Conexão entre as redes complexas e estatística de Kaniadakis e busca eficiente das propriedades críticas do processo epidêmico difusivo 1D

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 DB. The simulations show that the DEP has the same critical exponents as are expected from field-theoretical arguments. Moreover, we find that, contrary to a renormalization group prediction, the system does not show a discontinuous phase transition in the regime o DA >DB.

Análises estatísticas em redes complexas: propriedades topológicas, críticas e dinâmicas

In this thesis, we address two issues of broad conceptual and practical relevance in the study of complex networks. The first is associated with the topological characterization of networks while the second relates to dynamical processes that occur on top of them. Regarding the first line of study, we initially designed a model for networks growth where preferential attachment includes: (i) connectivity and (ii) homophily (links between sites with similar characteristics are more likely). From this, we observe that the competition between these two aspects leads to a heterogeneous pattern of connections with the topological properties of the network showing quite interesting results. In particular, we emphasize that there is a region where the characteristics of sites play an important role not only for the rate at which they get links, but also for the number of connections which occur between sites with similar and dissimilar characteristics. Finally, we investigate the spread of epidemics on the network topology developed, whereas its dissemination follows the rules of the contact process. Using Monte Carlo simulations, we show that the competition between states (infected/healthy) sites, induces a transition between an active phase (presence of sick) and an inactive (no sick). In this context, we estimate the critical point of the transition phase through the cumulant Binder and ratio between moments of the order parameter. Then, using finite size scaling analysis, we determine the critical exponents associated with this transition

The aggregation process in tetraethoxysilane-derived sonogels as an analogy to the critical phenomenon

The structural evolution in silica sols prepared from tetraethoxysilane (TEOS) sonohydrolysis was studied 'in situ' using small-angle x-ray scattering (SAXS). The structure of the gelling system can be reasonably well described by a correlation function given by gamma(r) similar to (1/R(2))(1/r) exp(- r/xi), where xi is the structure correlation length and R is a chain persistence length, as an analogy to the Ornstein-Zernike theory in describing critical phenomenon. This approach is also expected for the scattering from some linear and branched molecules as polydisperse coils of linear chains and random f-functional branched polycondensates. The characteristic length. grows following an approximate power law with time t as xi similar to t(1) (with the exponent quite close to 1) while R remains undetermined but with a constant value, except at the beginning of the process in which the growth of. is slower and R increases by only about 15% with respect to the value of the initial sol. The structural evolution with time is compatible with an aggregation process by a phase separation by coarsening. The mechanism of growth seems to be faster than those typically observed for pure diffusion controlled cluster-cluster aggregation. This suggests that physical forces (hydrothermal forces) could be actuating together with diffusion in the gelling process of this system. The data apparently do not support a spinodal decomposition mechanism, at least when starting from the initial stable acid sol studied here.

White matter abnormalities associated with Alzheimer's disease and mild cognitive impairment: A critical review of MRI studies

In this article, the authors aim to present a critical review of recent MRI studies addressing white matter (WM) abnormalities in Alzheimer's disease (AD) and mild cognitive impairment (MCI), by searching PubMed and reviewing MRI studies evaluating subjects with AD or MCI using WM volumetric methods, diffusion tensor imaging and assessment of WM hyperintensities. Studies have found that, compared with healthy controls, AD and MCI samples display WM volumetric reductions and diffusion tensor imaging findings suggestive of reduced WM integrity. These changes affect complex networks relevant to episodic memory and other cognitive processes, including fiber connections that directly link medial temporal structures and the corpus callosum. Abnormalities in cortico-cortical and cortico-subcortical WM interconnections are associated with an increased risk of progression from MCI to dementia. It can be concluded that WM abnormalities are detectable in early stages of AD and MCI. Degeneration of WM networks causes disconnection among neural cells and the degree of such changes is related to cognitive decline. © 2013 2013 Expert Reviews Ltd.

