In this paper, we attempt to understand complex network evolution from the underlying evolutionary relationship between biological organisms. Firstly, we construct a Pfam domain interaction network for each of the 470...In this paper, we attempt to understand complex network evolution from the underlying evolutionary relationship between biological organisms. Firstly, we construct a Pfam domain interaction network for each of the 470 completely sequenced organisms, and therefore each organism is correlated with a specific Pfam domain interaction network; secondly, we infer the evolutionary relationship of these organisms with the nearest neighbour joining method; thirdly, we use the evolutionary relationship between organisms constructed in the second step as the evolutionary course of the Pfam domain interaction network constructed in the first step. This analysis of the evolutionary course shows： （i） there is a conserved sub-network structure in network evolution; in this sub-network, nodes with lower degree prefer to maintain their connectivity invariant, and hubs tend to maintain their role as a hub is attached preferentially to new added nodes; （ii） few nodes are conserved as hubs; most of the other nodes are conserved as one with very low degree; （iii） in the course of network evolution, new nodes are added to the network either individually in most cases or as clusters with relative high clustering coefficients in a very few cases.展开更多
Using complex network methods,we construct undirected and directed heatwave networks to systematically analyze heatwave events over China from 1961 to 2023,exploring their spatiotemporal evolution patterns in differen...Using complex network methods,we construct undirected and directed heatwave networks to systematically analyze heatwave events over China from 1961 to 2023,exploring their spatiotemporal evolution patterns in different regions.The findings reveal a significant increase in heatwaves since the 2000s,with the average occurrence rising from approximately 3 to 5 times,and their duration increasing from 15 to around 30 days,nearly doubling.An increasing trend of“early onset and late withdrawal”of heatwaves has become more pronounced each year.In particular,eastern regions experience heatwaves that typically start earlier and tend to persist into September,exhibiting greater interannual variability compared to western areas.The middle and lower reaches of the Yangtze River and Xinjiang are identified as high-frequency heatwave areas.Complex network analysis reveals the dynamics of heatwave propagation,with degree centrality and synchronization distance indicating that the middle and lower reaches of the Yangtze River,Northeast China,and Xinjiang are key nodes in heatwave spread.Additionally,network divergence analysis shows that Xinjiang acts as a“source”area for heatwaves,exporting heat to surrounding regions,while the central region functions as a major“sink,”receiving more heatwave events.Further analysis from 1994 to 2023 indicates that heatwave events exhibit stronger network centrality and more complex synchronization patterns.These results suggest that complex networks provide a refined framework for depicting the spatiotemporal dynamics of heatwave propagation,offering new avenues for studying their occurrence and development patterns.展开更多
Social propagation denotes the spread phenomena directly correlated to the human world and society, which includes but is not limited to the diffusion of human epidemics, human-made malicious viruses, fake news, socia...Social propagation denotes the spread phenomena directly correlated to the human world and society, which includes but is not limited to the diffusion of human epidemics, human-made malicious viruses, fake news, social innovation, viral marketing, etc. Simulation and optimization are two major themes in social propagation, where network-based simulation helps to analyze and understand the social contagion, and problem-oriented optimization is devoted to contain or improve the infection results. Though there have been many models and optimization techniques, the matter of concern is that the increasing complexity and scales of propagation processes continuously refresh the former conclusions. Recently, evolutionary computation(EC) shows its potential in alleviating the concerns by introducing an evolving and developing perspective. With this insight, this paper intends to develop a comprehensive view of how EC takes effect in social propagation. Taxonomy is provided for classifying the propagation problems, and the applications of EC in solving these problems are reviewed. Furthermore, some open issues of social propagation and the potential applications of EC are discussed.This paper contributes to recognizing the problems in application-oriented EC design and paves the way for the development of evolving propagation dynamics.展开更多
In order to reveal the complex network characteristics and evolution principle of China aviation network, the relationship between the node degree and the nearest neighbor average degree and its evolution trace of Chi...In order to reveal the complex network characteristics and evolution principle of China aviation network, the relationship between the node degree and the nearest neighbor average degree and its evolution trace of China aviation network in 1988, 1994, 2001, 2008 and 2015 were studied. According to the theory and method of complex network, the network system was constructed with the city where the airport was located as the network node and the airline as the edge of the network. According to the statistical data, the node nearest neighbor average degree of China aviation network in 1988, 1994, 2001, 2008 and 2015 was calculated. Through regression analysis, it was found that the node degree had a negative exponential relationship with the nearest neighbor average degree, and the two parameters of the negative exponential relationship had linear evolution trace.展开更多
In order to reveal the complex network characteristics and evolution principle of China aviation network, the probability distribution and evolution trace of average degree of edge vertices of China aviation network w...In order to reveal the complex network characteristics and evolution principle of China aviation network, the probability distribution and evolution trace of average degree of edge vertices of China aviation network were studied based on the statistics data of China civil aviation network in 1988, 1994, 2001, 2008 and 2015. According to the theory and method of complex network, the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network. Based on the statistical data, the average degrees of edge vertices in China aviation network in 1988, 1994, 2001, 2008 and 2015 were calculated. Using the probability statistical analysis method and regression analysis approach, it was found that the average degree of edge vertices had the probability distribution of normal function and the position parameters and scale parameters of the probability distribution had linear evolution trace.展开更多
