Abstract
The Portuguese governmental network comprising all the 776 ministers and junior ministers who were part of the 19 governments between the year 1976 and 2013 is presented and analyzed. The data contain information on connections concerning business and other types of organizations and, to our knowledge, there is no such extensive research in previous literature. Upon the presentation of the data, a social network analysis considering the temporal dimension is performed at three levels of granularity: network-level, subnetwork-level (political groups) and node-level. A discussion based on the results is presented. We conclude that although it fits two of the four preconditions of a small-world model, the Portuguese governmental network is not a small-world network, although presenting an evolution pointing toward becoming one. Also, we use a resilience test to study the evolution of the robustness of the Portuguese governmental network, pinpointing the moment when a set of members became structurally important.

Abstract
Este projeto de investigação, em fase de desenvolvimento, visa conceber e implementar a Gamificação de uma rede social académica baseada na plataforma Ellg customizada. A revisão da literatura sobre gamificação em educação evidencia factores de impacto na aprendizagem e envolvimento dos indivíduos. potenciando o desenvolvimento de comunidades e de aprendizagem social. A comunicação pretende descrever o desenvolvimento e a implementação de um projeto de gamificação no ensino superior, as suas fases e desenvolvimento de um protótipo e as expetativas de implementação na plataforma. Fundamentando-se na investigação sobre Comunidades e o modelo COI, na Aprendizagem Social e na Gamificação e o seu uso em Educação, apresenta-se o contexto, as fases do projeto e uma breve apresentação dos resultados já obtidos.

Abstract
Over the last few years the Laboratoire d'Astrophysique de Marseille (LAM) has been heavily involved in R&D for adaptive optics systems dedicated to future large telescopes, particularly in preparation for the European Extremely Large Telescope (E-ELT). Within this framework an investigation into a Pyramid wave-front sensor is underway. The Pyramid sensor is at the cutting edge of high order, high precision wave-front sensing for ground based telescopes. Investigations have demonstrated the ability to achieve a greater sensitivity than the standard Shack-Hartmann wave-front sensor whilst the implementation of a Pyramid sensor on the Large Binocular Telescope (LBT) has provided compelling operational results.1, 2 The Pyramid now forms part of the baseline for several next generation Extremely Large Telescopes (ELTs). As such its behaviour under realistic operating conditions must be further understood in order to optimise performance. At LAM a detailed investigation into the performance of the Pyramid aims to fully characterise the behaviour of this wave-front sensor in terms of linearity, sensitivity and operation. We have implemented a Pyramid sensor using a high speed OCAM2 camera (with close to 0 readout noise and a frame rate of 1.5kHz) in order to study the performance of the Pyramid within a full closed loop adaptive optics system. This investigation involves tests on all fronts, from theoretical models and numerical simulations to experimental tests under controlled laboratory conditions, with an aim to fully understand the Pyramid sensor in both modulated and non-modulated configurations. We include results demonstrating the linearity of the Pyramid signals, compare measured interaction matrices with those derived in simulation and evaluate the performance in closed loop operation. The final goal is to provide an on sky comparison between the Pyramid and a Shack-Hartmann wave-front sensor, at Observatoire de la Côte d'Azur (ONERA-ODISSEE bench). Here we present the adaptive optics setup at LAM and latest experimental and modelling results. The loop is closed on different static wave-front errors: The initial shape of the deformable mirror (DM) and a turbulent-like shape projected onto the DM. The results demonstrate a Pyramid closed loop performance of 7-8nm rms wave-front error compared to a reference at surface.

Abstract

Abstract
Object representation is one of the most challenging tasks in robotics because it must provide reliable information in real-time to enable the robot to physically interact with the objects in its environment. To ensure robustness, a global object descriptor must be computed based on a unique and repeatable object reference frame. Moreover, the descriptor should contain enough information enabling to recognize the same or similar objects seen from different perspectives. This paper presents a new object descriptor named Global Orthographic Object Descriptor (GOOD) designed to be robust, descriptive and efficient to compute and use. We propose a novel sign disambiguation method, for computing a unique reference frame from the eigenvectors obtained through Principal Component Analysis of the point cloud of the target object view captured by a 3D sensor. Three principal orthographic projections and their distribution matrices are computed by exploiting the object reference frame. The descriptor is finally obtained by concatenating the distribution matrices in a sequence determined by entropy and variance features of the projections. Experimental results show that the overall classification performance obtained with GOOD is comparable to the best performances obtained with the state-of-the-art descriptors. Concerning memory and computation time, GOOD clearly outperforms the other descriptors. Therefore, GOOD is especially suited for real-time applications. The estimated object's pose is precise enough for real-time object manipulation tasks.

Abstract
In order to support the intensive development of agricultural crops and, in particular the floricultural inside a greenhouse, with the perspective of a quick distribution in the market, increasing the economic benefits and supported on efficient and intelligent management systems energy, it is mandatory to conceive a model based on Cyber-Physical Systems (CPS) This implies, accordingly, increases in renewable primary energy sources utilization coupled with sensing technologies, include developments on Internet of Things (IoT) and Cloud Computing (CC), supported with Information and Communication Technologies (ICT) that will lead to new architectural approach applied to a proposed energy system, based on a sustainable and more engineering autonomous process. This work comes up with a new energy model that retrofits the system of a greenhouse supported with multiple sensors in one grid, to expand into CPS concept to manage sensors and controllers that will improve a profitable energy system.