951 resultados para Complex networks. Magnetic system. Metropolis
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Differently from theoretical scale-free networks, most real networks present multi-scale behavior, with nodes structured in different types of functional groups and communities. While the majority of approaches for classification of nodes in a complex network has relied on local measurements of the topology/connectivity around each node, valuable information about node functionality can be obtained by concentric (or hierarchical) measurements. This paper extends previous methodologies based on concentric measurements, by studying the possibility of using agglomerative clustering methods, in order to obtain a set of functional groups of nodes, considering particular institutional collaboration network nodes, including various known communities (departments of the University of Sao Paulo). Among the interesting obtained findings, we emphasize the scale-free nature of the network obtained, as well as identification of different patterns of authorship emerging from different areas (e.g. human and exact sciences). Another interesting result concerns the relatively uniform distribution of hubs along concentric levels, contrariwise to the non-uniform pattern found in theoretical scale-free networks such as the BA model. (C) 2008 Elsevier B.V. All rights reserved.
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In this work, we propose a hierarchical extension of the polygonality index as the means to characterize geographical planar networks. By considering successive neighborhoods around each node, it is possible to obtain more complete information about the spatial order of the network at progressive spatial scales. The potential of the methodology is illustrated with respect to synthetic and real geographical networks.
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In the present work, the effects of spatial constraints on the efficiency of task execution in systems underlain by geographical complex networks are investigated, where the probability of connection decreases with the distance between the nodes. The investigation considers several configurations of the parameters defining the network connectivity, and the Barabasi-Albert network model is also considered for comparisons. The results show that the effect of connectivity is significant only for shorter tasks, the locality of connection simplied by the spatial constraints reduces efficiency, and the addition of edges can improve the efficiency of the execution, although with increasing locality of the connections the improvement is small.
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This paper applies the concepts and methods of complex networks to the development of models and simulations of master-slave distributed real-time systems by introducing an upper bound in the allowable delivery time of the packets with computation results. Two representative interconnection models are taken into account: Uniformly random and scale free (Barabasi-Albert), including the presence of background traffic of packets. The obtained results include the identification of the uniformly random interconnectivity scheme as being largely more efficient than the scale-free counterpart. Also, increased latency tolerance of the application provides no help under congestion.
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The relationship between the structure and function of biological networks constitutes a fundamental issue in systems biology. Particularly, the structure of protein-protein interaction networks is related to important biological functions. In this work, we investigated how such a resilience is determined by the large scale features of the respective networks. Four species are taken into account, namely yeast Saccharomyces cerevisiae, worm Caenorhabditis elegans, fly Drosophila melanogaster and Homo sapiens. We adopted two entropy-related measurements (degree entropy and dynamic entropy) in order to quantify the overall degree of robustness of these networks. We verified that while they exhibit similar structural variations under random node removal, they differ significantly when subjected to intentional attacks (hub removal). As a matter of fact, more complex species tended to exhibit more robust networks. More specifically, we quantified how six important measurements of the networks topology (namely clustering coefficient, average degree of neighbors, average shortest path length, diameter, assortativity coefficient, and slope of the power law degree distribution) correlated with the two entropy measurements. Our results revealed that the fraction of hubs and the average neighbor degree contribute significantly for the resilience of networks. In addition, the topological analysis of the removed hubs indicated that the presence of alternative paths between the proteins connected to hubs tend to reinforce resilience. The performed analysis helps to understand how resilience is underlain in networks and can be applied to the development of protein network models.