In order to reveal the complex network characteristics and evolution principle of China aviation network,the probability distribution and evolution trace of node nearest neighbor average degree of China aviation netwo...In order to reveal the complex network characteristics and evolution principle of China aviation network,the probability distribution and evolution trace of node nearest neighbor average degree of China aviation network were studied based on the statistics data of China civil aviation network in 1988,1994,2001,2008 and 2015.According to the theory and method of complex network,the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network.Based on the statistical data,the nearest neighbor average degrees of nodes in China aviation network in 1988,1994,2001,2008 and 2015 were calculated.Using the probability statistical analysis method,it was found that the nearest neighbor average degree had the probability distribution of normal function and the position parameters and scale parameters of the probability distribution had linear evolution trace.展开更多
In order to reveal the complex network characteristics and evolution principle of China aviation network, the probability distribution and evolution trace of ratio of China aviation network edge vertices degree were s...In order to reveal the complex network characteristics and evolution principle of China aviation network, the probability distribution and evolution trace of ratio of China aviation network edge vertices degree were studied based on the statistics data of China civil aviation network in 1988, 1994, 2001, 2008 and 2015. According to the theory and method of complex network, the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network. Based on the statistical data, the ratio of edge vertices degree in China aviation network in 1988, 1994, 2001, 2008 and 2015 were calculated. Using the probability statistical analysis method and regression analysis approach, it was found that the ratio of edge vertices degree had linear probability distribution and the two parameters of the probability distribution had linear evolution trace.展开更多
In order to reveal the complex network characteristics and evolution principle of China aviation network,the probability distribution and evolution trace of arithmetic average of edge vertices nearest neighbor average...In order to reveal the complex network characteristics and evolution principle of China aviation network,the probability distribution and evolution trace of arithmetic average of edge vertices nearest neighbor average degree values of China aviation network were studied based on the statistics data of China civil aviation network in 1988,1994,2001,2008 and 2015.According to the theory and method of complex network,the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network.Based on the statistical data,the arithmetic averages of edge vertices nearest neighbor average degree values of China aviation network in 1988,1994,2001,2008 and 2015 were calculated.Using the probability statistical analysis method,it was found that the arithmetic average of edge vertices nearest neighbor average degree values had the probability distribution of normal function and the position parameters and scale parameters of the probability distribution had linear evolution trace.展开更多
Self-organization theory informs an analysis on the evolution of labor self-organizations (LSOs), but lacks technical analysis on the evolution of their organizational structures. Fortunately, complex network technolo...Self-organization theory informs an analysis on the evolution of labor self-organizations (LSOs), but lacks technical analysis on the evolution of their organizational structures. Fortunately, complex network technology offers a new approach to analyzing these structures. Built on an extension of the Barabási-Albert (BA) model, we can simulate the evolution of LSOs by analyzing indicators including the clustering coefficient, degree distribution (DD) and average path length (APL) of workers, thereby demonstrating the evolving patterns of LSOs. Accordingly, governmental mechanism designs based on such patterns may not only stimulate energy growth and functional realization of LSOs, but also reduce the social percussions of abrupt evolutions. A comparative analysis of the evolutionary trajectories of LSOs in China and the U.S. finds that the U.S. government’s mechanism designs for protecting capitalism not only prevented the effective gathering of workers, but also prolonged the history of industrial conflicts. Such mechanism designs also led to the early dispersion and decline of LSOs and hindered the evolution of the working class. In contrast, the Chinese government established a socialist system that allowed workers to become the underlying force of socialist productivity. This design reduced labor strife while accelerating the evolution of workers towards higher stages.展开更多
Software systems are a typical kind of man-made complex systems. Understanding their evolutions can lead to better software engineering practices. In this paper, the authors use complex network theory as a tool to ana...Software systems are a typical kind of man-made complex systems. Understanding their evolutions can lead to better software engineering practices. In this paper, the authors use complex network theory as a tool to analyze the evolution of object-oriented （OO） software from a multi-granularity perspective. First, a multi-granularity software networks model is proposed to represent the topological structures of a multi-version software system from three levels of granularity. Then, some parameters widely used in complex network theory are applied to characterize the software networks. By tracing the parameters＇ values in consecutive software systems, we have a better understanding about software evolution. A case study is conducted on an open source OO project, Azureus, as an example to illustrate our approach, and some underlying evolution characteristics are uncovered. These results provide a different dimension to our understanding of software evolutions and also are very useful for the design and development of OO software systems.展开更多
