Assessing edge-coupled interdependent network disintegration via rank aggregation and elite enumeration

The disintegration of networks is a widely researched topic with significant applications in fields such as counterterrorism and infectious disease control. While the traditional approaches for achieving network disintegration involve identifying critical sets of nodes or edges, limited research has been carried out on edge-based disintegration strategies. We propose a novel algorithm, i.e., a rank aggregation elite enumeration algorithm based on edge-coupled networks(RAEEC),which aims to implement tiling for edge-coupled networks by finding important sets of edges in the network while balancing effectiveness and efficiency. Our algorithm is based on a two-layer edge-coupled network model with one-to-one links, and utilizes three advanced edge importance metrics to rank the edges separately. A comprehensive ranking of edges is obtained using a rank aggregation approach proposed in this study. The top few edges from the ranking set obtained by RAEEC are then used to generate an enumeration set, which is continuously iteratively updated to identify the set of elite attack edges.We conduct extensive experiments on synthetic networks to evaluate the performance of our proposed method, and the results indicate that RAEEC achieves a satisfactory balance between efficiency and effectiveness. Our approach represents a significant contribution to the field of network disintegration, particularly for edge-based strategies.

Percolation transitions in edge-coupled interdependent networks with directed dependency links

We propose a model of edge-coupled interdependent networks with directed dependency links(EINDDLs)and develop the theoretical analysis framework of this model based on the self-consistent probabilities method.The phase transition behaviors and parameter thresholds of this model under random attacks are analyzed theoretically on both random regular(RR)networks and Erd¨os-Renyi(ER)networks,and computer simulations are performed to verify the results.In this EINDDL model,a fractionβof connectivity links within network B depends on network A and a fraction(1-β)of connectivity links within network A depends on network B.It is found that randomly removing a fraction(1-p)of connectivity links in network A at the initial state,network A exhibits different types of phase transitions(first order,second order and hybrid).Network B is rarely affected by cascading failure whenβis small,and network B will gradually converge from the first-order to the second-order phase transition asβincreases.We present the critical values ofβfor the phase change process of networks A and B,and give the critical values of p andβfor network B at the critical point of collapse.Furthermore,a cascading prevention strategy is proposed.The findings are of great significance for understanding the robustness of EINDDLs.

Optimization and coordination model of information system security investment for interdependent risk

The impact of risk correlation on firm＇s investments in information system security is studied by using quantification models combining the ideas of the risk management theory and the game theory. The equilibrium levels of self-protection and insurance coverage under the non- cooperative condition are compared with socially optimal solutions, and the associated coordination mechanisms are proposed. The results show that self-protection investment increases in response to an increase in potential loss when the interdependent risk is small; the interdependent risk of security investments often induce firms to underinvest in security relative to the socially efficient level by ignoring marginal external costs or benefits conferred on others. A subsidy on self-protection investment from the government can help coordinate a firm＇s risk management decision and, thereby, improve individual security level and overall social welfare.

A fiber-section model based Timoshenko beam element using shear-bending interdependent shape function

A fiber-section model based Timoshenko beam element is proposed in this study that is founded on the nonlinear analysis of frame elements considering axial, flexural, and shear deformations. This model is achieved using a shear-bending interdependent formulation （SBIF）. The shape function of the element is derived from the exact solution of the homogeneous form of the equilibrium equation for the Timoshenko deformation hypothesis.The proposed element is free from shear-locking. The sectional fiber model is constituted with a multi-axial plasticity material model, which is used to simulate the coupled shear-axial nonlinear behavior of each fiber. By imposing deformation compatibility conditions among the fibers, the sectional and elemental resisting forces are calculated. Since the SBIF shape functions are interactive with the shear-corrector factor for different shapes of sections, an iterative procedure is introduced in the nonlinear state determination of the proposed Timoshenko element. In addition, the proposed model tackles the geometric nonlinear problem by adopting a corotational coordinate transformation approach. The derivation procedure of the corotational algorithm of the SBIF Timoshenko element for nonlinear geometrical analysis is presented. Numerical examples confirm that the SBIF Timoshenko element with a fiber-section model has the same accuracy and robustness as the flexibility-based formulation. Finally, the SBIF Timoshenko element is extended and demonstratedin a three-dimensional numerical example.

Weighted Gini-Simpson Quadratic Index of Biodiversity for Interdependent Species

The weighted Gini-Simpson quadratic index is the simplest measure of biodiversity which takes into account the relative abundance of species and some weights assigned to the species. These weights could be assigned based on factors such as the phylogenetic distance between species, or their relative conservation values, or even the species richness or vulnerability of the habitats where these species live. In the vast majority of cases where the biodiversity is measured the species are supposed to be independent, which means that the relative proportion of a pair of species is the product of the relative proportions of the component species making up the respective pair. In the first section of the paper, the main versions of the weighted Gini-Simpson index of biodiversity for the pairs and triads of independent species are presented. In the second section of the paper, the weighted Gini-Simpson quadratic index is calculated for the general case when the species are interdependent. In this instance, the weights reflect the conservation values of the species and the distribution pattern variability of the subsets of species in the respective habitat induced by the inter-dependence between species. The third section contains a numerical example.

