Chaos in complex motor networks induced by Newman-Watts small-world connections

We investigate how dynamical behaviours of complex motor networks depend on the Newman-Watts small-world （NWSW） connections. Network elements are described by the permanent magnet synchronous motor （PMSM） with the values of parameters at which each individual PMSM is stable. It is found that with the increase of connection probability p, the motor in networks becomes periodic and falls into chaotic motion as p further increases. These phenomena imply that NWSW connections can induce and enhance chaos in motor networks. The possible mechanism behind the action of NWSW connections is addressed based on stability theory.

Exploring Biocomplexity in Cancer: A Comprehensive Review

Living objects have complex internal and external interactions. The complexity is regulated and controlled by homeostasis, which is the balance of multiple opposing influences. The environmental effects finally guide the self-organized structure. The living systems are open, dynamic structures performing random, stationary, stochastic, self-organizing processes. The self-organizing procedure is defined by the spatial-temporal fractal structure, which is self-similar both in space and time. The system’s complexity appears in its energetics, which tries the most efficient use of the available energies;for that, it organizes various well-connected networks. The controller of environmental relations is the Darwinian selection on a long-time scale. The energetics optimize the healthy processes tuned to the highest efficacy and minimal loss (minimalization of the entropy production). The organism is built up by morphogenetic rules and develops various networks from the genetic level to the organism. The networks have intensive crosstalk and form a balance in the Nash equilibrium, which is the homeostatic state in healthy conditions. Homeostasis may be described as a Nash equilibrium, which ensures energy distribution in a “democratic” way regarding the functions of the parts in the complete system. Cancer radically changes the network system in the organism. Cancer is a network disease. Deviation from healthy networking appears at every level, from genetic (molecular) to cells, tissues, organs, and organisms. The strong proliferation of malignant tissue is the origin of most of the life-threatening processes. The weak side of cancer development is the change of complex information networking in the system, being vulnerable to immune attacks. Cancer cells are masters of adaptation and evade immune surveillance. This hiding process can be broken by electromagnetic nonionizing radiation, for which the malignant structure has no adaptation strategy. Our objective is to review the different sides of living complexity and use the knowledge to fight against cancer.

Worldwide Marine Transportation Network： Efficiency and Container Throughput

Through empirical analysis of the global structure of the Worldwide Marine Transportation Network （WMTN）, we find that the WMTN, a small-world network, exhibits an exponential-like degree distribution. We hereby investigate the efficiency of the WMTN by employing a simple definition. Compared with many other transportation networks, the WMTN possesses relatively low efficiency. Furthermore, by exploring the relationship between the topological structure and the container throughput, we find that strong correlations exist among the container throughout the degree and the clustering coefficient. Also, considering the navigational process that a ship travels in a real shipping line, we obtain that the weight of a seaport is proportional to the total probability contributed by all the passing shipping lines.

A new local-world evolving network model

In some real complex networks, only a few nodes can obtain the global information about the entire networks, but most of the nodes own only local connections therefore own only local information of the networks. A new local-world evolving network model is proposed in this paper. In the model, not all the nodes obtain local network information, which is different from the local world network model proposed by Li and Chen （LC model）. In the LC model, each node has only the local connections therefore owns only local information about the entire networks. Theoretical analysis and numerical simulation show that adjusting the ratio of the number of nodes obtaining the global information of the network to the total number of nodes can effectively control the valuing range for the power-law exponent of the new network. Therefore, if the topological structure of a complex network, especially its exponent of power-law degree distribution, needs controlling, we just add or take away a few nodes which own the global information of the network.

Topological Structure of US Flight Network Based on Complex Network Theory

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.