With the flourishing development of Unmanned Aerial Vehicles(UAVs), the mission tasks of UAVs have become more and more complex. Consequently, a Real-Time Operating System(RTOS) that provides operating environments fo...With the flourishing development of Unmanned Aerial Vehicles(UAVs), the mission tasks of UAVs have become more and more complex. Consequently, a Real-Time Operating System(RTOS) that provides operating environments for various mission services on these UAVs has become crucial, which leads to the necessity of having a deep understanding of an RTOS. In this paper, an empirical study is conducted on FreeRTOS, a commonly used RTOS for UAVs, from a complex network perspective. A total of 85 releases of FreeRTOS, from V2.4.2 to V10.0.0, are modeled as directed networks, in which the nodes represent functions and the edges denote function calls. It is found that the size of the FreeRTOS network has grown almost linearly with the evolution of the versions, while its main core has evolved steadily. In addition, a k-core analysis-based metric is proposed to identify major functionality changes of FreeRTOS during its evolution.The result shows that the identified versions are consistent with the version change logs. Finally,it is found that the clustering coefficient of the Linux OS scheduler is larger than that of the FreeRTOS scheduler. In conclusion, the empirical results provide useful guidance for developers and users of UAV RTOSs.展开更多
During the process of landslide, its dynamic mechanism is important to understand and predict these kinds of natural hazard. In this paper, a new method, based on concepts of complex networks, has been proposed to inv...During the process of landslide, its dynamic mechanism is important to understand and predict these kinds of natural hazard. In this paper, a new method, based on concepts of complex networks, has been proposed to investigate the evolution of contact networks in mesoscale during the sliding process of slope. A slope model was established using the discrete element method (DEM), and influences of inter-particle frictional coefficients with four different values on?dynamic landslides were studied. Both macroscopic analysis on slope?landslide?and mesoanalysis on structure evolution of contact networks, including the?average degree, clustering coefficient?and N-cycle, were done during the process?of landslide. The analysis results demonstrate that: 1) with increasing inter-particle?frictional coefficients, the displacement of slope decreases and the stable angle of slope post-failure increases, which is smaller than the peak internal frictional angle;2) the average degree decreases with the increase of inter-particle frictional coefficient. When the displacement at the toe of the slope is smaller,?the average degree there changes more greatly with increasing inter-particle?frictional coefficient;3) during the initial stage of landslide, the clustering coefficient?reduces sharply, which may leads to easily slide of slope. As the landslide?going?on, however, the clustering coefficient?increases denoting increasing stability?with?increasing inter-particle frictional coefficients. When the inter-particle?frictional coefficient is smaller than 0.3, its variation can affect the clustering coefficient?and stable inclination of slope post-failure greatly;and 4) the number of?3-cycle increases, but 4-cycle and 5-cycle decrease with increasing inter-particle frictional coefficients.展开更多
We investigate the mixing structure of directed and evolutionary US flight network. It is shown that such a network is a hierarchical network, with average assortativity coefficient-0.37. Application of the informatio...We investigate the mixing structure of directed and evolutionary US flight network. It is shown that such a network is a hierarchical network, with average assortativity coefficient-0.37. Application of the informationbased method that can give the same result provides a way to explore the structure of complex networks.展开更多
A continuum opinion dynamic model is presented based on two rules. The first one considers the mobilities of the individuals, the second one supposes that the individuals update their opinions independently. The resul...A continuum opinion dynamic model is presented based on two rules. The first one considers the mobilities of the individuals, the second one supposes that the individuals update their opinions independently. The results of the model indicate that the bounded confidence εc, separating consensus and incoherent states, of a scale-free network is much smaller than the one of a lattice. If the system can reach the consensus state, the sum of all individuals＇ opinion change Oc（t） quickly decreases in an exponential form, while if it reaches the incoherent state finally, Oc（t） decreases slowly and has the punctuated equilibrium characteristic.展开更多
The research of complex networks facilitates the progress of various disciplines,including biology,chemistry,social science,computer,and communication engineering.Recently,it is popular to utilize complex networks to ...The research of complex networks facilitates the progress of various disciplines,including biology,chemistry,social science,computer,and communication engineering.Recently,it is popular to utilize complex networks to study the communication networks,such as designing efficient routing strategies and robust communication networks.However,exploiting the advantages of communication networks to investigate networks in various disciplines beyond telecommunications is still in infancy.Because of this situation,this paper proposes an information-defined network(IDN)framework by which a complex network can be abstracted as a communication network associated with multiple intelligent agents.Specifically,each component and dynamic process in this framework can be defined by information.We show that the IDN framework promotes the research of unsolved problems in the current complex network field,especially for detecting new interaction types in realworld networks.展开更多
We propose a model of weighted networks in which the structural evolution is coupled with weight dynamics. Based on a simple merging and regeneration process, the model gives powel-law distributions of degree, strengt...We propose a model of weighted networks in which the structural evolution is coupled with weight dynamics. Based on a simple merging and regeneration process, the model gives powel-law distributions of degree, strength and weight, as observed in many real networks. It should be emphasized that, in our model, the nontrivial degree-strength correlation can be reproduced and in agreement with empirical data. Moreover, the size-growing evolution model is also presented to meet the properties of real-world systems.展开更多
