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Abstract: We investigate a population of individuals who play the Rock–Paper–Scissors (RPS) game. The players choose strategies not only by optimizing their payoffs, but also taking into account the popularity of the strategies. For the standard RPS game, we find an asymptotically stable polymorphism with coexistence of all strategies. For the general RPS game we find the limit cycles. Their stability depends exclusively on two model parameters: the sum of the entries of the RPS payoff matrix, and a sensitivity parameter which characterizes the personality of the players. Apart from the supercritical Hopf bifurcation, we found the subcritical bifurcation numerically for some intervals of the parameters of the model. [Copyright &y& Elsevier]

Abstract: The game ‘rock–paper–scissors’ model, with the consideration of the effect of the psychology of conformity, is investigated. The interaction between each two agents is global, but the strategy of the conformity is local for individuals. In the statistical opinion, the probability of the appearance of each strategy is uniform. The dynamical analysis of this model indicates that the equilibrium state may lose its stability at a threshold and is replaced by a globally oscillating state. The global oscillation is induced by the local conformity, which is originated from the synchronization of individual strategies. [Copyright &y& Elsevier]

Abstract: Cyclic competition game models, particularly the “rock–paper–scissors” model, play important roles in exploring the problem of multi-species coexistence in spatially ecological systems. We propose an extended “rock–paper–scissors” game to model cyclic interactions among five species, and find that two of the five can coexistent when biodiversity disappears, which is different from the “rock–paper–scissors” game. As the number of fingers is five, we named the new model the “fingers” game, where the thumb, forefinger, middle finger, ring finger, and little finger cyclically dominate their subsequent species and are dominated by their former species. We investigate the “fingers” model in two ways: direct simulations and nonlinear partial differential equations. An important finding is that the number of species in a cyclic competition game has an influence on the emergence of biodiversity. To be specific, the “rock–paper–scissors” model is in favor of maintaining biodiversity in comparison with the “fingers” model when the variables (population size, reproduction rate, selection rate, and migration rate) are the same. It is also shown that the mobility and reproduction rate can promote or jeopardize biodiversity. [Copyright &y& Elsevier]

Abstract In this paper, a generalized car-following model is proposed to investigate the trip cost of each commuter in a traffic corridor with one entry and one exit at equilibrium state. Trip cost consists of the travel time cost and the penalty cost of arriving at destination early or late. At equilibrium, all commuters experience identical trip cost regardless of their departure time. We use the full velocity difference (FVD) model to compute the trip cost of a commuter who leaves home at specific time, find a function to fit each commuter's time headway at the equilibrium state, and verify the fitted function from different perspectives. Finally, we utilize the fitted function of time headway to explore some extension cases (e.g., the number of commuters or the first commuter's departure time is changed). The paper has revealed some properties of the traffic corridor and proposed some methods to research the traffic corridor in deep from microscopic perspective, which can be easily extended to investigate complex traffic corridor problems and policy making. Highlights • The properties of the traffic corridor considering late arrival is analyzed. • Two methods are proposed to study the time headway pattern. • The fitting method is verified by the microscopic method. • The fitting method is used to explore some extension cases. [ABSTRACT FROM AUTHOR]

There is a certain relationship between the global financial markets, which creates an interactive network of global finance. Transfer entropy, a measurement for information transfer, offered a good way to analyse the relationship. In this paper, we analysed the relationship between 9 stock indices from the U.S., Europe and China (from 1995 to 2015) by using transfer entropy (TE), effective transfer entropy (ETE), Rényi transfer entropy (RTE) and effective Rényi transfer entropy (ERTE). We compared the four methods in the sense of the effectiveness for identification of the relationship between stock markets. In this paper, two kinds of information flows are given. One reveals that the U.S. took the leading position when in terms of lagged-current cases, but when it comes to the same date, China is the most influential. And ERTE could provide superior results. [ABSTRACT FROM AUTHOR]

Predicting missing links is of both theoretical value and practical interest in network science. In this paper, we empirically investigate a new link prediction method base on similarity and compare nine well-known local similarity measures on nine real networks. Most of the previous studies focus on the accuracy, however, it is crucial to consider the link predictability as an initial property of networks itself. Hence, this paper has proposed a new link prediction approach called evidential measure (EM) based on Dempster–Shafer theory. Moreover, this paper proposed a new method to measure link predictability via local information and Shannon entropy. [ABSTRACT FROM AUTHOR]

The Kiyotaki and Wright (1989) (henceforth KW) model of money emergence as a medium of exchange has been studied from various perspectives in recent papers. In the present work we propose a minimalistic model for the behavior of agents in the KW framework, which may either reproduce the theoretical predictions of Kiyotaki and Wright (1989) on the emerging Nash equilibria, or (less closely) the empirical results of Brown (1996), Duffy and Ochs (1999) and our own, introduced in a first part of the present paper. The main import is the systematic computer scanning of speculative monetary equilibria under drastic bounded rationality of agents, based on behavior previously observed in the lab. [ABSTRACT FROM AUTHOR]

In this paper new Value at Risk (VaR) model is proposed and investigated. We consider the multifractal property of financial time series and develop a multifractal Value at Risk (MFVaR). MFVaR introduced in this paper is analytically tractable and not based on simulation. Empirical study showed that MFVaR can provide the more stable and accurate forecasting performance in volatile financial markets where large loss can be incurred. This implies that our multifractal VaR works well for the risk measurement of extreme credit events. [ABSTRACT FROM AUTHOR]

