Abstract
We consider linear sampled data dynamical systems subject to additive and bounded disturbances, and study properties of their forward and backward reach sets as well as robust positively invariant sets. We propose topologically compatible notions for the sampled data forward and backward reachability as well as robust positive invariance. We also propose adequate notions for maximality and minimality of related robust positively invariant sets.

Abstract
With the collapse of communism, some former communist States of Eastern Europe managed to muddle through their way to a market economy and entered the European Union. This brought about the acceleration of Foreign Direct Investment (FDI) among the European economies and accelerated the globalization process. Although there is plenty of research on FDI and trade among countries, the aim of this chapter is to analyze how trade between Portugal and the Czech Republic have evolved over form 2000 until 2015. The chapter seeks to complement previous studies on FDI and trade as Portugal and the Czech Republic are part of the European Union, but have had different historical, cultural, and economic paths. The main conclusion of the chapter is that trade between both countries has grown significantly. The main reason affecting trade between both countries is the economic unrest Portugal has been through since 2008. © 2017 by IGI Global.

Abstract
The general energy demand of the residential sector and the ensuing option for fossil fuels produce adverse results by both CO2, greenhouse gases (GHG) and extra air pollutant emissions. As domestic energy demand consists mostly of energy necessities for space and water heating alongside the energy dedicated for appliances, distinct strategies that target to foment a practical consumption of energy have to be reinforced at all levels of human activity. In this paper the aim is to make a comparison between proportional-integral-derivative (PID), thermostat (ON/OFF) control and Model Predictive Control (MPC) models of a domestic heating, ventilation and air conditioning (HVAC) system controlling the temperature of a room. The model of the household with local solar microgeneration is implicit to be located in a Portuguese city. The house of the case study is at the mercy to the local solar temperature, irradiance and 5 Time-of-Use (ToU) electricity rates applied on a complete week of August, 2016. The second purpose of this study is to assess which is the best electricity ToU rate option provided by the local electricity retailer for the residential sector.

Abstract
Prior statistical knowledge of atmospheric turbulence is essential for designing, optimizing and evaluating tomographic adaptive optics systems. We present the statistics of the vertical profiles of CN2 and the outer scale at Maunakea estimated using a SLOpe Detection And Ranging (SLODAR) method from on-sky telemetry taken by a multi-object adaptive optics (MOAO) demonstrator, called RAVEN, on the Subaru telescope. In our SLODAR method, the profiles are estimated by fitting the theoretical autocorrelations and cross-correlations of measurements from multiple Shack-Haltmann wavefront sensors to the observed correlations via the non-linear Levenberg-Marquardt Algorithm (LMA). The analytical derivatives of the spatial phase structure function with respect to its parameters for the LMA are also developed. From a total of 12 nights in the summer season, a large ground CN2 fraction of 54.3 per cent is found, with median estimated seeing of 0.460 arcsec. This median seeing value is below the results for Maunakea from the literature (0.6-0.7 arcsec). The average CN2 profile is in good agreement with results from the literature, except for the ground layer. The median value of the outer scale is 25.5 m and the outer scale is larger at higher altitudes; these trends of the outer scale are consistent with findings in the literature.

Abstract
In recent years, we have been witnessing a real explosion of information, due in large part to the development in Information and Knowledge Technologies (ICTs). As in-formation is the raw material for the discovery of knowledge, there has been a rapid growth, both in the scientific community and in ICT itself, in the approach and study of the phenomenon called Big Data (BD) [1]. The concept of Smart Grids (SG) has emerged as a way of rethinking how to produce and consume energy imposed by economic, political and ecological issues [2]. To become a reality, SGs must be sup-ported by intelligent and autonomous IT systems, to make the right decisions in real time. Knowledge needed for real-time decision-making can only be achieved if SGs are equipped with systems capable of efficiently managing all the information sur-rounding their ecosystem. Multi-Agent systems have been increasingly used from this purpose. This work proposes a system for the management of information in the context of agent based SG to enable the monitoring, in real time, of the events that occur in the ecosystem and to predict upcoming events.

Abstract
We address the problem of generating electricity through Underwater Kite Power Systems. For this problem, we develop an optimal control problem formulation using a continuous-time model of the kite to devise the trajectories and controls for the kite that maximize the total energy produced in a given time interval. This is an highly nonlinear problem for which the optimization is challenging. We also develop a numerical solution scheme for the optimal control problem based on direct methods and on adaptive time-mesh refinement. We report results that show that the problem can be quickly solved with a high level of accuracy when using our adaptive mesh refinement strategy. The results confirm the values of electrical power that can be produced with such device.