We investigate the dynamics of random walks on weighted networks. Assuming that the edge weight and the node strength are used as local information by a random walker. Two kinds of walks, weight-dependent walk and str...We investigate the dynamics of random walks on weighted networks. Assuming that the edge weight and the node strength are used as local information by a random walker. Two kinds of walks, weight-dependent walk and strength-dependent walk, are studied. Exact expressions for stationary distribution and average return time are derived and confirmed by computer simulations. The distribution of average return time and the mean-square displacement are calculated for two walks on the Barrat-Barthelemy-Vespignani （BBV） networks. It is found that a weight-dependent walker can arrive at a new territory more easily than a strength-dependent one.展开更多
Pancreatic ductal adenocarcinoma(PDAC) remains a deadly disease with no efficacious treatment options. PDAC incidence is projected to increase, which may be caused at least partially by the obesity epidemic. Significa...Pancreatic ductal adenocarcinoma(PDAC) remains a deadly disease with no efficacious treatment options. PDAC incidence is projected to increase, which may be caused at least partially by the obesity epidemic. Significantly enhanced efforts to prevent or intercept this cancer are clearly warranted. Oncogenic KRAS mutations are recognized initiating events in PDAC development, however, they are not entirely sufficient for the development of fully invasive PDAC.Additional genetic alterations and/or environmental, nutritional, and metabolic signals, as present in obesity, type-2 diabetes mellitus, and inflammation, are required for full PDAC formation. We hypothesize that oncogenic KRAS increases the intensity and duration of the growth-promoting signaling network.Recent exciting studies from different laboratories indicate that the activity of the transcriptional co-activators Yes-associated protein(YAP) and WW-domaincontaining transcriptional co-activator with PDZ-binding motif(TAZ) play a critical role in the promotion and maintenance of PDAC operating as key downstream target of KRAS signaling. While initially thought to be primarily an effector of the tumor-suppressive Hippo pathway, more recent studies revealed that YAP/TAZ subcellular localization and co-transcriptional activity is regulated by multiple upstream signals. Overall, YAP has emerged as a central node of transcriptional convergence in growth-promoting signaling in PDAC cells. Indeed, YAP expression is an independent unfavorable prognostic marker for overall survival of PDAC. In what follows, we will review studies implicating YAP/TAZ in pancreatic cancer development and consider different approaches to target these transcriptional regulators.展开更多
The evolution of Internet topology is not always smooth but sometimes with unusual sudden changes. Consequently, identifying patterns of unusual topology evolution is critical for Internet topology modeling and simula...The evolution of Internet topology is not always smooth but sometimes with unusual sudden changes. Consequently, identifying patterns of unusual topology evolution is critical for Internet topology modeling and simulation. We analyze IPv6 Internet topology evolution in IP-level graph to demonstrate how it changes in uncommon ways to restructure the Internet. After evaluating the changes of average degree, average path length, and some other metrics over time, we find that in the case of a large-scale growing the Internet becomes more robust; whereas in a top–bottom connection enhancement the Internet maintains its efficiency with links largely decreased.展开更多
As a fundamental problem in the field of the network science,the study of topological evolution model is of great significance for revealing the inherent dynamics and mechanisms of complex network evolution.In order t...As a fundamental problem in the field of the network science,the study of topological evolution model is of great significance for revealing the inherent dynamics and mechanisms of complex network evolution.In order to study the influence of different scales of preferential attachment on topological evolution,a topological evolution model based on the attraction of the motif vertex is proposed.From the perspective of network motif,this model proposes the concept of attraction of the motif vertex based on the degree of the motif,quantifies the influence of local structure on the node preferential attachment,and performs the preferential selection of the new link based on the Local World model.The simulation experiments show that the model has the small world characteristic apparently,and the clustering coefficient varies with the scale of the local world.The degree distribution of the model changes from power-law distribution to exponential distribution with the change of parameters.In some cases,the piecewise power-law distribution is presented.In addition,the proposed model can present a network with different matching patterns as the parameters change.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 70671089 and 30871521)the State Key Program of National Natural Science of China (Grant No. 10635040)
文摘In this paper, we attempt to understand complex network evolution from the underlying evolutionary relationship between biological organisms. Firstly, we construct a Pfam domain interaction network for each of the 470 completely sequenced organisms, and therefore each organism is correlated with a specific Pfam domain interaction network; secondly, we infer the evolutionary relationship of these organisms with the nearest neighbour joining method; thirdly, we use the evolutionary relationship between organisms constructed in the second step as the evolutionary course of the Pfam domain interaction network constructed in the first step. This analysis of the evolutionary course shows： （i） there is a conserved sub-network structure in network evolution; in this sub-network, nodes with lower degree prefer to maintain their connectivity invariant, and hubs tend to maintain their role as a hub is attached preferentially to new added nodes; （ii） few nodes are conserved as hubs; most of the other nodes are conserved as one with very low degree; （iii） in the course of network evolution, new nodes are added to the network either individually in most cases or as clusters with relative high clustering coefficients in a very few cases.
