Abstract
This paper develops a sustainable approach in the productive context associated with the fish industry. The supply network design problem is addressed by using mathematical programming in order to avail the best configuration for the productive system. In this study, some environmental constraints for each echelon have been presented. Two mathematical models are proposed: cost and profit model. The models are validated with actual data obtained from a Colombian fish industry. The obtained results indicate an improved performance of the new supply network design by considering the sustainability approach derived from sustainable supply chain management (SSCM).

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.

Abstract
Transthyretin Familial Amyloid Polyneuropathy (TTR-FAP) is a rare neurological disease caused by a genetic mutation with a variable presentation and consequent challenging diagnosis, complex follow-up and treatment. At this moment, this condition has no cure and treatment options are under development. One of the disease's implications is a definite and progressive motor impairment that from the early stages compromises walking ability and daily life activities. The detection of this impairment is key for the disease onset diagnosis. With the goal of improving diagnosis of the symptoms and patients' quality of life, the authors have assessed the gait characteristics of subjects suffering from this condition. This contribution shows the results of a preliminary study, using a non-intrusive, markerless vision-based gait analysis tool. To the best of our knowledge, the reported results constitute the first gait analysis data of TTR-FAP mutation carriers.

Abstract
The remarkable number of real applications under dynamic scenarios is driving a novel ability to generate and gatherinformation.Nowadays,amassiveamountofinforma- tion is generated at a high-speed rate, known as data streams. Moreover, data are collected under evolving environments. Due to memory restrictions, data must be promptly processed and discarded immediately. Therefore, dealing with evolving data streams raises two main questions: (i) how to remember discarded data? and (ii) how to forget outdated data? To main- tain an updated representation of the time-evolving data, this paper proposes fading histograms. Regarding the dynamics of nature, changes in data are detected through a windowing scheme that compares data distributions computed by the fading histograms: the adaptive cumulative windows model (ACWM). The online monitoring of the distance between data distributions is evaluated using a dissimilarity measure based on the asymmetry of the Kullback–Leibler divergence.The experimental results support the ability of fading his- tograms in providing an updated representation of data. Such property works in favor of detecting distribution changes with smaller detection delay time when compared with stan- dard histograms. With respect to the detection of concept changes, the ACWM is compared with 3 known algorithms taken from the literature, using artificial data and using pub- lic data sets, presenting better results. Furthermore, we the proposed method was extended for multidimensional and the experiments performed show the ability of the ACWM for detecting distribution changes in these settings.

Abstract
In this paper, a hexagonal structure of ethanol filled solid core photonic crystal fiber having dispersion shifted properties is presented. The guiding properties, like effective mode area and dispersion, of the ethanol filled photonic crystal fiber are studied by using the full vectorial finite element method. The numerical simulation results show that the selectively filling of the ethanol in the cladding holes of photonic crystal fiber shifts the zero dispersion wavelength from near infrared region (0.98 µm) to mid infrared region (1.55 µm). This kind of photonic crystal fiber structure is very useful for dispersion compensating tool, sensing applications, fiber laser devices and non-linear applications like supercontinuum generation. © 2017 Elsevier GmbH

Abstract
Learning contents creation supported on computer tools has triggered the scientific community for a couple of decades. However, teachers have been facing more and different challenges, namely the emergence of other delivery learning approaches besides the traditional educational settings, the diversification of the student target population, and the recognition of different ways of learning. In education domain, diverse recommender systems have been developed so far for recommending learning activities and more specifically, learning objects. This research work is focused on teaching-learning techniques recommendation to assist teachers by providing them recommendation about which teaching-learning techniques should scaffold teaching-learning activities to be carried out by students. This paper presents a recommender model sustained in diverse elements, namely, a hybrid recommender system, an association rules mechanism to infer possible combinations of teaching-learning techniques, and collaborative work among several actors in education. An evaluation is carried out and the preliminary results are very encouraging, revealing that teachers seem very enthusiastic and motivated to rethink their teaching-learning techniques when designing teaching-learning activities.