259 research outputs found

    Seed selection for information cascade in multilayer networks

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    Information spreading is an interesting field in the domain of online social media. In this work, we are investigating how well different seed selection strategies affect the spreading processes simulated using independent cascade model on eighteen multilayer social networks. Fifteen networks are built based on the user interaction data extracted from Facebook public pages and tree of them are multilayer networks downloaded from public repository (two of them being Twitter networks). The results indicate that various state of the art seed selection strategies for single-layer networks like K-Shell or VoteRank do not perform so well on multilayer networks and are outperformed by Degree Centrality

    Distance-generalized Core Decomposition

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    The kk-core of a graph is defined as the maximal subgraph in which every vertex is connected to at least kk other vertices within that subgraph. In this work we introduce a distance-based generalization of the notion of kk-core, which we refer to as the (k,h)(k,h)-core, i.e., the maximal subgraph in which every vertex has at least kk other vertices at distance h\leq h within that subgraph. We study the properties of the (k,h)(k,h)-core showing that it preserves many of the nice features of the classic core decomposition (e.g., its connection with the notion of distance-generalized chromatic number) and it preserves its usefulness to speed-up or approximate distance-generalized notions of dense structures, such as hh-club. Computing the distance-generalized core decomposition over large networks is intrinsically complex. However, by exploiting clever upper and lower bounds we can partition the computation in a set of totally independent subcomputations, opening the door to top-down exploration and to multithreading, and thus achieving an efficient algorithm

    Singularities in ternary mixtures of k-core percolation

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    Heterogeneous k-core percolation is an extension of a percolation model which has interesting applications to the resilience of networks under random damage. In this model, the notion of node robustness is local, instead of global as in uniform k-core percolation. One of the advantages of k-core percolation models is the validity of an analytical mathematical framework for a large class of network topologies. We study ternary mixtures of node types in random networks and show the presence of a new type of critical phenomenon. This scenario may have useful applications in the stability of large scale infrastructures and the description of glass-forming systems.Comment: To appear in Complex Networks, Studies in Computational Intelligence, Proceedings of CompleNet 201

    The evolution of interdisciplinarity in physics research

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    Science, being a social enterprise, is subject to fragmentation into groups that focus on specialized areas or topics. Often new advances occur through cross-fertilization of ideas between sub-fields that otherwise have little overlap as they study dissimilar phenomena using different techniques. Thus to explore the nature and dynamics of scientific progress one needs to consider the large-scale organization and interactions between different subject areas. Here, we study the relationships between the sub-fields of Physics using the Physics and Astronomy Classification Scheme (PACS) codes employed for self-categorization of articles published over the past 25 years (1985-2009). We observe a clear trend towards increasing interactions between the different sub-fields. The network of sub-fields also exhibits core-periphery organization, the nucleus being dominated by Condensed Matter and General Physics. However, over time Interdisciplinary Physics is steadily increasing its share in the network core, reflecting a shift in the overall trend of Physics research.Comment: Published version, 10 pages, 8 figures + Supplementary Informatio

    СУЧАСНІ МЕТОДИ ФІЗИЧНОЇ РЕАБІЛІТАЦІЇ ХВОРИХ ПІСЛЯ АРТРОСКОПІЧНОЇ РЕКОНСТРУКЦІЇ ПЕРЕДНЬОЇ ХРЕСТОПОДІБНОЇ ЗВ’ЯЗКИ КОЛІННОГО СУГЛОБА

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    The article represents basic principles of application of methods of rehabilitation treatment in patients with the damage of the anterior cruciate ligament of the knee-joint. The deep analysis of scientific literary sources is conducted in relation to the disease course. Considerable attention is paid to the methodology of physical rehabilitation in pre- and postoperative periods.У статті висвітлено основні принципи застосування методів реабілітаційного лікування хворих з ушкоджен­ням хрестоподібної зв’язки колінного суглоба. Проведено поглиблений аналіз наукових літературних джерел стосовно перебігу цього захворювання. Значну увагу приділено методології проведення фізичної реабілітації доопераційного та післяопераційного періодів

    ПРИНЦИПИ ФІЗИЧНОЇ РЕАБІЛІТАЦІЇ ХВОРИХ іЗ ТРАВМОЮ КОЛІННОГО СУГЛОБА ПІСЛЯ проведення АРТРОСКОПІЧНОГО ОПЕРАційНОГО ВТРУЧАННЯ.

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    The article describes main principles of physical rehabilitation methods for patients with traumatic injury of the knee joint after arthroscopic surgery. Considerable attention is paid to the definition of the program of physical rehabilitation, which is aimed to reduce postoperative complications and restore functional capacity of the injured joint.У статті висвітлено основні принципи застосування методів фізичної реабілітації хворих із травматичним ушкодженням колінного суглоба після проведення артроскопічного втручання. Значну увагу приділено визначенню програми фізичної реабілітації, яка спрямована на зниження післяопераційних ускладнень та відновлення функціональної здатності ушкодженого суглоба

    Hyperbolic Geometry of Complex Networks

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    We develop a geometric framework to study the structure and function of complex networks. We assume that hyperbolic geometry underlies these networks, and we show that with this assumption, heterogeneous degree distributions and strong clustering in complex networks emerge naturally as simple reflections of the negative curvature and metric property of the underlying hyperbolic geometry. Conversely, we show that if a network has some metric structure, and if the network degree distribution is heterogeneous, then the network has an effective hyperbolic geometry underneath. We then establish a mapping between our geometric framework and statistical mechanics of complex networks. This mapping interprets edges in a network as non-interacting fermions whose energies are hyperbolic distances between nodes, while the auxiliary fields coupled to edges are linear functions of these energies or distances. The geometric network ensemble subsumes the standard configuration model and classical random graphs as two limiting cases with degenerate geometric structures. Finally, we show that targeted transport processes without global topology knowledge, made possible by our geometric framework, are maximally efficient, according to all efficiency measures, in networks with strongest heterogeneity and clustering, and that this efficiency is remarkably robust with respect to even catastrophic disturbances and damages to the network structure

    Worldwide spreading of economic crisis

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    We model the spreading of a crisis by constructing a global economic network and applying the Susceptible-Infected-Recovered (SIR) epidemic model with a variable probability of infection. The probability of infection depends on the strength of economic relations between the pair of countries, and the strength of the target country. It is expected that a crisis which originates in a large country, such as the USA, has the potential to spread globally, like the recent crisis. Surprisingly we show that also countries with much lower GDP, such as Belgium, are able to initiate a global crisis. Using the {\it k}-shell decomposition method to quantify the spreading power (of a node), we obtain a measure of ``centrality'' as a spreader of each country in the economic network. We thus rank the different countries according to the shell they belong to, and find the 12 most central countries. These countries are the most likely to spread a crisis globally. Of these 12 only six are large economies, while the other six are medium/small ones, a result that could not have been otherwise anticipated. Furthermore, we use our model to predict the crisis spreading potential of countries belonging to different shells according to the crisis magnitude.Comment: 13 pages, 4 figures and Supplementary Materia
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