基金Project supported by the National Key Research and Development Program of China(Grant Nos.2022YFE0136000 and 2024YFC3013100)the Joint Meteorological Fund(Grant No.U2342211)+1 种基金the Joint Research Project for Meteorological Capacity Improvement(Grant No.22NLTSZ004)the National Meteorological Information Center(Grant No.NMICJY202301)。
文摘Using complex network methods,we construct undirected and directed heatwave networks to systematically analyze heatwave events over China from 1961 to 2023,exploring their spatiotemporal evolution patterns in different regions.The findings reveal a significant increase in heatwaves since the 2000s,with the average occurrence rising from approximately 3 to 5 times,and their duration increasing from 15 to around 30 days,nearly doubling.An increasing trend of“early onset and late withdrawal”of heatwaves has become more pronounced each year.In particular,eastern regions experience heatwaves that typically start earlier and tend to persist into September,exhibiting greater interannual variability compared to western areas.The middle and lower reaches of the Yangtze River and Xinjiang are identified as high-frequency heatwave areas.Complex network analysis reveals the dynamics of heatwave propagation,with degree centrality and synchronization distance indicating that the middle and lower reaches of the Yangtze River,Northeast China,and Xinjiang are key nodes in heatwave spread.Additionally,network divergence analysis shows that Xinjiang acts as a“source”area for heatwaves,exporting heat to surrounding regions,while the central region functions as a major“sink,”receiving more heatwave events.Further analysis from 1994 to 2023 indicates that heatwave events exhibit stronger network centrality and more complex synchronization patterns.These results suggest that complex networks provide a refined framework for depicting the spatiotemporal dynamics of heatwave propagation,offering new avenues for studying their occurrence and development patterns.
基金by National Key Research and Development Project,Ministry of Science and Technology,China(No.2018AAA0101300)National Natural Science Foundation of China(Nos.61976093 and 61873097)+1 种基金Guangdong-Hong Kong Joint Innovative Platform of Big Data and Computational Intelligence(No.2018B050502006)Guangdong Natural Science Foundation Research Team(No.2018B030312003).
文摘Social propagation denotes the spread phenomena directly correlated to the human world and society, which includes but is not limited to the diffusion of human epidemics, human-made malicious viruses, fake news, social innovation, viral marketing, etc. Simulation and optimization are two major themes in social propagation, where network-based simulation helps to analyze and understand the social contagion, and problem-oriented optimization is devoted to contain or improve the infection results. Though there have been many models and optimization techniques, the matter of concern is that the increasing complexity and scales of propagation processes continuously refresh the former conclusions. Recently, evolutionary computation(EC) shows its potential in alleviating the concerns by introducing an evolving and developing perspective. With this insight, this paper intends to develop a comprehensive view of how EC takes effect in social propagation. Taxonomy is provided for classifying the propagation problems, and the applications of EC in solving these problems are reviewed. Furthermore, some open issues of social propagation and the potential applications of EC are discussed.This paper contributes to recognizing the problems in application-oriented EC design and paves the way for the development of evolving propagation dynamics.
文摘In order to reveal the complex network characteristics and evolution principle of China aviation network, the relationship between the node degree and the nearest neighbor average degree and its evolution trace of China aviation network in 1988, 1994, 2001, 2008 and 2015 were studied. According to the theory and method of complex network, the network system was constructed with the city where the airport was located as the network node and the airline as the edge of the network. According to the statistical data, the node nearest neighbor average degree of China aviation network in 1988, 1994, 2001, 2008 and 2015 was calculated. Through regression analysis, it was found that the node degree had a negative exponential relationship with the nearest neighbor average degree, and the two parameters of the negative exponential relationship had linear evolution trace.