A Security Enhancement Model Based on Switching Edge Strategy in Interdependent Heterogeneous Cyber-Physical Systems

With the advent of cross-domain interconnection,large-scale sensor network systems such as smart grids,smart homes,and intelligent transportation have emerged.These complex network systems often have a CPS(Cyber-Physical System)architecture and are usually composed of multiple interdependent systems.Minimal faults between interdependent networks may cause serious cascading failures between the entire system.Therefore,in this paper,we will explore the robustness detection schemes for interdependent networks.Firstly,by calculating the largest giant connected component in the entire system,the security of interdependent network systems under different attack models is analyzed.Secondly,a comparative analysis of the cascade failure mechanism between interdependent networks under the edge enhancement strategy is carried out.Finally,the simulation results verify the impact of system reliability under different handover edge strategies and show how to choose a better handover strategy to enhance its robustness.The further research work in this paper can also help design how to reduce the interdependence between systems,thereby further optimizing the interdependent network system’s structure to provide practical support for reducing the cascading failures.In the later work,we hope to explore our proposed strategies in the network model of real-world or close to real networks.

Controllability of heterogeneous interdependent group systems under undirected and directed topology

The controllability problem of heterogeneous interdependent group systems with undirected and directed topology is investigated in this paper. First, the interdependent model of the heterogeneous system is set up according to the difference of individual characteristics. An extended distributed protocol with the external sliding-mode control is designed, under which it is shown that a heterogeneous interdependent group system is controllable when the corresponding communication topology is controllable. Then, using the network eigenvalue method, the driving individuals are determined for a heterogeneous system with undirected topology. Under directed topology, the maximum match method is utilized to confirm the driving individuals. Some sufficient and necessary conditions are presented to assure that the heterogeneous interdependent group system is structurally controllable. Via theoretical analysis, the controllability of heterogeneous interdependent systems is related to the interdependent manner and the structure of the heterogeneous system. Numerical simulations are provided to demonstrate the effectiveness of the theoretical results.

The Interdependent Coexistence of the Rational Civilizations: The Mental Origin of Civilizations

The paper purposes that the three major civilizations are territorial rational civilization originated from the tribes before the Axial Age, discrete Western rational civilization originated from the mega empires in Middle East and Greece during the Axial Age, and the connective Eastern rational civilization originated from the mega empires in India and China during the Axial Age. Territorial rational civilization with territorial worldview for ingroup and outgroup individuals produces territorial nationalist democracy based on rule of boundary to deal with ingroup and outgroup individuals. Discrete Western rational civilization with discrete worldview for discrete and independent individuals produces discrete liberty-equality democracy based on rule of law to deal with discrete individuals. Connective Eastern rational civilization with connective worldview for connective and related individuals produces connective common wellbeing democracy based on rule of relation to deal with connective individuals. The current highly international interdependence produces the purposed internationalized interdependent community which allows the interdependent coexistence of the three rational civilizations by establishing the promotion of rational civilizations, the basic rules of relation and law, the potential civilizational and the regional defense boundaries, and the cooperation in international relations. The mental origin of the rational civilization consists of the social brain for instinctive intragroup relations and worldviews to form the original human social group, the mental immune system for instinctive mental therapy, theory of imaginary mind for imaginary religious and political entities with their own minds to form cohesive large social groups, and the thinking brain for rule to form rational civilization.

The Invulnerability of Directed Interdependent Networks with Multiple Dependency Relations

The paper aims to study the invulnerability of directed interdependent networks with multiple dependency relations: dependent and supportive. We establish three models and simulate in three network systems to deal with this question. To improve network invulnerability, we’d better avoid dependent relations transmission and add supportive relations symmetrically.

Investigation of Probability Generating Function in an Interdependent <i>M/M/</i>1:(∞;GD) Queueing Model with Controllable Arrival Rates Using Rouche’s Theorem

Present paper deals a M/M/1:(∞;GD) queueing model with interdependent controllable arrival and service rates where- in customers arrive in the system according to poisson distribution with two different arrivals rates-slower and faster as per controllable arrival policy. Keeping in view the general trend of interdependent arrival and service processes, it is presumed that random variables of arrival and service processes follow a bivariate poisson distribution and the server provides his services under general discipline of service rule in an infinitely large waiting space. In this paper, our central attention is to explore the probability generating functions using Rouche’s theorem in both cases of slower and faster arrival rates of the queueing model taken into consideration;which may be helpful for mathematicians and researchers for establishing significant performance measures of the model. Moreover, for the purpose of high-lighting the application aspect of our investigated result, very recently Maurya [1] has derived successfully the expected busy periods of the server in both cases of slower and faster arrival rates, which have also been presented by the end of this paper.