Disentangling social networks from spatiotemporal dynamics: the temporal structure of a dolphin society

Social networks are static illustrations of dynamic societies, within which social interactions are constantly changing. Fundamental sources of variation include ranging behaviour and temporal demographic changes. Spatiotemporal dynamics can favour or limit opportunities for individuals to interact, and then a network may not essentially represent social processes. We examined whether a social network can embed such nonsocial effects in its topology, whereby emerging modules depict spatially or temporally segregated individuals. To this end, we applied a combination of spatial, temporal and demographic analyses to a long-term study of the association patterns of Guiana dolphins, Sotalia guianensis. We found that association patterns are organized into a modular social network. Space use was unlikely to reflect these modules, since dolphins' ranging behaviour clearly overlapped. However, a temporal demographic turnover, caused by the exit/entrance of individuals (most likely emigration/immigration), defined three modules of associations occurring at different times. Although this factor could mask real social processes, we identified the temporal scale that allowed us to account for these demographic effects. By looking within this turnover period (32 months), we assessed fission-fusion dynamics of the poorly known social organization of Guiana dolphins. We highlight that spatiotemporal dynamics can strongly influence the structure of social networks. Our findings show that hypothetical social units can emerge due to the temporal opportunities for individuals to interact. Therefore, a thorough search for a satisfactory spatiotemporal scale that removes such nonsocial noise is critical when analysing a social system. (C) 2012 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

Breaking down complex saproxylic communities: understanding sub-networks structure and implications to network robustness

Saproxylic insect communities inhabiting tree hollow microhabitats correspond with large food webs which simultaneously are constituted by multiple types of plant-animal and animal-animal interactions, according to the use of trophic resources (wood- and insect-dependent sub-networks), or to trophic habits or interaction types (xylophagous, saprophagous, xylomycetophagous, predators and commensals). We quantitatively assessed which properties of specialised networks were present in a complex networks involving different interacting types such as saproxylic community, and how they can be organised in trophic food webs. The architecture, interacting patterns and food web composition were evaluated along sub-networks, analysing their implications to network robustness from random and directed extinction simulations. A structure of large and cohesive modules with weakly connected nodes was observed throughout saproxylic sub-networks, composing the main food webs constituting this community. Insect-dependent sub-networks were more modular than wood-dependent sub-networks. Wood-dependent sub-networks presented higher species degree, connectance, links, linkage density, interaction strength, and were less specialised and more aggregated than insect-dependent sub-networks. These attributes defined high network robustness in wood-dependent sub-networks. Finally, our results emphasise the relevance of modularity, differences among interacting types and interrelations among them in modelling the structure of saproxylic communities and in determining their stability.

Critical behavior of one-particle spectral weights in the transverse Ising model

We investigate the critical behavior of the spectral weight of a single quasiparticle, one of the key observables in experiment, for the particular case of the transverse Ising model. Series expansions are calculated for the linear chain and the square and simple cubic lattices. For the chain model, a conjectured exact result is discovered. For the square and simple cubic lattices, series analyses are used to estimate the critical exponents. The results agree with the general predictions of Sachdev [Quantum Phase Transitions (Cambridge University Press, Cambridge, England, 1999)].

The value of indirect ties in citation networks:SNA analysis with OWA operator weights

This paper seeks to advance the theory and practice of the dynamics of complex networks in relation to direct and indirect citations. It applies social network analysis (SNA) and the ordered weighted averaging operator (OWA) to study a patent citations network. So far the SNA studies investigating long chains of patents citations have rarely been undertaken and the importance of a node in a network has been associated mostly with its number of direct ties. In this research OWA is used to analyse complex networks, assess the role of indirect ties, and provide guidance to reduce complexity for decision makers and analysts. An empirical example of a set of European patents published in 2000 in the renewable energy industry is provided to show the usefulness of the proposed approach for the preference ranking of patent citations.

