Band Selection in Multispectral Images by Minimization of Dependent Information

In this paper, a band selection technique for hyperspectral image data is proposed. Supervised feature extraction techniques allow a reduction of the dimensionality to extract relevant features through a labeled training set. This implies an analysis of the existing class distributions, which usually means, in the case of hyperspectral imaging, a large number of samples, making the labeling process difficult. A possible alternative could be the use of information measures, which are the basis of the proposed method. The present approach basically behaves as an unsupervised feature selection criterion, to obtain the relevant spectral bands from a set of sample images. The relations of information content between spectral bands are analyzed, leading to the proposed technique based on the minimization of the dependent information between spectral bands, while trying to maximize the conditional entropies of the selected bands     

Mechanisms underlying the dualistic mode of action of major soy isoflavones in relation to cell proliferation and cancer risks

Isoflavones are phytoestrogens that have been linked to both beneficial as well as adverse effects in relation to cell proliferation and cancer risks. The present article presents an overview of these seemingly contradicting health effects and of mechanisms that could be involved in this dualistic mode of action. One mechanism relates to the different ultimate cellular effects of activation of estrogen receptor (ER) α, promoting cell proliferation, and of ERβ, promoting apoptosis, with the major soy isoflavones genistein and daidzein activating especially ERβ. A second mode of action includes the role of epigenetics, including effects of isoflavones on DNA methylation, histone modification and miRNA expression patterns. The overview presented reveals that we are only at the start of unraveling the complex underlying mode of action for effects of isoflavones, both beneficial or adverse, on cell proliferation and cancer risks. It is evident that whatever model system will be applied, its relevance to human tissues with respect to ERα and ERβ levels, co‐repressor and co‐activator characteristics as well as its relevance to human exposure regimens, needs to be considered and defined.     

Experimental study on prototype optimisation algorithms for prototype-based classification in vector spaces

Prototype-based classification relies on the distances between the examples to be classified and carefully chosen prototypes. A small set of prototypes is of interest to keep the computational complexity low, while maintaining high classification accuracy. An experimental study of some old and new prototype optimisation techniques is presented, in which the prototypes are either selected or generated from the given data. These condensing techniques are evaluated on real data, represented in vector spaces, by comparing their resulting reduction rates and classification performance.Usually the determination of prototypes is studied in relation with the nearest neighbour rule. We will show that the use of more general dissimilarity-based classifiers can be more beneficial. An important point in our study is that the adaptive condensing schemes here discussed allow the user to choose the number of prototypes freely according to the needs. If such techniques are combined with linear dissimilarity-based classifiers, they provide the best trade-off of small condensed sets and high classification accuracy.     

Synthetic content generation for auto-stereoscopic displays

Due to the appearance of auto-stereoscopic visualization as one of the most emerging tendencies used in displays, new content generation techniques for this kind of visualization are required. In this paper we present a study for the generation of multi-view synthetic content, studying several camera setups (planar, cylindrical and hyperbolic) and their configurations. We discuss the different effects obtained varying the parameters of these setups. A study with several users was made to analyze visual perceptions, asking them for their optimal visualization. To create the virtual content, a multi-view system has been integrated in a powerful game engine, which allows us to use the latest graphics hardware advances. This integration is detailed and several demos and videos are attached with this paper, which represent a virtual world for auto-stereoscopic displays and the same scenario in a two-view anaglyph representation for being visualized in any conventional display. In all these demos, the parameters studied can be modified offering the possibility of easily appreciate their effects in a virtual scene.     

An analysis of how training data complexity affects the nearest neighbor classifiers

The k-nearest neighbors (k-NN) classifier is one of the most popular supervised classification methods. It is very simple, intuitive and accurate in a great variety of real-world domains. Nonetheless, despite its simplicity and effectiveness, practical use of this rule has been historically limited due to its high storage requirements and the computational costs involved. On the other hand, the performance of this classifier appears strongly sensitive to training data complexity. In this context, by means of several problem difficulty measures, we try to characterize the behavior of the k-NN rule when working under certain situations. More specifically, the present analysis focuses on the use of some data complexity measures to describe class overlapping, feature space dimensionality and class density, and discover their relation with the practical accuracy of this classifier.

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A model of the specific growth rate inhibition by weak acids in yeasts based on energy requirements

Zygosaccharomyces bailii, a spoilage yeast, capable of metabolic activity in food environments with low pH, low a_w and in the presence of weak acid preservatives was chosen for a study on the effect of benzoic acid on growth parameters. In batch cultures, under controlled pH, this food preservative inhibited growth, decreasing the specific growth rate (μ) and the yield coefficient (Y_S) on glucose. Data obtained at pH 3.5, 4.0 and 4.5 showed that this inhibition was exclusively promoted by the undissociated form of the acid since the effect was independent of pH when the concentration of the acid was expressed in this form. Moreover, the relationship between the values for μ and Y_S, provided evidence that the specific consumption rate of glucose (q_S) was not affected by benzoic acid, indicating that the inhibition of growth should be completely explained by a decrease of Y_S. The outcome of parallel experiments performed in continuous culture was that the decrease of Y_S was due to an increase of the maintenance coefficient (m), defined as the fraction of q_S diverted from growth to cope with stress, represented in this case by the presence of the preservative. Based on these results a model was built, assuming that m increased hyperbolically with the concentration of benzoic acid, from zero in the absence of the acid up to q_S when growth was completely inhibited. The concentration of the acid, for which m=q_S/2, is a constant (K_W), and represents a measure of the tolerance for a preservative, in this case benzoic acid. The simple equation μ/μ₀=1+W/K_W predicts the value of μ for a concentration (W) of the preservative, requiring the knowledge of two parameters: the specific growth rate in the absence of the preservative (μ₀) and K_W. The equation fitted very well the data of the effect of benzoic acid on the specific growth rate of Z. bailii, having K_W=0.96 mM benzoic acid. The model was also validated with other spoilage yeasts grown in the presence of benzoic acid in microtiter plates in an automated spectrophotometer. The values obtained for K_W under these conditions confirm Z. bailii as the most tolerant (K_W=2.1 mM) followed by Pichia sp. (K_W=0.78 mM), Saccharomyces cerevisiae (K_W=0.53 mM) and Debaryomyces hansenii (K_W=0.11 mM).     

Urban growth management in Catalonia, 2005–2010

The Catalan experience between 2005 and 2010 constitutes an interesting example of urban & regional planning policies responding to the dramatic changes that took place at the turn of the real estate crisis of 2008: there is probably no other European case study where such a quantity of planning and legislative initiatives addressing urban growth were approved in such a short period. The article frames them in the Spanish framework and provides an integrative understanding of how the Catalan territory was planned in a period of critical changing conditions, from regional to local scale as well as from urban to rural land.     

Depth estimation improvement in 3D integral imaging using an edge removal approach

Pattern Analysis and Applications - A new depth estimation method for 3D reconstruction in a synthetic aperture integral imaging framework is presented. This method removes the edges of the objects...