This paper aims to study the combined impact of reinstalling system and network topology on the spread of computer viruses over the Internet. Based on scale-free network, this paper proposes a novel computer viruses propagation model— SLBOS model. A systematic analysis of this new model shows that the virus-free equilibrium is globally asymptotically stable when its spreading threshold is less than one; nevertheless, it is proved that the viral equilibrium is permanent if the spreading threshold is greater than one. Then, the impacts of different model parameters on spreading threshold are analyzed. Next, an optimally controlled SLBOS epidemic model on complex networks is also studied. We prove that there is an optimal control existing for the control problem. Some numerical simulations are finally given to illustrate the main results. [ABSTRACT FROM AUTHOR]

The projection of the intensity of the epidemics based on their prolonged history remains wanting or lagging altogether. Numerous modeling techniques are being developed to forecast the future of the disease. Various mathematical models have been developed in the literature which assume the spread of infection by considering interaction among the susceptible and infected classes only. In this paper, we propose a more realistic modified SEIR (susceptible–exposed–infected–recovered) model with a time delay in which the origin of infection by interaction within the susceptible and exposed classes is also analyzed. Moreover, various stochastic characteristics, such as population migration and linkages at local levels, are also taken into account to depict more logical population dynamics. We compute the basic reproductive number and investigate the existence and stability of disease-free equilibrium and endemic equilibrium. The effect of crucial parameters influencing disease dynamics on basic reproductive numbers is also being investigated. It has been seen that the basic reproductive number increases with the increase in time delay, contrary to observations in the past. This highlights the significance of the incorporated modified interactions within susceptible and exposed classes along with their factual parameters on the disease dynamics. • We propose a modified SEIR model with time delay. • Interaction within the susceptible and exposed classes is considered. • The parameters like population movement and local connections are incorporated. • The existence and stability of disease-free and endemic equilibrium are examined. • The basic reproductive number and its relation with important parameters is analyzed. [ABSTRACT FROM AUTHOR]

The global spread of COVID-19 has not been effectively controlled, posing a huge threat to public health and the development of the global economy. Currently, a number of vaccines have been approved for use and vaccination campaigns have already started in several countries. This paper designs a mathematical model considering the impact of vaccination to study the spread dynamics of COVID-19. Some basic properties of the model are analyzed. The basic reproductive number ℜ 1 of the model is obtained, and the conditions for the existence of endemic equilibria are provided. There exist two endemic equilibria when ℜ 1 < 1 under certain conditions, which will lead to backward bifurcation. The stability of equilibria are analyzed, and the condition for the backward bifurcation is given. Due to the existence of backward bifurcation, even if ℜ 1 < 1 , COVID-19 may remain prevalent. Sensitivity analysis and simulations show that improving vaccine efficacy can control the spread of COVID-19 faster, while increasing the vaccination rate can reduce and postpone the peak of infection to a greater extent. However, in reality, the improvement of vaccine efficacy cannot be realized in a short time, and relying only on increasing the vaccination rate cannot quickly achieve the control of COVID-19. Therefore, relying only on vaccination may not completely and quickly control COVID-19. Some non-pharmaceutical interventions should continue to be enforced to combat the virus. According to the sensitivity analysis, we improve the model by including some non-pharmaceutical interventions. Combining the sensitivity analysis with the simulation of the improved model, we conclude that together with vaccination, reducing the contact rate of people and increasing the isolation rate of infected individuals will greatly reduce the number of infections and shorten the time of COVID-19 spread. The analysis and simulations in this paper can provide some useful suggestions for the prevention and control of COVID-19. [ABSTRACT FROM AUTHOR]

A range of new fractional-order love dynamics is modelled in this paper using the Caputo (power-law), Caputo–Fabrizio (exponential decay-law) and Atangana–Baleanu (Mittag-Leffler-law) fractional operators. We utilize the new fractional Adams–Bashforth schemes for the approximation of these derivatives. This method was developed with the standard differentiation technique by applying the fundamental theorem of calculus and taking the difference of two times levels at t = (t n , t n + 1). The stability analysis applies the theory of classical order differential equations and dynamical system. The Existence and uniqueness of solution of fractional dynamics is proved by adopting the fixed-point theorem. Numerical results presented for various α − values justify the theoretical findings. It was observed that modelling of interpersonal and romantic love affairs with fractional derivative could exhibit some strange emotional attractors. • Fractional two-step Adams–Bashforth methods. • Numerical approximation and simulation. • Existence and uniqueness of solutions via fixed-point theorem. • The Caputo, Caputo–Fabrizio and Atangana–Baleanu fractional derivatives. [ABSTRACT FROM AUTHOR]

Spatial epidemic has increasingly become the focus of attention of the global population, and epidemics modeling is an important tool for its prevention and control. However, how to choose the better model has always the challenge faced by modelers. This paper provides a possible method of model selection based on two Turing's diffusive thresholds of a spatial epidemic model: the inherent diffusive threshold and the practical diffusive threshold. It is a new classification in terms of original Turing region obtained by linear analysis. The inherent diffusive threshold of the model is mathematical without realistic significance; on the contrary, the practical diffusive threshold is the physical diffusive threshold. The region between two thresholds has both realistic and mathematical significance. For a classical spatial epidemic model, we derive these two types of thresholds, and find that the larger the area size between two thresholds, the more models contain dynamical behaviors possibly describing spatial epidemic transmission dynamics which are also the models needed by modelers. Our approach may provide a new insight into the selection of spatial epidemic models. • Two types of thresholds are proposed on spatial epidemics: the inherent and practical diffusive thresholds. • The larger the area between two thresholds, the more dynamical behaviors models contain possibly describing spatial epidemic transmission dynamics. • A possible method of model selection on spatial epidemics is given based on two Turing's diffusive thresholds of a spatial epidemic model. [ABSTRACT FROM AUTHOR]