Application of Small-World Measures to Multichannel Event-Related Potential Activity during Generation of Global and Local Imagery

The Small world model has been successfully used to explore the abnormal pattern of brain information processing in some neuropsychiatric diseases, but not engaged in the study of cognitive functions. We apply the small-world measures： the clustering coefficient and average path length, to evaluate multi-channel event-related potential activity during the generation of global and local imagery. Results show that the brain functional networks of the global and local imagery generation are both small-world ones. In addition, the local imagery generation has a larger clustering coefficient, while the global imagery generation has a shorter average path length. These results support the global precedence in the global-local imagery generation, and reflect the different processing modes in which global imagery emphasizes particularly on global integration, while local imagery on local specialization. Our results indicate that small-world measures could be applied to quantify the difference of brain activities in different cognitive tasks, and further provide some explanations for cognitive behavior.

Phase synchronization on small-world networks with community structure

In this paper, we propose a simple model that can generate small-world network with community structure. The network is introduced as a tunable community organization with parameter r, which is directly measured by the ratio of inter- to intra-community connectivity, and a smaller r corresponds to a stronger community structure. The structure properties, including the degree distribution, clustering, the communication efficiency and modularity are also analysed for the network. In addition, by using the Kuramoto model, we investigated the phase synchronization on this network, and found that increasing the fuzziness of community structure will markedly enhance the network synchronizability; however, in an abnormal region （r ≤ 0.001）, the network has even worse synchronizability than the case of isolated communities （r = 0）. Furthermore, this network exhibits a remarkable synchronization behaviour in topological scales： the oscillators of high densely interconnected communities synchronize more easily, and more rapidly than the whole network.

Structural Properties of Complex Networks

When complex networks describe a wide range of systems in nature and society,it is increasingly recognized that the topology of real networks are governed by robust organizing principles.Here we discuss the structural metrics such as average path length,clustering coefficient and degree distribution,the main models covering random graphs,small-world and scale-free networks,the interplay between structural properties and the synchronization of complex networks.

Evolutionary dynamics analysis of complex network with fusion nodes and overlap edges

Multiple complex networks, each with different properties and mutually fused, have the problems that the evolving process is time varying and non-equilibrium, network structures are layered and interlacing, and evolving characteristics are difficult to be measured. On that account, a dynamic evolving model of complex network with fusion nodes and overlap edges（CNFNOEs） is proposed. Firstly, we define some related concepts of CNFNOEs, and analyze the conversion process of fusion relationship and hierarchy relationship. According to the property difference of various nodes and edges, fusion nodes and overlap edges are subsequently split, and then the CNFNOEs is transformed to interlacing layered complex networks（ILCN）. Secondly,the node degree saturation and attraction factors are defined. On that basis, the evolution algorithm and the local world evolution model for ILCN are put forward. Moreover, four typical situations of nodes evolution are discussed, and the degree distribution law during evolution is analyzed by means of the mean field method.Numerical simulation results show that nodes unreached degree saturation follow the exponential distribution with an error of no more than 6%; nodes reached degree saturation follow the distribution of their connection capacities with an error of no more than 3%; network weaving coefficients have a positive correlation with the highest probability of new node and initial number of connected edges. The results have verified the feasibility and effectiveness of the model, which provides a new idea and method for exploring CNFNOE＇s evolving process and law. Also, the model has good application prospects in structure and dynamics research of transportation network, communication network, social contact network,etc.

Evolutionary snowdrift game on heterogeneous Newman-Watts small-world network

We study the evolutionary snowdrift game in a heterogeneous Newman-Watts small-world network. The heterogeneity of the network is controlled by the number of hubs. It is found that the moderate heterogeneity of the network can promote the cooperation best. Besides, we study how the hubs affect the evolution of cooperative behaviours of the heterogeneous Newman-Watts small-world network. Simulation results show that both the initial states of hubs and the connections between hubs can play an important role. Our work gives a further insight into the effect of hubs on the heterogeneous networks.