Rethinking Care Through Social Reproduction: Articulating Circuits of Migration

Care has come to dominate much feminist research on globalized migrations and the transfer of labor from the South to the North, while the older concept of reproduction had been pushed into the background but is now becoming the subject of debates on the commodification of care in the household and changes in welfare state policies. This article argues that we could achieve a better understanding of the different modalities and trajectories of care in the reproduction of individuals, families, and communities, both of migrant and nonmigrant populations by articulating the diverse circuits of migration, in particular that of labor and the family. In doing this, I go back to the earlier North American writing on racialized minorities and migrants and stratified social reproduction. I also explore insights from current Asian studies of gendered circuits of migration connecting labor and marriage migrations as well as the notion of global householding that highlights the gender politics of social reproduction operating within and beyond households in institutional and welfare architectures. In contrast to Asia, there has relatively been little exploration in European studies of the articulation of labor and family migrations through the lens of social reproduction. However, connecting the different types of migration enables us to achieve a more complex understanding of care trajectories and their contribution to social reproduction.

(Quantum-) critical dynamics of magnetoelectric materials

In this thesis the critical dynamics of several magnetoelectric compounds at their phase transition were examined. Mostly measurements of the dielectric properties in the frequency range of below 1 Hz up to 5 GHz were employed to evaluate the critical exponents for both magnetic field and temperature-dependent measurements. Most of the materials that are part of this work show anomalous behavior, especially at very low temperatures where quantum fluctuations are of the order of or even dominate those induced thermally. This anomalous behavior manifests in different forms. In Dy2Ti2O7 we demonstrate the existence of electric dipoles on magnetic monopoles. Here the dynamics at the critical endpoint located at 0.36K and in a magnetic field of 1T parallel to the [111] direction are of special interest. At this critical endpoint the expected critical slowing down of the dynamics could not only not be observed but instead the opposite, critical speeding-up by several orders of magnitude, could be demonstrated. Furthermore, we show that the phase diagram of Dy2Ti2O7 in this field direction can be reproduced solely from the dynamical properties, for example the resonance frequency of the observed relaxation that is connected to the monopole movement. Away from this point of the phase diagram the dynamics are slowing-down with reduction of temperature as one would expect. Additional measurements on Y2Ti2O7, a structurally identical but non-magnetic material, show only slowing down with reduction of temperature and no additional features. A possible explanation for the observed critical speeding-up is a coherent movement of magnetic monopoles close to the critical field that increases the resonance frequency by reducing the damping of the process. LiCuVO4 on the other hand behaves normally at its phase transition as long as the temperature is higher than 0.4 K. In this temperature regime the dynamics show critical slowing-down analogous to classical ferroelectric materials. This analogy extends also towards higher frequencies where the permittivity displays a ‘dispersion’ minimum that is temperature-dependent but of the order of 2 GHz. Below 0.4K the observed behavior changes drastically. Here we found no longer relaxational behavior but instead an excitation with very low energy. This low energy excitation was predicted by theory and is caused by nearly gapless soliton excitations within the 1D Cu2+ chains of LiCuVO4. Finally, in TbMnO3 the dynamics of the phase transition into the multiferroic phase was observed at roughly 27 K, a much higher temperature compared to the other materials. Here the expected critical slowing-down was observed, even though in low-frequency measurements this transition into the ferroelectric phase is overshadowed by the so-called c-axis relaxation. Therefore, only frequencies above 1MHz could be used to determine the critical exponents for both temperatureand magnetic-field-dependent measurements. This was done for both the peak frequency as well as the relaxation strength. In TbMnO3 an electromagnetic soft-mode with small optical weight causes the observed fluctuations, similar to the case of multiferroic MnWO4.

Data collapse, scaling functions, and analytical solutions of generalized growth models

We consider a nontrivial one-species population dynamics model with finite and infinite carrying capacities. Time-dependent intrinsic and extrinsic growth rates are considered in these models. Through the model per capita growth rate we obtain a heuristic general procedure to generate scaling functions to collapse data into a simple linear behavior even if an extrinsic growth rate is included. With this data collapse, all the models studied become independent from the parameters and initial condition. Analytical solutions are found when time-dependent coefficients are considered. These solutions allow us to perceive nontrivial transitions between species extinction and survival and to calculate the transition's critical exponents. Considering an extrinsic growth rate as a cancer treatment, we show that the relevant quantity depends not only on the intensity of the treatment, but also on when the cancerous cell growth is maximum.

