Enhancing Robustness and Resilience of Multiplex Networks against Node-community Cascading Failures

National Natural Science Foundation of China; National Key Research and Development Program of China; Natural Science Foundation of Guangdong Province-Outstanding Youth Program; Natural Science Foundation of Guangdong Province; Technology Research Project of Shenzhen City; Consejo Nacional de Ciencia y Tecnología; SEP-Cinvestav 2018 Project application no. 4

Multilayer Networks

In most natural and engineered systems, a set of entities interact with each other in complicated patterns that can encompass multiple types of relationships, change in time, and include other types of complications. Such systems include multiple subsystems and layers of connectivity, and it is important to take such "multilayer" features into account to try to improve our understanding of complex systems. Consequently, it is necessary to generalize "traditional" network theory by developing (and validating) a framework and associated tools to study multilayer systems in a comprehensive fashion. The origins of such efforts date back several decades and arose in multiple disciplines, and now the study of multilayer networks has become one of the most important directions in network science. In this paper, we discuss the history of multilayer networks (and related concepts) and review the exploding body of work on such networks. To unify the disparate terminology in the large body of recent work, we discuss a general framework for multilayer networks, construct a dictionary of terminology to relate the numerous existing concepts to each other, and provide a thorough discussion that compares, contrasts, and translates between related notions such as multilayer networks, multiplex networks, interdependent networks, networks of networks, and many others. We also survey and discuss existing data sets that can be represented as multilayer networks. We review attempts to generalize single-layer-network diagnostics to multilayer networks. We also discuss the rapidly expanding research on multilayer-network models and notions like community structure, connected components, tensor decompositions, and various types of dynamical processes on multilayer networks. We conclude with a summary and an outlook.Comment: Working paper; 59 pages, 8 figure

Percolation sur graphes aléatoires - modélisation et description analytique -

Tableau d’honneur de la Faculté des études supérieures et postdoctorales, 2013-2014.Les graphes sont des objets mathématiques abstraits utilisés pour modéliser les interactions entre les éléments constitutifs des systèmes complexes. Cette utilisation est motivée par le fait qu’il existe un lien fondamental entre la structure de ces interactions et les propriétés macroscopiques de ces systèmes. La théorie de la percolation offre un paradigme de choix pour analyser la structure de ces graphes, et ainsi mieux comprendre les conditions dans lesquelles ces propriétés émergent. Les interactions dans une grande variété de systèmes complexes partagent plusieurs propriétés structurelles universelles, et leur incorporation dans un cadre théorique unique demeure l’un des principaux défis de l’étude des systèmes complexes. Exploitant une approche multitype, une idée toute simple mais étonnamment puissante, nous avons unifié l’ensemble des modèles de percolation sur graphes aléatoires connus en un même cadre théorique, ce qui en fait le plus général et le plus réaliste proposé à ce jour. Bien plus qu’une simple compilation, le formalisme que nous proposons augmente significativement la complexité des structures pouvant être reproduites et, de ce fait, ouvre la voie à plusieurs nouvelles avenues de recherche. Nous illustrons cette assertion notamment en utilisant notre modèle pour valider et formaliser certaines intuitions inspirées de résultats empiriques. Dans un premier temps, nous étudions comment la structure en réseau de certains systèmes complexes (ex. réseau de distribution électrique, réseau social) facilite leur surveillance, et par conséquent leur éventuel contrôle. Dans un second temps, nous explorons la possibilité d’utiliser la décomposition en couches “k-core” en tant que structure effective des graphes extraits des systèmes complexes réels. Enfin, nous utilisons notre modèle pour identifier les conditions pour lesquelles une nouvelle stratégie d’immunisation contre des maladies infectieuses est la stratégie optimale.Graphs are abstract mathematical objects used to model the interactions between the elements of complex systems. Their use is motivated by the fact that there exists a fundamental relationship between the structure of these interactions and the macroscopic properties of these systems. The structure of these graphs is analyzed within the paradigm of percolation theory whose tools and concepts contribute to a better understanding of the conditions for which these emergent properties appear. The underlying interactions of a wide variety of complex systems share many universal structural properties, and including these properties in a unified theoretical framework is one of the main challenges of the science of complex systems. Capitalizing on a multitype approach, a simple yet powerful idea, we have unified the models of percolation on random graphs published to this day in a single framework, hence yielding the most general and realistic framework to date. More than a mere compilation, this framework significantly increases the structural complexity of the graphs that can now be mathematically handled, and, as such, opens the way to many new research opportunities. We illustrate this assertion by using our framework to validate hypotheses hinted at by empirical results. First, we investigate how the network structure of some complex systems (e.g., power grids, social networks) enhances our ability to monitor them, and ultimately to control them. Second, we test the hypothesis that the “k-core” decomposition can act as an effective structure of graphs extracted from real complex systems. Third, we use our framework to identify the conditions for which a new immunization strategy against infectious diseases is optimal

