Abstract
In the coming years, many countries are going to bet on the exploitation of offshore wind energy. This is the case of southern European countries, where there is great wind potential for offshore exploitation. Although the conditions for energy production are more advantageous, all the costs involved are substantially higher when compared to onshore. It is, therefore, crucial to maximize system efficiency. In this paper, an optimization model based on a Mixed-Integer Linear Programming model is proposed to find the best wind turbines location in offshore wind farms taking into account the wake effect. A case study, concerning the design of an offshore wind farm, were carried out and several performance indicators were calculated and compared. The results show that the placement of the wind turbines diagonally presents better results for all performance indicators and corresponds to a lower percentage of energy production losses.

Abstract
Teaching project management and industrial optimization to engineering students requires real-world experiences in which they can explicitly integrate, apply and develop work-ready skills, such as critical thinking, communication, and teamwork. This paper presents an exploratory case study research describing an online Project-based Learning (PjBL) experience aimed at tackling the challenge of decreasing the ecological footprint in the university campus generated by the local locomotion of students from university-home and/or home-university. The experience was implemented from February to June 2020, in the middle of the COVID-19 pandemic, with 9 participating students enrolled in the 'Industrial Management I' course, part of the Master of Science in Mechanical Engineering at the University of Tras-os-Montes and Alto Douro (UTAD), Portugal. We firstly describe the course in terms of the key driving question, the learning goals, the educational activities, the collaboration among students, the scaffolding technologies, and the tangible artefacts produced. We further discuss the preliminary results of the study by taking into account the main tangible learning artefact produced by the students - a carpooling model proposal for the UTAD student community - as well as the data collected from a post, self-completion questionnaire on students' perceptions about the PjBL experience. Finally, we outline implications for the teaching practice and some concerns that need to be addressed in future course editions.

Abstract
The increase in the world's population combined with the development of new economies has led to a large scale increase in the demand for energy resources. New technologies have emerged that allow for the maintenance of the energy supply. Renewable sources and energy storage systems (ESS) are emerging as a crucial option for the development of Smart Grids. Using a Mixed Integer Linear Programming (MILP) optimization model, the effects of renewable production sources and storage systems on an electrical grid were studied, in order to maximize the profit of a Virtual Power Plant (VPP). The obtained results allowed us to verify the efficiency of the proposed method. The placement of renewable producers and the ESS, as well as the management optimization of the purchase and transfer process of the stored energy definitely increased the profit of VPP. The use of these technologies also improves the voltage profile and decreased the active power losses by 84% along with the network.

Abstract
Nowadays, power distribution systems face some challenges related to power losses minimization and voltage stability improvement along the networks. These challenges can also be a big opportunity to develop smarter and more efficient distribution networks, ensuring the continuity of service and the power quality supplied to consumers. At the same time, there are several international standards that regulate the power quality levels required for distribution networks.This paper addresses deeply these issues and provide a solution to solve both of these problems using Distributed Generators (DG) on optimal locations of the grid. The proposed method will analyze the injection of both real and reactive power in a regulated IEEE-69 bus system. In the first stage, the voltage and loss sensitivity of the load flow analysis is calculated using a MatLab algorithm. In a second stage, the methodology uses the voltage stability index (VSI) to obtain the optimal location of the DGs to ensure the best results of both, power loss and voltage stability for the grid. The obtained results show the good effectiveness of the proposed method.

Abstract
Forests assume a great socioeconomic and environmental importance, requiring good management decisions to value and care for these natural resources. In Portugal, forest land use accounts for 34.5% of the continental area. The softwood species with the highest representation is maritime pine (Pinus pinaster Ait.). Traditionally, the species is managed as pure and even-aged stands for timber production, with a rotation age of 45 to 50 years. Depending on the initial stand density, the stands are thinned 2 to 4 times during the rotation period. Disturbances associated with forest fires have a negative impact on the age structure of stands over time, as they result in a narrow range of stand ages. This age homogenization over large forest areas increases with the recurrence and size of forest fires, bringing new challenges to forest management, namely the difficulty in ensuring the long-term sustainability of the wood supply. The problem aggravates with the increasing demand pressure on pine wood. This article aims to suggest a framework of DSS for Pinus pinaster that can effectively support the management of forest areas under these circumstances, i.e., narrow age ranges and high demand of harvested timber volume. A communal woodland area in the Northern region of Portugal affected by forest fires was selected as a study case. The Modispinaster model was used as the basis of the DSS, to simulate growth scenarios and interventions along the optional rotation period. Two clear-cut ages were considered: 25 and 40 years. The results obtained were the input data for an integer linear programming (ILP) model to obtain the plan that maximizes the volume of timber harvested in the study area, during the planning horizon. The ILP model has constraints bounding the area of clearings, and sustainability, operational and forestry restrictions. The computational results are a powerful tool for guidance in the decision-making of scheduling and forecasting the execution of interventions determining the set of stands that are exploited according to the different scenarios and the period in which the clear-cut is made throughout the planning horizon. Considering all constraints, the solution allows a balanced extraction of a total of 685 m(3)center dot ha(-1), over the 50-year horizon, as well as the representation of all age classes at the end of the planning period.

Abstract
Twitter has become a major platform to share ideas and promoting discussion on relevant topics. However, with a large number of users to resort to it as their primary source of information and with an increasing number of accounts spreading newsworthy content, a characterization of the political bias associated with the social network ecosystem becomes necessary. In this work, we aim at analyzing accounts spreading or publishing content from five different classes of the political spectrum. We also look further and study accounts who spread content from both right and left sides. Conclusions show that there is a large presence of accounts which disseminate right bias content although it is the more central classes that have a higher influence on the network. In addition, users who spread content from both sides are more actively spreading right content with opposite content associated with criticism towards left political parties or promoting right political decisions.