Desire, Hierarchy, and Agency: Youth, Homosexuality, and Difference Markers in Sao Paulo

In this article, we present the results of ethnographic research undertaken in areas with concentrated recreational venues frequented by diverse youth groups in the city of Sao Paulo, Brazil. This material is part of the larger ""Relationships between race, gender and sexuality in different national and local contexts"" research initiative. Here, we focus upon data collected through ethnographic observation and interviews conducted in various locales where young men meet to engage in homoerotic sociability, demonstrating different degrees of conviviality among groups of different socioeconomic profiles and distinct esthetic preferences, consumer habits, and body types. We explore the production of styles and body presentations that link markers of color/race, gender, and sexuality, as well as the relationships that these maintain with opening or restricting possibilities for the establishment of erotic and affective partnerships involving these boys.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

Support vector machines for detecting age-related changes in running kinematics

Age-related changes in running kinematics have been reported in the literature using classical inferential statistics. However, this approach has been hampered by the increased number of biomechanical gait variables reported and subsequently the lack of differences presented in these studies. Data mining techniques have been applied in recent biomedical studies to solve this problem using a more general approach. In the present work, we re-analyzed lower extremity running kinematic data of 17 young and 17 elderly male runners using the Support Vector Machine (SVM) classification approach. In total, 31 kinematic variables were extracted to train the classification algorithm and test the generalized performance. The results revealed different accuracy rates across three different kernel methods adopted in the classifier, with the linear kernel performing the best. A subsequent forward feature selection algorithm demonstrated that with only six features, the linear kernel SVM achieved 100% classification performance rate, showing that these features provided powerful combined information to distinguish age groups. The results of the present work demonstrate potential in applying this approach to improve knowledge about the age-related differences in running gait biomechanics and encourages the use of the SVM in other clinical contexts. (C) 2010 Elsevier Ltd. All rights reserved.

Normal Versus Pathological Voice Signals Using Wavelet Analysis and Least Squares Support-Vector Machines

State of Sao Paulo Research Foundation (FAPESP)

Remote control of CNC machines using the CyberOPC communication system over public networks

During the last few years, the evolution of fieldbus and computers networks allowed the integration of different communication systems involving both production single cells and production cells, as well as other systems for business intelligence, supervision and control. Several well-adopted communication technologies exist today for public and non-public networks. Since most of the industrial applications are time-critical, the requirements of communication systems for remote control differ from common applications for computer networks accessing the Internet, such as Web, e-mail and file transfer. The solution proposed and outlined in this work is called CyberOPC. It includes the study and the implementation of a new open communication system for remote control of industrial CNC machines, making the transmission delay for time-critical control data shorter than other OPC-based solutions, and fulfilling cyber security requirements.

Reliability-based evaluation of design code provisions for circular concrete-filled steel columns

This paper presents an investigation of design code provisions for steel-concrete composite columns. The study covers the national building codes of United States, Canada and Brazil, and the transnational EUROCODE. The study is based on experimental results of 93 axially loaded concrete-filled tubular steel columns. This includes 36 unpublished, full scale experimental results by the authors and 57 results from the literature. The error of resistance models is determined by comparing experimental results for ultimate loads with code-predicted column resistances. Regression analysis is used to describe the variation of model error with column slenderness and to describe model uncertainty. The paper shows that Canadian and European codes are able to predict mean column resistance, since resistance models of these codes present detailed formulations for concrete confinement by a steel tube. ANSI/AISC and Brazilian codes have limited allowance for concrete confinement, and become very conservative for short columns. Reliability analysis is used to evaluate the safety level of code provisions. Reliability analysis includes model error and other random problem parameters like steel and concrete strengths, and dead and live loads. Design code provisions are evaluated in terms of sufficient and uniform reliability criteria. Results show that the four design codes studied provide uniform reliability, with the Canadian code being best in achieving this goal. This is a result of a well balanced code, both in terms of load combinations and resistance model. The European code is less successful in providing uniform reliability, a consequence of the partial factors used in load combinations. The paper also shows that reliability indexes of columns designed according to European code can be as low as 2.2, which is quite below target reliability levels of EUROCODE. (C) 2009 Elsevier Ltd. All rights reserved.

