameter, the mean of ratio degree, of the signed networks. The extraction of serial correlation has been illustrated through numerical simulations and verified through an empirical climate time series. • A new method mapping time series into signed networks has been proposed. • Degree distributions have been derived for periodic and random time series. • A complexity measure based on signed networks has been proposed. • Correlation information of time series can be extracted from signed networks. [ABSTRACT FROM AUTHOR]

Distributed statistical inference has received enormous attracted attention in recent years. In this paper, a novel communication efficient one-step estimator on a distributed system is presented, which only needs one round of communication, effectively lowers the communication cost and sufficiently reduces the local computation complexity compared with the existing one-step method. The resulting estimator is statistically efficient as that the entire dataset is analyzed on one machine. Under mild conditions, a risk upper bound is established and the consistency together with asymptotic normality is demonstrated for the proposed estimator. Finally, numerical simulations are carried out to conform the theoretical result. [ABSTRACT FROM AUTHOR]

Studies of crowd behavior with related research on computer simulation provide an effective basis for architectural design and effective crowd management. Based on low-density group organization patterns, a modified two-layer social force model is proposed in this paper to simulate and reproduce a group gathering process. First, this paper studies evacuation videos from the Luan’xian earthquake in 2012, and extends the study of group organization patterns to a higher density. Furthermore, taking full advantage of the strength in crowd gathering simulations, a new method on grouping and guidance is proposed while using crowd dynamics. Second, a real-life grouping situation in earthquake evacuation is simulated and reproduced. Comparing with the fundamental social force model and existing guided crowd model, the modified model reduces congestion time and truly reflects group behaviors. Furthermore, the experiment result also shows that a stable group pattern and a suitable leader could decrease collision and allow a safer evacuation process. [ABSTRACT FROM AUTHOR]

This paper investigates the fixed-time synchronization of complex networks (CNs) with nonidentical nodes and stochastic noise perturbations. By designing new controllers, constructing Lyapunov functions and using the properties of Weiner process, different synchronization criteria are derived according to whether the node systems in the CNs or the goal system satisfies the corresponding conditions. Moreover, the role of the designed controllers is analyzed in great detail by constructing a suitable comparison system and a new method is presented to estimate the settling time by utilizing the comparison system. Results of this paper can be applied to both directed and undirected weighted networks. Numerical simulations are offered to verify the effectiveness of our new results. [ABSTRACT FROM AUTHOR]

The incorporation of different equations of state into single-component multiphase lattice Boltzmann model is considered in this paper. The original pseudopotential model is first detailed, and several cubic equations of state, the Redlich–Kwong, Redlich–Kwong–Soave, and Peng–Robinson are then incorporated into the lattice Boltzmann model. A comparison of the numerical simulation achievements on the basis of density ratios and spurious currents is used for presentation of the details of phase separation in these non-ideal single-component systems. The paper demonstrates that the scheme for the inter-particle interaction force term as well as the force term incorporation method matters to achieve more accurate and stable results. The velocity shifting method is demonstrated as the force term incorporation method, among many, with accuracy and stability results. Kupershtokh scheme also makes it possible to achieve large density ratio (up to 1 0 4 ) and to reproduce the coexistence curve with high accuracy. Significant reduction of the spurious currents at vapor–liquid interface is another observation. High-density ratio and spurious current reduction resulted from the Redlich–Kwong–Soave and Peng–Robinson EOSs, in higher accordance with the Maxwell construction results. [ABSTRACT FROM AUTHOR]

In the real word, the periodic disturbance in traffic flow caused by disrupting maneuvers has a huge impact on the car-following stability. As analyzed in this paper, the asymptotic stability of a car-following model, quantified by the coefficient of dynamic responses, is relatively low at low disturbing frequencies, and gradually increases as the disturbing frequency increases. Fortunately, the development of connected and automated vehicle (CAV) technology and the existing researching works on CAV platoon control have shown great prospect of CAV platooning in the improvement of car-following stability. In order to develop a method to manage the CAV platooning with the explicit purpose of optimizing the car-following stability under periodic disturbance, this study presents an autonomous platoon formation strategy (APFS) for CAV platoon. At certain disturbing frequency, APFS can automatically split a large CAV car-following group into a leading CAV and a number of small CAV platoons, and all CAVs in each platoon follow either the last CAV in the previous platoon or the leading CAV, abiding by the newly designed platoon-based IDM (P-IDM) car-following strategy, so that the overall car-following stability of the CAV group can be optimized. Results of numerical simulations demonstrate that, compared with several existing platoon control strategies, the proposed APFS is capable of significantly enhancing the stability of CAV car-following group, as well as passenger comfort and fuel economy of CAVs, under various types of periodic disturbance. In general, APFS works most effectively when the disturbing frequency is around 0.4 ∼ 0.6 rad/s. Therefore, the proposed APFS shows good potentials in mitigating the oscillation in traffic flow due to periodic perturbations and improving the asymptotic stability of CAV car-following groups. • The asymptotic stability of car-following model under periodic disturbance is analyzed. • A coefficient of dynamic response is defined to quantify the car-following stability under periodic disturbance. • A platoon-based IDM (P-IDM) strategy is designed to elevate the car-following stability of CAV platoon. • An autonomous platoon formation strategy (APFS) is proposed to optimize the car-following stability of CAV platoon. [ABSTRACT FROM AUTHOR]