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Drawing upon Brazilian experience, this research explores some of the key issues to be addressed in using e-government technical cooperation designed to enhance service provision of Patent Offices in developing countries. While the development of software applications is often seen merely as a technical engineering exercise, localization and adaptation are context bounded matters that are characterized by many entanglements of human and non-humans. In this work, technical, legal and policy implications of technical cooperation are also discussed in a complex and dynamic implementation environment characterized by the influence of powerful hidden agendas associated with the arena of intellectual property (IP), which are shaped by recent technological, economic and social developments in our current knowledge-based economy. This research employs two different theoretical lenses to examine the same case, which consists of transfer of a Patent Management System (PMS) from the European Patent Office (EPO) to the Brazilian Patent Office that is locally named ‘Instituto Nacional da Propriedade Industrial’ (INPI). Fundamentally, we have opted for a multi-paper thesis comprising an introduction, three scientific articles and a concluding chapter that discusses and compares the insights obtained from each article. The first article is dedicated to present an extensive literature review on e-government and technology transfer. This review allowed the proposition on an integrative meta-model of e-government technology transfer, which is named E-government Transfer Model (ETM). Subsequently, in the second article, we present Actor-Network Theory (ANT) as a framework for understanding the processes of transferring e-government technologies from Patent Offices in developed countries to Patent Offices in developing countries. Overall, ANT is seen as having a potentially wide area of application and being a promising theoretical vehicle in IS research to carry out a social analysis of messy and heterogeneous processes that drive technical change. Drawing particularly on the works of Bruno Latour, Michel Callon and John Law, this work applies this theory to a longitudinal study of the management information systems supporting the Brazilian Patent Office restructuration plan that involved the implementation of a European Patent Management System in Brazil. Based upon the ANT elements, we follow the actors to identify and understand patterns of group formation associated with the technical cooperation between the Brazilian Patent Office (INPI) and the European Patent Office (EPO). Therefore, this research explores the intricate relationships and interactions between human and non-human actors in their attempts to construct various network alliances, thereby demonstrating that technologies embodies compromise. Finally, the third article applies ETM model as a heuristic frame to examine the same case previously studied from an ANT perspective. We have found evidence that ETM has strong heuristic qualities that can guide practitioners who are engaged in the transfer of e-government systems from developed to developing countries. The successful implementation of e-government projects in developing countries is important to stimulate economic growth and, as a result, we need to understand the processes through which such projects are being implemented and succeed. Here, we attempt to improve understanding on the development and stabilization of a complex social-technical system in the arena of intellectual property. Our preliminary findings suggest that e-government technology transfer is an inherently political process and that successful outcomes require continuous incremental actions and improvisations to address the ongoing issues as they emerge.
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Ropivacaine (RVC) is an enantiomerically pure local anesthetic (LA) largely used in surgical procedures, which presents physico-chemical and therapeutic properties similar to those of bupivacaine (BPV), but associated to less systemic toxicity This study focuses on the development and pharmacological evaluation of a RVC in 2-hydroxypropyl-beta-cyclodextrin (HP-P-CD) inclusion complex. Phase-solubility diagrams allowed the determination of the association constant between RVC and HP-beta-CD (9.46 M-1) and showed an increase on RVC solubility upon complexation. Release kinetics revealed a decrease on RVC release rate and reduced hemolytic effects after complexation. (onset at 3.7 mM and 11.2 mM for RVC and RVCHP-beta-CD, respectively) were observed. Differential scanning calorimetry (DSC), scanning electron microscopy (SEM) and X-ray analysis (X-ray) showed the formation and the morphology of the complex. Nuclear magnetic resonance (NMR) and job-plot experiments afforded data regarding inclusion complex stoichiometry (1:1) and topology. Sciatic nerve blockade studies showed that RVCHP-beta-CD was able to reduce the latency without increasing the duration of motor blockade, but prolonging the duration and intensity of the sensory blockade (p < 0.001) induced by the LA in mice. These results identify the RVCHP-beta-CD complex as an effective novel approach to enhance the pharmacological effects of RVC, presenting it as a promising new anesthetic formulation. (c) 2007 Elsevier B.V All rights reserved.
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In this work we study a connection between a non-Gaussian statistics, the Kaniadakis
statistics, and Complex Networks. We show that the degree distribution P(k)of
a scale free-network, can be calculated using a maximization of information entropy in
the context of non-gaussian statistics. As an example, a numerical analysis based on the
preferential attachment growth model is discussed, as well as a numerical behavior of
the Kaniadakis and Tsallis degree distribution is compared. We also analyze the diffusive
epidemic process (DEP) on a regular lattice one-dimensional. The model is composed
of A (healthy) and B (sick) species that independently diffusive on lattice with diffusion
rates DA and DB for which the probabilistic dynamical rule A + B → 2B and B → A. This
model belongs to the category of non-equilibrium systems with an absorbing state and a
phase transition between active an inactive states. We investigate the critical behavior of
the DEP using an auto-adaptive algorithm to find critical points: the method of automatic
searching for critical points (MASCP). We compare our results with the literature and we
find that the MASCP successfully finds the critical exponents 1/ѵ and 1/zѵ in all the cases
DA =DB, DA