The Missing Part of Seed Dispersal Networks: Structure and Robustness of Bat-Fruit Interactions

Mutualistic networks are crucial to the maintenance of ecosystem services. Unfortunately, what we know about seed dispersal networks is based only on bird-fruit interactions. Therefore, we aimed at filling part of this gap by investigating bat-fruit networks. It is known from population studies that: (i) some bat species depend more on fruits than others, and (ii) that some specialized frugivorous bats prefer particular plant genera. We tested whether those preferences affected the structure and robustness of the whole network and the functional roles of species. Nine bat-fruit datasets from the literature were analyzed and all networks showed lower complementary specialization (H(2)' = 0.3760.10, mean 6 SD) and similar nestedness (NODF = 0.5660.12) than pollination networks. All networks were modular (M=0.32 +/- 0.07), and had on average four cohesive subgroups (modules) of tightly connected bats and plants. The composition of those modules followed the genus-genus associations observed at population level (Artibeus-Ficus, Carollia-Piper, and Sturnira-Solanum), although a few of those plant genera were dispersed also by other bats. Bat-fruit networks showed high robustness to simulated cumulative removals of both bats (R = 0.55 +/- 0.10) and plants (R = 0.68 +/- 0.09). Primary frugivores interacted with a larger proportion of the plants available and also occupied more central positions; furthermore, their extinction caused larger changes in network structure. We conclude that bat-fruit networks are highly cohesive and robust mutualistic systems, in which redundancy is high within modules, although modules are complementary to each other. Dietary specialization seems to be an important structuring factor that affects the topology, the guild structure and functional roles in bat-fruit networks.

Generalized connectivity between any two nodes in a complex network

This article focuses on the identification of the number of paths with different lengths between pairs of nodes in complex networks and how these paths can be used for characterization of topological properties of theoretical and real-world complex networks. This analysis revealed that the number of paths can provide a better discrimination of network models than traditional network measurements. In addition, the analysis of real-world networks suggests that the long-range connectivity tends to be limited in these networks and may be strongly related to network growth and organization.

Deformed Gaussian-orthogonal-ensemble description of small-world networks

The study of spectral behavior of networks has gained enthusiasm over the last few years. In particular, random matrix theory (RMT) concepts have proven to be useful. In discussing transition from regular behavior to fully chaotic behavior it has been found that an extrapolation formula of the Brody type can be used. In the present paper we analyze the regular to chaotic behavior of small world (SW) networks using an extension of the Gaussian orthogonal ensemble. This RMT ensemble, coined the deformed Gaussian orthogonal ensemble (DGOE), supplies a natural foundation of the Brody formula. SW networks follow GOE statistics until a certain range of eigenvalue correlations depending upon the strength of random connections. We show that for these regimes of SW networks where spectral correlations do not follow GOE beyond a certain range, DGOE statistics models the correlations very well. The analysis performed in this paper proves the utility of the DGOE in network physics, as much as it has been useful in other physical systems.

Formation of atomic carbon chains from graphene nanoribbons

The formation of one-dimensional carbon chains from graphene nanoribbons is investigated using ab initio molecular dynamics. We show under what conditions it is possible to obtain a linear atomic chain via pulling of the graphene nanoribbons. The presence of dimers composed of two-coordinated carbon atoms at the edge of the ribbons is necessary for the formation of the linear chains, otherwise there is simply the full rupture of the structure. The presence of Stone-Wales defects close to these dimers may lead to the formation of longer chains. The local atomic configuration of the suspended atoms indicates the formation of single and triple bonds, which is a characteristic of polyynes.