Homogeneous and Heterogeneous Traffic of Data Packets on Complex Networks: The Traffic Congestion Phenomenon

We study the congestion phenomenon in a mathematical model of the data packets traffic in transmission networks as a function of the topology and of the load of the network. Two types of traffic are considered: homogeneous and heterogeneous traffic. The congestion phenomenon is studied in stationary conditions through the behaviour of two quantities: the mean travel time of a packet and the mean number of packets that have not reached their destination and are traveling in the network. We define a transformation that maps a network having the small world property (Inet 3037 in our numerical experiments) into a (modified) lattice network that has the same number of nodes. This map changes the capacity of the branches of the graphs representing the networks and can be regarded as an “interpolation” between the two classes of networks. Using this transformation we compare the behaviour of Inet 3037 to the behaviour of a modified rectangular lattice and we study the behaviour of the interpolating networks. This study suggests how to change the network topology and the branch capacities in order to alleviate the congestion phenomenon. In the website: http://www.ceri.uniroma1.it/ceri/zirilli/w6 some auxiliary material including animations and stereo?graphic scenes that helps the understanding of this paper is shown.

遗产综合体构建研究--以盐城世界自然遗产为例

世界遗产管理已经进入可持续、高质量发展的新阶段,亟须探索保护与发展联动的管理模式。借鉴“旅游综合体”这一功能复合、高效互动、以点带面的旅游开发模式,在遗产地构建“遗产综合体”,即以遗产保护为核心,由与遗产相关的监测、研究、展示、服务、产业等多种设施或机构以及管理体制、利益相关者协调机制等制度环境共同构成的功能复合体。它遵循多元综合、保护与发展联动、区域促进等原则,旨在实现遗产保护与地区可持续发展的双重目标。以中国黄(渤)海候鸟栖息地(I期)为例,探讨盐城遗产综合体的现状、问题和优化对策。

前交通动脉动脉瘤112例诊治真实世界数据分析:单中心报告

目的对前交通动脉动脉瘤(anterior communicating artery aneurysm,ACoAA)病例资料进行真实世界数据(real world data,RWD)分析,总结救治经验。方法回顾性分析112例ACoAA病例资料。男69例,女43例,年龄30~80岁、平均(45.00±11.05)岁。发生蛛网膜下腔出血就诊110例,未破裂就诊2例。行开颅夹闭66例,血管内介入治疗46例,其中应用支架辅助栓塞5例。统计病人的人口学资料、基础疾病、个人史、家族史、入院状况及影像学资料、动脉瘤解剖学特征、病人预后等资料。结果依据改良Rankin量表(modified Rankin Scale,mRS)评分:良好(mRS 0~2分)82例,残疾(mRS 3~5分)22例,死亡(mRS 6)8例。RWD将预后不良的相关因素,纳入有序多分类Logistic回归分析,显示年龄与饮酒史是ACoAA术后预后的独立危险因素,病人居住地、高血压病史及不同治疗术式(开颅夹闭和栓塞治疗)不是病人预后的独立危险因素。结论ACoAA确诊后接受积极治疗(开颅夹闭或栓塞治疗),病人术后恢复良好率较高。ACoAA不良预后可能与年龄、饮酒等因素相关。

《水浒传》人物关系网络分析

复杂网络作为复杂系统的一种抽象描述,可用于文学作品中人物关系网络的建模工具。以《水浒传》中的108将为研究对象,采用复杂网络分析方法对该作品中的人物关系进行构建与分析,小说中的人物对应于网络中的节点,人物之间的关系对应于网络中的边。人工搜索标记人物名称,以任意两个人物在同一章回的共现关系为前提,构建人物关系网络,并计算度、介数、集聚系数、稀疏性、相关性等网络指标。结果表明《水浒传》人物关系网络是异配网络,并且具有小世界特性和社区特性。

基于复杂网络演化博弈的无线传感器网络入侵检测方法

针对无线传感器网络资源受限和入侵检测系统策略优化问题,本文提出一种基于复杂网络演化博弈的无线传感器网络入侵检测方法。结合小世界模型理论,模拟网络节点之间的连接关系,在不改变节点原有关系的前提下增强网络连通性并降低传输能耗;构建关于簇头节点和恶意节点的无线传感器网络攻防博弈模型,通过收益矩阵计算节点收益,利用奖惩机制描述节点在博弈过程中选择不同策略的收益变化;引入经验加权吸引力学习算法改进传统博弈的策略更新规则并将该算法应用于入侵检测系统,使得簇头节点能够动态更新策略选择,得到不同条件下的入侵检测最优策略。实验结果表明,与传统方法相比,所提算法的簇头节点检测策略扩散深度可以达到79%,该算法下簇头节点在保障自身检测收益的同时尽可能选择检测传感器网络中出现的攻击,保证网络检测率并减少网络各类资源的消耗。