The explosive development of research on real networks have led to the proposal of many mathematical network models explaining properties shared in the real networked systems. However, considering that different models can similarly reproduce the typical properties of networks, the estimation of the evolutionary process is more essential for appropriate network modeling than is the description of current network structures. In this paper, we propose a new measure "distribution of distances between neighbors (DDN) of each vertex" to investigate network development. We first examine several model networks, including growth models based on the attachment rule and on the local rule and their hybrid models, and show that the DDN profiles of these networks accurately reflect the differences in growth mechanisms. In particular, for the local rule model, the dependence of the mean DDN of vertices on the vertex degree records the evolution of the local network structure. The application of the same analysis to several real networks show that they share the characteristics of DDN profiles with the local rule and hybrid models. These results imply that these model networks appropriately describe the evolutionary processes of real networks. In addition, we examine the characteristics of DDN specific to fractal and non-fractal networks, and show that the presence or absence of fractality of some real networks can be explained by the influence of long-range edges on the local rule. An exception to this is the co-authorships network, which is expected to be generated by connecting several fractal sub-networks. • Distance distribution between neighbors (DDN) is newly proposed to examine networks. • Mean DDN records the evolutionary process of local network structures. • Evolutionary processes of real networks were characterized by DDN profiles. • The origin of fractality of networks was uncovered by the investigation using DDN. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we translate the two higher levels of the Ergodic Hierarchy [11], the Kolmogorov level and the Bernoulli level, to quantum language. Moreover, this paper can be considered as the second part of [3]. As in [3], we consider the formalism where the states are positive functionals on the algebra of observables and we use the properties of the Wigner transform [12]. We illustrate the physical relevance of the Quantum Ergodic Hierarchy with two emblematic examples of the literature: the Casati–Prosen model [13,14] and the kicked rotator [6–8]. [Copyright &y& Elsevier]

Abstract: Pareto distributions, and power laws in general, have demonstrated to be very useful models to describe very different phenomena, from physics to finance. In recent years, the econophysical literature has proposed a large amount of papers and models justifying the presence of power laws in economic data. Most of the times, this Paretianity is inferred from the observation of some plots, such as the Zipf plot and the mean excess plot. If the Zipf plot looks almost linear, then everything is ok and the parameters of the Pareto distribution are estimated. Often with OLS. Unfortunately, as we show in this paper, these heuristic graphical tools are not reliable. To be more exact, we show that only a combination of plots can give some degree of confidence about the real presence of Paretianity in the data. We start by reviewing some of the most important plots, discussing their points of strength and weakness, and then we propose some additional tools that can be used to refine the analysis. [Copyright &y& Elsevier]

Abstract: This paper explores a statistical mechanics approach as a means to better understand specific land cover changes on a continental scale. Integrated assessment models are used to calculate the impact of anthropogenic emissions via the coupling of technoeconomic and earth/atmospheric system models and they have often overlooked or oversimplified the evolution of land cover change. Different time scales and the uncertainties inherent in long term projections of land cover make their coupling to integrated assessment models difficult. The mainstream approach to land cover modelling is rule-based methodology and this necessarily implies that decision mechanisms are often removed from the physical geospatial realities, therefore a number of questions remain: How much of the predictive power of land cover change can be linked to the physical situation as opposed to social and policy realities? Can land cover change be understood using a statistical approach that includes only economic drivers and the availability of resources? In this paper, we use an energy transition paradigm as a means to predict this change. A cost function is applied to developed land covers for urban and agricultural areas. The counting of area is addressed using specific examples of a Pólya process involving Maxwell–Boltzmann and Bose–Einstein statistics. We apply an iterative counting method and compare the simulated statistics with fractional land cover data with a multi-national database. An energy level paradigm is used as a basis in a flow model for land cover change. The model is compared with tabulated land cover change in Europe for the period 1990–2000. The model post-predicts changes for each nation. When strong extraneous factors are absent, the model shows promise in reproducing data and can provide a means to test hypothesis for the standard rules-based algorithms. [Copyright &y& Elsevier]

Abstract: In China, both the mountainous areas and the number of people who live in mountain areas occupy a significant proportion. When production accidents or natural disasters happen, the residents in mountain areas should be evacuated and the evacuation is of obvious importance to public safety. But it is a pity that there are few studies on safety evacuation in rough terrain. The particularity of the complex terrain in mountain areas, however, makes it difficult to study pedestrian evacuation. In this paper, a three-dimensional surface cellular automata model is proposed to numerically simulate the real time dynamic evacuation of residents. The model takes into account topographic characteristics (the slope gradient) of the environment and the biomechanics characteristics (weight and leg extensor power) of the residents to calculate the walking speed. This paper only focuses on the influence of topography and the physiological parameters are defined as constants according to a statistical report. Velocity varies with the topography. In order to simulate the behavior of a crowd with varying movement velocities, and a numerical algorithm is used to determine the time step of iteration. By doing so, a numerical simulation can be conducted in a 3D surface CA model. Moreover, considering residents evacuation around a gas well in a mountain area as a case, a visualization system for a three-dimensional simulation of pedestrian evacuation is developed. In the simulation process, population behaviors of congestion, queuing and collision avoidance can be observed. The simulation results are explained reasonably. Therefore, the model presented in this paper can realize a 3D dynamic simulation of pedestrian evacuation vividly in complex terrain and predict the evacuation procedure and evacuation time required, which can supply some valuable information for emergency management. [Copyright &y& Elsevier]

