US flight network,composed of 285airports(nodes)and 3 971flights(edges)is studied.A static network model and a dynamic network model of US flight network are established.Firstly,the characteristics of static network a...US flight network,composed of 285airports(nodes)and 3 971flights(edges)is studied.A static network model and a dynamic network model of US flight network are established.Firstly,the characteristics of static network are analyzed.One finds that such a network is a″small-world″and″scale-free″network.The cumulative degree distributions of weighted network and unweighted network follow″Double Pareto Law″.And the degree exponent of weighted network is smaller than unweighted network.The average shortest-path length is 2.368 9,which is smaller than previous results.The clustering coefficient of unweighted network is 0.637 1and of weighted network is 0.653 6,which are both bigger than previous results.The correlation of degree,unweighted clustering coefficient and weighted clustering coefficient are also discussed.Secondly,the characteristics of dynamic network are studied.The structure of flight network is changing as the time goes by on a day.In rush hours,the network′s character of″scale-free″is stronger than other times.And then the relationships of topological structures and congestion effects are addressed.展开更多
Objective: To observe the therapeutic effect of Shenmai Injection (SI) in treating congestive heart failure (CHF). Methods: The changes in cAMP, cGMP, serum cardiac troponin T (cTnT, a specific marker reflecting myoca...Objective: To observe the therapeutic effect of Shenmai Injection (SI) in treating congestive heart failure (CHF). Methods: The changes in cAMP, cGMP, serum cardiac troponin T (cTnT, a specific marker reflecting myocardial injury), creatine kinase (CK) and creatine kinase isoenzyme (CK-展开更多
Cascading failures often occur in congested complex networks. Cascading failures can be expressed as a three-phase process： generation, diffusion, and dissipation of congestion. Different from the betweenness central...Cascading failures often occur in congested complex networks. Cascading failures can be expressed as a three-phase process： generation, diffusion, and dissipation of congestion. Different from the betweenness centrality, a congestion function is proposed to represent the extent of congestion on a given node. Inspired by the restart process of a node, we introduce the concept of ＂delay time,＂ during which the overloaded node Cannot receive or forward any traffic, so an intergradation between permanent removal and nonremoval is built and the flexibility of the presented model is demonstrated. Considering the connectivity of a network before and after cascading failures is not cracked because the overloaded node are not removed from network permanently in our model, a new evaluation function of network efficiency is also proposed to measure the damage caused by cascading failures. Finally, we investigate the effects of network structure and size, delay time, processing ability, and traffic generation speed on congestion propagation. Cascading processes composed of three phases and some factors affecting cascade propagation are uncovered as well.展开更多
基金supported by the Projects in the National Science & Technology Pillar Program (2011BAH24B10)the Joint Funds of National Natural Science Foundation of China (61571441)+2 种基金the Fundamental Research Funds for the Central Universities of Civil Aviation University of China in 2016the Open Fund of Air Traffic Management Research Base(No.KGJD201503)the Scientific Research Foundation of Civil Aviation University of China(No.2014QD01S)
文摘US flight network,composed of 285airports(nodes)and 3 971flights(edges)is studied.A static network model and a dynamic network model of US flight network are established.Firstly,the characteristics of static network are analyzed.One finds that such a network is a″small-world″and″scale-free″network.The cumulative degree distributions of weighted network and unweighted network follow″Double Pareto Law″.And the degree exponent of weighted network is smaller than unweighted network.The average shortest-path length is 2.368 9,which is smaller than previous results.The clustering coefficient of unweighted network is 0.637 1and of weighted network is 0.653 6,which are both bigger than previous results.The correlation of degree,unweighted clustering coefficient and weighted clustering coefficient are also discussed.Secondly,the characteristics of dynamic network are studied.The structure of flight network is changing as the time goes by on a day.In rush hours,the network′s character of″scale-free″is stronger than other times.And then the relationships of topological structures and congestion effects are addressed.
文摘Objective: To observe the therapeutic effect of Shenmai Injection (SI) in treating congestive heart failure (CHF). Methods: The changes in cAMP, cGMP, serum cardiac troponin T (cTnT, a specific marker reflecting myocardial injury), creatine kinase (CK) and creatine kinase isoenzyme (CK-
基金supported by the China –BC ICSD Grant(No. 2008DFA12140)the Ph.D. Programs Foundation of Ministry of Education of China(No. 20060183043)Jilin University 985 Program Graduate Student Innovation Foundation(No. 20080235)
文摘Cascading failures often occur in congested complex networks. Cascading failures can be expressed as a three-phase process： generation, diffusion, and dissipation of congestion. Different from the betweenness centrality, a congestion function is proposed to represent the extent of congestion on a given node. Inspired by the restart process of a node, we introduce the concept of ＂delay time,＂ during which the overloaded node Cannot receive or forward any traffic, so an intergradation between permanent removal and nonremoval is built and the flexibility of the presented model is demonstrated. Considering the connectivity of a network before and after cascading failures is not cracked because the overloaded node are not removed from network permanently in our model, a new evaluation function of network efficiency is also proposed to measure the damage caused by cascading failures. Finally, we investigate the effects of network structure and size, delay time, processing ability, and traffic generation speed on congestion propagation. Cascading processes composed of three phases and some factors affecting cascade propagation are uncovered as well.