In this paper, we study the horizontal visibility graphs mapped from multifractal trinomial measures, which are determined by three parameters, p 1 , p 2 , and p 3 , where 0 < p 1 < p 2 < p 3 < 1 , p 1 + p 2 + p 3 = 1. First, we regard multifractal trinomial measures as time series and map them into horizontal visibility graphs. Then, we study the degree distributions in the three cases of p 1 p 3 = p 2 2 , p 1 p 3 > p 2 2 , and p 1 p 3 < p 2 2 . Due to the self-similarity of the induced graphs, the degree distributions of the series are derived using an iterative method. And the numerical simulations coincide excellently with the theoretical degree distributions. • HVGs mapped from multifractal trinomial measures are studied. • Degree distributions of HVGs are derived in an iterative method. • The numerical results obtained support the theoretical analysis. [ABSTRACT FROM AUTHOR]

This paper proposes a novel cascading failure dynamics model for duplex weighted network with unequal flow distribution between layers and taking into account the collapse probability of overloaded nodes. Firstly, the parameter of failure elasticity is introduced to the redundancy capacity of the nodes to carry the load, and the expressions for the tolerance threshold of the entire network in different cases are derived. In addition, the cascading failure processes caused by different deliberate attack strategies are simulated on idealized networks and the IEEE39 network, respectively. Inflection points for the effectiveness of the two attack strategies are obtained, and tolerance thresholds of the theoretical calculations are compared and analyzed with the results of the numerical simulations. Meanwhile, our results indicate that the collapse probability and the redistribution rule are vital in the vulnerability of the network, and the protection mechanism is more effective against attacks on the node of lowest load. Finally, the duplex network becomes more robust as the parameter of failure elasticity increases. Furthermore, the tolerance threshold of the networks presents an ascending trend after dropping initially as the inter-layer distribution proportion increases, and the trend of the numerical simulation is consistent with the theoretical analysis. • A novel cascading failure model of two-layer weighted networks is presented. • We derive the expression of the tolerance threshold for overall duplex network. • Inflection points for the effectiveness of the two attack strategies are obtained. • Duplex networks become more robust as the parameter of failure elasticity increases. [ABSTRACT FROM AUTHOR]

Psychological factors affect the movement of people in the competitive or panic mode of evacuation, in which the density of pedestrians is relatively large and the distance among them is small. In this paper, a crowd is divided into groups according to their social relations to simulate the actual movement of crowd evacuation more realistically and increase the attractiveness of the group based on social force model. The force of group attraction is the synthesis of two forces; one is the attraction of the individuals generated by their social relations to gather, and the other is that of the group leader to the individuals within the group to ensure that the individuals follow the leader. The synthetic force determines the trajectory of individuals. The evacuation process is demonstrated using the improved social force model. In the improved social force model, the individuals with close social relations gradually present a closer and coordinated action while following the leader. In this paper, a grouping algorithm is proposed based on grid density and relationship via computer simulation to illustrate the features of the improved social force model. The definition of the parameters involved in the algorithm is given, and the effect of relational value on the grouping is tested. Reasonable numbers of grids and weights are selected. The effectiveness of the algorithm is shown through simulation experiments. A simulation platform is also established using the proposed grouping algorithm and the improved social force model for crowd evacuation simulation. [ABSTRACT FROM AUTHOR]