Abstract: In this paper Chinese phrases are modeled using complex networks theory. We analyze statistical properties of the networks and find that phrase networks display some important features: not only small world and the power-law distribution, but also hierarchical structure and disassortative mixing. These statistical traits display the global organization of Chinese phrases. The origin and formation of such traits are analyzed from a macroscopic Chinese culture and philosophy perspective. It is interesting to find that Chinese culture and philosophy may shape the formation and structure of Chinese phrases. To uncover the structural design principles of networks, network motif patterns are studied. It is shown that they serve as basic building blocks to form the whole phrase networks, especially triad 38 (feed forward loop) plays a more important role in forming most of the phrases and other motifs. The distinct structure may not only keep the networks stable and robust, but also be helpful for information processing. The results of the paper can give some insight into Chinese language learning and language acquisition. It strengthens the idea that learning the phrases helps to understand Chinese culture. On the other side, understanding Chinese culture and philosophy does help to learn Chinese phrases. The hub nodes in the networks show the close relationship with Chinese culture and philosophy. Learning or teaching the hub characters, hub-linking phrases and phrases which are meaning related based on motif feature should be very useful and important for Chinese learning and acquisition. [Copyright &y& Elsevier]

Abstract: Scientific communication is an essential part of modern science: whereas Archimedes worked alone, Newton (correspondence with Hooke, 1676) acknowledged that “If I have seen a little further, it is by standing on the shoulders of Giants.” How is scientific communication reflected in the patterns of citations in scientific papers? How have these patterns changed in the 20th century, as both means of communication and individual transportation changed rapidly, compared to the earlier post-Newton 18th and 19th centuries? Here we discuss a diffusive model for scientific communications, based on a unique 2009 scientometric study of 25 million papers and 600 million citations that encapsulates the epistemology of modern science. The diffusive model predicts and explains, using no adjustable parameters, a surprisingly universal internal structure in the development of scientific research, which is essentially constant across the natural sciences, but which because of globalization changed qualitatively around 1960. Globalization corresponds physically to anomalous diffusion, which has been observed near the molecular glass transition, and can enhance molecular diffusion by factors as large as 100. [Copyright &y& Elsevier]

Abstract: For the study of citation networks, a challenging problem is modeling the high clustering. Existing studies indicate that the promising way to model the high clustering is a copying strategy, i.e., a paper copies the references of its neighbor as its own references. However, the line of models highly underestimates the number of abundant triangles observed in real citation networks and thus cannot well model the high clustering. In this paper, we point out that the failure of existing models lies in that they do not capture the connecting patterns among existing papers. By leveraging the knowledge indicated by such connecting patterns, we further propose a new model for the high clustering in citation networks. Experiments on two real world citation networks, respectively from a special research area and a multidisciplinary research area, demonstrate that our model can reproduce not only the power-law degree distribution as traditional models but also the number of triangles, the high clustering coefficient and the size distribution of co-citation clusters as observed in these real networks. [Copyright &y& Elsevier]

Abstract Since Generative Adversarial Nets (GANs) has been proposed in 2014, it has become one of the most popular hot topics. Deep Convolutional Generative Adversarial Networks (DCGAN) is greatly promoted the development and application of GANs. In this paper, we have made an in-depth exploration for the most popular DCGAN at present via utilizing TensorFlow deep learning framework, using the open CelebA face dataset of The Chinese University of Hong Kong as the data source. By comparing DCGAN unconstrained and DCGAN constrained, the experimental results show that the DCGAN model significantly improves the virtual face generation model after adding constraints in the training phase, which enhance the ability of the generator to deceive the discriminator. Finally, we have evaluated the proposed model from the perspective of TensorBoard and achieved the desired experimental results. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we utilize route flow to propose a network traffic flow model with consideration of interruption factors. The proposed model is then used to study the effects of two typical interruption factors (e.g., bus station and accident) and the divergence effect at the shared node on each link's traffic flow. The model is conducted under the stochastic route choice behavior in a network with an origin–destination (OD) pair and two routes, where the numerical results indicate that the proposed model can qualitatively describe some complex physical phenomena (e.g., shock, rarefaction wave, stop-and-go, jam and route divergence). The above phenomena are related to each route's initial density, where the formation and propagation speed are affected by network structure and route choice behavior. Highlights • A route-based network traffic flow model is proposed. • The impacts of three bus stations on each link's traffic flow are studied in a simple network. • The impacts of an accident on each link's traffic flow are studied under two situations. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we studied a HIV latent infection model with two time delays, where one delay is the time between viral entry into a cell and establishment of HIV latency and the other delay is the time between cell infection and viral production. The infection usually considered is linear, but in this article we consider that the infection rate of modeling HIV infection is nonlinear, where the rate of infection is β T V 1 + b V , and logistic growth of the uninfected target cells T. We defined the basic reproductive number and showed the local and global stability of the disease-free equilibrium and the permanence of the infected equilibrium. Furthermore, we discussed the dynamics of system under the three conditions: (1) τ 1 = τ 2 = 0 , (2) τ 1 = 0 , τ 2 > 0 , (3) τ 1 > 0 , τ 2 ∈ [ 0 , τ 2 ∗). Highlights • A new HIV latent infection model with two time delays is introduced. • Numerical simulations are provided to support the theoretical analyses. • The basic reproduction number is obtained. • Our results show that the size of the delay can affect the infected equilibrium leading to a Hopf bifurcation. [ABSTRACT FROM AUTHOR]

Abstract The emergence and maintenance of cooperation among selfish individuals is still a fundamental problem in evolutionary biology and social science, and Prisoner's Dilemma game (PDG) is an important metaphor to study the evolution of cooperation. In this paper, we propose a three-dimensional model based on the PDG in which the harsh ecological environment (indicated by predation stress) is considered. Our results show that proper predation stress is a positive factor for the evolution of cooperation. Moderate predation stress lead to the increase of cooperators, but too large predation stress result in the extinction of cooperators. Moreover, we find that the fraction of cooperators decreases monotonously with the increasing of the cost-to-benefit ratio, but increases monotonously with the increasing of encounter probability. These results indicate that our model represents a step towards understanding how the harsh ecological environment can affect the evolution of cooperation. Highlights • We present a model which is added the predation stress in the PDG. • Moderate predation stress lead to the increase of the cooperation. • Cooperation decreases monotonously with the increasing of the cost-to-benefit ratio. [ABSTRACT FROM AUTHOR]

