Paracoccidioidomycosis-related mortality trend, state of Sao Paulo, Brazil: a study using multiple causes of death

Objective. To investigate mortality in which paracoccidioidomycosis appears on any line or part of the death certificate. Method. Mortality data for 1985-2005 were obtained from the multiple cause-of-death database maintained by the Sao Paulo State Data Analysis System (SEADE). Standardized mortality coefficients were calculated for paracoccidioidomycosis as the underlying cause-of-death and as an associated cause-of-death, as well as for the total number of times paracoccidioidomycosis was mentioned on the death certificates. Results. During this 21-year period, there were 1950 deaths related to paracoccidioidomycosis; the disease was the underlying cause-of-death in 1 164 cases (59.69%) and an associated cause-of-death in 786 (40.31%). Between 1985 and 2005 records show a 59.8% decline in the mortality coefficient due to paracoccidioidomycosis as the underlying cause and a 53.0% decline in the mortality as associated cause. The largest number of deaths occurred among men, in the older age groups, and among rural workers, with an upward trend in winter months. The main causes associated with paracoccidioidomycosis as the underlying cause-of-death were pulmonary fibrosis, chronic lower respiratory tract diseases, and pneumonias. Malignant neoplasms and AIDS were the main underlying causes when paracoccidioidomycosis was an associated cause-of-death. The decision tables had to be adapted for the automated processing of causes of death in death certificates where paracoccidioidomycosis was mentioned. Conclusions. Using the multiple cause-of-death method together with the traditional underlying cause-of-death approach provides a new angle on research aimed at broadening our understanding of the natural history of paracoccidioidomycosis.

Recurrence quantification analysis of electrostatic fluctuations in fusion plasmas

We have investigated plasma turbulence at the edge of a tokamak plasma using data from electrostatic potential fluctuations measured in the Brazilian tokamak TCABR. Recurrence quantification analysis has been used to provide diagnostics of the deterministic content of the series. We have focused our analysis on the radial dependence of potential fluctuations and their characterization by recurrence-based diagnostics. Our main result is that the deterministic content of the experimental signals is most pronounced at the external part of the plasma column just before the plasma radius. Since the chaoticity of the signals follows the same trend, we have concluded that the electrostatic plasma turbulence at the tokamak plasma edge can be partially explained by means of a deterministic nonlinear system. (C) 2007 Elsevier B.V. All rights reserved.

Universal trend for heavy-ion total reaction cross-sections at energies above the Coulomb barrier

Heavy-ion total reaction cross-section measurements for more than 1100 reaction cases covering 61 target nuclei in the range (6)Li-(238)U and 158 projectile nuclei from (2)H to (84)Kr (mostly exotic ones) have been analyzed in a systematic way by using an empirical, three-parameter formula that is applicable to the cases of projectile kinetic energies above the Coulomb barrier. The analysis has shown that the average total nuclear binding energy per nucleon of the interacting nuclei and their radii are the chief quantities that describe the cross-section patterns. A great amount of cross-section data (87%) has been quite satisfactorily reproduced by the proposed formula; therefore, the total reaction cross-section predictions for new, not yet experimentally investigated reaction cases can be obtained within 25% (or much less) uncertainty.

Texture analysis and classification using deterministic tourist walk

In this paper, we present a study on a deterministic partially self-avoiding walk (tourist walk), which provides a novel method for texture feature extraction. The method is able to explore an image on all scales simultaneously. Experiments were conducted using different dynamics concerning the tourist walk. A new strategy, based on histograms. to extract information from its joint probability distribution is presented. The promising results are discussed and compared to the best-known methods for texture description reported in the literature. (C) 2009 Elsevier Ltd. All rights reserved.

Texture analysis using graphs generated by deterministic partially self-avoiding walks

Texture is one of the most important visual attributes for image analysis. It has been widely used in image analysis and pattern recognition. A partially self-avoiding deterministic walk has recently been proposed as an approach for texture analysis with promising results. This approach uses walkers (called tourists) to exploit the gray scale image contexts in several levels. Here, we present an approach to generate graphs out of the trajectories produced by the tourist walks. The generated graphs embody important characteristics related to tourist transitivity in the image. Computed from these graphs, the statistical position (degree mean) and dispersion (entropy of two vertices with the same degree) measures are used as texture descriptors. A comparison with traditional texture analysis methods is performed to illustrate the high performance of this novel approach. (C) 2011 Elsevier Ltd. All rights reserved.

Density-Profile Processes Describing Biological Signaling Networks: Almost Sure Convergence to Deterministic Trajectories

We introduce jump processes in R(k), called density-profile processes, to model biological signaling networks. Our modeling setup describes the macroscopic evolution of a finite-size spin-flip model with k types of spins with arbitrary number of internal states interacting through a non-reversible stochastic dynamics. We are mostly interested on the multi-dimensional empirical-magnetization vector in the thermodynamic limit, and prove that, within arbitrary finite time-intervals, its path converges almost surely to a deterministic trajectory determined by a first-order (non-linear) differential equation with explicit bounds on the distance between the stochastic and deterministic trajectories. As parameters of the spin-flip dynamics change, the associated dynamical system may go through bifurcations, associated to phase transitions in the statistical mechanical setting. We present a simple example of spin-flip stochastic model, associated to a synthetic biology model known as repressilator, which leads to a dynamical system with Hopf and pitchfork bifurcations. Depending on the parameter values, the magnetization random path can either converge to a unique stable fixed point, converge to one of a pair of stable fixed points, or asymptotically evolve close to a deterministic orbit in Rk. We also discuss a simple signaling pathway related to cancer research, called p53 module.