Possible states in the flow around two circular cylinders in tandem with separations in the vicinity of the drag inversion spacing

The possible states in the flow around two identical circular cylinders in tandem arrangements are investigated for configurations in the vicinity of the drag inversion separation. By means of numerical simulations, the hysteresis in the transition between the shedding regimes is studied and the relationship between (three-dimensional) secondary instabilities and shedding regime determination is addressed. The differences observed in the behavior of two- and three-dimensional flows are analyzed, and the regions of bistable flow are delimited. Very good agreement is found between the proposed scenario and results available in the literature. (C) 2010 American Institute of Physics. [doi: 10.1063/1.3420111]

Influence of memory in deterministic walks in random media: Analytical calculation within a mean-field approximation

Consider a random medium consisting of N points randomly distributed so that there is no correlation among the distances separating them. This is the random link model, which is the high dimensionality limit (mean-field approximation) for the Euclidean random point structure. In the random link model, at discrete time steps, a walker moves to the nearest point, which has not been visited in the last mu steps (memory), producing a deterministic partially self-avoiding walk (the tourist walk). We have analytically obtained the distribution of the number n of points explored by the walker with memory mu=2, as well as the transient and period joint distribution. This result enables us to explain the abrupt change in the exploratory behavior between the cases mu=1 (memoryless walker, driven by extreme value statistics) and mu=2 (walker with memory, driven by combinatorial statistics). In the mu=1 case, the mean newly visited points in the thermodynamic limit (N >> 1) is just < n >=e=2.72... while in the mu=2 case, the mean number < n > of visited points grows proportionally to N(1/2). Also, this result allows us to establish an equivalence between the random link model with mu=2 and random map (uncorrelated back and forth distances) with mu=0 and the abrupt change between the probabilities for null transient time and subsequent ones.

Holographic superconductors with various condensates in Einstein-Gauss-Bonnet gravity

We study holographic superconductors in Einstein-Gauss-Bonnet gravity. We consider two particular backgrounds: a d-dimensional Gauss-Bonnet-AdS black hole and a Gauss-Bonnet-AdS soliton. We discuss in detail the effects that the mass of the scalar field, the Gauss-Bonnet coupling and the dimensionality of the AdS space have on the condensation formation and conductivity. We also study the ratio omega(g)/T(c) for various masses of the scalar field and Gauss-Bonnet couplings.

Feature selection environment for genomic applications

Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e., for dimensionality reduction). There are many genomic and proteomic applications that rely on feature selection to answer questions such as selecting signature genes which are informative about some biological state, e. g., normal tissues and several types of cancer; or inferring a prediction network among elements such as genes, proteins and external stimuli. In these applications, a recurrent problem is the lack of samples to perform an adequate estimate of the joint probabilities between element states. A myriad of feature selection algorithms and criterion functions have been proposed, although it is difficult to point the best solution for each application. Results: The intent of this work is to provide an open-source multiplataform graphical environment for bioinformatics problems, which supports many feature selection algorithms, criterion functions and graphic visualization tools such as scatterplots, parallel coordinates and graphs. A feature selection approach for growing genetic networks from seed genes ( targets or predictors) is also implemented in the system. Conclusion: The proposed feature selection environment allows data analysis using several algorithms, criterion functions and graphic visualization tools. Our experiments have shown the software effectiveness in two distinct types of biological problems. Besides, the environment can be used in different pattern recognition applications, although the main concern regards bioinformatics tasks.

Reliability and validity of the Impact of Event Scale (IES): version for Brazilian burn victims

