Abstract
Long period fiber gratings (LPFGs) were coated with iron (Fe) and exposed to oxidation in air and in water having different concentrations of sodium chloride (NaCl) to detect the formation of iron oxides and hydroxides. The process was monitored in real time by measuring the characteristics of the LPFGs attenuation bands. Thin films of Fe were deposited on top of silica (SiO2) substrates, annealed in air, and exposed to water with NaCl. The composition of the oxide and hydroxide layers was analyzed by SEM/EDS and X-ray diffraction. It observed the formation of oxide phases, Fe3O4 (magnetite), and Fe2O3 (hematite) when annealing in air, and Fe-2(OH)(3) Cl (hibbingite) and FeO(OH) (lepidocrocite) when exposed to water with NaCl. Results shows that Fe-coated LPFGs can be used as sensors for real-time monitoring of corrosion in offshore and in coastal projects where metal structures made of iron alloys are in contact with sea or brackish water. In addition, LPFGs coated with hematite were characterized for sensing, leading to the conclusion that the sensitivity to the refractive index of the surrounding medium can be tuned by proper choice of hematite thickness.

Abstract
Solving the robot localization problem is one of the most necessary requirements for autonomous robots. Several methodologies can be used to determine its location as accurately as possible. What makes this difficult is the existence of uncertainty in the sensing of the robot. The uncertain information needs to be combined in an optimal way. This paper stresses a Kalman filter to combine information from the odometry and Ultra Wide Band Time of Flight distance modules, which lacks the orientation. The proposed system validated in a real developed platform performs the fusion task which outputs position and orientation of the robot. It is used to localize the robot and make a 3 DoF scanning of magnetic field in a room. Other examples can be pointed out with the same localization techniques in service and industrial autonomous robots. © Springer International Publishing AG 2018.

Abstract
This work addresses the lot-sizing and scheduling problem under multistage demand uncertainty. A flexible production system is considered, with the possibility to adjust the size and the schedule of lots in every time period based on a rolling-horizon planning scheme. Computationally intractable multistage stochastic programming models are often employed on this problem. An adaptation strategy to the multistage setting for two-stage programming and robust optimization models is proposed. We also present an approximate heuristic strategy to address the problem more efficiently, relying on multistage stochastic programming and adjustable robust optimization. In order to evaluate each strategy and model proposed, a Monte Carlo simulation experiment under a rolling-horizon scheme is performed. Results show that the strategies are promising in solving large-scale problems: the approximate strategy based on adjustable robust optimization has, on average, 6.72% better performance and is 7.9 times faster than the deterministic model.

Abstract
In order to avoid voltage problems derived from the connection of large amounts of renewable-based energy generation to distribution networks, new advanced tools need to be developed that are able to exploit the presence of Distributed Energy Resources (DER). This paper describes the approach proposed for a predictive voltage control algorithm to be used in LV distribution networks in order to make use of available flexibilities from domestic consumers via their Home Energy Management System (HEMS) and more traditional Distribution System Operator's (DSO's) resources, such as transformers with On-Load Tap Changer (OLTC) and storage devices. The proposed algorithm for the Low Voltage Control (LVC) is detailed in this paper. The algorithm was then tested through simulation using a representative Portuguese Low Voltage (LV) network in order to assess its performance in several future scenarios with different operating conditions. The future prospects for field-trial validation in a Portuguese smart grids pilot are also discussed.

Abstract
The Weighted Policy Learner (WPL) algorithm has been shown to converge to Nash Equilibria (NE) in several challenging environments with minimum knowledge. However, WPL has trouble converging to deterministic strategies, since the policy update rate approaches zero. We propose a new update rule that bounds this update rate such that, in pure NE games, the algorithm’s speed is not slowed down, while its behavior in stochastic NE games remains unchanged. We demonstrate our proposal’s behavior in several common game-theoretic environments (with stochastic and deterministic equilibrium policies), in complex maze-related games (where some actions dominate others in most states), against the original WPL as well as other state of the art algorithms. We draw conclusions over the benefits of our solution and its advantages. © Springer Nature Switzerland AG 2019.

Abstract
Foreseen climate change points to shifts in agricultural production patterns worldwide, which may impact ecosystems directly, as well as the economic and cultural contexts of the wine industry. Moreover, the combined effects of environmental threats (light, temperature, and water relations) at different scales are expected to impair natural grapevine mechanisms, decreasing yield and the quality of grapes. Hence, the interaction between several factors, such as climate, terroir features, grapevine stress responses, site-specific spatial-temporal variability, and the management practices applied, which represents and effective challenge for sustainable Mediterranean viticulture, allowed researchers to develop adaptive strategies to cope with environmental stresses. Here, we review the effects of abiotic stresses on Mediterranean-like climate viticulture and the impacts of summer stress on grapevine growth, yield, and quality potential, as well as the subsequent plant responses and the available adaptation strategies for winegrowers and researchers. Our main findings are as follows: (1) environmental stresses can trigger dynamic responses in grapevines, comprising photosynthesis, phenology, hormonal balance, berry composition, and the antioxidant machinery; (2) field research methodologies, laboratory techniques, and precision viticulture are essential tools to evaluate grapevine performance and the potential quality for wine production; and (3) advances in the existing adaptation strategies are vital to maintain sustainability and regional wine identity in a changing climate. Also, these topics suggest that rational and focused management of grapevines may enlighten grapevine summer stress responses and improve the resilience of agro-ecosystems under harsh conditions. Despite the challenge of developing different strategic responses, winegrowers should clearly define their objectives, so applied research can provide rational technical support for the decision making process towards sustainable viticulture.