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In the upstream of the highway work zone, vehicles will change lanes automatically or forcibly, which has complexity and randomness. Most studies fail to consider the impact of actual mixed traffic characteristics on traffic flow. For example, the dependence of the lane-changing behaviors of Connected and Automated Vehicles (CAVs) on the length of the zone is ignored in upstream of work zone. In addition, it is assumed that vehicles in the merge lane of the work zone would “yield” or not consider an impact on vehicles in the through lane. This simplifies the complex dynamics of the interaction between the two streams of traffic, which leads to the results of the study and the actual situation inconsistency. Based on the Gipps model, the adaptive cruise control (ACC) and the collaborative adaptive cruise control (CACC) vehicle-following models, this paper proposes a continuous cellular automata model under Vehicle-Road Collaboration and studies the mixed traffic flow characteristics in the work zone. By setting a metering zone before the lane reduction sign, ACC/CACC can adjust headway by obtaining road information in advance. The simulation results indicate that ACC/CACC vehicles have better following response compared to human-driven vehicles. In other words, the platoon composed of ACC/CACC vehicles has stability and can improve the traffic capacity of the work zone. The results of the study also found that the insertion of vehicles from adjacent lane into the ACC/CACC vehicles platoon is detrimental, especially when the penetration rate (Pinter) is high. Furthermore, when the length of the metering zone (Lmeter) is set at 120–150m, it can significantly improve the road congestion in the work zone. [ABSTRACT FROM AUTHOR]

The communication networks in real world often couple with each other to save costs, which results in any network does not have a stand-alone function and efficiency. To investigate this, in this paper we propose a transportation model on two coupled networks with bandwidth sharing. We find that the free-flow state and the congestion state can coexist in the two coupled networks, and the free-flow path and congestion path can coexist in each network. Considering three bandwidth-sharing mechanisms, random, assortative and disassortative couplings, we also find that the transportation capacity of the network only depends on the coupling mechanism, and the fraction of coupled links only affects the performance of the system in the congestion state, such as the traveling time. In addition, with assortative coupling, the transportation capacity of the system will decrease significantly. However, the disassortative coupling has little influence on the transportation capacity of the system, which provides a good strategy to save bandwidth. Furthermore, a theoretical method is developed to obtain the bandwidth usage of each link, based on which we can obtain the congestion transition point exactly. [ABSTRACT FROM AUTHOR]

In the field of statistical mechanics and system science, it is acknowledged that the financial crisis has a profound influence on stock market. However, the influence of total asset of enterprise on stock quote was not considered in the previous studies. In this work, a modified cross-correlation matrix that focuses on the influence of total asset on stock quote is introduced into the analysis of the stocks collected from Asian and American stock markets, which is different from the previous studies. The key results are obtained as follows. Firstly, stock is more greatly correlated with big asset than with small asset. Secondly, the higher the correlation coefficient among stocks, the larger the eigenvector is. Thirdly, in different periods, like the pre-subprime crisis period and the peak of subprime crisis period, Asian stock quotes show that the component of the third eigenvector of the cross-correlation matrix decreases with the asset of the enterprise decreasing. Fourthly, by simulating the threshold network, the small network constructed by 10 stocks with large assets can show the large network state constructed by 30 stocks. In this research we intend to fully explain the physical mechanism for understanding the historical correlation between stocks and provide risk control strategies in the future. [ABSTRACT FROM AUTHOR]

