Abstract
Echocardiography assessment of cardiac valves plays a vital role in the diagnosis of rheumatic heart disease. In the vast majority of cases, the mitral valve gets affected, leading to the thickening of its leaflets that may result in the fusion of their tips. This changes the appearance and reduces the mobility of the leaflets, which also reduce the heart efficiency. Quantifying such parameters provides diagnostic insight. To achieve that, the first step is to identify and then track fast moving leaflets. This work is focused on Anterior Mitral Leaflet (AML) tracking. Open ended active contours are employed in this work by removing its boundary conditions. The external and internal energy of the contour is modified that extend the capture range, improve snake energy and encourages the leftmost end point of the contour to converge on the moving tip of the AML. Results show that contour points are tracked accurately with an average error of 4.9 pixels and a standard deviation of 2.1 pixels in 9 fully annotated normal sequences of real children clinical assessments.

Abstract
Coefficient diagram method is a controller design technique for linear time-invariant systems. This design procedure occurs into two different domains: an algebraic and a graphical. The former is closely paired to a conventional pole placement method and the latter consists on a diagram whose reading from the plotted curves leads to insights regarding closed-loop control system time response, stability and robustness. The controller structure has two degrees of freedom and the design process leads to both low overshoot closed-loop time response and good robustness performance regarding mismatches between the real system and the design model. This article presents an overview on this design method. In order to make more transparent the presented theoretical concepts, examples in Matlab (R) code are provided. The included code illustrates both the algebraic and the graphical nature of the coefficient diagram design method.

Abstract
The aim of this work is to give an overview on the development of theoretical concepts and methodological approaches to investigate innovation networks, in particular the use of social network analysis in the study of university industry relations. The structure of networks can be analysed through the lens of Social Network Analysis. This methodological approach is described and its fundamental concepts are presented. The paper then reviews the applications of this approach on the study of university industry relations. These relations can be considered as an innovation network, in the sense that the interactions established by its participants have more or less defined innovation goals. Different structures in the relations may result in different innovation outcomes, and the use of SNA may be particularly useful to understand differential outcomes. It is thus important to take stock of the knowledge concerning the efforts that have been made to probe the complex phenomena of university industry relations and, in particular, how approaches based on social network analysis have been used to understand it. This work is based on a review of available literature on the topics. The paper aims at systematizing the information and knowledge related to the application of SNA on university industry networks, highlighting the main research pathways, the main conclusions and pointing possible future research questions.

Abstract
Probabilistic Inductive Logic Programming (PILP) systems extend ILP by allowing the world to be represented using probabilistic facts and rules, and by learning probabilistic theories that can be used to make predictions. However, such systems can be inefficient both due to the large search space inherited from the ILP algorithm and to the probabilistic evaluation needed whenever a new candidate theory is generated. To address the latter issue, this work introduces probability estimators aimed at improving the efficiency of PILP systems. An estimator can avoid the computational cost of probabilistic theory evaluation by providing an estimate of the value of the combination of two subtheories. Experiments are performed on three real-world datasets of different areas (biology, medical and web-based) and show that, by reducing the number of theories to be evaluated, the estimators can significantly shorten the execution time without losing probabilistic accuracy.

Abstract

Abstract
O artigo discute a importância da indústria de petróleo para a economia do estado do Rio de Janeiro e municípios produtores. Através de dados, mostra o papel que o boom das commodities teve sobre a dinâmica econômica fluminense. Por fim, apresenta questõe