Design of concrete-filled steel tubular columns under axial loading according to NBR 8800:2008 and Eurocode 4:2004: tests results and comparisons

In this paper results of tests on 32 concrete-filled steel tubular columns under axial load are reported. The test parameters were the concrete compressive strength, the column slenderness (L/D) and the wall thickness (t). The test results were compared with predictions from the codes NBR 8800:2008 and EN 1994-1-1:2004 (EC4). The columns were 3, 5, 7 and 10 length to diameter ratios (L/D) and were tested with 30MPa, 60MPa, 80MPa and 100MPa concrete compressive strengths. The results of ultimate strength predicted by codes showed good agreement with experimental results. The results of NBR 8800 code were the most conservative and the EC4 showed the best results, in mean, but it was not conservative for usual concrete-filled short columns.

Comparison Between Voltage Control Structures of Synchronous Machines

This paper compares the behaviour of two different control structures of automatic voltage regulators of synchronous machines equipped with static excitation systems. These systems have a fully controlled thyristor bridge that supplies DC current to the rotor winding. The rectifier bridge is fed by the stator terminals through a step-down transformer. The first control structure, named ""Direct Control"", has a single proportional-integral (PI) regulator that compares stator voltage setpoint with measured voltage and acts directly on the thyristor bridge`s firing angle. This control structure is usually employed in commercial excitation systems for hydrogenerators. The second structure, named ""Cascade Control"", was inspired on control loops of commercial DC motor drives. Such drives employ two PIs in a cascade arrangement, the external PI deals with the motor speed while the internal one regulates the armature current. In the adaptation proposed, the external PI compares setpoint with the actual stator voltage and produces the setpoint to the internal PI-loop which controls the field current.

Corrosion behavior of carbon steel protected with single and bi-layer of silane films filled with silica nanoparticles

The electrochemical behaviour of carbon steel coated with bis-[trimethoxysilylpropyl]amine (BTSPA) filled with silica nanoparticles in naturally aerated 0.1 mol L-1 NaCl solutions was evaluated. The coating was prepared by adding different concentrations of silica nanoparticles (100, 200, 300, 400 and 500 ppm) to the hydrolysis solution and then a second layer without silica nanoparticles was applied. The electrochemical behavior of the coated steel was evaluated by means of open-circuit potential (E-OC), electrochemical impedance spectroscopy (EIS) and polarization curves. Surface characterization was made by atomic force microscopy (AFM), and its hydrophobicity assessed by contact angle measurements. EIS diagrams have shown an improvement of the barrier properties of the silane layer with the silica addition, which was further improved on the bi-layer system. However, a dependence on the filler concentration was verified, and the best electrochemical response was obtained for samples modified with 300 ppm of silica nanoparticles. AFM images have shown a homogeneous distribution of the silica nanoparticles on the sample surface; however particles agglomeration was detected, which degraded the corrosion protection performance. The results were explained on the basis of the improvement of the barrier properties of the coating due to the filler addition and on the onset of defective regions on the more heavily filled coatings allowing easier electrolyte penetration. (C) 2007 Elsevier B.V. All rights reserved.

Democracy versus Republic: Inclusion and Desire in Social Struggles

This paper argues that the idea of inclusion is linked to the democratic tradition rather than to the republican one. By analyzing the origins and meaning of these two concepts, the author holds that democracy is rather linked to desire and republic to will (and to the expression of desire), and concludes that, since North Atlantic political tradition has not given a key role to desire, democracy, in order to overcome the difficulties it has been encountering in all parts of the world, should take more account of desire and of the social struggles it brings to the fore.

Characterization of blood-filled cyst by contrast echocardiography and computed tomography

Contrast echocardiography has been demonstrated useful for left ventricular opacification and improvement of endocardial border delineation. Another important clinical application of this technique refers to the better characterization of cardiac tumors and masses. We here described an asymptomatic patient with cystic mass attached to submitral valve apparatus in which contrast echocardiography was performed after intravenous injection of lipid-encapsulated microbubbles. It resulted in enhancement of the cystic borders and allowed for better definition of its diagnosis. Multislice computed tomography confirmed the echocardiographic findings. This case illustrates the potential of contrast echocardiography to improve the anatomic evaluation of cardiac masses.