An interdependent world

The financial crisis that first struck the United States is unfolding into a worldwide economic recession.When the U.S.coughs,the world catches a cold,now a once-in-acentury cold.This is unexpected to most people,including most economists.It is often said that everything in

"Independent Self"and"Interdependent Self"reflections on the reference to the body perspective in psychotherapy and psychosomatics in China

The introduction of western psychotherapy methods to China is an enormous transcultural challenge.It touches the different concepts of"independent self"and"interdependent self"in China.The different constructions of self are contingent upon society and culture.It is important to give particular consideration to this aspect in the transfer of western(body)psychotherapy to China.In this article,the author describes general and concrete examples of his own experiences in China.

Resilience assessment framework toward interdependent bus-rail transit network:Structure,critical components,and coupling mechanism

Understanding the interdependent nature of multimodal public transit networks(PTNs)is vital for ensuring the resilience and robustness of transportation systems.However,previous studies have predominantly focused on assessing the vulnerability and characteristics of single-mode PTNs,neglecting the impacts of heterogeneous disturbances and shifts in travel behavior within multimodal PTNs.Therefore,this study introduces a novel resilience assessment framework that comprehensively analyzes the coupling mechanism,structural and functional characteristics of bus-rail transit networks(BRTNs).In this framework,a network performance metric is proposed by considering the passengers’travel behaviors under various disturbances.Additionally,stations and subnetworks are classified using the k-means algorithm and resilience metric by simulating various disturbances occurring at each station or subnetwork.The proposed framework is validated via a case study of a BRTN in Beijing,China.Results indicate that the rail transit network(RTN)plays a crucial role in maintaining network function and resisting external disturbances in the interdependent BRTN.Furthermore,the coupling interactions between the RTN and bus transit network(BTN)exhibit distinct characteristics under infrastructure component disruption and functional disruption.These findings provide valuable insights into emergency management for PTNs and understanding the coupling relationship between BTN and RTN.

Bayesian network-based resilience assessment of interdependent infrastructure systems under optimal resource allocation strategies

Critical infrastructure systems(CISs)play a key role in the socio-economic activity of a society,but are exposed to an array of disruptive events that can greatly impact their function and performance.Therefore,understanding the underlying behaviors of CISs and their response to perturbations is needed to better prepare for,and mitigate the impact of,future disruptions.Resilience is one characteristic of CISs that influences the extent and severity of the impact induced by extreme events.Resilience is often dissected into four dimensions:robustness,redundancy,resourcefulness,and rapidity,known as the“4Rs”.This study proposes a framework to assess the resilience of an infrastructure network in terms of these four dimensions under optimal resource allocation strategies and incorporates interdependencies between different CISs,with resilience considered as a stochastic variable.The proposed framework combines an agent-based infrastructure interdependency model,advanced optimization algorithms,Bayesian network techniques,and Monte Carlo simulation to assess the resilience of an infrastructure network.The applicability and flexibility of the proposed framework is demonstrated with a case study using a network of CISs in Austin,Texas,where the resilience of the network is assessed and a“what-if”analysis is performed.

Node interdependent percolation of multiplex hypergraph with weak interdependence

In recent years, there has been considerable attention and research on the higher-order interactions that are prevalent in various real-world networks. Hypergraphs, especially in the study of complex systems, are proved effective in capturing these interactions. To better characterize the model in reality, this paper proposes a theoretical model of node interdependent percolation in multiplex hypergraphs, considering “weak” interdependence. The proposed model includes pairwise and higher-order interactions, where the removal of nodes triggers cascading failures. However, interdependent nodes connected to failed nodes experience partial loss of connections due to “weak” interdependence, reflecting the self-sustaining capabilities of real-world systems. Percolation theory is applied to the analysis to investigate the properties of the percolation threshold and phase transition. Both analysis and simulation results show that as the strength of interdependence between nodes weakens, the network transitions from a discontinuous to a continuous phase, thereby increasing its robustness.

