Abstract
The problem of reconfiguration for active distribution systems is formulated as a stochastic mixed-integer second-order conic programming (MISOCP) model that simultaneously considers the minimization of energy power losses and CO2 emissions. The solution of the model determines the optimal radial topology, the operation of switchable capacitor banks, and the operation of dispatchable and non - dispatchable distributed generators. A stochastic scenario-based model is considered to handle uncertainties in load behavior, solar irradiation, and energy prices. The optimal solution of this model can be reached with a commercial solver; however, this is not computationally efficient. To tackle this issue a novel methodology which explores the efficiency of classical optimization techniques and heuristic based on neighborhood structures, referred as matheuristic algorithm is proposed. In this algorithm. the neighborhood search is carried out using the solution of reduced MISOCP models that are obtained from the original formulation of the problem. Numerical experiments are performed using several systems to compare the performance of the proposed matheuristic against the direct solution by the commercial solver CPLEX. Results demonstrate the superiority of the proposed methodology solving the problem for large-scale systems.

Abstract
This article presents a study on web accessibility in the health sector in Portugal. For this, 253 pages were automatically analyzed, among the various health actors: public and private institutions, health subsystems, insurance companies, pharmacies, pharmacists and informational websites. Following the Web Content Accessibility Guidelines 2.1, we seek to understand the importance and potential of accessibility today, particularly in the health sector. Once the main errors have been identified, improvements and clues for future work are pointed out.

Abstract
Berth allocation problem (BAP) is concerned to assign ships to port terminal positions, seeking to minimize the total service time and maximize the quay occupation. A dynamic model with special features is developed to deal with real scenarios from Port Administration of Paranaguá and Antonina (APPA), located on the Brazilian coast. To solve the problem, this work proposes two metaheuristics comprise by a novel combination of genetic algorithm and an approximated dynamic programming employed as a local search. Two heuristics for solution space reductions, a confinement procedure in a reduced neighborhood, known as Corridor Method, and an elimination process for unpromising solution regions are designed for local search approach. Case studies present a problem complexity discussion and comparative analysis of the metaheuristics regarding two standard genetic algorithms. The computational experiments explore the optimal solutions for small instances and the best results, solutions variability, and probabilistic plots resorting by ten instances based on real data available by APPA. The results show the reliability of the metaheuristics to deal with large instances and tight schedules in busy port systems.

Abstract
The increasing penetration of renewable electricity generation is complicating the bidding and estimating processes of electricity prices, partly due to the shift of the overall cost sensitivity from operation (fuel) costs to investment costs. However, cost minimization models for capacity expansion are frequently based on the principle that, for a perfectly adapted system allowing non-served energy, marginal remuneration allows overall operation and investments costs recovery. In addition, these models are usually formulated as finite-horizon problems when they should be theoretically solved for infinite horizons under the assumption of companies' infinite lifespan, but infinite horizon cannot be dealt with mathematical programming since it requires finite sets. Previous approaches have tried to overcome this drawback with finite horizon models that tend asymptotically to the original infinite ones and, in many cases, the investment costs are annualized based on the plants' lifespan, sometimes including a cost residual value. This paper proposes a novel approach with a finite horizon that guarantees the investment costs' recovery. It is also able to obtain the marginal electricity costs of the original infinite horizon model, without the need for residual values or non-served energy. This new approach is especially suited for long-term electricity pricing with investments in renewable assets when non-served demand is banned or when no explicit capacity remuneration mechanisms are considered.

Abstract
The Smart Transformer (ST) is being envisioned as the possible backbone of future distribution grids given the enhanced controllability it provides. Moreover, the ST offers DC-link connectivity, making it an attractive solution for the deployment of hybrid AC/DC distribution grids which offer important advantages for the deployment of Renewable Energy Sources, Energy Storage Systems (ESSs) and Electric Vehicles. However, compared to traditional low-frequency magnetic transformers, the ST is inherently more vulnerable to fault disturbances which may force the ST to disconnect in order to protect its power electronic converters, posing important challenges to the hybrid AC/DC grid connected to it. This paper proposes a Fault-Ride-Through (FRT) strategy suited for grid-tied ST with no locally available ESS, which exploits a dump-load and the sensitivity of the hybrid AC/DC distribution grid's power to voltage and frequency to provide enhanced control to the ST in order to handle AC-side voltage sags. The proposed FRT strategy can exploit all the hybrid AC/DC distribution grid (including the MV DC sub-network) and existing controllable DER resources, providing FRT against balanced and unbalanced faults in the upstream AC grid. The proposed strategy is demonstrated in this paper through computational simulation.

Abstract
The European Structural and Investment Funds (ESIF) represent the main instrument of European Cohesion Policy to sustain territorial development and to eliminate regional disparities between the EU member states. The study of the impacts of ESIF on the economic growth and development of EU members has gained increasing attention in the academic community, and there has been significant scientific production on this topic. This study consists of a bibliometric analysis of articles published in the period from 2011 to 2020 and indexed in two of the main scientific databases: Web of Science (WoS) and Scopus. The results of the bibliometric analysis point to relevant trends on the subject, such as the growing number of publications over the years; the great concentration of studies applied in Central and Eastern European (CEE) countries, namely Romania; and the current interest of researchers in important topics associated with European funds, such as the competitiveness and innovation of SMEs, climate change, economic impact of global crises, sustainable development, institutional capacity of organisations, and cross-border cooperation.