Abstract Most of previous research on complex networks always concentrates on topology, ignoring the coordinates of components. However, the spatial information of components may be a key factor influencing the invulnerability of actual networks. For interdependent infrastructures, considering space constraints, dependency links may be established locally, where only nodes within certain connection radius r c o n n e c t can be connected as dependent node pairs. Therefore, based on the topology-based cascading failure model, the invulnerability of interdependent scale-free networks is studied by introducing five coupling patterns in this paper, including global and local random couplings GR and LR , global and local degree–degree inter-similarity couplings GD and LD and nearest neighbor coupling NN. Under topological attacks, the inter-similarity couplings GD and LD have better performance, and as r c o n n e c t increases, the effect of LD will gradually approach to GD. In order to ensure a good invulnerability and low construction cost, a novel hybrid coupling pattern of NN and LD is proposed. With numerical simulations, we find that selecting nodes with large degree to establish LD coupling has significant effect, and there is an optimal selection fraction. Under localized attacks, the local couplings perform better, and LD is better for small r c o n n e c t while NN is better for large r c o n n e c t. In addition, we also study a simplified localized attacking strategy analytically based on percolation theory, which is proved to be consistent with the numerical results. For LD coupling, the effect will be influenced by r c o n n e c t , and there are minimum and maximum invulnerability values for topological and localized attacks, respectively. These findings can help to understand the characteristics of spatially embedded interdependent infrastructures. Highlights • The connection radius of dependency links is studied based on network connectivity. • A hybrid coupling is proposed to ensure invulnerability and short dependency links. • A simplified localized attacking strategy is studied based on percolation theory. [ABSTRACT FROM AUTHOR]

Abstract In this paper we demonstrate the “Trump Effect” based on the cross-correlations between the occurrence of the term “Donald Trump” in Google Trends and the volatilities and returns of indices corresponding to several stock exchanges around the world. For that, we associate the ρ D C C A coefficient with its significance test. We observe that the occurrence of the term “Donald Trump” has an effect of moderate and weak intensities with positive and significant correlation on the volatilities of the Mexican, Japanese, Australian and Brazilian stock exchanges. Regarding returns, the occurrence of the term “Donald Trump” has a positive effect of weak and moderate intensities with positive and significant correlation on the North American stock exchange and a negative and significant effect of weak intensity on the Mexican stock exchanges. The results show that news related to the current North American president are correlated with fluctuations in the financial markets. Highlights • We examine the Trump’s Effect on stock markets based on a multiscalar approach. • The term Donald Trump has some significant values on the volatilities and returns. • The proposed analysis contributes to understanding financial risks. [ABSTRACT FROM AUTHOR]

Radicalization is the process by which people come to adopt increasingly extreme political, social or religious ideologies. When radicalization leads to violence, radical thinking becomes a threat to national security. De-radicalization programs are part of an effort to combat violent extremism and terrorism. This type of initiatives attempt to alter violent extremists radical beliefs and violent behavior with the aim to reintegrate them into society. In this paper we introduce a simple compartmental model suitable to describe de-radicalization programs. The population is divided into four compartments: ( S ) susceptible, ( E ) extremists, ( R ) recruiters, and ( T ) treatment. We calculate the basic reproduction number R 0 . For R 0 < 1 the system has one globally asymptotically stable equilibrium where no extremist or recruiters are present. For R 0 > 1 the system has an additional equilibrium where extremists and recruiters are endemic to the population. A Lyapunov function is used to show that, for R 0 > 1 , the endemic equilibrium is globally asymptotically stable. We use numerical simulations to support our analytical results. Based on our model we assess strategies to counter violent extremism. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the finite-time event-triggered synchronization problem of the reaction–diffusion complex networks (RDCNs) with Dirichlet boundary conditions. A novel nonlinear event-triggered controller is developed, which is based on the random sampled-data. Under the proposed controller, it is found that the Zeno behavior is naturally excluded and the finite-time synchronization of RDCNs is guaranteed. Moreover, by utilizing Lyapunov functional method and the inequality techniques, the finite-time synchronization condition of the RDCNs is derived as well as the finite time is calculated. Finally, numerical simulation results are provided to demonstrate the theoretical results. [ABSTRACT FROM AUTHOR]

Heterogeneity has received increasing attention over the past decade, and it is widely considered to have a great effect on promoting cooperation. In our paper, we investigate the influence of heterogeneous investment on the cooperative behavior of the system, which is based on the number of players in different groups in the evolutionary public goods game (PGG). A parameter α is used to tune the heterogeneous investment mechanism: if α > 0 , cooperators invest more in the groups centered on high-degree nodes, but if α < 0 , the groups centered on small-degree nodes attract more investment from cooperators. Simulation results and analysis suggest that the cooperation level is enhanced in a large range. For a smaller enhancement factor r in the PGG model, the cooperation frequency decreases monotonously with the increase of α . For a larger r , the highest cooperation level can only be obtained by α = 0 , which is a non-monotonous phenomenon. By investigating the mean payoffs of nodes of different degrees for different α , it is found that the strategy utilized by hubs is more prominent in the system. Some explanations are provided for the strategy orientation of hubs and show that the investment propensity will change it. Our work may be useful for understanding the influence of individual investment in different groups on the level of cooperation. [ABSTRACT FROM AUTHOR]