The signalized traffic is considerably complex due to the fact that various driving behaviors have emerged to respond to traffic signals. However, the existing cellular automaton models take the signal–vehicle interactions into account inadequately, resulting in a potential risk that vehicular traffic flow dynamics may not be completely explored. To remedy this defect, this paper proposes a more realistic cellular automaton model by incorporating a number of the driving behaviors typically observed when the vehicles are approaching a traffic light. In particular, the anticipatory behavior proposed in this paper is realized with a perception factor designed by considering the vehicle speed implicitly and the gap to its preceding vehicle explicitly. Numerical simulations have been performed based on a signal controlled road which is partitioned into three sections according to the different reactions of drivers. The effects of microscopic driving behaviors on Kerner’s time-delayed traffic breakdown at signal (Kerner 2011, 2013) have been investigated with the assistance of spatiotemporal pattern and trajectory analysis. Furthermore, the contributions of the driving behaviors on the traffic breakdown have been statistically examined. Finally, with the activation of the anticipatory behavior, the influences of the other driving behaviors on the formation of platoon have been investigated in terms of the number of platoons, the averaged platoon size, and the averaged flow rate. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the Turing pattern formation of a reaction–diffusion parasite–host model analytically and numerically. We give the stability of the constant positive steady-state which shows that the model exhibits stationary Turing pattern as a result of diffusion. Via numerical simulations, we present the pattern formation and find that the model dynamics exhibits a diffusion-controlled formation growth of "spots → spots-stripes → stripes → holes-stripes → holes" pattern replication. The results show that we must do our best to regulate the parameters in the special range to avoid disease outbreak. • A reaction–diffusion parasite–host model is developed. • The existence/nonexistence of Turing pattern formation are established. • The complex diffusion-controlled formation growth are shown. • The control strategy to avoid disease outbreak is indicated. [ABSTRACT FROM AUTHOR]

In this paper, a stochastic multimolecular biochemical reaction model with lévy jumps is investigated. Firstly, we prove the existence and uniqueness of the global positive solution. Then we derive the conditions when the reaction will end and when the reaction will proceed. Moreover, the existence of positive recurrence to the solutions is studied by constructing suitable Lyapunov functions. Results show that the end and persistence of the reaction are closely related to the intensity of lévy noise. Finally, numerical simulations are carried out to illustrate the theoretical results. • A stochastic multimolecular biochemical reaction model with lévy jumps is studied. • We establish sufficient conditions for the end and persistence of the reaction. • The existence of positive recurrence to the solutions is investigated. • Numerical simulations are carried out to illustrate the results. [ABSTRACT FROM AUTHOR]

In this paper, a stochastic chemostat model with single-species growth on two perfectly substitutable nutrients under telegraph noise is investigated. Firstly, we prove the solution of the system is positive and global. Then we establish sufficient conditions for the existence of ergodic stationary distribution of the model by constructing suitable Lyapunov functions with regime switching. Finally, numerical simulations are carried out to demonstrate our theoretical results. • A stochastic chemostat model with two nutrients under telegraph noise is considered. • We establish sufficient conditions for the existence of stationary distribution. • The existence of stationary distribution implies stochastic weak stability. • Numerical simulations are carried out to illustrate the results. [ABSTRACT FROM AUTHOR]

Real complex networks usually have small-world effect, scale-free features and hierarchical modularity, a construction method for deterministic hierarchical network is proposed in this paper. The network model with growth and global preferential attachment characteristic and connected by the copy network modules to establish hierarchical network model. By theoretical calculation and numerical simulation about the deterministic hierarchical complex network model, the results illustrate that the complex network model satisfy the small-world effect, scale-free feature and hierarchical modularity, the calculation results show that the size of the hierarchical network model for exponential growth with the network size increased, and the average degree of nodes is shown as linear growth; at the same time, the model of scale-free feature and the hierarchical modularity with network parameters do not have correlation which is an inherent attribute of network model itself; the clustering-degree correlations in the network model satisfy power-law characteristics and the nodes contact closely together in the modules which are connected by the Hub nodes in the complex network model.. • We introduce a complex hierarchical network model through network module replication. • The complex hierarchical network model satisfies the small-world effect and scale-free characteristics. • The clustering-degree correlations of the complex hierarchical network model satisfies the power-law. • The complex hierarchical network model can reflect the characteristics of many complex networks. [ABSTRACT FROM AUTHOR]

Recently, more and more attentions have been applied to rumor spreading, and the reaction of each individual to the rumor appears to be different. Considering the reactions of the susceptible person first time hearing the rumors, in this paper, we divide the whole people in the network into four groups: the susceptible, the believable, the incubative and the uninterested. S I b I n I u rumor spreading model is proposed in both homogeneous networks and heterogeneous networks. By mean-field equations and numerical simulations in both networks, theoretical analysis and the simulation results demonstrate that both losing-interest rate and stifling rate exert negative effect on final rumor spreading scale. • We divide the whole people in the network into four groups. • S I b I n I u rumor spreading model is proposed in both homogeneous networks and heterogeneous networks. • By mean-field equations and numerical simulations in both networks. • The both losing-interest rate and stifling rate exert negative effect on final rumor spreading scale. [ABSTRACT FROM AUTHOR]