文摘In order to reveal the complex network characteristics and evolution principle of China aviation network, the probability distribution and evolution trace of average degree of edge vertices of China aviation network were studied based on the statistics data of China civil aviation network in 1988, 1994, 2001, 2008 and 2015. According to the theory and method of complex network, the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network. Based on the statistical data, the average degrees of edge vertices in China aviation network in 1988, 1994, 2001, 2008 and 2015 were calculated. Using the probability statistical analysis method and regression analysis approach, it was found that the average degree of edge vertices had the probability distribution of normal function and the position parameters and scale parameters of the probability distribution had linear evolution trace.
文摘In order to reveal the complex network characteristics and evolution principle of China aviation network,the probability distribution and evolution trace of node nearest neighbor average degree of China aviation network were studied based on the statistics data of China civil aviation network in 1988,1994,2001,2008 and 2015.According to the theory and method of complex network,the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network.Based on the statistical data,the nearest neighbor average degrees of nodes in China aviation network in 1988,1994,2001,2008 and 2015 were calculated.Using the probability statistical analysis method,it was found that the nearest neighbor average degree had the probability distribution of normal function and the position parameters and scale parameters of the probability distribution had linear evolution trace.
文摘In order to reveal the complex network characteristics and evolution principle of China aviation network, the probability distribution and evolution trace of ratio of China aviation network edge vertices degree were studied based on the statistics data of China civil aviation network in 1988, 1994, 2001, 2008 and 2015. According to the theory and method of complex network, the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network. Based on the statistical data, the ratio of edge vertices degree in China aviation network in 1988, 1994, 2001, 2008 and 2015 were calculated. Using the probability statistical analysis method and regression analysis approach, it was found that the ratio of edge vertices degree had linear probability distribution and the two parameters of the probability distribution had linear evolution trace.
文摘In order to reveal the complex network characteristics and evolution principle of China aviation network,the probability distribution and evolution trace of arithmetic average of edge vertices nearest neighbor average degree values of China aviation network were studied based on the statistics data of China civil aviation network in 1988,1994,2001,2008 and 2015.According to the theory and method of complex network,the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network.Based on the statistical data,the arithmetic averages of edge vertices nearest neighbor average degree values of China aviation network in 1988,1994,2001,2008 and 2015 were calculated.Using the probability statistical analysis method,it was found that the arithmetic average of edge vertices nearest neighbor average degree values had the probability distribution of normal function and the position parameters and scale parameters of the probability distribution had linear evolution trace.
基金a deliverable of the “Research on the Accounting of ‘Trade in Value-added’ in Chinese Services Sector and its Place in the Global Value Chain,” a project funded by the National Social Science Foundation of China(15BGJ036)“The Impacts of Economic Globalization on Entrepreneurship in China—Theoretical Research and Empirical Analysis,” a youth project funded by the National Natural Science Foundation of China(NSFC)(71603142)+3 种基金“Research on Approaches to Labor-Management Cooperation with Chinese Characteristics—A Labor Relations Evolutionary Perspective,” a Ministry of Education humanities and social sciences research youth project(16YJC790115)“Research on the Evolution of Labor Relations with Chinese Characteristics Since the 18th CPC National Congress,” a Shandong planned social sciences research project(16CZLJ05)“Research on the Evolution Mechanisms and Paths of the Marxist Labor System from a Complex Network Perspective,” a project funded by the China Postdoctoral Science Foundation(CPSF)(2017M612180)“Research on Mechanism Design of the Spatial Structure of Labor-Management Cooperation with Chinese Characteristics,” a Qingdao postdoctoral applied research project
文摘Self-organization theory informs an analysis on the evolution of labor self-organizations (LSOs), but lacks technical analysis on the evolution of their organizational structures. Fortunately, complex network technology offers a new approach to analyzing these structures. Built on an extension of the Barabási-Albert (BA) model, we can simulate the evolution of LSOs by analyzing indicators including the clustering coefficient, degree distribution (DD) and average path length (APL) of workers, thereby demonstrating the evolving patterns of LSOs. Accordingly, governmental mechanism designs based on such patterns may not only stimulate energy growth and functional realization of LSOs, but also reduce the social percussions of abrupt evolutions. A comparative analysis of the evolutionary trajectories of LSOs in China and the U.S. finds that the U.S. government’s mechanism designs for protecting capitalism not only prevented the effective gathering of workers, but also prolonged the history of industrial conflicts. Such mechanism designs also led to the early dispersion and decline of LSOs and hindered the evolution of the working class. In contrast, the Chinese government established a socialist system that allowed workers to become the underlying force of socialist productivity. This design reduced labor strife while accelerating the evolution of workers towards higher stages.
基金This research is supported by the National Basic Research 973 Program of China under Grant No 2007CB310801, the National Natural Science Foundation of China under Grant Nos. 60873083 and 61003073 the Research Fund for the Doctoral Program of Higher Education of China under Grant No. 20090141120022 the Fundamental Research Funds for the Central Universities of China under Grant Nos. 114013 and 6082005 and the Scientific Research Fund of Zhejiang Provincial Education Department under Grant No. Y201018008.
