Analytic Expressions for Stochastic Distances Between Relaxed Complex Wishart Distributions

The scaled complex Wishart distribution is a widely used model for multilook full polarimetric SAR data whose adequacy has been attested in the literature. Classification, segmentation, and image analysis techniques which depend on this model have been devised, and many of them employ some type of dissimilarity measure. In this paper we derive analytic expressions for four stochastic distances between relaxed scaled complex Wishart distributions in their most general form and in important particular cases. Using these distances, inequalities are obtained which lead to new ways of deriving the Bartlett and revised Wishart distances. The expressiveness of the four analytic distances is assessed with respect to the variation of parameters. Such distances are then used for deriving new tests statistics, which are proved to have asymptotic chi-square distribution. Adopting the test size as a comparison criterion, a sensitivity study is performed by means of Monte Carlo experiments suggesting that the Bhattacharyya statistic outperforms all the others. The power of the tests is also assessed. Applications to actual data illustrate the discrimination and homogeneity identification capabilities of these distances.Comment: Accepted for publication in the IEEE Transactions on Geoscience and Remote Sensing journa

Classification of Biomedical Signals using the Dynamics of the False Nearest Neighbours (DFNN) Algorithm

* This study was supported in part by the Natural Sciences and Engineering Research Council of Canada, and by the Gastrointestinal Motility Laboratory (University of Alberta Hospitals) in Edmonton, Alberta, Canada.Accurate and efficient analysis of biomedical signals can be facilitated by proper identification based on their dominant dynamic characteristics (deterministic, chaotic or random). Specific analysis techniques exist to study the dynamics of each of these three categories of signals. However, comprehensive and yet adequately simple screening tools to appropriately classify an unknown incoming biomedical signal are still lacking. This study is aimed at presenting an efficient and simple method to classify model signals into the three categories of deterministic, random or chaotic, using the dynamics of the False Nearest Neighbours (DFNN) algorithm, and then to utilize the developed classification method to assess how some specific biomedical signals position with respect to these categories. Model deterministic, chaotic and random signals were subjected to state space decomposition, followed by specific wavelet and statistical analysis aiming at deriving a comprehensive plot representing the three signal categories in clearly defined clusters. Previously recorded electrogastrographic (EGG) signals subjected to controlled, surgically-invoked uncoupling were submitted to the proposed algorithm, and were classified as chaotic. Although computationally intensive, the developed methodology was found to be extremely useful and convenient to use

Unsaturated Fatty Acids Revert Diet-Induced Hypothalamic Inflammation in Obesity

Background: In experimental models, hypothalamic inflammation is an early and determining factor in the installation and progression of obesity. Pharmacological and gene-based approaches have proven efficient in restraining inflammation and correcting the obese phenotypes. However, the role of nutrients in the modulation of hypothalamic inflammation is unknown. Methodology/Principal Findings: Here we show that, in a mouse model of diet-induced obesity, partial substitution of the fatty acid component of the diet by flax seed oil (rich in C18:3) or olive oil (rich in C18:1) corrects hypothalamic inflammation, hypothalamic and whole body insulin resistance, and body adiposity. In addition, upon icv injection in obese rats, both v3 and v9 pure fatty acids reduce spontaneous food intake and body mass gain. These effects are accompanied by the reversal of functional and molecular hypothalamic resistance to leptin/insulin and increased POMC and CART expressions. In addition, both, v3 and v9 fatty acids inhibit the AMPK/ACC pathway and increase CPT1 and SCD1 expression in the hypothalamus. Finally, acute hypothalamic injection of v3 and v9 fatty acids activate signal transduction through the recently identified GPR120 unsaturated fatty acid receptor. Conclusions/Significance: Unsaturated fatty acids can act either as nutrients or directly in the hypothalamus, reverting dietinduced inflammation and reducing body adiposity. These data show that, in addition to pharmacological and geneti