Exclusion processes are hot study issues in statistical physics and corresponding complex systems. Among fruitful exclusion processes, totally asymmetric simple exclusion process (namely, TASEP) attracts much attention due to its insight physical mechanisms in understanding such nonequilibrium dynamical processes. However, interactions among isolated TASEP are the core of controlling the dynamics of multiple TASEPs that are composed of a certain amount of isolated one-dimensional TASEP. Different from previous researches, the interaction factor is focused on the critical characteristic parameter used to depict the interaction intensity of these components of TASEPs. In this paper, a much weaker constraint condition ∏ i = 1 K ω i d = ∏ i = 1 K ω i u is derived as the analytical expression of interaction factor. Self-propelled particles in the subsystem i of multiple TASEPs can perform hopping forward at p i , moving into the target site of the (i − 1)th TASEP channel at ω i u or updating into the (i + 1)th TASEP channel at ω i d . The comparison of this proposed interaction factor and other previous factors is performed by investigating the computational efficiency of obtaining analytical solutions and simulation ones of order parameters of the proposed TASEP system. Obtained exact solutions are observed to match well with Monte Carlo simulations. This research attempts to have a more comprehensive interpretation of physical mechanisms in the impact of interaction factors on TASEPs, especially corresponding to stochastic dynamics of self-propelled particles in such complex statistical dynamical systems. [ABSTRACT FROM AUTHOR]

The box-covering method that covers a network with a minimum number of boxes is critical to demonstrate network fractals and the re-normalization analysis of complex networks. Moreover, one is able to investigate the network structure by analyzing the re-normalization flow or categorizing networks into several universal classes. A number of compelling methods are not well adapted to the large-scale networks due to high time complexity, or low accuracy. In this paper, we introduce a hybrid method that has high accuracy and low time consumption based the maximum-excluded-mass-burning (MEMB) method and the random sequential (RS) method. Our method combines the characteristics of the MEMB method that search as fewer boxes as possible with the high efficiency of the RS method by selecting a few unimportant central nodes, especially for large-scale networks. We also optimize the storage mechanism of the method so that the excluded mass of nodes can be updated efficiently. Experiments in the real networks with different structures demonstrate that the improvement of our method can be substantial. Our method reduces the time consumption of the MEMB method by more than 40% with only 10% more boxes than the MEMB method. • A new box-covering method is proposed that has high accuracy and low time consumption. • Optimized the cache mechanism of the proposed method where excluded mass of nodes can be updated efficiently. • Experiments in five real networks demonstrate that the improvement of our method is significant. • Both speed and efficiency of proposed method are improved and easily adopted. [ABSTRACT FROM AUTHOR]

Most of the conventional cellular automaton (CA) traffic flow models have two shortcomings: unlimited deceleration capabilities and incapability of reproducing the synchronized flow in the three-phase traffic flow theory. Based on an original deceleration CA model that emphasizes limited mechanical capabilities and human overreaction as the origin of congested traffic states, this paper proposes a new deceleration CA model where the slow-to-start rules are incorporated. For periodic boundary conditions, one also finds that the present model can reproduce well the three different phases of traffic flow (free flow, synchronized traffic flow, wide moving jam) as well as two first-order phase transitions (the transitions from free flow to synchronized flow and from synchronized flow to wide moving jam) among them. Compared to the original deceleration CA model, one notes that the phase transition from the synchronized flow to wide moving jam becomes distinguishable. Furthermore, the present model can reliably reproduce most empirical findings including synchronized flow with different slopes, the so-called pinch effect, and the time-headway distribution of free flow and so on. Importantly, the synchronized flow with different slopes is supported by spatiotemporal diagrams and the statistical distribution of velocity and so on. For open boundary conditions, the present model can reproduce the spatiotemporal diagrams of well-known five patterns including moving synchronized flow pattern, localized synchronized flow pattern, widening synchronized flow pattern, dissolving general pattern and general pattern. [ABSTRACT FROM AUTHOR]

In order to study the universality of the interactions among different markets, we analyze the cross-correlation matrix of the price of the Chinese and American bank stocks. We then find that the stock prices of the emerging market are more correlated than that of the developed market. Considering that the values of the components for the eigenvector may be positive or negative, we analyze the differences between two markets in combination with the endogenous and exogenous events which influence the financial markets. We find that the sparse pattern of components of eigenvectors out of the threshold value has no change in American bank stocks before and after the subprime crisis. However, it changes from sparse to dense for Chinese bank stocks. By using the threshold value to exclude the external factors, we simulate the interactions in financial markets. [ABSTRACT FROM AUTHOR]