This paper concerns a predator–prey model perturbed by a complex type of noises. The main difficulty is to give the threshold λ. We introduce some important lemmas and establish sufficient conditions for persistence stochastically and extinction. In fact, the conditions obtained are very close to the necessary conditions. Finally, numerical simulations and comparisons to existing literatures are given to illustrate our theoretical analysis. • A predator–prey model with nonlinear noises isroposed. • The condition for stochastic persistence is established. • The threshold of extinction is obtained. [ABSTRACT FROM AUTHOR]

Focusing on epidemic model in random environments, this paper uses white noise and Lévy noise to model the dynamics of the SIS epidemic model subject to the random changes of the external environment. We show that the jump encourages the extinction of the disease in the population. We first, give a rigorous proof of the global stability of the disease-free equilibrium state. We also establish sufficient conditions for the persistence of the disease. The presented results are demonstrated by numerical simulations. • We use white noise and Lévy noise to model the dynamics of an SIS epidemic model subject to random changes produced by the external environment. • We showed that jumps encourage the extinction of the disease in the population. • Also we give a rigorous proof for the global stability of the disease-free equilibrium state, and we next establish sufficient conditions ensuring persistence of diseases. [ABSTRACT FROM AUTHOR]

In this paper, we discuss the threshold R 0 ̃ of a stochastic SIS epidemic model with saturated incidence based on [10]. If R 0 ̃ < 1 , the disease will die out for any intensity noise σ 2 > 0 , which is not proved in [10]. Then, it is obtained that the disease will also go to extinction in probability if R 0 ̃ = 1 , which has been left as an open problem in [10] and many other literatures. And when R 0 ̃ > 1 , we get the stochastic persistence of the disease (which is different from the persistence in mean in previous literatures) by using Chebyshev's inequality. And it shows the smaller noise will strengthen the stability of systems. Besides, the existence of the stationary distribution is gotten. Finally, numerical simulations are given to illustrate the results. • A stochastic SIS model with saturated incidence rate is proposed. • The critical result on the threshold is observed. • Smaller noise can strengthen the stability of systems. [ABSTRACT FROM AUTHOR]

Abstract Considering that network community might have a profound effect on the cascading failure of R&D network, we generate the weighted scale-free R&D network and quantify the network community through network modularity Q. Afterwards, we propose the cascading failure model of R&D network based on SIR-CA model, and analyze the special effects on the cascading failure of R&D network through numerical simulation. The simulation results show that network modularity Q has a U-shaped effect on the robustness of R&D network, there is a negative correlation between the delay effect and the robustness of R&D network. Additionally, we verify that overlapping firms have more significant influence than those firms with the same degree and K-shell on the robustness of R&D network. This paper reveals the law of cascading failure of R&D network considering the network community, which is of practical significance to enhance the robustness of R&D network, and enrich the theory of dynamics of the network community. Highlights • The cascading failure model of R&D network based on the SIR-CA model. • The impact of community structure on the cascading failure of R&D network. • The effect of the delay effect on the cascading failure of R&D network. • The effect of overlapping firms on the cascading failure of R&D network. [ABSTRACT FROM AUTHOR]

Abstract Cascading failures are emergent phenomena on interdependent networks and plenty of models have been proposed to explore the features of cascading failures. However, few of them focus on energy-supported dependence relations between interdependent networks including control nodes. In this paper, a load-based energy-supported cascading failure model is proposed on interdependent networks, where the energy control factor λ and control nodes are considered. According to the numerical simulations, it is found that as the energy control factor λ increases, both interdependent Erdős–Rényi (ER) networks and scale-free (SF) networks become more vulnerable. Meanwhile, with the increase of energy control factor λ , interdependent SF networks become more robust than ER networks against random failures. In addition, increasing the power exponent γ can improve the robustness of interdependent SF networks. Finally, although coupling preferences and control node setting strategies have few impacts on cascading failures on interdependent ER networks, the assortative coupling preference (AC) and betweenness control node setting strategy (BS) can improve the robustness of interdependent SF networks. Highlights • An energy-supported cascading failure model is proposed on interdependent networks. • Increasing factor λ makes interdependent SF networks more robust than ER networks. • Increasing exponent γ improves the robustness of interdependent SF networks. • The AC and BS can improve the robustness of interdependent SF networks. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we formulate and study the single-species population models with impulsive toxicant input in polluted environments. For the deterministic single-species population model, the threshold between persistence and extinction is established for single-species population. For the stochastic single-species population model, there is a unique positive solution, which is a prerequisite for analyzing the long-term behavior of the stochastic model. Then, a threshold dynamic determined by μ ̄ is established, which mainly determines the persistence or extinction of the single-species. Numerical simulations are carried out to support our theoretical results. Highlights • Single-species population models with impulsive toxicant input in polluted environments are developed. • The threshold between persistence and extinction of models are given. • The smaller speed of reversion or bigger intensity of volatility can result in the extinction of the single-species. [ABSTRACT FROM AUTHOR]

