Abstract
Purpose This study aims to address the topic of ethics, responsibility and sustainability (ERS) orientation of students enrolled in schools of economics and management master's degrees. It examines the effect of educational background and gender on Portuguese students' orientation towards ERS, as well as the extent to which there is a relation between the scientific area of the master degree in which the student is enrolled and his/her ERS orientation. Design/methodology/approach The authors used a sample of 201 students from several master degrees offered by the School of Economics and Management of a large public Portuguese university and analysed their ERS orientation using a survey by questionnaire. Findings Findings suggest that there are differences in orientation across gender, with female students valuing ERS more than their male counterparts. Educational background has minimal effects on the responses. It was also found some sort of selection effect in terms of the scientific area of the master degree and ERS orientation. Originality/value This study contributes to the literature by analysing the issue of whether students with an educational background in economics and management present different ERS orientation than their counterparts, as well as by examining whether there is some sort of self-selection into the study of disciplines in which ERS orientation is likely to be a week. As far as the authors are aware, this is the first study analysing this type of issue regarding ERS.

Abstract
Wearable devices have been showing promising results in a large range of applications: since industry, to entertainment and, in particular, healthcare. In the scope of movement disorders, wearable devices are being widely implemented for motor symptoms objective assessment. Currently, clinicians evaluate patients' motor symptoms resorting to subjective scales and visual perception, such as in Parkinson's Disease. The possibility to make use of wearable devices to quantify this disorder motor symptoms would bring an accurate follow-up on the disease progression, leading to more efficient treatments. Here we present a novel textile embedded low-power wearable device capable to be used in any scenario of movement disorders assessment due to its seamless, comfort and versatility. Regarding our research, it has already improved the setup of a wrist rigidity quantification system for Parkinson's Disease patients: the iHandU system. The wearable comprises a hardware sensing unit integrated in a textile band with an innovative design assuring higher comfort and easiness-to-use in movement disorders assessment. It enables to collect inertial data (9-axis) and has the possibility to integrate two analog sensors. A web platform was developed for data reading, visualization and recording. To ensure inertial data reliability, validation tests for the accelerometer and gyroscope sensors were conducted by comparison with its theoretical behavior, obtaining very good results.

Abstract
The aim of this article is to show how autoethnography is a useful and revealing research methodology that should be encouraged in academia, especially in higher education. With objectivity, autoethnography, which is a relatively new approach, may be a path toward deeper cultural discussions that are so important in everyday life. Moreover, autoethnography leads to important reflexive and critical observations made by students. Autoethnography is a readily accessible, low-cost methodology and thus very appealing to students and younger researchers. With this article, the author exemplifies autoethnographic accounts and narrates three different stories that occurred while trekking with three different trekking guides in Patagonia (El Chaltén), Argentina. Argentinian culture, in South America, is the focus. Researchers need to be careful of misleading statements in the literature, such as that in Argentina modesty is apparently not tolerated. We found that two of our guides and leaders – Mariano and Liz – both had modest (and pleasant) demeanors. Hence, we conclude that it is important to maintain an open mind and resist categorizing people. This is a vital point of cultural studies that is often not taken seriously. Cultures are made up of individuals and thus many differences can be found in the midst of an attempted standardization, and the desire to put everyone in the same “basket”. © 2020 by the author. Licensee MDPI, Basel, Switzerland.

Abstract
One of the teacher's first goals should be to inspire students to learn. Using project-based learning (PBL) to involve students in the learning process could be a useful and powerful tool to prepare the students for their professional future. As part of a degree course in Biomedical Engineering, students were asked to look at society and identify a possible biomedical-related failure or daily-life problem. From this, the students were challenged to work towards a solution, by preparing a project and creating a prototype or a minimum viable product. In this article we present the case study of a students' team, whose project was candidate and winner of a national prize. This prize was related to health innovation. Despite the particularization of this case study case, the students considered the experience innovative, motivating, and challenging. They also underlined the added value of a project whose impact goes beyond the classroom. Therefore, this method of teaching and learning, based on projects, may have a special effect on the students and, therefore on the civil society. The PBL can help higher education institutions to have a more prominent social presence, as innovation drivers and as forces of intervention.

Abstract
Biometric authentication (i.e., verification of a given subject’s identity using biological characteristics) relying on gait characteristics obtained in a non-intrusive way can be very useful in the area of security, for smart surveillance and access control. In this contribution, we investigated the possibility of carrying out subject identification based on a predictive model built using machine learning techniques, and features extracted from 3-D body joint data provided by a single low-cost RGB-D camera (Microsoft Kinect v2). We obtained a dataset including 400 gait cycles from 20 healthy subjects, and 25 anthropometric measures and gait parameters per gait cycle. Different machine learning algorithms were explored: k-nearest neighbors, decision tree, random forest, support vector machines, multilayer perceptron, and multilayer perceptron ensemble. The algorithm that led to the model with best trade-off between the considered evaluation metrics was the random forest: overall accuracy of 99%, class accuracy of 100±Â0%, and F 1 score of 99±Â2%. These results show the potential of using a RGB-D camera for subject identification based on quantitative gait analysis. © 2020, Springer Nature Switzerland AG.

Abstract
The K-means algorithm is widely used to find correlations between data in different application domains. However, given the massive amount of data stored, known as Big Data, the need for high-speed processing to analyze data has become even more critical, especially for real-time applications. A solution that has been adopted to increase the processing speed is the use of parallel implementations on FPGA, which has proved to be more efficient than sequential systems. Hence, this paper proposes a fully parallel implementation of the K-means algorithm on FPGA to optimize the system & x2019;s processing time, thus enabling real-time applications. This proposal, unlike most implementations proposed in the literature, even parallel ones, do not have sequential steps, a limiting factor of processing speed. Results related to processing time (or throughput) and FPGA area occupancy (or hardware resources) were analyzed for different parameters, reaching performances higher than 53 millions of data points processed per second. Comparisons to the state of the art are also presented, showing speedups of more than over a partially serial implementation.