The routing strategy plays a very important role in complex networks such as Internet system and Peer-to-Peer networks. However, most of the previous work concentrates only on the path selection, e.g. Flooding and Random Walk, or finding the shortest path (SP) and rarely considering the local load information such as SP and Distance Vector Routing. Flow-based Routing mainly considers load balance and still cannot achieve best optimization. Thus, in this paper, we propose a novel dynamic routing strategy on complex network by incorporating the local load information into SP algorithm to enhance the traffic flow routing optimization. It was found that the flow in a network is greatly affected by the waiting time of the network, so we should not consider only choosing optimized path for package transformation but also consider node congestion. As a result, the packages should be transmitted with a global optimized path with smaller congestion and relatively short distance. Analysis work and simulation experiments show that the proposed algorithm can largely enhance the network flow with the maximum throughput within an acceptable calculating time. The detailed analysis of the algorithm will also be provided for explaining the efficiency. [ABSTRACT FROM AUTHOR]

To understand the relations between developers and software, we study a collaborative coding platform from the perspective of networks, including follower networks, dependence networks and developer-project bipartite networks. Through the analyzing of degree distribution, PageRank and degree-dependent nearest neighbors’ centrality, we find that the degree distributions of all networks have a power-law form except the out-degree distributions of dependence networks. The nearest neighbors’ centrality is negatively correlated with degree for developers but fluctuates around the average for projects. In order to measure the diversity of profession levels of interests, a new index called dependence centrality similarity is proposed and the correlation between dependence centrality similarity and degree is investigated. The result shows an obvious negative correlations between dependence centrality similarity and degree. [ABSTRACT FROM AUTHOR]

In this paper, we utilize Spearman rank correlation coefficient to measure mixing patterns in complex networks. Compared with the widely used Pearson coefficient, Spearman coefficient is rank-based, nonparametric, and size-independent. Thus it is more effective to assess linking patterns of diverse networks, especially for large-size networks. We demonstrate this point by testing a variety of empirical and artificial networks. Moreover, we show that normalized Spearman ranks of stubs are subject to an interesting linear rule where the correlation coefficient is just the Spearman coefficient. This compelling linear relationship allows us to directly produce networks with any prescribed Spearman coefficient. Our method apparently has an edge over the well known uncorrelated configuration model. [ABSTRACT FROM AUTHOR]

In this paper, a cellular automata model with dual cruise-control limit is refined where the length of each cell is set to 1.5 m and each vehicle can still occupy five cells. The prominent feature of this new model is that these vehicles with low-speed and high-speed are not affected by noise and the slow start rule of the Takayasu and Takayasu model is introduced if there is an empty cell in front of the stationary vehicle. Based on the computer simulation results, one obtains that the new refined model can successfully reproduce the empirical characteristics of three-phase traffic flow theory. In the fundamental diagram, there are three-phase traffic states: Free flow, synchronized flow and wide moving jam. In particular, 2 Z -characteristic for phase transitions can be presented. Furthermore, the propagation speed of the downstream front of the moving synchronized pattern (MSP) and wide moving jam is within the range of empirical observation data or close to the range of empirical observation data. [ABSTRACT FROM AUTHOR]

Abstract: How to promote the innovative activities is an important problem for modern society. In this paper, combining the evolutionary games with information spreading, we propose a lattice model to investigate dynamics of human innovative behaviors based on benefit-driven assumption. Simulations show several properties in agreement with peoples’ daily cognition on innovative behaviors, such as slow diffusion of innovative behaviors, gathering of innovative strategy on “innovative centers”, and quasi-localized dynamics. Furthermore, our model also emerges rich non-Poisson properties in the temporal–spatial patterns of the innovative status, including the scaling law in the interval time of innovation releases and the bimodal distributions on the spreading range of innovations, which would be universal in human innovative behaviors. Our model provides a basic framework on the study of the issues relevant to the evolution of human innovative behaviors and the promotion measurement of innovative activities. [Copyright &y& Elsevier]