Abstract In this paper, taking the white noises, Markovian switching and Lévy jumps into account, a stochastic service–resource mutualism model in a polluted environment with pulse toxicant input is proposed and analyzed. The critical value between persistence in the mean and extinction for each species is obtained. Several numerical simulations are also introduced to illustrate the theoretical results. The results reveal that random perturbations, the impulsive period and the toxicant input amount each time have close relationships with the persistence and extinction of the species. Highlights • An stochastic service–resource mutualism model with pollution is proposed. • Threshold between persistence and extinction for each species is given. • Different random perturbations have different impacts on the persistence of the species. • Impulsive period and toxicant input amount can change the persistence of the species. [ABSTRACT FROM AUTHOR]

Abstract Pedestrian dynamics under adverse sight conditions is a difficult point in the field of pedestrian flow. In this paper, an extended cellular automata model is proposed to simulate pedestrian evacuation under adverse sight conditions by considering the effect of uncertain information, in which, the concept of "memory angle" is introduced to quantitatively reflect the accuracy of the evacuation information. The numerical simulations are performed to investigate the effect of the position distribution, the numbers of the memory points and the range of the view field for memory angle on the evacuation process in the room. And the spatiotemporal dynamic characteristics during the evacuation process are also discussed. The results show that the reasonable position distribution of memory points can obviously improve the evacuation efficiency and avoid the crowd caused by the pedestrian flow crash. The pedestrian evacuation efficiency is highest when the more evacuation information near the exit is obtained. In addition, when view field is poor, the accuracy of evacuation information has a significant influence on evacuation time. Highlights • An extended CA model describing the uncertain evacuation information is presented. • The concept of "memory angle" is firstly introduced to quantitatively reflect the accuracy of the evacuation information. • The reasonable position distribution of memory points can improve evacuation efficiency obviously. [ABSTRACT FROM AUTHOR]

Abstract Defending critical infrastructures has received enormous attentions by security agencies. Many infrastructures function as networks such as transportation and communication systems. It is necessary for us to protect them from a network science perspective. In many real-world scenarios, the attacker can observe the defender's action and then choose its best strategy accordingly. Therefore, we propose a Stackelberg game where the defender commits to a strategy, either a pure strategy or a mixed one, and the attacker makes its choice after knowing the defender's action. The strategies and payoffs in this game are defined on the basis of the topology structure of the network. For the convenience of analysis, only two attack and defense strategies, namely, targeted strategy and random strategy, are considered in this paper. The simulation results reveal that in infrastructures with a small cost-sensitive parameter, representing the degree to which costs increase with the importance of a target, the defender commits to a mixed strategy and the attacker's best response is to attack hub nodes with the largest degrees. When the cost-sensitive parameter exceeds a threshold, both the defender and the attacker switch to the random strategy. We also implement experiments with different cost-sensitive parameters and find that the attack-cost-sensitive parameter is the key factor influencing the equilibrium strategies. Our work is a rudimentary attempt to analyze the Stackelberg game in protecting networked infrastructures and it is worth further study. Highlights • We propose a Stackelberg game model to depict the confrontations between the strategic attacker and defender in critical infrastructures. • We define the strategies and payoffs of the game on the basis of the topology structure of the network. • We explore the Strong Stackelberg Equilibriums of the game in different kinds of networks. • We find that the cost sensitivity is the main factor influencing the equilibrium results. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we present an alternative representation of the advection–reaction diffusion model involving fractional-order derivatives with Mittag-Leffler kernel. The study includes three main aspects: existence and uniqueness of solutions, Hyers–Ulam stability, and numerical simulations. For the existence and uniqueness of solutions, we use fixed point approach; also, we presents the Hyers–Ulam stability. For the numerical simulations, a new numerical scheme that involve Lagrange interpolation, Laplace transform and forward Euler technique is considered. Numerical simulations were obtained for some specific parameters. Highlights • Existence, uniqueness solutions and Hyers–Ulam stability are obtained. • Atangana–Baleanu fractional derivative with Mittag-Leffler (M-L) kernel is considered. • Numerical simulations are presented for specific parameters. • The ABC-fractional advection–reaction diffusion model has a unique pair of solutions and is HU-stable. [ABSTRACT FROM AUTHOR]

