Abstract
In this paper, a novel hybrid single-objective metaheuristic, the so called C-DEEPSO (Canonical Differential Evolutionary Particle Swarm Optimization), is proposed and tested. C-DEEPSO can be viewed as an evolutionary algorithm with recombination rules borrowed from PSO, or a swarm optimization method with selection and self-adaptiveness properties proper from DE. A case study on the problem of optimal control for reactive sources in energy production by Wind Power Plants (WPP), solved by means of Optimal Power Flow (OPF-like), is used to test the new hybrid algorithm and to evaluate its performance. C-DEEPSO is compared to the baseline algorithm, DEEPSO, and to a reference algorithm, Mean-Variance Mapping Optimization (MVMO). The experiments indicate that the proposed algorithm is efficient and competitive, capable to tackle this large-scale problem. The results also show that the new approach exhibits better results, when compared to MVMO.

Abstract
Power systems worldwide are complex and challenging environments. The increasing necessity for an adequate integration of renewable energy sources is resulting in a rising complexity in power systems operation. Multi-agent based simulation platforms have proven to be a good option to study the several issues related to these systems, including the involved players that act in this domain. To take better advantage of these systems, their integration is mandatory. The main contribution of this paper is the development of the Electricity Markets Ontology, which integrates the essential concepts necessary to interpret all the available information related to electricity markets, while enabling an easier cooperation and adequate communication between related systems. Additionally, the concepts and rules defined by this ontology can be extended and complemented according to the needs of other simulation and real systems in this area. Each system's particular ontology must import the proposed ontology, thus enabling the effective interoperability between independent systems.

Abstract
The hierarchical control scheme for three phase parallel connected voltage source inverters (VSI), forming a low voltage AC MicroGrid (MG)is presented and analyzed in this paper. The proposed control scheme consists of two controllers, a local controller and a centralized controller. The local controller consists of inner control loops that are composed by a voltage and current proportional resonant controllers with selective harmonics compensation, and the power sharing controller that includes the droop control and the virtual output impedance loops in order to share properly the active and reactive power between the connected VSIs. In this system, the centralized controller is designed to restore the magnitude and the frequency deviations of the AC bus voltage produced by the power sharing controller. Simulation results for three parallel connected VSIs forming a low voltage AC MG that operates in islanded mode are provided to show the effectiveness of the proposed control scheme. Active and reactive power are properly shared as well as good harmonics compensation is achieved when both linear and non-linear loads are connected to the load bus.

Abstract
The actual flexibility of the electricity sector, with a distributed nature and new players, such as the smart grid operator and several types of aggregators, brings new business models and introduces new challenges from the power systems technical operation point of view. In this context, the Network Operator Agent of the Multi-Agent Simulator of Competitive Electricity Markets ( MASCEM) plays a crucial role, not only in the scope of the technical validation of the economic transactions established by the market, but also has an agent that can be supporting the grid operation under the scope of a smart grid. A set of new features has been added to the Network Operator making it a "new agent", bringing a more effective decision support, from the grid technical operation point of view, and achieving its usefulness beyond MASCEM. In this paper the new features are described. A case study is also included to better illustrate the approach and to highlight its usefulness under the scope of a smart grid scenario.

Abstract
Nowadays, online communities are becoming an important resource for health consumers who want to retrieve and share information about health subjects. These communities have the potential to influence patients' health behaviors and increase their engagement with therapies. However, the interaction dynamics in this type of media remains poorly understood what might hinder the development of strategies that facilitate and encourage participation. Social Network Analysis is a technique that tries to expose the hidden channels of communication and information flow, leading to a better understanding of how members relate to each other on online social network. In this study we do a systematic review of the literature regarding the apply this technique in the study of online health communities. We show that this type of studies is scarce and that, in this domain, Social Network Analysis is mainly applied to identify influential key members, as well as the most active members in terms of posting or answering questions.

Abstract
After carrying out a revision of the literature on the enhancement of Er3+ diffusion in LiNbO3 crystals by Er3+/Ti4+ co-diffusion and analyzing our own experimental results, we conclude that no reproducible results were reported, meaning that further research on this subject is necessary.