Abstract: In this work, the depreciation effect of public goods is considered in the public goods games, which is realized by rescaling the multiplication factor of each group as (). It is assumed that each individual enjoys the full profit of the public goods if all the players of this group are cooperators. Otherwise, the value of public goods is reduced to . It is found that compared with the original version (), the emergence of cooperation is remarkably promoted for , and there exist intermediate values of inducing the best cooperation. Particularly, there exists a range of inducing the highest cooperative level, and this range of broadens as increases. It is further presented that the variation of cooperator density with noise has close relations with the values of and , and cooperation at an intermediate value of is most tolerant to noise. [Copyright &y& Elsevier]

Abstract: Heritability is ubiquitous within most real biological or social systems. A heritable trait is most simply an offspring’s trait that resembles the parent’s corresponding trait, which can be fitness, strategy, or the way of strategy adoption for evolutionary games. Here we study the effects of heritability on the evolution of spatial public goods games. In our model, the fitness of players is determined by the payoffs from the current interactions and their history. Based on extensive simulations, we find that the density of cooperators is enhanced by increasing the heritability of players over a wide range of the multiplication factor. We attribute the enhancement of cooperation to the inherited fitness that stabilizes the fitness of players, and thus prevents the expansion of defectors effectively. [Copyright &y& Elsevier]

Abstract: As a killing machine and a decisive factor of history, wars play an important role in social system. In this paper, we present an empirical exploration of the distribution of recurrent time of wars in ancient China and find that it obeys a stretched exponential form. The pattern we found implies that there are undetected mechanisms that underlie the dynamics of wars. In order to explain the origin of this form, a model mainly based on the correlation between two consecutive wars is constructed, which is somewhat similar to the Bak–Sneppen model. The simulation results of the model are in agreement with the empirical statistics and suggest that the dynamics of wars could relate with self-organized criticality. [Copyright &y& Elsevier]

Abstract: In traffic systems, a reasonable information feedback can improve road capacity. In this Letter, we study dynamics of traffic flow with real-time information. And the influence of a feedback strategy named Weighted Congestion Coefficient Feedback Strategy (WCCFS) is introduced, based on a two-route scenario in which dynamic information can be generated and displayed on the board to guide road users to make a choice. Our model incorporates the effects of adaptability into the cellular automaton models of traffic flow and simulation results adopting this optimal information feedback strategy have demonstrated high efficiency in controlling spatial distribution of traffic patterns compared with the other three information feedback strategies, i.e., vehicle number and flux. [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]

This study examines the cellular automata traffic flow model, which considers the asynchronous update of vehicles' velocities. Computer simulations are used to identify three typical phases: linear free flow phase, nonlinear moving phase and traffic jam phase. Compared to the original NaSch model, the system of the present model can reach the maximum flow when the vehicle density is higher. The influence of the delay probability and the maximum time step in which drivers intend to keep their current velocity on fundamental diagram is discussed. [ABSTRACT FROM AUTHOR]

Totally asymmetric simple exclusion process (TASEP) is an important stochastic dynamic process in the area of statistical physics, which can be used to model microscopic transport in nonequilibrium processes. Due to its rich stochastic dynamics and nonequilibrium phase transition mechanisms, the importance of TASEP in statistical physics is similar with that of Ising model, which has attracted many attentions. In this paper, multiple TASEPs are introduced and coupled with various strong and weak interacting effects of self-driven particles. Both strong and weak couplings are calculated by means of mean-field analyses and Monte Carlo simulations. Tremendous cluster dynamics, evolution law of topological structures of phase diagrams and mechanisms of shock evolution are found in thermodynamic limit of proposed particle system. Monte Carlo simulation results like phase boundaries are found to be a good match with mean-field analyses, which reflect the validity of the research. The research work will be conducive to exploring the mechanisms of stochastic dynamics in the process of nonequilibrium phase transitions of multi-body interacting particle systems. [ABSTRACT FROM AUTHOR]