Aims. The aims of this study were to assess the internal reliability (internal consistency), construct validity, sensitivity and ceiling and floor effects of the Brazilian-Portuguese version of the Impact of Event Scale (IES). Design. Methodological research design. Method. The Brazilian-Portuguese version of the IES was applied to a group of 91 burned patients at three times: the first week after the burn injury (time one), between the fourth and the sixth months (time two) and between the ninth and the 12th months (time three). The internal consistency, construct validity (convergent and dimensionality), sensitivity and ceiling and floor effects were tested. Results. Cronbach`s alpha coefficients showed high internal consistency for the total scale (0 center dot 87) and for the domains intrusive thoughts (0 center dot 87) and avoidance responses (0 center dot 76). During the hospitalisation (time one), the scale showed low and positive correlations with pain measures immediately before (r = 0 center dot 22; p < 0 center dot 05) and immediately after baths and dressings (r = 0 center dot 21; p < 0 center dot 05). After the discharge, we found strong and negative correlations with self-esteem (r = -0 center dot 52; p < 0 center dot 01), strong and positive with depression (r = 0 center dot 63; p < 0 center dot 01) and low and negative with the Bodily pain (r = -0 center dot 24; p < 0 center dot 05), Social functioning (r = -0 center dot 34; p < 0 center dot 01) and Mental health (r = -0 center dot 27; p < 0 center dot 05) domains of the SF-36 at time two. Regarding the sensitivity, no statistically significant differences were observed between mean scale scores according to burned body surface (p = 0 center dot 21). The floor effect was observed in most of the IES items. Conclusion. The adapted version of the scale showed to be reliable and valid to assess postburn reactions on the impact of the event in the group of patients under analysis. Relevance to clinical practice. The Impact of Event Scale can be used in research and clinical practice to assess nursing interventions aimed at decreasing stress during rehabilitation.

Performance of the Equivalent Reservoir Modelling Technique for Multi-Reservoir Hydropower Systems

This paper investigates the validity of a simplified equivalent reservoir representation of a multi-reservoir hydroelectric system for modelling its optimal operation for power maximization. This simplification, proposed by Arvanitidis and Rosing (IEEE Trans Power Appar Syst 89(2):319-325, 1970), imputes a potential energy equivalent reservoir with energy inflows and outflows. The hydroelectric system is also modelled for power maximization considering individual reservoir characteristics without simplifications. Both optimization models employed MINOS package for solution of the non-linear programming problems. A comparison between total optimized power generation over the planning horizon by the two methods shows that the equivalent reservoir is capable of producing satisfactory power estimates with less than 6% underestimation. The generation and total reservoir storage trajectories along the planning horizon obtained by equivalent reservoir method, however, presented significant discrepancies as compared to those found in the detailed modelling. This study is motivated by the fact that Brazilian generation system operations are based on the equivalent reservoir method as part of the power dispatch procedures. The potential energy equivalent reservoir is an alternative which eliminates problems with the dimensionality of state variables in a dynamic programming model.

Reliability and validity of the Brazilian-Portuguese version of the Burns Specific Pain Anxiety Scale (BSPAS)

Background: Pain and anxiety are a common problem in all recovery phases after a burn. The Burns Specific Pain Anxiety Scale (BSPAS) was proposed to assess anxiety in burn patients related to painful procedures. Objectives: To assess internal consistency, discriminative construct validity, dimensionality and convergent construct validity of the Brazilian-Portuguese version of the Burns Specific Pain Anxiety Scale. Design: In this cross-sectional study, the original version of the BSPAS, adapted into Brazilian Portuguese, was tested for internal consistency (Cronbach`s Alpha), discriminative validity (related to total body surface area burned and sex), dimensionality (through factor analysis), and convergent construct validity (applying the Visual Analogue Scale for pain and State-Anxiety-STAI) in a group of 91 adult burn patients. Results: The adapted version of the BSPAS displayed a moderate and positive correlation with pain assessments: immediately before baths and dressings (r = 0.32; p < 0.001), immediately after baths and dressings (r = 0.31; p < 0.001) and during the relaxation period (r= 0.31; p < 0.001) and with anxiety assessments (r = 0.34; p < 0.001). No statistically significant differences were observed when comparing the mean of the adapted version of the BSPAS scores with sex (p = 0.194) and total body surface area burned (p = 0.162) (discriminative validity). The principal components analysis applied to our sample seems to confirm anxiety as one single domain of the Brazilian-Portuguese version of the BSPAS. Cronbach`s Alpha showed high internal consistency of the adapted version of the scale (0.90). Conclusion: The Brazilian-Portuguese version of the BSPAS 9-items has shown statically acceptable levels of reliability and validity for pain-related anxiety evaluation in burn patients. This scale can be used to assess nursing interventions aimed at decreasing pain and anxiety related to the performance of painful procedures. (c) 2010 Elsevier Ltd. All rights reserved.