An fMRI Normative Database for Connectivity Networks Using One-Class Support Vector Machines

The application of functional magnetic resonance imaging (fMRI) in neuroscience studies has increased enormously in the last decade. Although primarily used to map brain regions activated by specific stimuli, many studies have shown that fMRI can also be useful in identifying interactions between brain regions (functional and effective connectivity). Despite the widespread use of fMRI as a research tool, clinical applications of brain connectivity as studied by fMRI are not well established. One possible explanation is the lack of normal pattern, and intersubject variability-two variables that are still largely uncharacterized in most patient populations of interest. In the current study, we combine the identification of functional connectivity networks extracted by using Spearman partial correlation with the use of a one-class support vector machine in order construct a normative database. An application of this approach is illustrated using an fMRI dataset of 43 healthy Subjects performing a visual working memory task. In addition, the relationships between the results obtained and behavioral data are explored. Hum Brain Mapp 30:1068-1076, 2009. (C) 2008 Wiley-Liss. Inc.

The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.

Hypoactive sexual desire disorder in a population-based study of Brazilian women: associated factors classified according to their importance

Objective: The etiology of hypoactive sexual desire disorder (HSDD) is known to be multifactorial, involving biological, psychosexual, and context-related factors. The objective of the present study was to analyze the factors associated with female HSDD and to stratify these factors according to their importance. Methods: This was a population-based, hierarchical study conducted in Brazil, based on data from previous research on the Brazilian Sexual Life Study, conducted between November 2002 and February 2003 in various Brazilian cities. The primary study consisted of a self-administered and anonymous questionnaire, addressing sociodemographic parameters, general health, life habits, behavior, and complaints related to sexual function. The association between HSDD and various other factors was assessed. The data were evaluated by hierarchical multiple regression analysis. Results: The prevalence of HSDD in this sample was 9.5%. Associations were found with cardiovascular disease, breast cancer, posttraumatic stress, poorer education level, being older, being married, a lack of information on sexuality in childhood/adolescence, and a limited sexual repertoire. Women who consumed moderate amounts of alcohol were found to be less likely to have HSDD. Conclusions: Analysis of the associated factors classified in order of importance and analysis of the characteristics of the sexual relationships provide additional information to currently available data on the traditional concepts of HSDD.

Tailoring of physical properties in highly filled experimental nanohybrid resin composites

Objectives. To assess the elastic modulus (EM), volumetric shrinkage (VS), and polymerization shrinkage stress (PSS) of experimental highly filled nanohybrid composites as a function of matrix composition, filler distribution, and density. Methods. One regular viscosity nanohybrid composite (Grandio, VOCO, Germany) and one flowable nanohybrid composite (Grandio Flow, VOCO) were tested as references along with six highly filled experimental nanohybrid composites (four Bis-GMA-based, one UDMA-based, and one Ormocer (R) -based). The experimental composites varied in filler size and density. EM values were obtained from the ""three-point bending"" load-displacement curve. VS was calculated with Archimedes` buoyancy principle. PSS was determined in 1-mm thick specimens placed between two (poly) methyl methacrylate rods (empty set = 6 mm) attached to an universal testing machine. Data were analyzed using oneway ANOVA, Tukey`s test (alpha = 0.05), and linear regression analyses. Results. The flowable composite exhibited the highest VS and PSS but lowest EM. The PSS was significantly lower with Ormocer. The EM was significantly higher among experimental composites with highest filler levels. No significant differences were found between all other experimental composites regarding VS and PSS. Filler density and size did not influence EM, VS, or PSS. Significance. Neither the filler configuration nor matrix composition in the investigated materials significantly influenced composite shrinkage and mechanical properties. The highest filled experimental composite seemed to increase EM by keeping VS and PSS low; however, matrix composition seemed to be the determinant factor for shrinkage and stress development. The Ormocer, with reduced PSS, deserves further investigation. Filler size and density did not influence the tested parameters. (C) 2011 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.