Abstract Training schools widely exist in China and congestion occurs during the pickup period. However, most researches focus on investigating the pedestrian flow in classroom. In this paper, we study the adult–child matching behavior and each pedestrian's motion (including child and adult) at a training school during the pickup period. Based on the scenario at the training school, and the features of children's and adults' motions, we design three strategies to describe the adult–child matching behavior, and then incorporate the matching behavior into a CA (cellular automaton) model and propose an extended CA model to study each pedestrian's motion under each strategy during the pickup period. The numerical results indicate that each strategy has great effects on the matching behavior and the evacuation efficiency during the pickup period. The results can help administrators to design effective evacuation strategy at training school during the pickup period (especially when an emergency occurs). Highlights • Three child–adult matching strategies are proposed. • An extended CA model is developed to explore the pedestrian flow at training school during the pickup period. • The impacts of the three matching strategies on the pickup efficiency are studied. [ABSTRACT FROM AUTHOR]

Abstract This paper uses the second canteen of Beihang University to study the statistical features of pedestrian flow during the lunch peak period. We first use camera to collect the pedestrian flow data, then analyze the statistical features of data, thirdly propose a model to explore the pedestrian flow during the lunch peak period and finally testify the simulation results and the experiment data. The results show that the proposed model can perfectly reproduce the complex traffic phenomena that occur at university canteen during the peak period. The results can help administrators design some effective evacuation strategies when some emergencies occur at university canteen. Highlights • The statistical features of the pedestrian data during the peak period at a university canteen are studied. • A simple model is proposed to explore the pedestrian flow during the peak period at the canteen. • Some parameters are calibrated by the data. • Some numerical tests are conducted to testify the reasonability of the proposed model. [ABSTRACT FROM AUTHOR]

Abstract In this paper, natural convection in a porous cavity filled with Bingham fluids has been simulated numerically. In order to study the problem, an innovative Lattice Boltzmann method for porous media of Bingham fluid is introduced. In this study, the Papanastasiou regularisation of the Bingham constitutive model has been applied for the studied Bingham fluid and moreover the Darcy–Brinkman–Forchheimer model has been employed for the porous media. Fluid flow, heat transfer, and yielded/unyielded parts have been conducted for certain pertinent parameters of Rayleigh number (R a = 1 0 4 – 1 0 7), Darcy number (D a = 1 0 − 2 , 1 0 − 4 , 1 0 − 6), and porosity (ϵ = 0.1 – 0.9). Moreover, the Bingham number (B n) is studied in a wide range of different studied parameters. Results indicate that the heat transfer increases and the unyielded section diminishes as Rayleigh number rises. For specific Rayleigh and Darcy numbers, the increase in the Bingham number decreases the heat transfer. Furthermore, the growth of the Bingham number expands the unyielded sections in the cavity. Finally, for fixed Rayleigh and Bingham numbers, the unyielded region is decreased by the augmentation of the porosity. In addition, heat transfer augments gradually as the porosity increases. Highlights • For fixed Rayleigh and Bingham numbers, the augmentation of the porosity decreases the unyielded region. • Heat transfer augments gradually as the porosity increases. • The growth of the Bingham number expands the unyielded sections in the cavity. [ABSTRACT FROM AUTHOR]

Abstract An exact formula for computing the average hopcount of the shortest path in finite-size tree-like components of undirected unweighted random networks is proposed. In a tree-like component with size s , there exists virtually only one shortest path between two arbitrary nodes. The summation of hopcounts of all shortest paths can be calculated approximately by the summation of the betweenness of all nodes, and the difference between them is only a constant s (s − 1). Therefore, the average hopcount can be calculated by further dividing the summation by the number of all shortest paths. In this paper, we first derive the conditional probability p (k | s) of the degree distribution of finite components with size s and the summation of all nodal betweenness respectively. By means of these results, we obtain the exact formula for calculating the average hopcount. Also, We confirm the proposed formula by simulations for networks with Poisson and power law degree distributions respectively. [ABSTRACT FROM AUTHOR]

