Aninhamento em redes bipartidas

We present a nestedness index that measures the nestedness pattern of bipartite networks, a problem that arises in theoretical ecology. Our measure is derived using the sum of distances of the occupied elements in the adjacency matrix of the network. This index quantifies directly the deviation of a given matrix from the nested pattern. In the most simple case the distance of the matrix element ai,j is di,j = i+j, the Manhattan distance. A generic distance is obtained as di,j = (i¬ + j¬)1/¬. The nestedness índex is defined by = 1 − where is the temperature of the matrix. We construct the temperature index using two benchmarks: the distance of the complete nested matrix that corresponds to zero temperature and the distance of the average random matrix that is defined as temperature one. We discuss an important feature of the problem: matrix occupancy. We address this question using a metric index ¬ that adjusts for matrix occupancy

Versão breve da social rhythm metric: um instrumento para avaliar ritmo social de pacientes com acidente vascular cerebral

Stroke is a neurological disorder caused by restriction of blood flow to the brain, which generates directly a deficit of functionality that affects the quality of life of patients. The aim of this study was to establish a short version of the Social Rhythm Scale (SRM), to assess the social rhythm of stroke patients. The sample consisted of 84 patients, of both sexes, with injury time exceeding 6 months. For seven days, patients recorded the time held 17 activities of SRM. Data analysis was performed using a principal components factor analysis with varimax rotation of the full version of SRM in order to determine which activities could compose brief versions of SRM. We then carried out a comparison of hits, the ALI (Level Activity Index) and SRM, between versions, by Kruskal-Walls and the Mann-Whitney test. The Spearman correlation test was used to evaluate the correlation between the score of the full version of SRM with short versions. It was found that the activities of SRM were distributed in three versions: the first and second with 6 activities and third with 3 activities. Regarding hits, it was found that they ranged from 4.9 to 5.8 on the first version; 2.3 to 3.8 in version 2 and 2.8 to 6.2 in version 3, the first the only version that did not show low values. The analysis of ALI, in version 1, the median was 29, in version 2 was 14 and in version 3 was 18. Significant difference in the values of ALI between versions 1 and 2, between 2 and 3 and between versions 1 and 3. The highest median was found in the first version, formed by activities: out of bed, first contact, drink coffee, watch TV in the evening and go to bed. The lowest median was observed in the second version and this was not what had fewer activities, but which had social activities. The medians of the SRM version 1 was 6, version 2 was 4 and version 3 was 6. Significant difference in the values of SRM between versions 1 and 2 and between 2 and 3, but no significant difference between versions 1 and 3. Through analysis, we found a significant correlation only between the full version and the version 1 (R2 = 0.61) (p <0.05), no correlation was found with version 2 (R2 = 0.007) nor with version 3 (R2 = 0.002), this was finally a factor to consider version 1 as the short brazilian version of the Social Rhythm Metric for stroke patients

Generalizações do conceito de distância, i-distâncias, distâncias intervalares e topologia

In this dissertation we present some generalizations for the concept of distance by using more general value spaces, such as: fuzzy metrics, probabilistic metrics and generalized metrics. We show how such generalizations may be useful due to the possibility that the distance between two objects could carry more information about the objects than in the case where the distance is represented just by a real number. Also in this thesis we propose another generalization of distance which encompasses the notion of interval metric and generates a topology in a natural way. Several properties of this generalization are investigated, and its links with other existing generalizations

Contribuição ao estudo de redes complexas: modelo de afinidade com métrica

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