基于复杂网络的盐城市区公交系统研究

城市交通系统是一个动态、开放的复杂系统。交通堵塞和交通事故频发会对现代化城市建设和发展造成负面影响,合理安排交通线路及站点无疑具有较大的现实意义。基于复杂网络的基本理论,建立了盐城市区公交站点的网络模型,并分析其拓扑性质;根据盐城市公交网络实际数据,利用所建网络模型计算公交网络特征参数,验证了该模型的小世界性和无标度性;构建评价指标,对实际采集数据进行仿真和分析,结果表明:盐城市区公交网络具有较强的鲁棒性。

高原复杂地形倾斜摄影测量技术应用

高原山区地形复杂,自然环境恶劣,由此造成了工作条件受到多重限制。应用传统测量手段安全风险大、效率低、成本高,很难进行实施。随着无人机技术的飞速发展,高原山区复杂地形快速、高效测量已成为可能。经过实践研究,采用无人机倾斜摄影测量技术可以对高原复杂地形进行测量,且实现了低风险、低成本、高精度。

基于复杂网络理论的汉语“N+N”组块网络研究

“组块”最初是认知理论中提出的概念,被看作语言记忆和存储、输出和使用的最小单位,符合认知规律,能够有效强化认知操作。“网络”是由若干节点和边构成的图(Graph),表示诸多对象及其相互联系。作为新兴热点科学,复杂网络是对存在的网络现象及其复杂性进行解释的学科。语言网络是一种极为复杂的网络。运用复杂网络理论及方法对汉语组块结构进行定量描述与定性分析,发现汉语“N+N”组块网络是小世界网络,其度分布服从幂律分布,是一种无标度网络。从生物性角度来看,组块网络受人类使用影响程度较大,属于社会网络。

复杂网络视角下交通网络拓扑结构分析

对交通流量数据构建复杂的网络模型,从矩阵视角对其拓扑结构进行分析。结果表明,此交通复杂网络位置节点的度分布符合幂律分布,即BA无标度网络。经过对数据处理,聚类系数较大,平均路径长度较小,网络呈小世界性,通过MATLAB分析数据得到Laplace矩阵的特征值,得到此网络的同步能力较弱。相关部门可根据此结果对公共交通及共享交通工具进行合理安排及调整,进一步提升通行效率及公共资源的利用率,使拥堵现象和资源浪费导致的环境污染问题得到缓解。

中国航空网络空间结构的复杂性

航空运输是现代交通运输的重要组成部分,以机场和航线构建的网络是其提供运输服务的空间载体。基于复杂网络理论,借助度分布、平均路径长度、簇系数、度度相关性、簇度相关性等指标对以城市为节点的中国航空网络空间结构进行分析,发现其度累计概率分布表现为具有置信度较高的指数分布,且具有较小的平均路径长度(2.23)和较大的簇系数(0.69),整体结构呈现"小世界网络"的特点。由于中国航空网络规模较小,且新建机场倾向于直接与最高级枢纽机场建立航线联系,不利于区域枢纽机场的形成。因而除顶层结构(北京—上海—广州)外,中国航空网络的其它层级结构并不十分明显。从节点的度、簇系数、可达性等指标及其相关性分析,中国航空网络空间结构特征差异明显,表现出较强的集聚性,且可达性与城市体系上层结构在空间分布上较为吻合。随着中国航空运输需求的快速增加,未来航空网络在市场经济的推动下,将进一步表现出向具有"无标度"特征的"小世界网络"演变的趋势,航空网络的空间结构将日趋复杂化。