Abstract
Construction of LEGO models is a popular hobby, not only among children and young teenagers, but also for adults of all ages. Following the technological evolution and the integration of computers into the everyday life, several applications for virtual LEGO modelling have been created. However, these applications generally have interfaces based on windows, icons, menus and pointing devices, the so-called WIMP interfaces, thus being unnatural and hard-to-use for many users. Taking advantage of new trends in of interaction paradigms we developed an innovative solution for virtual LEGO modelling using a horizontal multi-touch surface. To achieve better results, we selected the most common virtual LEGO applications and performed a comparative study, identifying advantages and disadvantages of each one. In this paper we briefly present that study and describe the application developed upon it.

Abstract
Pectus excavatum is the most common congenital deformity of the anterior chest wall, in which several ribs and the sternum grow abnormally. Nowadays, the surgical correction is carried out in children and adults through Nuss technic. This technic has been shown to be safe with major drivers as cosmesis and the prevention of psychological problems and social stress. Nowadays, no application is known to predict the cosmetic outcome of the pectus excavatum surgical correction. Such tool could be used to help the surgeon and the patient in the moment of deciding the need for surgery correction. This work is a first step to predict postsurgical outcome in pectus excavatum surgery correction. Facing this goal, it was firstly determined a point cloud of the skin surface along the thoracic wall using Computed Tomography (before surgical correction) and the Polhemus FastSCAN (after the surgical correction). Then, a surface mesh was reconstructed from the two point clouds using a Radial Basis Function algorithm for further affine registration between the meshes. After registration, one studied the surgical correction influence area (SCIA) of the thoracic wall. This SCIA was used to train, test and validate artificial neural networks in order to predict the surgical outcome of pectus excavatum correction and to determine the degree of convergence of SCIA in different patients. Often, ANN did not converge to a satisfactory solution (each patient had its own deformity characteristics), thus invalidating the creation of a mathematical model capable of estimating, with satisfactory results, the postsurgical outcome.

Abstract
The relation between patient and physician in most modern Health Care Systems is sparse, limited in time and very inflexible. On the other hand, and in contradiction with several recent studies, most physicians do not rely their patient diagnostics evaluations on intertwined psychological and social nature factors. Facing these problems and trying to improve the patient/physician relation we present a mobile health care solution to improve the interaction between the physician and his patients. The solution serves not only as a privileged mean of communication between physicians and patients but also as an evolutionary intelligent platform delivering a mobile rule based system.

Abstract
Protein aggregation became a widely accepted marker of many polyQ disorders, including Machado-Joseph disease (MJD), and is often used as readout for disease progression and development of therapeutic strategies. The lack of good platforms to rapidly quantify protein aggregates in a wide range of disease animal models prompted us to generate a novel image processing application that automatically identifies and quantifies the aggregates in a standardized and operator-independent manner. We propose here a novel image processing tool to quantify the protein aggregates in a Caenorhabditis elegans (C. elegans) model of MJD. Confocal microscopy images were obtained from animals of different genetic conditions. The image processing application was developed using MeVisLab as a platform to process, analyse and visualize the images obtained from those animals. All segmentation algorithms were based on intensity pixel levels. The quantification of area or numbers of aggregates per total body area, as well as the number of aggregates per animal were shown to be reliable and reproducible measures of protein aggregation in C. elegans. The results obtained were consistent with the levels of aggregation observed in the images. In conclusion, this novel imaging processing application allows the non-biased, reliable and high throughput quantification of protein aggregates in a C. elegans model of MJD, which may contribute to a significant improvement on the prognosis of treatment effectiveness for this group of disorders.

Abstract
The integration and composition of software systems requires a good architectural design phase to speed up communications between (remote) components. However, during implementation phase, the code to coordinate such components often ends up mixed in the main business code. This leads to maintenance problems, raising the need for, on the one hand, separating the coordination code from the business code, and on the other hand, providing mechanisms for analysis and comprehension of the architectural decisions once made. In this context our aim is at developing a domain-specific language, CoordL, to describe typical coordination patterns. From our point of view, coordination patterns are abstractions, in a graph form, over the composition of coordination statements from the system code. These patterns would allow us to identify, by means of pattern-based graph search strategies, the code responsible for the coordination of the several components in a system. The recovering and separation of the architectural decisions for a better comprehension of the software is the main purpose of this pattern language.

Abstract
Laparoscopy is a surgical procedure on which operations in the abdomen are performed through small incisions using several specialized instruments. The laparoscopic surgery success greatly depends on surgeon skills and training. To achieve these technical high-standards, different apprenticeship methods have been developed, many based on in vivo training, an approach that involves high costs and complex setup procedures. This paper explores Virtual Reality (VR) simulation as an alternative for novice surgeons training. Even though several simulators are available on the market claiming successful training experiences, their use is extremely limited due to the economic costs involved. In this work, we present a low-cost laparoscopy simulator able to monitor and assist the trainee's surgical movements. The developed prototype consists of a set of inexpensive sensors, namely an accelerometer, a gyroscope, a magnetometer and a flex sensor, attached to specific laparoscopic instruments. Our approach allows repeated assisted training of an exercise, without time constraints or additional costs, since no human artificial model is needed. A case study of our simulator applied to instrument manipulation practice (hand-eye coordination) is also presented. © 2011 IEEE.