Abstract
Heart sounds are difficult to interpret because a) they are composed by several different sounds, all contained in very tight time windows; b) they vary from physiognomy even if the show similar characteristics; c) human ears are not naturally trained to recognize heart sounds. Computer assisted decision systems may help but they require robust signal processing algorithms. In this paper, we use a real life dataset in order to compare the performance of a hidden Markov model and several hidden semi Markov models that used the Poisson, Gaussian, Gamma distributions, as well as a non-parametric probability mass function to model the sojourn time. Using a subject dependent approach, a model that uses the Poisson distribution as an approximation for the sojourn time is shown to outperform all other models. This model was able to recreate the "true" state sequence with a positive predictability per state of 96%. Finally, we used a conditional distribution in order to compute the confidence of our classifications. By using the proposed confidence metric, we were able to identify wrong classifications and boost our system (in average) from an approximate to 83% up to approximate to 90% of positive predictability per sample.

Abstract
In this work, we present a method to extract features from heart sound signals in order to enhance segmentation performance. The approach is data-driven, since the way features are extracted from the recorded signals is adapted to the data itself. The proposed method is based on the extraction of delay vectors, which are modeled with Gaussian mixture model priors, and an information-theoretic dimensionality reduction step which aims to maximize discrimination between delay vectors in different segments of the heart sound signal. We test our approach with heart sounds from the publicly available PhysioNet dataset showing an average F-1 score of 92.6% in detecting S-1 and S-2 sounds.

Abstract
Automatic and simultaneous electrocardiogram (ECG) and phonocardiogram (PCG) segmentation is a good example of current challenges when designing multi-channel decision support systems for healthcare. In this paper, we implemented and tested a Montazeri coupled hidden Markov model (CHMM), where two HMM's cooperate to recreate the "true" state sequence. To evaluate its performance, we tested different settings (two fully connected and two partially connected channels) on a real dataset annotated by an expert. The fully connected model achieved 71% of positive predictability (P+) on the ECG channel and 67% of P+ on the PCG channel. The partially connected model achieved 90% of P+ on the ECG channel and 80% of P+ in the PCG channel. These results validate the potential of our approach for real world multichannel application systems.

Abstract
At the celebration of its 30th anniversary, Erasmus is recognised as the most successful exchange program ever implemented. The prospects of attaining a common European consciousness challenged the program's ability to blend together knowledge, attitudes and skills in a winning combination. It is no longer sufficient to communicate and integrate: mobility should actively foster skills to support students's professional career at national and international levels. Although literature on mobility is vast and interesting, studies on the impact of the mobility experience in the students' future employability profile rarely provide first-hand data on their expectations in this regard. This exploratory research comprises a qualitative focus group approach with Erasmus students during their exchange period in a Portuguese university and collected some insightful data on how students consider their mobility in terms of new learning outcomes, the professional value of the experience and the development of new skills. Results indicate that students seem to be quite aware of the positive implications of mobility in their professional careers and of the set of skills developed during that period. Overall, this article contributes to demonstrating the importance of assessing skills development during Erasmus mobility experiences. Managerial implications and suggestions for future research are provided.

Abstract
This study aims to contribute to the growing literature on teachers' mobility by exploring perceptions and motivations to join these activities, in particular through the collection of evidence on the impact a first and only exchange experience has had on the participants. The research adopts a qualitative methodology in the form of phenomenological interviews with 6 teachers that engaged on only one mobility initiative. The interviewees shared their personal impressions on mobility, including reasons, facilitators, and outcomes of the experience. Bureaucratic, financial and residual professional impact, are among the most cited inhibitors for repeating the initiative. However, most of the participants expect to be become involved again on mobility assignments someday, especially teachers that identified greater impact from this first experience. The analysis provides interesting clues for international offices, Erasmus coordinators and university top managers, who devote considerable effort to the promotion and support of mobility practices.

Abstract
Internationalization is a broad concept encompassing multiple facets. Higher Education Institutions (HEI) collaborators are key actors of the internationalization process and outcomes, being essential for education managers to promote internationalization initiatives, namely among their teachers. Nevertheless, the literature indicates that the number of teachers involved in those initiatives is still modest. It is therefore of utmost importance to understand how teachers initiate and maintain mobility assignments, so that HEI can implement effective strategies to promote this facet of internationalization. In this paper, we explore the teacher mobility topic through the lens of the Theory of Reasoned Action and the Theory of Planned Behavior. These two theories have been widely used to explain how people initiate and maintain behaviors, and are particularly relevant to understand teacher mobility. The paper includes results from phenomenological interviews with teachers that had one or more mobility experience under the Erasmus programme. The narratives of the participants in the study evidence the importance of prior intentions, attitudes and subjective norms in the resolution to undertake international assignments. Self-efficacy was also shown as determinant in the decision process of first and subsequent mobility initiatives. This paper also provides cues on how HEI can facilitate and encourage mobility experiences amongst their teaching staff.