Mathematical models in the form of differential equations with a time lag have been widely used in economics, biology, engineering and medicine to model dynamical interactions. In this paper, a heuristic estimation algorithm of delay values is offered in discrete deterministic systems by minimizing the average quadratic deviation for parameter identification. A well-known “predator–prey” model falls within the solution set we offer and is widely used in economics. Obviously, real data requires the analysis of random measurement innovations be taken into account; however, this aspect is not considered for the sake of convenience. [ABSTRACT FROM AUTHOR]

Building occupancy simulation and estimation simulates the dynamics of occupants and estimates their real-time spatial distribution in a building. It requires a simulation model and an algorithm for data assimilation that assimilates real-time sensor data into the simulation model. Existing building occupancy simulation models include agent-based models and graph-based models. The agent-based models suffer high computation cost for simulating large numbers of occupants, and graph-based models overlook the heterogeneity and detailed behaviors of individuals. Recognizing the limitations of existing models, this paper presents a new graph-based agent-oriented model which can efficiently simulate large numbers of occupants in various kinds of building structures. To support real-time occupancy dynamics estimation, a data assimilation framework based on Sequential Monte Carlo Methods is also developed and applied to the graph-based agent-oriented model to assimilate real-time sensor data. Experimental results show the effectiveness of the developed model and the data assimilation framework. The major contributions of this work are to provide an efficient model for building occupancy simulation that can accommodate large numbers of occupants and an effective data assimilation framework that can provide real-time estimations of building occupancy from sensor data. [ABSTRACT FROM AUTHOR]

In this paper, we consider two interacting pathogens spreading on multiplex networks. Each pathogen spreads only on its single layer, and different layers have the same individuals but different network topology. A state-dependent infectious rate is proposed to describe the nonlinear mutual interaction during the propagation of two pathogens. Then a novel epidemic spreading model incorporating treatment control strategy is established. We investigate the global asymptotic stability of the equilibrium points by using Dulac’s criterion, Poincaré-Bendixson theorem and Lyapunov method. Furthermore, we discuss an optimal strategy to minimize the total number of the infected individuals and the cost associated with treatment control for both spreading of two pathogens. Finally, numerical simulations are presented to show the validity and efficiency of our results. [ABSTRACT FROM AUTHOR]

Irreversibility is an important property of time series. In this paper, we propose the higher moments and multiscale Kullback–Leibler divergence to analyze time series irreversibility. The higher moments Kullback–Leibler divergence (HMKLD) can amplify irreversibility and make the irreversibility variation more obvious. Therefore, many time series whose irreversibility is hard to be found are also able to show the variations. We employ simulated data and financial stock data to test and verify this method, and find that HMKLD of stock data is growing in the form of fluctuations. As for multiscale Kullback–Leibler divergence (MKLD), it is very complex in the dynamic system, so that exploring the law of simulation and stock system is difficult. In conventional multiscale entropy method, the coarse-graining process is non-overlapping, however we apply a different coarse-graining process and obtain a surprising discovery. The result shows when the scales are 4 and 5, their entropy is nearly similar, which demonstrates MKLD is efficient to display characteristics of time series irreversibility. [ABSTRACT FROM AUTHOR]

Rumor spreading has a profound influence on people’s well-being and social stability. There are many factors influencing rumor spreading. In this paper, we recommended an assumption that among the common mass there are three attitudes towards rumors: to like rumor spreading, to dislike rumor spreading, and to be hesitant (or neutral) to rumor spreading. Based on such an assumption, a Susceptible–Hesitating–Affected–Resistant(SHAR) model is established, which considered individuals’ different attitudes towards rumor spreading. We also analyzed the local and global stability of rumor-free equilibrium and rumor-existence equilibrium, calculated the basic reproduction number of our model. With numerical simulations, we illustrated the effect of parameter changes on rumor spreading, analyzing the parameter sensitivity of the model. The results of the theoretical analysis and numerical simulations illustrated the conclusions of this study. People having different attitudes towards rumors may play different roles in the process of rumor spreading. It was surprising to find, in our research, that people who hesitate to spread rumors have a positive effect on the spread of rumors. [ABSTRACT FROM AUTHOR]

The fractal and self-similarity are important properties in complex networks. Information dimension is a useful dimension for complex networks to reveal these properties. In this paper, an information dimension is proposed for weighted complex networks. Based on the box-covering algorithm for weighted complex networks (BCANw), the proposed method can deal with the weighted complex networks which appear frequently in the real-world, and it can get the influence of the number of nodes in each box on the information dimension. To show the wide scope of information dimension, some applications are illustrated, indicating that the proposed method is effective and feasible. [ABSTRACT FROM AUTHOR]

While properties of human traffic flow are described by speed, density and flow, the locomotion of pedestrian is based on steps. To relate characteristics of human locomotor system with properties of human traffic flow, this paper aims to connect gait characteristics like step length, step frequency, swaying amplitude and synchronization with speed and density and thus to build a ground for advanced pedestrian models. For this aim, observational and experimental study on the single-file movement of pedestrians at different densities is conducted. Methods to measure step length, step frequency, swaying amplitude and step synchronization are proposed by means of trajectories of the head. Mathematical models for the relations of step length or frequency and speed are evaluated. The problem how step length and step duration are influenced by factors like body height and density is investigated. It is shown that the effect of body height on step length and step duration changes with density. Furthermore, two different types of step in-phase synchronization between two successive pedestrians are observed and the influence of step synchronization on step length is examined. [ABSTRACT FROM AUTHOR]