The intersecting pedestrian flow on the 2 D lattice with parallel update rule is studied. Each pedestrian has three moving directions without a back step. An intermediate phase has been found in which some pedestrians could move along the border of jamming stripes. A improved cluster mean field method has been proposed for the moving phase. A mean field analysis was also developed to analyze the intermediate phase. The analytical results agree with the simulation results well. The empty site moves along the interface of jamming stripes when the system only has one empty site. The average movement of empty site in each time step has been analyzed through the master equations. • The intersecting pedestrian flow on the 2D lattice with parallel update rule is studied. • An intermediate phase was found at which some pedestrians could move along the border of jamming stripes. • An improved cluster mean field method has been proposed for the moving phase. • The analytical results for the intermediate phase agree with the simulation results well. • The average movement of empty site when density approach 1 has been analyzed. [ABSTRACT FROM AUTHOR]

Assortativity is one of the important characteristics in real networks. To study the effects of this characteristic on the robustness of networks, we propose a percolation model on networks with assortative dependence group. The assortativity in this model means that the nodes with the same or similar degrees form dependence groups, for which one node fails, other nodes in the same group are very likely to fail. We find that the assortativity makes the nodes with large degrees easier to survive from the cascading failure. In this way, such networks are more robust than that with random dependence group, which also proves the assortative network is robust in another perspective. Furthermore, we also present exact solutions to the size of the giant component and the critical point, which are in agreement with the simulation results well. [ABSTRACT FROM AUTHOR]

Two species of particles driven perpendicularly and interacting through hardcore exclusion on the 2D lattice is studied. Each particle has three moving directions without the back step. Under periodic boundary conditions, an intermediate phase has been found at which some particles could move along the border of jamming stripes. We have performed mean field analysis for the moving and intermediate phase respectively. The analytical results agree with the simulation results well. The empty site moves along the interface of jamming stripes when the system only has one empty site. The average movement of empty site in one Monte Carlo step (MCS) has been analyzed through the master equation. Under open boundary conditions, the system exhibits moving and jamming phases. The critical injection probability α c shows non-monotonically against the forward moving probability q . The analytical results of average velocity, the density and the flow rate against the injection probability in the moving phase also agree with simulation results well. [ABSTRACT FROM AUTHOR]

Comparing with single networks, the multiplex networks bring two main effects on the spreading process among individuals. First, the pathogen or information can be transmitted to more individuals through different layers at one time, which enlarges the spreading scope. Second, through different layers, an individual can also transmit the pathogen or information to the same individuals more than once at one time, which makes the spreading more effective. To understand the different roles of the spreading scope and effectiveness, we propose an epidemic model on multiplex networks with link overlapping, where the spreading effectiveness of each interaction as well as the variety of channels (spreading scope) can be controlled by the number of overlapping links. We find that for Poisson degree distribution, increasing the epidemic scope (the first effect) is more efficient than enhancing epidemic probability (the second effect) to facilitate the spreading process. However, for power-law degree distribution, the effects of the two factors on the spreading dynamics become complicated. Enhancing epidemic probability makes pathogen or rumor easier to outbreak in a finite system. But after that increasing epidemic scopes is still more effective for a wide spreading. Theoretical results along with reasonable explanation for these phenomena are all given in this paper, which indicates that the epidemic scope could play an important role in the spreading dynamics. [ABSTRACT FROM AUTHOR]

In this paper, we propose a model of task-deletion mechanism based on the priority queueing system of Barabási (2005) to deep research the pattern diversity of human behaviors. The analytical solution for our model with two tasks is presented. In different cases of the parameter of task-deletion, our model can produce rich statistical behavior patterns, which are consistent with lots of empirical studies. Therefore, the model can theoretically explain more human behavior phenomena than the model of Barabási. These results have important significance for understanding the mechanism of pattern diversity of human behaviors. [ABSTRACT FROM AUTHOR]