Identification of Important FPGA Modules Based on Complex Network

The globalization of hardware designs and supply chains,as well as the integration of third-party intellectual property(IP)cores,has led to an increased focus from malicious attackers on computing hardware.However,existing defense or detection approaches often require additional circuitry to perform security verification,and are thus constrained by time and resource limitations.Considering the scale of actual engineering tasks and tight project schedules,it is usually difficult to implement designs for all modules in field programmable gate array(FPGA)circuits.Some studies have pointed out that the failure of key modules tends to cause greater damage to the network.Therefore,under limited conditions,priority protection designs need to be made on key modules to improve protection efficiency.We have conducted research on FPGA designs including single FPGA systems and multi-FPGA systems,to identify key modules in FPGA systems.For the single FPGA designs,considering the topological structure,network characteristics,and directionality of FPGA designs,we propose a node importance evaluationmethod based on the technique for order preference by similarity to an ideal solution(TOPSIS)method.Then,for the multi-FPGA designs,considering the influence of nodes in intra-layer and inter-layers,they are constructed into the interdependent network,and we propose a method based on connection strength to identify the important modules.Finally,we conduct empirical research using actual FPGA designs as examples.The results indicate that compared to other traditional indexes,node importance indexes proposed for different designs can better characterize the importance of nodes.

MODELING AND SIMULATION OF THE VULNERABILITY OF INTERDEPENDENT POWER-WATER INFRASTRUCTURE NETWORKS TO CASCADING FAILURES

Critical infrastructures are becoming increasingly interdependent and vulnerable to cascading failures. Existing studies have analyzed the vulnerability of interdependent networks to cascading failures from the static perspective of network topology structure. This paper develops a more realistic cascading failures model that considers the dynamic redistribution of load in power network to explore the vulnerability of interdependent power-water networks. In this model, the critical tolerance threshold is originally proposed to indicate the vulnerability of network to cascading failures. In addition, some key parameters that are important to network vulnerability are identified and quantified through numerical simulation. Results show that cascading failures can be prevented when the values of tolerance parameter are above a critical tolerance threshold. Otherwise interdependent networks collapse after attacking a critical fraction of power nodes. Interdependent networks become more vulnerable with the increase in interdependence strength, which implies the importance of protecting those interconnected nodes to reduce the consequences of cascading failures. Interdependent networks are most vulnerable under high-load attack, which shows the significance of protecting high-load nodes.

Co-optimization approach to post-storm recovery for interdependent power and transportation systems

The power and transportation systems are urban interdependent critical infrastructures(CIs).During the post-disaster restoration process,transportation mobility and power restoration process are interdependent,and their functionalities significantly affect the well-beings of other urban CIs.Therefore,to enhance the resilience of urban CIs,successful recovery strategies should promote CI function cooperatively and synergistically to distribute goods and services efficiently.This paper develops an integrative framework that addresses the challenges of enhancing the recovery efficiency of urban power and transportation systems in short-term recovery period.Specifically,the post-storm recovery process is considered as a scheduling problem with the constraints representingcrew dispatch,equipment and fuel limit.We propose a new framework for co-optimizing the recovery scheduling of power and transportation systems,respecting precedency requirement and network constraints.The advantages and benefits of co-optimized recovery scheduling are validated in a testing system.

Vulnerable Point Identification Using Heterogeneous Interdependent Node Theory for Distribution Systems

In order to reduce the occurrence or expansion of accidents and maintain safety in distribution networks,it is essential to find out the vulnerable points for the power system in time.In this paper,a vulnerable point identification method based on heterogeneous interdependent(HI)node theory and risk theory is proposed.Compared with the methods based on betweenness theory,the method based on HI nodes theory can deal with the shortcomings of the power flow shortest path,and consider the direct and indirect relationship of nodes.It is more suitable for identifying vulnerable points in a realistic power system.First,according to the analysis of heterogenous interdependent networks,the HI nodes are defined and used to evaluate the utility coupling value of each node.Then an identification indicator,which combines the utility coupling value and the risk indicators,is utilized to evaluate the vulnerability of each node.Results show that the proposed method is a suitable one to find the vulnerable points and better than betweennessbased methods for a distribution network.

Impact of asymptomatic infected individuals on epidemic transmission dynamics in multiplex networks with partial coupling

The theory of network science has attracted great interest of many researchers in the realm of biomathematics and public health,and numerous valuable epidemic models have been developed.In previous studies,it is common to set up a one-to-one correspondence between the nodes of a multi-layer network,ignoring the more complex situations in reality.In the present work,we explore this situation by setting up a partially coupled model of a two-layer network and investigating the impact of asymptomatic infected individuals on epidemics.We propose a self-discovery mechanism for asymptomatic infected individuals,taking into account situations such as nucleic acid testing in the community and individuals performing self-antigen testing during the epidemic.Considering these factors together,through the microscopic Markov chain approach(MMCA)and extensive Monte Carlo(MC)numerical simulations,we find that the greater the coupling between the networks,the more information dissemination is facilitated.In order to control the epidemics,more asymptomatic infected individuals should be made aware of their infection.Massive adoption of nucleic acid testing and individual adoption of antigenic self-testing can help to contain epidemic outbreaks.Meanwhile,the epidemic threshold of the proposed model is derived,and then miscellaneous factors affecting the epidemic threshold are also discussed.Current results are conducive to devising the prevention and control policies of pandemics.