Abstract Identifying the influential spreaders of information spreading dynamics is a hot topic in the field of network science. To identify the influential spreaders, most previous studies were based on the global information of the network. In this paper, we propose a strategy for identifying the influential spreaders from a randomly selected initial-seed node. The seeds are connected as a chain, and are localized to the initial-seed. In our proposed preferentially random walk based influential spreaders identifying strategy, the walker's movement is adjusted by neighbors' degrees. The seeds are those nodes that the walker ever visited. Through extensive numerical simulations on artificial networks and four real-world networks, we find that selecting large degree nodes preferentially is more likely to find the most influential spreaders. The outbreak threshold decreases when preferentially select hubs. Our results shed some light into identifying the most localized influential spreaders. Highlights • Proposing a strategy for identifying the localized influential spreaders from a randomly selected initial-seed node. • Selecting large degree nodes preferentially is more likely to find the most influential spreaders. • The effectiveness of the strategy is verified in both artificial and real-world networks. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we study the effects of heterogeneous population on the dynamics of social contagions on multiplex networks. We assume a fraction of f nodes with a higher adoption threshold T > 1 , and the remaining fraction of 1 − f nodes with adoption threshold 1. A social contagion model is proposed to describe the social contagions, in which a susceptible node adopting the contagion only when its received accumulated information is larger than the adoption threshold in either subnetwork. With an edge-based compartmental approach and extensive numerical simulations, we find that the system exhibits a continuous phase transition for small values of f , while shows a hybrid phase transition for relatively large values of f and T. For homogeneous multiplex networks the hybrid phase transition occurs, while there is only a continuous phase transition for heterogeneous multiplex networks. Our theoretical predictions agree well with numerical simulations. Highlights • Proposing a social contagion model on multiplex networks with heterogeneous population. • An edge-based compartmental approach is developed, and well predicts numerical simulations. • The system exhibits a continuous or hybrid phase transition. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we propose the multiscale joint permutation entropy (MJPE) to study the synchronism between two complex time series from the view of ordinal pattern and multiple scales. First, we use the Rossler system using active control, two-component ARFIMA processes to test the effectiveness of MJPE and also add some noise to the ARFIMA time series and apply MJPE to find the effect of noise. The results show the necessity of investigating the synchronism on the multiple scales, prove the effectiveness of MJPE method and show the sensitiveness of MJPE method to noise. Then MJPE method is employed to financial time series and traffic time series to validate the applicability of the proposed MJPE method for the complex time series in the real world. The conclusion from these MJPE results for financial time series is consistent with the actual situation of the synchronism and correlation between stock indices. Meanwhile, the results for traffic time series suggest the need for study the synchronism from the perspective of multiple scales and point out the different synchronisms for traffic time series of weekdays and weekends. MJPE method has a broad application prospect on the investigation of synchronism on the complex time series from different fields. Highlights • We propose MJPE method to study the synchronism between two time series. • We apply MJPE method to the simulated time series to test the validity. • The results show the necessity of multiscale and prove the effectiveness of MJPE. • MJPE method is employed to the financial and traffic time series. • MJPE results present the synchronisms from multiscale view successfully. [ABSTRACT FROM AUTHOR]

Abstract Self-stabilization effect reflects the adaptive change of the current lattice in traffic flow. To improve traffic flow, a new self-stabilization term in this paper is inserted into lattice hydrodynamic model for two-lane freeway. It is shown that the self-stabilization effect can increase traffic stability on two lanes whether lane changing occurs or not according to linear stability analysis. In view of numerical simulation, the self-stabilization effect enhances the stability of the traffic flow in the modified lattice hydrodynamic model for two-lane freeway. Highlights • A new lattice model is proposed with self-stabilization effect for two lanes. • Linear stability condition is obtained with self-stabilization effect on two-lane highway. • Simulation tests verify that traffic jams are suppressed efficiently with self-stabilization effect besides lane changing. [ABSTRACT FROM AUTHOR]

Abstract This paper focuses on exploring the effects of the prevision relative velocity on the dynamics characteristic of the simulated traffic flow in the ACC strategy. Firstly, an improved car-following considering the prevision relative velocity is developed for numerical simulations. Secondly, an adaptive neural-fuzzy inference system is trained and employed to predict the relative velocity. Thirdly, a microscopic traffic simulation program is created to analyze the traffic flow evolution process, further to explore the effects of the prevision relative velocity on the dynamics characteristic. The results show that considering the prevision relative velocity in designing the ACC control strategy can significantly affect the dynamics characteristic of the simulated traffic flow, which can improve the traffic flow stability in the ITS environment. Highlights • An improved car-following model considering the prevision relative velocity is proposed. • The stable condition of the proposed model is obtained. • The effects of the prevision relative velocity on the traffic dynamics is explored. [ABSTRACT FROM AUTHOR]