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In this thesis we investigate physical problems which present a high degree of complexity using tools and models of Statistical Mechanics. We give a special attention to systems with long-range interactions, such as one-dimensional long-range bondpercolation, complex networks without metric and vehicular traffic. The flux in linear chain (percolation) with bond between first neighbor only happens if pc = 1, but when we consider long-range interactions , the situation is completely different, i.e., the transitions between the percolating phase and non-percolating phase happens for pc < 1. This kind of transition happens even when the system is diluted ( dilution of sites ). Some of these effects are investigated in this work, for example, the extensivity of the system, the relation between critical properties and the dilution, etc. In particular we show that the dilution does not change the universality of the system. In another work, we analyze the implications of using a power law quality distribution for vertices in the growth dynamics of a network studied by Bianconi and Barabási. It incorporates in the preferential attachment the different ability (fitness) of the nodes to compete for links. Finally, we study the vehicular traffic on road networks when it is submitted to an increasing flux of cars. In this way, we develop two models which enable the analysis of the total flux on each road as well as the flux leaving the system and the behavior of the total number of congested roads
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Following the study of Andrade et al. (2009) on regular square lattices, here we investigate the problem of optimal path cracks (OPC) in Complex Networks. In this problem we associate to each site a determined energy. The optimum path is defined as the one among all possible paths that crosses the system which has the minimum cost, namely the sum of the energies along the path. Once the optimum path is determined, at each step, one blocks its site with highest energy, and then a new optimal path is calculated. This procedure is repeated until there is a set of blocked sites forming a macroscopic fracture which connects the opposite sides of the system. The method is applied to a lattice of size L and the density of removed sites is computed. As observed in the work by Andrade et al. (2009), the fractured system studied here also presents different behaviors depending on the level of disorder, namely weak, moderated and strong disorder intensities. In the regime of weak and moderated disorder, while the density of removed sites in the system does not depend of the size L in the case of regular lattices, in the regime of high disorder the density becomes substantially dependent on L. We did the same type of study for Complex Networks. In this case, each new site is connected with m previous ones. As in the previous work, we observe that the density of removed sites presents a similar behavior. Moreover, a new result is obtained, i.e., we analyze the dependency of the disorder with the attachment parameter m
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Currently the interest in large-scale systems with a high degree of complexity has been much discussed in the scientific community in various areas of knowledge. As an example, the Internet, protein interaction, collaboration of film actors, among others. To better understand the behavior of interconnected systems, several models in the area of complex networks have been proposed. Barabási and Albert proposed a model in which the connection between the constituents of the system could dynamically and which favors older sites, reproducing a characteristic behavior in some real systems: connectivity distribution of scale invariant. However, this model neglects two factors, among others, observed in real systems: homophily and metrics. Given the importance of these two terms in the global behavior of networks, we propose in this dissertation study a dynamic model of preferential binding to three essential factors that are responsible for competition for links: (i) connectivity (the more connected sites are privileged in the choice of links) (ii) homophily (similar connections between sites are more attractive), (iii) metric (the link is favored by the proximity of the sites). Within this proposal, we analyze the behavior of the distribution of connectivity and dynamic evolution of the network are affected by the metric by A parameter that controls the importance of distance in the preferential binding) and homophily by (characteristic intrinsic site). We realized that the increased importance as the distance in the preferred connection, the connections between sites and become local connectivity distribution is characterized by a typical range. In parallel, we adjust the curves of connectivity distribution, for different values of A, the equation P(k) = P0e
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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The magnetic and structural properties of sol-gel derived organic/inorganic nanocomposites doped with Fe(II), Fe(III), Nd(III) and Eu (III) ions are discussed. These hybrids consist of poly(oxyethylene)-based chains grafted onto siloxane nanodomains by urea cross-linkages. Small angle X-ray scattering data show the presence of spatial correlations of siloxane domains embedded in the polymer matrix. The magnetic properties of rare-earth doped samples are determined by single ion crystal-field-splitted levels (Eu3+ J=0; Nd3+ J=9/2) and the small thermal irreversibility is mainly associated to structural effects. Fe2+ -doped samples behave as simple paramagnet with residual antiferromagnetic interactions. Fe3+-doped hybrids are much more complex, with magnetic hysterisis, exchange anisotropy and thermal irreversibility at low temperatures. Néel temperatures increase up to 14K for the highest (∼5.5%) Fe3+ mass concentration.
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Regulatory authorities in many countries, in order to maintain an acceptable balance between appropriate customer service qualities and costs, are introducing a performance-based regulation. These regulations impose penalties, and in some cases rewards, which introduce a component of financial risk to an electric power utility due to the uncertainty associated with preserving a specific level of system reliability. In Brazil, for instance, one of the reliability indices receiving special attention by the utilities is the Maximum Continuous Interruption Duration per customer (MCID). This paper describes a chronological Monte Carlo simulation approach to evaluate probability distributions of reliability indices, including the MCID, and the corresponding penalties. In order to get the desired efficiency, modern computational techniques are used for modeling (UML -Unified Modeling Language) as well as for programming (Object- Oriented Programming). Case studies on a simple distribution network and on real Brazilian distribution systems are presented and discussed. © Copyright KTH 2006.