Interdependency and vulnerability of multipartite networks under target node attacks

Complex networks in reality may suffer from target attacks which can trigger the breakdown of the entire network. It is therefore pivotal to evaluate the extent to which a network could withstand perturbations. The research on network robustness has proven as a potent instrument towards that purpose. The last two decades have witnessed the enthusiasm on the studies of network robustness. However, existing studies on network robustness mainly focus on multilayer networks while little attention is paid to multipartite networks which are an indispensable part of complex networks. In this study, we investigate the robustness of multipartite networks under intentional node attacks. We develop two network models based on the largest connected component theory to depict the cascading failures on multipartite networks under target attacks. We then investigate the robustness of computer-generated multipartite networks with respect to eight node centrality metrics. We discover that the robustness of multipartite networks could display either discontinuous or continuous phase transitions. Interestingly, we discover that larger number of partite sets of a multipartite network could increase its robustness which is opposite to the phenomenon observed on multilayer networks. Our findings shed new lights on the robust structure design of complex systems. We finally present useful discussions on the applications of existing percolation theories that are well studied for network robustness analysis to multipartite networks. We show that existing percolation theories are not amenable to multipartite networks. Percolation on multipartite networks still deserves in-depth efforts.Published versio

A COMPARISON BETWEEN MOTIVATIONS AND PERSONALITY TRAITS IN RELIGIOUS TOURISTS AND CRUISE SHIP TOURISTS

The purpose of this paper is to analyze the motivations and the personality traits that characterize tourists who choose religious travels versus cruises. Participating in the research were 683 Italian tourists (345 males and 338 females, age range 18–63 years); 483 who went to a pilgrimage travel and 200 who chose a cruise ship in the Mediterranean Sea. Both groups of tourists completed the Travel Motivation Scale and the Big Five Questionnaire. Results show that different motivations and personality traits characterize the different types of tourists and, further, that motivations for traveling are predicted by specific —some similar, other divergent— personality trait

Do business schools encourage entrepreneurship?

Entrepreneurship education has grown substantially over the past 25 years as governments, students, parents and alumni push for the inclusion of the subject area into mainstream university education. To date entrepreneurship programs have been housed for the most part in schools of business or, more specifically, in the functional area of management education. However questions are starting to arise whether or not traditional business schools that rely on lecture/discussion/case method of learning are actually encouraging students to consider entrepreneurship as a career option. This paper reports on the entrepreneurial intent of 120 fourth year business students and finds that business students view their education as a positive influence on entrepreneurial intentions, research that contradicts much of the current theory on the subject

Knowledge applicability versus knowledge application: a way to visualize the relevance of management education to the real world

A framework is described, based on three levels of management knowledge and its applicability versus three stages of knowledge application to some real-world situation during classroom learning. Nine teaching and learning Types are characterized and described

A partnership university: Cape Breton’s University College

The economy of Cape Breton Island has undergone a massive restructuring from heavy industry to service and knowledge based companies. In the sixties and early seventies, while steel and coal were in rapid decline, the various levels of government and the community at large had to deal with the economic transformation without the benefit of a local, post secondary institution. The University College of Cape Breton (UCCB) was born following decades of community activism and immediately was seen as a keystone to the “new economy” of Cape Breton. The paper draws upon the literature of “partnership universities”, explores their role in economic restructuring and develops the case of UCCB as a partnership university. A time line is developed which illustrates the investment in research centers and industry specific programming at UCCB, particular to the support of information technology and a nascent technology cluster