Abstract This paper presents an extended car-following model by taking driver's memory and the full velocity difference into the original optimal velocity model (OVM). The stability condition of this model is obtained by using linear stability theory. The TDGL equation and the mKdV equation are derived from nonlinear analysis. The energy consumption of new car-following models considering the driver's memory is discussed. Furthermore, the new car-following model is investigated in detail by numerical methods. Both analytical and simulation results show that the extended following car-following model will not only suppress the traffic congestion but also reduce energy consumption. Highlights • An extended car-following model is developed considering driver's memory. • Applying the linear stability theory, the new model's linear stability is obtained. • The time-dependent Ginzburg–Landau (TDGL) equation and the modified Korteweg–de Vries (mKdV) equation are derived. [ABSTRACT FROM AUTHOR]

Abstract Pedestrian dynamics with affected visual field under emergency situation is a difficult point in the simulation of pedestrian flow. In this paper, an extended cost potential field cellular automaton model is proposed to investigate the motion of pedestrians through obscure room lack of visibility (due to smoke, darkness, etc.). A novel visibility function is introduced to describe visual effect caused by poor vision, which will lead to the increasing cost of discomfort. The numerical simulations are performed to explore the effects of factors, such as psychology tension, visual radius and pedestrian density on pedestrian evacuation. It was found that evacuation time relies on visual radius and initial density. The evacuation time under affected visual field increases with the decrease of visual radius. At low density, a moderate tension degree can improve the evacuation efficiency. These findings will be helpful in pedestrian control and management under an emergency. Highlights • An extended cost potential CA model describing the restriction of visual field is presented. • A visibility function is introduced to describe visual effect. • The extended cost function is related to three factors: density, behavior variation and visual effect. • Evacuation time relies on visual radius and initial density. • A moderate tension degree can improve the evacuation efficiency at low density. [ABSTRACT FROM AUTHOR]

Abstract In this study, a three-dimensional mesoscopic simulation of magneto hydrodynamics (MHD) natural convection in a cubic cavity has been studied by new means of the Lattice Boltzmann method with double Multi-Relaxation-Time (MRT) model. In order to solve the momentum and energy equations, two different populations with various lattices have been used. This paper has been conducted for specific values of the Grashof number (Gr = 2 × 1 0 3 _ 2 × 1 0 5) and Hartmann number (Ha=0–100), while the Prandtl number is fixed at Pr = 0. 73. The results are presented in the form of average and local Nusselt number and contours of temperature and velocity at different planes of the cavity. It was found that the double MRT-LBM method is an appropriate approach to solve the studied case. The present results also show that the increase of the Hartmann number causes the heat transfer to drop considerably. Also, the effect of Hartmann number increases by enhancing the Grashof number, as the reduction of average Nusselt number is 12% for Gr = 2 × 1 0 3 and 71% for Gr = 2 × 1 0 5 when Hartmann number increases from 0 to 100. In contrast with Hartmann number, increasing of Grashof number raises heat transfer rate and the average Nusselt number increases by more than three times by enhancing the Grashof number from 2 × 1 0 3 to 2 × 1 0 5. Highlights • Double MRT LBM method has been developed for three-dimensional MHD flow. • Average Nusselt number drops 71% when the Hartmann number rises from 0 to 100 for Gr = 2 × 1 0 5. • Average Nusselt number enhances 330% when Grashof number alters from 2 × 1 0 3 to 2 × 1 0 5. [ABSTRACT FROM AUTHOR]

Abstract There is a close interplay between the disease spreading on contact network and corresponding information propagation on communication network. Especially, it will be of much interest when there are certain overlaps between the topological edges of communication network and contact network. In this paper, we study the effect of inter-layer edge overlap on the asymmetrically interacting spreading dynamics of disease and information, mainly including the final fraction of infected nodes and the epidemic threshold Though extensive simulations, we find that there is a so called double-edged sword effect on epidemic spreading and information propagation. Namely, when the disease spreads faster than information, a smaller amount of overlapping edges is able to effectively inhibit the epidemic spreading. On the contrary, when the information propagates more quickly than disease spreads, the more overlapping edges are, the better the epidemic spreading is suppressed. In further, we show that the epidemic threshold is improved when the overlapping edges increase. These results can provide a significant guidance to make optimal strategies for suppressing epidemic spreading. Highlights • We study the effect of inter-layer edge overlap on the asymmetrically interacting spreading of disease and information. • The edge overlapping has double-edged sword effect on the spreading of disease and information. • The epidemic threshold is improved when the amount of overlapping edges increase. [ABSTRACT FROM AUTHOR]