文摘Software systems are a typical kind of man-made complex systems. Understanding their evolutions can lead to better software engineering practices. In this paper, the authors use complex network theory as a tool to analyze the evolution of object-oriented （OO） software from a multi-granularity perspective. First, a multi-granularity software networks model is proposed to represent the topological structures of a multi-version software system from three levels of granularity. Then, some parameters widely used in complex network theory are applied to characterize the software networks. By tracing the parameters＇ values in consecutive software systems, we have a better understanding about software evolution. A case study is conducted on an open source OO project, Azureus, as an example to illustrate our approach, and some underlying evolution characteristics are uncovered. These results provide a different dimension to our understanding of software evolutions and also are very useful for the design and development of OO software systems.
基金supported by the National Natural Science Foundation of China (No. 61772055)Equipment Preliminary R&D Project of China (No. 41402020102)
文摘With the flourishing development of Unmanned Aerial Vehicles(UAVs), the mission tasks of UAVs have become more and more complex. Consequently, a Real-Time Operating System(RTOS) that provides operating environments for various mission services on these UAVs has become crucial, which leads to the necessity of having a deep understanding of an RTOS. In this paper, an empirical study is conducted on FreeRTOS, a commonly used RTOS for UAVs, from a complex network perspective. A total of 85 releases of FreeRTOS, from V2.4.2 to V10.0.0, are modeled as directed networks, in which the nodes represent functions and the edges denote function calls. It is found that the size of the FreeRTOS network has grown almost linearly with the evolution of the versions, while its main core has evolved steadily. In addition, a k-core analysis-based metric is proposed to identify major functionality changes of FreeRTOS during its evolution.The result shows that the identified versions are consistent with the version change logs. Finally,it is found that the clustering coefficient of the Linux OS scheduler is larger than that of the FreeRTOS scheduler. In conclusion, the empirical results provide useful guidance for developers and users of UAV RTOSs.
文摘During the process of landslide, its dynamic mechanism is important to understand and predict these kinds of natural hazard. In this paper, a new method, based on concepts of complex networks, has been proposed to investigate the evolution of contact networks in mesoscale during the sliding process of slope. A slope model was established using the discrete element method (DEM), and influences of inter-particle frictional coefficients with four different values on?dynamic landslides were studied. Both macroscopic analysis on slope?landslide?and mesoanalysis on structure evolution of contact networks, including the?average degree, clustering coefficient?and N-cycle, were done during the process?of landslide. The analysis results demonstrate that: 1) with increasing inter-particle?frictional coefficients, the displacement of slope decreases and the stable angle of slope post-failure increases, which is smaller than the peak internal frictional angle;2) the average degree decreases with the increase of inter-particle frictional coefficient. When the displacement at the toe of the slope is smaller,?the average degree there changes more greatly with increasing inter-particle?frictional coefficient;3) during the initial stage of landslide, the clustering coefficient?reduces sharply, which may leads to easily slide of slope. As the landslide?going?on, however, the clustering coefficient?increases denoting increasing stability?with?increasing inter-particle frictional coefficients. When the inter-particle?frictional coefficient is smaller than 0.3, its variation can affect the clustering coefficient?and stable inclination of slope post-failure greatly;and 4) the number of?3-cycle increases, but 4-cycle and 5-cycle decrease with increasing inter-particle frictional coefficients.
基金Supported in part by the National Natural Science Foundations of China under Grant Nos 70271067 and 70401020.
文摘We investigate the mixing structure of directed and evolutionary US flight network. It is shown that such a network is a hierarchical network, with average assortativity coefficient-0.37. Application of the informationbased method that can give the same result provides a way to explore the structure of complex networks.
基金Supported by the National Basic Research Programme of China under Grant No 2006CB705500, the National Natural Science Foundation of China under Grant Nos 10635040, 10532060, 70571074 and 10472116, the Special Research Funds for Theoretical Physics Frontier Problems （A0524701）, the President Fund of Chinese Academy of Sciences, the Specialized Research Fund for the Doctoral Programme of Higher Education of China, and the Research Fund of the Education Department of Liaoning Province （20060140）. The authors thank Dr Ming Zhao for her comments and suggestions.
文摘A continuum opinion dynamic model is presented based on two rules. The first one considers the mobilities of the individuals, the second one supposes that the individuals update their opinions independently. The results of the model indicate that the bounded confidence εc, separating consensus and incoherent states, of a scale-free network is much smaller than the one of a lattice. If the system can reach the consensus state, the sum of all individuals＇ opinion change Oc（t） quickly decreases in an exponential form, while if it reaches the incoherent state finally, Oc（t） decreases slowly and has the punctuated equilibrium characteristic.