Abstract: Complex network theory is a useful way to study many real systems. In this paper, an anti-attack model based on complex network theory is introduced. The mechanism of this model is based on a dynamic compensation process and a reverse percolation process in P2P networks. The main purpose of the paper is: (i) a dynamic compensation process can turn an attacked P2P network into a power-law (PL) network with exponential cutoff; (ii) a local healing process can restore the maximum degree of peers in an attacked P2P network to a normal level; (iii) a restoring process based on reverse percolation theory connects the fragmentary peers of an attacked P2P network together into a giant connected component. In this way, the model based on complex network theory can be effectively utilized for anti-attack and protection purposes in P2P networks. [Copyright &y& Elsevier]

Abstract: Regime-switching models seem to well capture the main features of power prices behavior in deregulated markets. In a recent paper, we have proposed an equilibrium methodology to derive electricity prices dynamics from the interplay between supply and demand in a stochastic environment. In particular, assuming that the supply function is described by a power law where the exponent is a two-state strictly positive Markov process, we derived a regime switching dynamics of power prices in which regime switches are induced by transitions between Markov states. In this paper, we provide a dynamical model to describe the random behavior of power prices where the only non-Brownian component of the motion is endogenously introduced by Markov transitions in the exponent of the electricity supply curve. In this context, the stochastic process driving the switching mechanism becomes observable, and we will show that the non-Brownian component of the dynamics induced by transitions from Markov states is responsible for jumps and spikes of very high magnitude. The empirical analysis performed on three Australian markets confirms that the proposed approach seems quite flexible and capable of incorporating the main features of power prices time-series, thus reproducing the first four moments of log-returns empirical distributions in a satisfactory way. [Copyright &y& Elsevier]

Abstract: In this paper, we propose a new hedging model combining the newly introduced multifractal volatility (MFV) model and the dynamic copula functions. Using high-frequency intraday quotes of the spot Shanghai Stock Exchange Composite Index (SSEC), spot China Securities Index 300 (CSI 300), and CSI 300 index futures, we compare the direct and cross hedging effectiveness of the copula–MFV model with several popular copula–GARCH models. The main empirical results show that the proposed copula–MFV model obtains better hedging effectiveness than the copula–GARCH-type models in general. Furthermore, the hedge operating strategy based MFV hedging model involves fewer transaction costs than those based on the GARCH-type models. The finding of this paper indicates that multifractal analysis may offer a new way of quantitative hedging model design using financial futures. [Copyright &y& Elsevier]

Abstract: In this paper we study the congested patterns upstream of an isolated on-ramp in a cellular automaton traffic flow model, which is proposed in our previous paper [Cheng-Jie Jin, Wei Wang, Rui Jiang, Kun Gao, J. Stat. Mech (2010) P03018]. The simulation results under open boundary conditions are presented by spatiotemporal diagrams. Our diagram of congested patterns is quite similar to that of the cellular automaton models within Kerner’s three-phase traffic theory, while some differences in the “moving synchronized flow pattern” (MSP) should be noted. In our model the upstream front of MSP propagates not only upstream, but also downstream. The propagation direction depends on the flow rates and densities of free flow and synchronized flow. Besides, in our model the outflow of wide moving jams or bottlenecks could be free flow or synchronized flow, as reported in many empirical data. In the dissolving of congestions, the form of free flow may be hindered and stable synchronized flow may emerge. This phenomenon can help us understand more about the outflow. All the interesting characteristics of our model are due to the nonmonotonic structure of synchronized flow branch in the fundamental diagram, which has not been found in previous models. [Copyright &y& Elsevier]

Abstract: The mathematical framework for small-world networks proposed in a seminal paper by Watts and Strogatz sparked a widespread interest in modeling complex networks in the past decade. However, most of research contributing to static models is in contrast to real-world dynamic networks, such as social and biological networks, which are characterized by rearrangements of connections among agents. In this paper, we study dynamic networks evolved by nonlinear preferential rewiring of edges. The total numbers of vertices and edges of the network are conserved, but edges are continuously rewired according to the nonlinear preference. Assuming power-law kernels with exponents and , the network structures in stationary states display a distinct behavior, depending only on . For , the network is highly heterogeneous with the emergence of starlike structures. For , the network is widely homogeneous with a typical connectivity. At , the network is scale free with an exponential cutoff. [Copyright &y& Elsevier]

Abstract: Rich-club and page-club coefficients and their null models are introduced for directed graphs. Null models allow for a quantitative discussion of the rich-club and page-club phenomena. These coefficients are computed for four directed real-world networks: Arxiv High Energy Physics paper citation network, Web network (released from Google), Citation network among US Patents, and email network from a EU research institution. The results show a high correlation between rich-club and page-club ordering. For journal paper citation network, we identify both rich-club and page-club ordering, showing that “elite” papers are cited by other “elite” papers. Google web network shows partial rich-club and page-club ordering up to some point and then a narrow declining of the corresponding normalized coefficients, indicating the lack of rich-club ordering and the lack of page-club ordering, i.e. high in-degree (PageRank) pages purposely avoid sharing links with other high in-degree (PageRank) pages. For UC patents citation network, we identify page-club and rich-club ordering providing a conclusion that “elite” patents are cited by other “elite” patents. Finally, for email communication network we show lack of both rich-club and page-club ordering. We construct an example of synthetic network showing page-club ordering and the lack of rich-club ordering. [Copyright &y& Elsevier]