Supporting content-based image retrieval and computer-aided diagnosis systems with association rule-based techniques

In this work, we take advantage of association rule mining to support two types of medical systems: the Content-based Image Retrieval (CBIR) systems and the Computer-Aided Diagnosis (CAD) systems. For content-based retrieval, association rules are employed to reduce the dimensionality of the feature vectors that represent the images and to improve the precision of the similarity queries. We refer to the association rule-based method to improve CBIR systems proposed here as Feature selection through Association Rules (FAR). To improve CAD systems, we propose the Image Diagnosis Enhancement through Association rules (IDEA) method. Association rules are employed to suggest a second opinion to the radiologist or a preliminary diagnosis of a new image. A second opinion automatically obtained can either accelerate the process of diagnosing or to strengthen a hypothesis, increasing the probability of a prescribed treatment be successful. Two new algorithms are proposed to support the IDEA method: to pre-process low-level features and to propose a preliminary diagnosis based on association rules. We performed several experiments to validate the proposed methods. The results indicate that association rules can be successfully applied to improve CBIR and CAD systems, empowering the arsenal of techniques to support medical image analysis in medical systems. (C) 2009 Elsevier B.V. All rights reserved.

PCA Tomography: how to extract information from data cubes

Astronomy has evolved almost exclusively by the use of spectroscopic and imaging techniques, operated separately. With the development of modern technologies, it is possible to obtain data cubes in which one combines both techniques simultaneously, producing images with spectral resolution. To extract information from them can be quite complex, and hence the development of new methods of data analysis is desirable. We present a method of analysis of data cube (data from single field observations, containing two spatial and one spectral dimension) that uses Principal Component Analysis (PCA) to express the data in the form of reduced dimensionality, facilitating efficient information extraction from very large data sets. PCA transforms the system of correlated coordinates into a system of uncorrelated coordinates ordered by principal components of decreasing variance. The new coordinates are referred to as eigenvectors, and the projections of the data on to these coordinates produce images we will call tomograms. The association of the tomograms (images) to eigenvectors (spectra) is important for the interpretation of both. The eigenvectors are mutually orthogonal, and this information is fundamental for their handling and interpretation. When the data cube shows objects that present uncorrelated physical phenomena, the eigenvector`s orthogonality may be instrumental in separating and identifying them. By handling eigenvectors and tomograms, one can enhance features, extract noise, compress data, extract spectra, etc. We applied the method, for illustration purpose only, to the central region of the low ionization nuclear emission region (LINER) galaxy NGC 4736, and demonstrate that it has a type 1 active nucleus, not known before. Furthermore, we show that it is displaced from the centre of its stellar bulge.

ADRB2 and LEPR Gene Polymorphisms: Synergistic Effects on the Risk of Obesity in Japanese

The objective of the present study was to validate a recently reported synergistic effect between variants located in the leptin receptor (LEPR) gene and in the beta-2 adrenergic receptor (ADRB2) gene on the risk of overweight/obesity. We studied a middle-aged/ elderly sample of 4,193 nondiabetic Japanese subjects stratified according gender (1,911 women and 2,282 men). The LEPR Gln223Arg (rs1137101) variant as well as both ADRB2 Arg16Gly (rs1042713) and Gln27Glu (rs1042714) polymorphisms were analyzed. The primary outcome was the risk of overweight/obesity defined as BMI >= 25 kg/m(2), whereas secondary outcomes included the risk of a BMI >= 27 kg/m(2) and BMI as a continuous variable. None of the studied polymorphisms showed statistically significant individual effects, regardless of the group or phenotype studied. Haplotype analysis also did not disclose any associations of ADRB2 polymorphisms with BMI. However, dimensionality reduction-based models confirmed significant interactions among the investigated variants for BMI as a continuous variable as well as for the risk of obesity defined as BMI >= 27 kg/m(2). All disclosed interactions were found in men only. Our results provide external validation for a male specific ADRB2-LEPR interaction effect on the risk of overweight/obesity, but indicate that effect sizes associated with these interactions may be smaller in the population studied.

