Formal derivation of finite state machines for class testing

Previous work on generating state machines for the purpose of class testing has not been formally based. There has also been work on deriving state machines from formal specifications for testing non-object-oriented software. We build on this work by presenting a method for deriving a state machine for testing purposes from a formal specification of the class under test. We also show how the resulting state machine can be used as the basis for a test suite developed and executed using an existing framework for class testing. To derive the state machine, we identify the states and possible interactions of the operations of the class under test. The Test Template Framework is used to formally derive the states from the Object-Z specification of the class under test. The transitions of the finite state machine are calculated from the derived states and the class's operations. The formally derived finite state machine is transformed to a ClassBench testgraph, which is used as input to the ClassBench framework to test a C++ implementation of the class. The method is illustrated using a simple bounded queue example.

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.

A new chemorheological analysis of highly filled thermosets used in integrated circuit packaging

Chemorheology (and thus process modeling) of highly filled thermosets used in integrated circuit (IC) packaging has been complicated by their highly filled nature, fast kinetics of curing, and viscoelastic nature. This article summarizes a more thorough chemorheological analysis of a typical IC packaging thermoset material, including novel isothermal and nonisothermal multiwave parallel-plate chemorheology. This new chemorheological analysis may be used to optimize existing and design new IC packaging processes. (C) 1997 John Wiley & Sons, Inc.

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.