Oxidative stress markers, cognitive functions, and psychosocial functioning in bipolar disorder: an empirical cross-sectional study

This study aimed to evaluate the relationship between oxidative stress markers and cognitive functions and domains of psychosocial functioning in bipolar disorder.

Fitting triangular norms to empirical data

This chapter discusses some specific tools that can be used to build triangular norms based on a finite number of (possibly noisy) observations. Such problem arises in applications, when observed data (e.g., decision patterns of experts) need to be modelled with a special class of functions, such as triangular norms. We show how this problem can be transformed into a constrained regression problem, and then efficiently solved. We also discuss related operators: uninorms, nullnorms and associative copulas.

Female labour force participation, fertility and infant mortality in Australia : some empirical evidence from Granger causality tests

This study applies Granger causality tests within a multivariate error correction framework to examine the relationship between female participation rates, infant mortality rates and fertility rates for Australia using annual data from 1960 to 2000. Decomposition of variance and impulse response functions are also considered. The main findings are twofold. First, in the short run there is unidirectional Granger causality running from the fertility rate to female labour force participation and from the infant mortality rate to female labour force participation while there is neutrality between the fertility rate and infant mortality rate. Second, in the long run both the fertility rate and infant mortality rate Granger cause female labour participation.

Prison officer's beliefs regarding self-harm in prisoners : an empirical investigation

The prevention of self-harm and suicide in prisoners depends on good interaction between the individual prisoner and prison staff. Staff perceptions of prisoner self-harm are likely to be a crucial factor influencing this interaction. The aim of the present study was to determine correctional officers' perception of the causes and functions of self-harm, and the effects of incident severity and repetitiveness on perceptions. A sample of 76 correctional officers was presented with a vignette depicting a self-harm in which the severity and repetitiveness of the incident was systematically altered. Officers' rated both the causes and functions of the behaviour. Four attributional dimensions were identified by factor analysis. These factors related primarily to personal factors about the individual prisoner. Staff perceived the functions of self-harm to be communicative rather than to commit suicide. Perceptions were not affected by severity or repetitiveness information, except for high severity leading to a greater perception of suicidal intent. Initiatives to help staff work more effectively and therapeutically with distressed prisoners are therefore likely to impact positively upon rates of self-harm.

Construction of k-Lipschitz triangular norms and conorms from empirical data

This paper examines the practical construction of k-Lipschitz triangular norms and conorms from empirical data. We apply a characterization of such functions based on k-convex additive generators and translate k-convexity of piecewise linear strictly decreasing functions into a simple set of linear inequalities on their coefficients. This is the basis of a simple linear spline-fitting algorithm, which guarantees k-Lipschitz property of the resulting triangular norms and conorms.

Dipole time correlation functions of the Stockmayer fluid in the microcanonical and canonical ensembles

Computer simulations of Stockmayer fluids were performed to generate dipole time correlation functions (TCF) at three temperatures and three dipole moments in both the microcanonical and canonical ensembles. The effect of Nosé constant-temperature dynamics on time-dependent quantities is discussed, and empirical results are given to show that the choice of thermal inertia parameter influences the speed with which a system moves through its phase space. The time correlation functions from the simulations were analyzed in terms of current theories for dipolar systems. A functional form is proposed to cover both the longtime and short-time behavior of the time correlation functions of dipoles. The relationship between this functional form and the dielectric function of the Stockmayer system is also discussed.

Developing an empirical algorithm for protecting text-based CAPTCHAs against segmentation attacks

In this paper, we aim to provide an effective and efficient method to generate text-based Captchas which are resilient against segmentation attack. Different to the popular industry practice of using very simple color schemes, we advocate to use multiple colors in our Captchas. We adopt the idea of brush and canvas when coloring our Captchas. Furthermore, we choose to use simple accumulating functions to achieve diffusion on painted colors and DES encryption to achieve a good level of confusion on the brush pattern. To facilitate ordinary users and developers, we propose an empirical algorithm with support of Taguchi method to guarantee the quality of the chosen color schemes. Our proposed methodology has at least three advantages — 1) the settings of color schemes can be fully customized by the user or developer; 2) the quality of selected colors have desirable statistical features that are ensured by Taguchi method; 3) the algorithm can be fully automated into computer programs. Moreover, our included examples and experiments prove the practicality and validity of our algorithm.

Fitting aggregation functions to data: part I-linearization and regularization

The use of supervised learning techniques for fitting weights and/or generator functions of weighted quasi-arithmetic means – a special class of idempotent and nondecreasing aggregation functions – to empirical data has already been considered in a number of papers. Nevertheless, there are still some important issues that have not been discussed in the literature yet. In the first part of this two-part contribution we deal with the concept of regularization, a quite standard technique from machine learning applied so as to increase the fit quality on test and validation data samples. Due to the constraints on the weighting vector, it turns out that quite different methods can be used in the current framework, as compared to regression models. Moreover, it is worth noting that so far fitting weighted quasi-arithmetic means to empirical data has only been performed approximately, via the so-called linearization technique. In this paper we consider exact solutions to such special optimization tasks and indicate cases where linearization leads to much worse solutions.

Fitting aggregation functions to data: Part II - idempotization

The use of supervised learning techniques for fitting weights and/or generator functions of weighted quasi-arithmetic means – a special class of idempotent and nondecreasing aggregation functions – to empirical data has already been considered in a number of papers. Nevertheless, there are still some important issues that have not been discussed in the literature yet. In the second part of this two-part contribution we deal with a quite common situation in which we have inputs coming from different sources, describing a similar phenomenon, but which have not been properly normalized. In such a case, idempotent and nondecreasing functions cannot be used to aggregate them unless proper preprocessing is performed. The proposed idempotization method, based on the notion of B-splines, allows for an automatic calibration of independent variables. The introduced technique is applied in an R source code plagiarism detection system.