Abstract
The pellet market in Portugal is a developing market where the main producers of wood pellets try to convince the small-scale buyer that wood pellets are a good alternative as a fuel because energy from them is cost-effective in long-term use. For this work, data about production, production capacity and consumption in Portugal were collected. Consumption levels are low since the majority of sales are exports. The different points of pellet production in Portugal have been located, and a price analysis has been made. To obtain data on the production capacity of the plants and get referrals from the market, the database Bioraise has been used in order to complement the information raised through prospecting and inquiries. Although it is noted that the pellet industry in Portugal is a sector in the initial stage of its development, the potential for growth is high, since internal consumption is low compared to the level of exports to other countries in which the pellet industry is booming. We conclude that the pellet industry is an important alternative in the Portuguese energy market due to the competitive price of this fuel compared to traditional fuels.

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Abstract
Ever since energy sustainability is an emergent concern, Plug-in Electric Vehicles (PEVs) significantly affect the approaching smart grids. Indeed, Demand Response (DR) brings a positive effect on the uncertainties of renewable energy sources, improving market efficiency and enhancing system reliability. This paper proposes a multi-stage stochastic model of a PEV aggregation agent to participate in day-ahead and intraday electricity markets. The stochastic model reflects several uncertainties such as the behaviour of PEV owners, electricity market prices, and activated quantity of reserve by the system operator. For this purpose, appropriate scenarios are utilized to realize the uncertain feature of the problem. Furthermore, in the proposed model, the PEV aggregation agents can update their bids/offers by taking part in the intraday market. To this end, these aggregation agents take part in Demand Response exchange (DRX), markets designed in the intraday session by employing DR resources. The numerical results show that DR provides a perfect opportunity for PEV aggregation agents to increase the profit. In addition, the results reveal that the PEV aggregation agent not only can increase its profit by participating in the DRX market, but also can become an important player in the mentioned market.

Abstract
Information and Communication Technologies (ICT) are part of the day to day activities of a large part of world population, however its use involves a growing generation of electronic waste (ewaste). Due to the increasing technological innovation, it occurs that in a short time, the products become obsolete and have their life cycle reduced. The article aims to present the development, verification and validation of models of computational simulation for assessment of environmental and financial impacts caused by the extension of the life cycle of personal computers (PC) through their remanufacturing. For the system modeling the System Dynamics theory was used. Results generated by the simulation model, show that the remanufacturing is a viable alternative for the reutilization of discarded computers and that it is possible, in advance, to discuss, assess and decide necessary measures for a better financial and environmental performance in the acquisition and use of ICT.

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Nowadays, breast cancer has become the most common cancer amongst females. As long as breast is assumed to be a feminine symbol, any imposed deformation of surgical procedures can affect the patients' quality of life. However, using a planning tool which is based on parametric modeling, not only improves surgeons' skills in order to perform surgeries with better cosmetic outcomes, but also increases the interaction between surgeons and patients during the decision for necessary procedures. In the current research, a methodology of parametric modeling, called Free-Form Deformation (FFD) is studied. Finally, confirmed by a quantitative analysis, we proposed two simplified versions of FFD methodology to increase model similarity to input data and decrease required fitting time.

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