Strategy selection in games, a typical decision making, usually brings noticeable reward for players which have discounted value if the delay appears. The discounted value is measure: earning sooner with a small reward or later with a delayed larger reward. Here, we investigate effects of delayed rewards on the cooperation in structured population. It is found that delayed reward supports the spreading of cooperation in square lattice, small-world and random networks. In particular, intermediate reward differences between delays impel the highest cooperation level. Interestingly, cooperative individuals with the same delay time steps form clusters to resist the invasion of defects, and cooperative individuals with lowest delay reward survive because they form the largest clusters in the lattice. [ABSTRACT FROM AUTHOR]

GitHub is a social collaborative coding platform on which software developers not only collaborate on codes but also share knowledge through blogs using GitHub Pages. In this article, we analyze the blogging behavior of software developers on GitHub Pages. The results show that both the commit number and the inter-event time of two consecutive blogging actions follow heavy-tailed distribution. We further observe a significant variety of activity among individual developers, and a strongly positive correlation between the activity and the power-law exponent of the inter-event time distribution. We also find a difference between the user behaviors of GitHub Pages and other online systems which is driven by the diversity of users and length of contents. In addition, our result shows an obvious difference between the majority of developers and elite developers in their burstiness property. [ABSTRACT FROM AUTHOR]

A generalized Langevin equation is suggested to describe a diffusion particle system with memory. The equation can be transformed into the Fokker–Planck equation by using the Kramers–Moyal expansion. The solution of Fokker–Planck equation can describe not only the diffusion of particles but also that of opinion particles based on the similarities between the two. We find that the memory can restrain some non-equilibrium phenomena of velocity distribution in the system, without memory, induced by correlation between the noise and space (Wang et al., 2021). However, the memory can enhance the effective collision among particles as shown by the variation of diffusion coefficients, and changes the diffusion mode between the dissipative and pumping region by comparing with that in the aforementioned system without memory. As the discussions in this physical system is paralleled to a social system, the random diffusion of social ideology, such as the information propagation, can be suppressed by the correlation between the noise and space. [ABSTRACT FROM AUTHOR]

The most common of strategy adoption in evolutionary games relies on players' payoffs of the last round. While a rational player usually fixes the coming strategy by comprehensively considering certain amount of payoff information within its memory length. Here, we explore several measures of historical payoffs in getting the weighted average payoff. Then, player sets the strategy by comparing the weighted average payoff of neighbour's and itself. We show that, cooperators can resist the invasion by referring to the most payoff information, when strategy and measure coevolve. In contrast, strategy adoption of defectors only relies on the nearest one round. Especially, our results suggest that, excessive attention of past payoffs is not favorable to spread cooperative behaviors. [ABSTRACT FROM AUTHOR]

This study examines the cellular automata traffic flow model, which considers the heterogeneity of vehicle acceleration and the delay probability of vehicles. Computer simulations are used to identify three typical phases in the model: free-flow, synchronized flow, and wide moving traffic jam. In the synchronized flow region of the fundamental diagram, the low and high velocity vehicles compete with each other and play an important role in the evolution of the system. The analysis shows that there are two types of bistable phases. However, in the original Nagel and Schreckenberg cellular automata traffic model, there are only two kinds of traffic conditions, namely, free-flow and traffic jams. The synchronized flow phase and bistable phase have not been found. [ABSTRACT FROM AUTHOR]

This paper investigates the bus operating system under the synchronized traffic light control strategies with cellular automation. Besides the insufficient capacity, the sufficient capacity is observed in the free-flow state of the phase diagram. An analytical equation for the critical passenger arrival rate is developed. The average velocity of free-flow and bunching state oscillates with the increase of signal period. With the increase of the ratio of green phase time, the oscillation amplitude of average velocity decreases while the oscillation frequency increases. At the same time, the critical passenger arrival rate and each region of the phase diagram also vary synchronously. An analytical equation for the average velocity is developed, which shows good agreement with the simulation results. Two states called lag and catch (LC) and variant LC state are observed. The exact condition for the LC state is presented. Finally, a monotonic decreasing curve instead of oscillation was observed under nonsynchronous traffic light. The results indicate that a proper signal period could improve the efficiency of bus system. [ABSTRACT FROM AUTHOR]