Abstract: In this paper, we incorporate a limitation on the interaction range between neighboring vehicles into the cellular automaton model proposed by Gao and Jiang et al. [K. Gao, R. Jiang, S. X. Hu, B. H. Wang and Q. S. Wu, Phys. Rev. E 76 (2007) 026105], which was established within the framework of Kerner’s three-phase traffic theory and has been shown to be able to reproduce the three-phase traffic flow. This modification eliminates an unrealistic phenomenon found in the previous model, where the velocity-adaptation effect between neighboring vehicles can exist even if those vehicles are infinitely far away from each other. Therefore, in the improved model, we regulate that such interactions can only occur within a finite distance. For simplicity, we suppose a constant value to describe this distance in this paper. As a result, when compared to the previous model, the improved model mainly simulates the following results which are believed to be an improvement. (1) The improved model successfully reproduces the expected discontinuous transition from free flow to synchronized flow and the related “moving synchronized flow pattern”, which are both absent in the original model but have been observed in real traffic. (2) The improved model simulates the correlation functions, time headway distributions and optimal velocity functions which are all more consistent with the empirical data than the previous model and most of the other models published before. (3) Together with the previous two models considering the velocity-difference effect, this model finally accomplishes a significative process of developing traffic flow models from the traditional “fundamental diagram approach” to the three-phase traffic theory. This process should be helpful for us to understand the traffic dynamics and mechanics further and deeper. [Copyright &y& Elsevier]

Abstract: In this paper, we discuss the incorporation of dynamic subgrid scale (SGS) models in the lattice-Boltzmann method (LBM) for large-eddy simulation (LES) of turbulent flows. The use of a dynamic procedure, which involves sampling or test-filtering of super-grid turbulence dynamics and subsequent use of scale-invariance for two levels, circumvents the need for empiricism in determining the magnitude of the model coefficient of the SGS models. We employ the multiple relaxation times (MRT) formulation of LBM with a forcing term, which has improved physical fidelity and numerical stability achieved by proper separation of relaxation time scales of hydrodynamic and non-hydrodynamic modes, for simulation of the grid-filtered dynamics of large-eddies. The dynamic procedure is illustrated for use with the common Smagorinsky eddy-viscosity SGS model, and incorporated in the LBM kinetic approach through effective relaxation time scales. The strain rate tensor in the SGS model is locally computed by means of non-equilibrium moments of the MRT-LBM. We also discuss proper sampling techniques or test-filters that facilitate implementation of dynamic models in the LBM. For accommodating variable resolutions, we employ conservative, locally refined grids in this framework. As examples, we consider the canonical anisotropic and inhomogeneous turbulent flow problem, i.e. fully-developed turbulent channel flow at two different shear Reynolds numbers of 180 and 395. The approach is able to automatically and self-consistently compute the values of the Smagorinsky coefficient, . In particular, the computed value in the outer or bulk flow region, where turbulence is generally more isotropic, is about 0.155 (or the model coefficient ) which is in good agreement with prior data. It is also shown that the model coefficient becomes smaller and approaches towards zero near walls, reflecting the dampening of turbulent length scales near walls. The computed turbulence statistics at these Reynolds numbers are also in good agreement with prior data. The paper also discusses a procedure for incorporation of more general scale-similarity based SGS stress models. [Copyright &y& Elsevier]

Abstract: This paper aims to analyze the linkages between international stock markets and to search for an optimum model for analyzing their interactions taking into consideration their geographical location, using the vector fractionally integrated autoregressive moving-average (VARFIMA) model. This model has not so far been employed in examining the interdependence among the stock markets of Germany, Japan, the UK, and the USA. The results of the paper show that there is an interconnection among the stock markets of these countries. [Copyright &y& Elsevier]

Abstract: This paper proposes a new model of Incomplete Minority Game (IMG), which features a default hierarchy of rules. This model introduces random bits into players’ individual strategies and is capable of applying the exception rules in the absence of the default one. Analysis of the numerical experiment results indicates that, in comparison with the standard Minority Game (SMG) model, this IMG model expands the maximum ensemble of uncorrelated strategies (MEUS) and excels in the effective strategy set and dynamic evolution of individual strategies, which enhance the overall performance by reaching an approximate ideal status in a shorter time with less memory steps and more stable combination of strategies. This paper also discusses the practical implication of the new IMG model. [Copyright &y& Elsevier]

Abstract: This paper reports the effort of deducing the initial strategy distributions (ISDs) of agents in mix-game models that is used to predict a real financial time series generated from a target financial market. Using mix-games to predict Shanghai Index, we find that the time series of prediction accurate rates is sensitive to the ISDs of agents in group 2 who play a minority game, but less sensitive to the ISDs of agents in group 1 who play a majority game. And agents in group 2 tend to cluster in full strategy space (FSS) if the real financial time series has obvious tendency (upward or downward), otherwise they tend to scatter in FSS. We also find that the ISDs and the number of agents in group 1 influence the level of prediction accurate rates. Finally, this paper gives suggestion about further research. [Copyright &y& Elsevier]

Abstract: This paper uses a structural econometric model to analyze an investment timing game that takes place during petroleum production. The model I develop enables one to estimate the structural parameters governing petroleum-producing firms’ investment timing decisions and therefore to assess the net effect of the information and extraction externalities they face. The econometric methodology presented in this paper can be employed to analyze any problem of dynamic multi-stage strategic decision-making in the presence of externalities. [Copyright &y& Elsevier]

This paper considers a simple model of an economy. The economy consists of agents. Each agent produces exactly one good. The good is sold on the market and the agent uses the resulting money to buy many other goods. All agents have the goal to maximize their own utility, which consists of a positive contribution from consumption, and a negative contribution from work. The problem for the agent thus is to balance work and consumption. In contrast to many other economic models, this model prescribes the process in all completeness. The paper looks both at analytical solutions and at simulation results. A particularly important results is that a well-defined market only emerges when prices adapt on a much slower time scale than consumption. This makes clear that a functioning market does not just emerge by itself. [Copyright &y& Elsevier]