Abstract
Acoustic heart signals are generated by a turbulence effect created when the heart valves snap shut, and therefore carrying significant information of the underlying functionality of the cardiovascular system. In this paper, we present a method for heart murmur classification divided into three major steps: a) features are extracted from the heart sound; b) features are selected using a Backward Feature Selection algorithm; c) signals are classified using a K-nearest neighbor's classifier. A new set of fractal features are proposed, which are based on the distinct signatures of complexity and self-similarity registered on the normal and pathogenic cases. The experimental results show that fractal features are the most capable of describing the non-linear structure and the underlying dynamics of heart sounds among the all feature families tested. The classification results achieved for the mitral auscultation spot (88% of accuracy) are in agreement with the current state of the art methods for heart murmur classification.

Abstract
We present a methodology to assess cell level alterations on the human retina responsible for functional changes observable in the Optical Coherence Tomography data in healthy ageing and in disease conditions, in the absence of structural alterations. The methodology is based in a 3D multilayer Monte Carlo computational model of the human retina. The optical properties of each layer are obtained by solving the Maxwell's equations for 3D domains representative of small regions of those layers, using a Discontinuous Galerkin Finite Element Method (DG-FEM). Here we present the DG-FEM Maxwell 3D model and its validation against Mie's theory for spherical scatterers. We also present an application of our methodology to the assessment of cell level alterations responsible for the OCT data in Diabetic Macular Edema. It was possible to identify which alterations are responsible for the changes observed in the OCT scans of the diseased groups.

Abstract
The goal of this work is to develop a computational model of the human retina and simulate light scattering through its structure aiming to shed light on data obtained by optical coherence tomography in human retinas. Currently, light propagation in scattering media is often described by Mie's solution to Maxwell's equations, which only describes the scattering patterns for homogeneous spheres, thus limiting its application for scatterers of more complex shapes. In this work, we propose a discontinuous Galerkin method combined with a low-storage Runge-Kutta method as an accurate and efficient way to numerically solve the time-dependent Maxwell's equations. In this work, we report on the validation of the proposed methodology by comparison with Mie's solution, a mandatory step before further elaborating the numerical scheme towards the propagation of electromagnetic waves through the human retina.

Abstract
This article studies the economic crisis' impact on consumers' behavior, and aims to help defining green marketing strategies appropriate for these periods. We conducted a survey to 412 Portuguese individuals. The majority of the respondents shows a medium or high green consumer behavior, and demonstrates reduced consumption during crisis. The purchase of green products is more present in products whose use cost is lower than the use cost of the alternative products. The crisis may have a bipolar effect on green consumption, encouraging certain practices and reducing others.

Abstract

Abstract
This paper presents an algorithm, in the context of speech analysis and pathologic/dysphonic voices evaluation, which splits the signal of the glottal excitation into harmonic and noise components. The algorithm uses a harmonic and noise splitter and a glottal inverse filtering. The combination of these two functionalities leads to an improved estimation of the glottal excitation and its components. The results demonstrate this improvement of estimates of the glottal excitation in comparison to a known inverse filtering method (IAIF). These results comprise performance tests with synthetic voices and application to natural voices that show the waveforms of harmonic and noise components of the glottal excitation. This enhances the glottal information retrieval such as waveform patterns with physiological meaning.