基金supported in part by Young Elite Scientists Sponsorship Program by CAST under Grant number 2018QNRC001National Science Foundation of China with Grant number 91738202, 62071194
文摘The research of complex networks facilitates the progress of various disciplines,including biology,chemistry,social science,computer,and communication engineering.Recently,it is popular to utilize complex networks to study the communication networks,such as designing efficient routing strategies and robust communication networks.However,exploiting the advantages of communication networks to investigate networks in various disciplines beyond telecommunications is still in infancy.Because of this situation,this paper proposes an information-defined network(IDN)framework by which a complex network can be abstracted as a communication network associated with multiple intelligent agents.Specifically,each component and dynamic process in this framework can be defined by information.We show that the IDN framework promotes the research of unsolved problems in the current complex network field,especially for detecting new interaction types in realworld networks.
基金Supported by the National 0utstanding Young Investigator Foundation of China under Grant No 70225005, the National Natural Science Foundation of China under Grant No 70471088.
文摘We propose a model of weighted networks in which the structural evolution is coupled with weight dynamics. Based on a simple merging and regeneration process, the model gives powel-law distributions of degree, strength and weight, as observed in many real networks. It should be emphasized that, in our model, the nontrivial degree-strength correlation can be reproduced and in agreement with empirical data. Moreover, the size-growing evolution model is also presented to meet the properties of real-world systems.
文摘We investigate the dynamics of random walks on weighted networks. Assuming that the edge weight and the node strength are used as local information by a random walker. Two kinds of walks, weight-dependent walk and strength-dependent walk, are studied. Exact expressions for stationary distribution and average return time are derived and confirmed by computer simulations. The distribution of average return time and the mean-square displacement are calculated for two walks on the Barrat-Barthelemy-Vespignani （BBV） networks. It is found that a weight-dependent walker can arrive at a new territory more easily than a strength-dependent one.
文摘Pancreatic ductal adenocarcinoma(PDAC) remains a deadly disease with no efficacious treatment options. PDAC incidence is projected to increase, which may be caused at least partially by the obesity epidemic. Significantly enhanced efforts to prevent or intercept this cancer are clearly warranted. Oncogenic KRAS mutations are recognized initiating events in PDAC development, however, they are not entirely sufficient for the development of fully invasive PDAC.Additional genetic alterations and/or environmental, nutritional, and metabolic signals, as present in obesity, type-2 diabetes mellitus, and inflammation, are required for full PDAC formation. We hypothesize that oncogenic KRAS increases the intensity and duration of the growth-promoting signaling network.Recent exciting studies from different laboratories indicate that the activity of the transcriptional co-activators Yes-associated protein(YAP) and WW-domaincontaining transcriptional co-activator with PDZ-binding motif(TAZ) play a critical role in the promotion and maintenance of PDAC operating as key downstream target of KRAS signaling. While initially thought to be primarily an effector of the tumor-suppressive Hippo pathway, more recent studies revealed that YAP/TAZ subcellular localization and co-transcriptional activity is regulated by multiple upstream signals. Overall, YAP has emerged as a central node of transcriptional convergence in growth-promoting signaling in PDAC cells. Indeed, YAP expression is an independent unfavorable prognostic marker for overall survival of PDAC. In what follows, we will review studies implicating YAP/TAZ in pancreatic cancer development and consider different approaches to target these transcriptional regulators.
基金the National Natural Science Foundation of China(Grant No.60973022)
文摘The evolution of Internet topology is not always smooth but sometimes with unusual sudden changes. Consequently, identifying patterns of unusual topology evolution is critical for Internet topology modeling and simulation. We analyze IPv6 Internet topology evolution in IP-level graph to demonstrate how it changes in uncommon ways to restructure the Internet. After evaluating the changes of average degree, average path length, and some other metrics over time, we find that in the case of a large-scale growing the Internet becomes more robust; whereas in a top–bottom connection enhancement the Internet maintains its efficiency with links largely decreased.
基金This work is supported by the National Natural Science Foundation of China(No.61803384).
文摘As a fundamental problem in the field of the network science,the study of topological evolution model is of great significance for revealing the inherent dynamics and mechanisms of complex network evolution.In order to study the influence of different scales of preferential attachment on topological evolution,a topological evolution model based on the attraction of the motif vertex is proposed.From the perspective of network motif,this model proposes the concept of attraction of the motif vertex based on the degree of the motif,quantifies the influence of local structure on the node preferential attachment,and performs the preferential selection of the new link based on the Local World model.The simulation experiments show that the model has the small world characteristic apparently,and the clustering coefficient varies with the scale of the local world.The degree distribution of the model changes from power-law distribution to exponential distribution with the change of parameters.In some cases,the piecewise power-law distribution is presented.In addition,the proposed model can present a network with different matching patterns as the parameters change.