Multilocus Analyses of Seven Candidate Genes Suggest Interacting Pathways for Obesity-Related Traits in Brazilian Populations

We investigated whether variants in major candidate genes for food intake and body weight regulation contribute to obesity-related traits under a multilocus perspective. We studied 375 Brazilian subjects from partially isolated African-derived populations (quilombos). Seven variants displaying conflicting results in previous reports and supposedly implicated in the susceptibility of obesity-related phenotypes were investigated: beta(2)-adrenergic receptor (ADRB2) (Arg16Gly), insulin induced gene 2 (INSIG2) (rs7566605), leptin (LEP) (A19G), LEP receptor (LEPR) (Gln223Arg), perilipin (PLIN) (6209T > C), peroxisome proliferator-activated receptor-gamma (PPARG) (Pro12Ala), and resistin (RETN) (-420C > G). Regression models as well as generalized multifactor dimensionality reduction (GMDR) were employed to test the contribution of individual effects and higher-order interactions to BMI and waist-hip ratio (WHR) variation and risk of overweight/obesity. The best multilocus association signal identified in the quilombos was further examined in an independent sample of 334 Brazilian subjects of European ancestry. In quilombos, only the PPARG polymorphism displayed significant individual effects (WHR variation, P = 0.028). No association was observed either with the risk of overweight/obesity (BMI >= 25 kg/m(2)), risk of obesity alone (BMI >= 30 kg/m(2)) or BMI variation. However, GMDR analyses revealed an interaction between the LEPR and ADRB2 polymorphisms (P = 0.009) as well as a third-order effect involving the latter two variants plus INSIG2 (P = 0.034) with overweight/obesity. Assessment of the LEPR-ADRB2 interaction in the second sample indicated a marginally significant association (P = 0.0724), which was further verified to be limited to men (P = 0.0118). Together, our findings suggest evidence for a two-locus interaction between the LEPR Gln223Arg and ADRB2 Arg16Gly variants in the risk of overweight/obesity, and highlight further the importance of multilocus effects in the genetic component of obesity.

Visual analysis of image collections

Multidimensional Visualization techniques are invaluable tools for analysis of structured and unstructured data with variable dimensionality. This paper introduces PEx-Image-Projection Explorer for Images-a tool aimed at supporting analysis of image collections. The tool supports a methodology that employs interactive visualizations to aid user-driven feature detection and classification tasks, thus offering improved analysis and exploration capabilities. The visual mappings employ similarity-based multidimensional projections and point placement to layout the data on a plane for visual exploration. In addition to its application to image databases, we also illustrate how the proposed approach can be successfully employed in simultaneous analysis of different data types, such as text and images, offering a common visual representation for data expressed in different modalities.

Two-Phase Mapping for Projecting Massive Data Sets

Most multidimensional projection techniques rely on distance (dissimilarity) information between data instances to embed high-dimensional data into a visual space. When data are endowed with Cartesian coordinates, an extra computational effort is necessary to compute the needed distances, making multidimensional projection prohibitive in applications dealing with interactivity and massive data. The novel multidimensional projection technique proposed in this work, called Part-Linear Multidimensional Projection (PLMP), has been tailored to handle multivariate data represented in Cartesian high-dimensional spaces, requiring only distance information between pairs of representative samples. This characteristic renders PLMP faster than previous methods when processing large data sets while still being competitive in terms of precision. Moreover, knowing the range of variation for data instances in the high-dimensional space, we can make PLMP a truly streaming data projection technique, a trait absent in previous methods.

SZNAJD MODEL AND PROPORTIONAL ELECTIONS: THE ROLE OF THE TOPOLOGY OF THE NETWORK

The Sznajd model (SM) has been employed with success in the last years to describe opinion propagation in a community. In particular, it has been claimed that its transient is able to reproduce some scale properties observed in data of proportional elections, in different countries, if the community structure (the network) is scale-free. In this work, we investigate the properties of the transient of a particular version of the SM, introduced by Bernardes and co-authors in 2002. We studied the behavior of the model in networks of different topologies through the time evolution of an order parameter known as interface density, and concluded that regular lattices with high dimensionality also leads to a power-law distribution of the number of candidates with v votes. Also, we show that the particular absorbing state achieved in the stationary state (or else, the winner candidate), is related to a particular feature of the model, that may not be realistic in all situations.