How to identify the influential spreaders in social networks is crucial for accelerating/hindering information diffusion, increasing product exposure, controlling diseases and rumors, and so on. In this paper, by viewing the k-shell value of each node as its mass and the shortest path distance between two nodes as their distance, then inspired by the idea of the gravity formula, we propose a gravity centrality index to identify the influential spreaders in complex networks. The comparison between the gravity centrality index and some well-known centralities, such as degree centrality, betweenness centrality, closeness centrality, and k-shell centrality, and so forth, indicates that our method can effectively identify the influential spreaders in real networks as well as synthetic networks. We also use the classical Susceptible–Infected–Recovered (SIR) epidemic model to verify the good performance of our method. [ABSTRACT FROM AUTHOR]

A method based on the breadth-first search tree is proposed in this paper to characterize the hierarchical structure of network. In this method, a similarity coefficient is defined to quantitatively distinguish networks, and quantitatively measure the topology stability of the network generated by a model. The applications of the method are discussed in ER random network, WS small-world network and BA scale-free network. The method will be helpful for deeply describing network topology and provide a starting point for researching the topology similarity and isomorphism of networks. [ABSTRACT FROM AUTHOR]

In this paper, we study how special patterns affect certain dynamic process on networks. The process we analyze is an iteration to generate a doubly-stochastic matrix consistent to the adjacent matrix of a network and the patterns can be described as h non-interconnected vertices only connect other g vertices ( h > g ) . From the perspective of network structure, we prove that the necessary and sufficient condition when the iteration converges is that these patterns do not exist in the network. For BA networks, there is a phase transition. The diverge–converge transition point is that the average degree is about 8, which is theoretically proved. The existence of these patterns depends on two factors: first, higher moments of degree distribution of the network; second, the probability that vertices with degree 1 exist in the network. Simulation results also support our theory. [ABSTRACT FROM AUTHOR]

Community detection is a significant and challenging task in network science. Nowadays, plenty of attention has been paid on local methods for community detection. Greedy expanding is a popular and efficient class of local algorithms, which typically starts from some selected central nodes and expands those nodes to obtain provisional communities by optimizing a certain quality function. In this paper, we propose a novel index, called local superiority index (LSI), to identify central nodes. In the process of expansion, we use a fitness function to estimate the quality of provisional communities and ensure that all provisional communities must be weak communities. Evaluation based on the normalized mutual information suggests: (1) LSI is superior to the global maximal degree index and the local maximal degree index on most considered networks; (2) The proposed greedy algorithm based on LSI is better than some state-of-the-art algorithms on most considered networks. • We proposed a novel index, called local superiority index (LSI), to identify central nodes of communities. • We proposed a greedy algorithm based on LSI to expand communities starting from selected central nodes and ensure that all provisional communities must be weak communities. • Evaluation suggests: LSI is superior to the global maximal degree index and the local maximal degree index on most considered networks. • Evaluation suggests: the greedy algorithm based on LSI is better than some state-of-the-art algorithms on most considered networks. [ABSTRACT FROM AUTHOR]

For past decades, the main attention of the evolutionary games has been focused on cooperation mechanism with the assumption that the strategy information of all players are known. However, it is difficult for observers to obtain the global information of players’ strategies in the real world, and some players even hide their strategy information to confuse their opponents. Here we try to solve the problem to predicate the hidden strategies with sparse historical behavior data in the evolutionary games. To quantify the similarity of strategies among the players in our method, the Euclidean distance of players is defined from the strategies of the players in the few past rounds. Then, the hidden strategy of a player will be determined from the tendency that players with minimum Euclidean distance will adopt similar strategies. The method has good performance on determining hidden strategy of human beings in both the prisoner’s dilemma game and the public goods game where strategies of twenty five percent players are hidden, and the success rate to determine hidden strategy reaches up to 0.9. It is also found that the success rate to determine hidden strategy depends on both length of historical behavior data and tempting payoff b (the prisoner’s dilemma game) or multiple factor r (the public goods game). [ABSTRACT FROM AUTHOR]