Suani Tavares Rubim de Pinho

Modelling the dynamics of dengue real epidemics

In this work, we use a mathematical model for dengue transmission with the aim of analysing and comparing two dengue epidemics that occurred in Salvador, Brazil, in 1995–1996 and 2002. Using real data, we obtain the force of infection, Λ, and the basic reproductive number, R0, for both epidemics. We also obtain the time evolution of the effective reproduction number, R(t), which results in a very suitable measure to compare the patterns of both epidemics. Based on the analysis of the behaviour of R0 and R(t) in relation to the adult mosquito control parameter of the model, we show that the control applied only to the adult stage of the mosquito population is not sufficient to stop dengue transmission, emphasizing the importance of applying the control to the aquatic phase of the mosquito.

A cellular automata model for avascular solid tumor growth under the effect of therapy

Tumor growth has long been a target of investigation within the context of mathematical and computer modeling. The objective of this study is to propose and analyze a two-dimensional stochastic cellular automata model to describe avascular solid tumor growth, taking into account both the competition between cancer cells and normal cells for nutrients and/or space and a time-dependent proliferation of cancer cells. Gompertzian growth, characteristic of some tumors, is described and some of the features of the time-spatial pattern of solid tumors, such as compact morphology with irregular borders, are captured. The parameter space is studied in order to analyze the occurrence of necrosis and the response to therapy. Our findings suggest that transitions exist between necrotic and non-necrotic phases (no-therapy cases), and between the states of cure and non-cure (therapy cases). To analyze cure, the control and order parameters are, respectively, the highest probability of cancer cell proliferation and the probability of the therapeutic effect on cancer cells. With respect to patterns, it is possible to observe the inner necrotic core and the effect of the therapy destroying the tumor from its outer borders inwards.

An Abelian model for rainfall

Statistical analyses of long-term records of daily rain suggest that rain phenomena might be a manifestation of self-organized criticality. In this work the essential mechanisms of rain phenomena, the growth of droplets inside a cloud and the subsequent rainfall, are described by an Abelian sandpile model of self-organized criticality. Several simulations support the existence of scale invariance. The introduction of variations of the basic model, to provide a better description of the phenomena, does not alter the critical behavior.

Some properties of deformed q-numbers

Nonextensive statistical mechanics has been a source of investigation in mathematical structures such as deformed algebraic structures. In this work, we present some consequences of q-operations on the construction of q-numbers for all numerical sets. Based on such a construction, we present a new product that distributes over the q-sum. Finally, we present different patterns of q-Pascals triangles, based on q-sum, whose elements are q-numbers.

Detecting Network Communities: An Application to Phylogenetic Analysis

This paper proposes a new method to identify communities in generally weighted complex networks and apply it to phylogenetic analysis. In this case, weights correspond to the similarity indexes among protein sequences, which can be used for network construction so that the network structure can be analyzed to recover phylogenetically useful information from its properties. The analyses discussed here are mainly based on the modular character of protein similarity networks, explored through the Newman-Girvan algorithm, with the help of the neighborhood matrix . The most relevant networks are found when the network topology changes abruptly revealing distinct modules related to the sets of organisms to which the proteins belong. Sound biological information can be retrieved by the computational routines used in the network approach, without using biological assumptions other than those incorporated by BLAST. Usually, all the main bacterial phyla and, in some cases, also some bacterial classes corresponded totally (100%) or to a great extent (>70%) to the modules. We checked for internal consistency in the obtained results, and we scored close to 84% of matches for community pertinence when comparisons between the results were performed. To illustrate how to use the network-based method, we employed data for enzymes involved in the chitin metabolic pathway that are present in more than 100 organisms from an original data set containing 1,695 organisms, downloaded from GenBank on May 19, 2007. A preliminary comparison between the outcomes of the network-based method and the results of methods based on Bayesian, distance, likelihood, and parsimony criteria suggests that the former is as reliable as these commonly used methods. We conclude that the network-based method can be used as a powerful tool for retrieving modularity information from weighted networks, which is useful for phylogenetic analysis.

Nondistributive algebraic structures derived from nonextensive statistical mechanics

We propose a two-parametric nondistributive algebraic structure that follows from (q,q′)-logarithm and (q,q′)-exponential functions. Properties of generalized (q,q′)-operators are analyzed. We also generalize the proposal into a multiparametric structure (generalization of logarithm and exponential functions and the corresponding algebraic operators). All n-parameter expressions recover (n−1)-generalization when the corresponding qn→1. Nonextensive statistical mechanics has been the source of successive generalizations of entropic forms and mathematical structures, in which this work is a consequence.

Comparative protein analysis of the chitin metabolic pathway in extant organisms: A complex network approach

Chitin is a structural endogenous carbohydrate, which is a major component of fungal cell walls and arthropod exoskeletons. A renewable resource and the second most abundant polysaccharide in nature after cellulose, chitin is currently used for waste water clearing, cosmetics, medical, and veterinary applications. This work comprises data mining of protein sequences related to the chitin metabolic pathway of completely sequenced genomes of extant organisms pertaining to the three life domains, followed by meta-analysis using traditional sequence similarity comparison and complex network approaches. Complex networks involving proteins of the chitin metabolic pathway in extant organisms were constructed based on protein sequence similarity. Several usual network indices were estimated in order to obtain information on the topology of these networks, including those related to higher order neighborhood properties. Due to the assumed evolutionary character of the system, we also discuss issues related to modularity properties, with the concept of edge betweenness playing a particularly important role in our analysis. Complex network approach correctly identifies clusters of organisms that belong to phylogenetic groups without any a priori knowledge about the biological features of the investigated protein sequences. We envisage the prospect of using such a complex network approach as a high-throughput phylogenetic method.

IDENTIFICATION OF COMMUNITY STRUCTURE IN NETWORKS USING HIGHER ORDER NEIGHBORHOOD CONCEPTS

The identification of community structures in networks is investigated within a framework based on the concepts of higher order neighborhoods and neighborhood matrix

Persistence and extinction in a mathematical model of cell populations affected by radiation

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Critical Behavior of an Ising Model with Aperiodic Interactions

. This procedure is of relevance especially for networks representing evolutionary situations, since several evidences show that they are assembled from pre-existing smaller structures, rather than by the mere adhesion of individual nodes. We proceed within the successive elimination of the links with largest betweenness degree. The effect of erasing a link at step k is quantified by the distance between