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Different factors have been related with interictal anxiety, reported in 10%-25% of patients with epilepsy. We determined the frequency of interictal anxiety in 196 patients with active epilepsy in a cross-sectional survey to know which symptoms of anxiety were most frequently reported in patients with epilepsy and to analyze the factors associated with their presence. Patients were assessed with the Beck Depression Inventory (BDI), MontgomeryAsberg Depression Rating Scale (MADRS), and the Hamilton Anxiety Scale (HAMA). Data were analyzed with a logistic regression model. The HAMA ratings revealed that 38.8% experienced signifi cant anxiety symptoms, as defi ned by a rating above 18 points. Use of primidone, depression, cryptogenic, and posttraumatic etiologies signifi cantly predicted anxiety after logistic regression. Symptoms related to higher scores on HAMA were anxious mood, tension, insomnia, intellectual function, depressed mood, cardiovascular and genitourinary symptoms. Further studies should be performed to defi ne the role of psychosocial factors in the development and evolution of anxiety among these patients.

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Abstract. Spatial patterns in an image that shows a visual perception of roughness or softness of the surface is known as the texture of the image. Most of the analysis and description of texture found in the literature is based on statistical or structural properties of this attribute [2]. The field of cellular automata (CA), which has been developed mainly to model the dynamical behavior of systems, is based on the behavior or arrangements of pixel values and their neighborhood which, according to some rules behaves in different manners [2,8]. In this paper, within the frame of structural approach, a novel method based on the properties of linear cellular automata is proposed to characterize different sort of textures. To this purpose, it is assumed that a binary version of the image under study was generated by a cellular automata technique. By using this model a number of textural primitives are found which allows the production of a characterizing image. In order to verify the feasibility of the proposed method, texture images generated by CA techniques as well as natural images has been used.

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Abstract. Nowadays, remote sensing is used in many environmental applications, helping to solve and improve the social problems derived from them. Examples of remotely sensed applications include soil quality studies, water resources searching, environmental protection or meteorology simulations. The classification algorithms are one of the most important techniques used in remote sensing that help developers to interpret the information contained in the satellite images. At present, there are several classification processes, i.e., maximum likelihood, paralelepiped or minimum distance classifier. In this paper we investigate a new satellite image classification Algorithm based on Cellular Automata (ACA), a technique usually used by researchers on complex systems. There are not previous works related to satellite image classification with cellular automata. This new kind of satellite image classifier, that improves the results obtained by classical algorithms in several aspects, has been validated and experimented in the SOLERES framework.

Detectando consumo de drogas en adolescentes mediante un programa de simulación 3DABSTRACT: This work presents a new 3d simulation program, called Mii School, and its application to the detection of problem behaviours appearing in school settings. We begin by describing some of the main features of the Mii School program. Then, we present the results of a study in which adolescents responded to Mii School simulations involving the consumption of alcoholic drinks, cigarettes, cannabis, cocaine, and MdMA (ecstasy). We established a "risk profile" based on the observed response patterns. We also present results concerning user satisfaction with the program and the extent to which users felt that the simulated scenes were realistic. Lastly, we discuss the usefulness of Mii School as a tool for assessing drug use in school settings.