Abstract
Invasive species present a global problem that requires better awareness from the general population. Serious games can serve as a tool for bringing attention to issues of this kind. People who are not informed cannot distinguish the invasive species apart from the ones native to a particular ecosystem. In this wok we present a serious game designed with the primary objective of informing people about the main characteristics of invasive plant species in Portugal, as well as showing proper ways of removing and disposing it, without allowing to spread throughout the local ecosystem. A game prototype was developed for mobile devices, since these are the most widely used platform, allowing the game's message to have a wider reach. Currently, the game has a single level focusing on a plant species, the water hyacinth, that thrive in rivers and lakes. User tests were performed to evaluate the prototype and to gather feedback and suggestions for future improvements. Results revealed a positive reception and an interest in further developments.

Abstract
Purpose This paper explores how service design can contribute to the evolution of health service systems, moving them toward people-centered, integrated and technology-enabled care; the paper develops a research agenda to leverage service design research for healthcare transformation. Design/methodology/approach This conceptual study starts by analyzing healthcare challenges in terms of demographic trends and economic constraints, along with the problems of lack of people-centricity, dispersion of care and slowness in incorporating emerging technologies. Then, it examines the theoretical underpinnings of service design to develop a framework for exploring how a human-centered, transformative and service systems approach can contribute to addressing healthcare challenges, with illustrative cases of service design research in healthcare being given. Findings The proposed framework explores how a human-centered service design approach can leverage the potential of technology and advance healthcare systems toward people-centered care; how a transformative service design approach can go beyond explanatory research of healthcare phenomena to develop innovative solutions for healthcare change and wellbeing; and how a service systems perspective can address the complexity of healthcare systems, hence moving toward integrated care. Originality/value This paper systematizes and develops a framework for how service design can contribute to healthcare transformation. It identifies key healthcare application areas for future service design research and pathways for advancing service design in healthcare by using new interdisciplinary bridges, methodological developments and theoretical foundations.

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Abstract
To study the magnetostriction of Co66Fe34 thin films, amorphous silicon microcantilevers were prepared by surface micromachining, and the 136 nm-thick magnetostrictive film was deposited by electron beam physical vapor deposition and patterned on top of the microcantilever structure. The magnetostriction of the Co66Fe34 films was confirmed by measuring the deflection of the cantilevers under a varying magnetic field, reaching displacements up to 8 nm. The configuration was simulated using COMSOL software, yielding a similar deflection behavior as a function of the magnetic field, with a film with a magneto strictive coefficient of ? S ~ 55 p.p.m. The experimental configuration uses a laser and a position sensitive detector to measure the displacement, based on an optical lever configuration, and a piezoelectric stage to calibrate the system.

Abstract
Currently, there is great interest in reducing the consumption of fossil fuels (and other non-renewable energy sources) in order to preserve the environment; smart buildings are commonly proposed for this purpose as they are capable of producing their own energy and using it optimally. However, at times, solar energy is not able to supply the energy demand fully; it is mandatory to know the quantity of energy needed to optimize the system. This research focuses on the prediction of output temperature from a solar thermal collector. The aim is to measure solar thermal energy and optimize the energy system of a house (or building). The dataset used in this research has been taken from a real installation in a bio-climate house located on the Sotavento Experimental Wind Farm, in north-west Spain. A hybrid intelligent model has been developed by combining clustering and regression methods such as neural networks, polynomial regression, and support vector machines. The main findings show that, by dividing the dataset into small clusters on the basis of similarity in behavior, it is possible to create more accurate models. Moreover, combining different regression methods for each cluster provides better results than when a global model of the whole dataset is used. In temperature prediction, mean absolute error was lower than 4 ° C.

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