Abstract

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
The impact of the digital revolution has influenced society significantly in many ways, including with Artificial Intelligence (AI). The advantages and disadvantages of AI and what can be and should be done in order to influence that in a positive way are discussed. The study is based on interviews (ten) and survey answers (from 100 respondents). The survey results show that there is a general concern about the impact of AI in the future (the negative impact on work and related to a general loss of control). Furthermore, more than 50% of the answers lead to the thought that "Humans will learn to use the power of computers to improve their own skills and be ahead of AI". As concerns the interviews, it was interesting to realize that practical courses, such as students studying engineering, were the ones who were afraid of AI instead of the social ones. This may be because the engineering students are the ones who know more about AI so they better realize the possible implications of AI on their future jobs. Another possible reason is that non-engineering students believe that human sensibility needed in their fields of study is more difficult to reproduce by AI machines than technical skills present in other fields of study/jobs.

Abstract
We consider the three-dimensional Bin Packing Problem in which a set of boxes must be packed into the minimum number of identical bins. We present a heuristic that iteratively creates new sequences of boxes that defines the packing order used to generate a new solution. The sequences are generated retaining, adaptively, characteristics of previous sequences for search intensification and diversification. Computational experiments of the effectiveness of this approach are presented and discussed.

Abstract
The circular economy contrasts with the traditional linear economy since it presents a sustainable way both to produce goods and services and to contribute to the development of economies. This paper aims to contribute to a better knowledge of the efficiency of resources productivity, a common indicator to compare how circular economies are, through the estimation of the main determinants for the circular economy in Europe. A systematic analysis and comparison of the performance of all the European Union countries was performed to get further insight into their root causes and to help designing future policies towards a more circular European Union economy. With this purpose, a set of determinant factors for a circular economy in Europe were analysed, under the period between 2000 and 2016. A cluster analysis was applied and complemented with three econometric estimation methods: panel unit root tests, panel cointegration tests and vector autoregression model. The main findings allowed to cluster European countries into three different groups according to the growth rate of their resources productivity and to explain them according to the selected exploratory factors. Special efforts were made to explain the highest productivity growth group, as a way to find relevant drivers towards sustainable productivity growths.

Abstract
This paper presents an experiment on newsreaders' behavior and preferences on the interaction with online personalized news. Different recommendation approaches, based on consumption profiles and user location, and the impact of personalized news on several aspects of consumer decision-making are examined on a group of volunteers. Results show a significant preference for reading recommended news over other news presented on the screen, regardless of the chosen editorial layout. In addition, the study also provides support for the creation of profiles taking into consideration the evolution of user's interests. The proposed solution is valid for users with different reading habits and can be successfully applied even to users with small consumption history. Our findings can be used by news providers to improve online services, thus increasing readers' perceived satisfaction.