Abstract
Fault-tolerance is a core feature in distributed database systems, particularly the ones deployed in cloud environments. The dependability of these systems often relies in middleware components that abstract the DBMS logic from the replication itself. The highly configurable nature of these systems makes their throughput very dependent on the correct tuning for a given workload. Given the high complexity involved, machine learning techniques are often considered to guide the tuning process and decompose the relations established between tuning variables. This paper presents a machine learning mechanism based on reinforcement learning that attaches to a hybrid replication middleware connected to a DBMS to dynamically live-tune the configuration of the middleware according to the workload being processed. Along with the vision for the system, we present a study conducted over a prototype of the self-tuned replication middleware, showcasing the achieved performance improvements and showing that we were able to achieve an improvement of 370.99% on some of the considered metrics.

Abstract
Carrying out the task of the exploration of a scene by an autonomous robot entails a set of complex skills, such as the ability to create and update a representation of the scene, the knowledge of the regions of the scene which are yet unexplored, the ability to estimate the most efficient point of view from the perspective of an explorer agent and, finally, the ability to physically move the system to the selected Next Best View (NBV). This paper proposes an autonomous exploration system that makes use of a dual OcTree representation to encode the regions in the scene which are occupied, free, and unknown. The NBV is estimated through a discrete approach that samples and evaluates a set of view hypotheses that are created by a conditioned random process which ensures that the views have some chance of adding novel information to the scene. The algorithm uses ray-casting defined according to the characteristics of the RGB-D sensor, and a mechanism that sorts the voxels to be tested in a way that considerably speeds up the assessment. The sampled view that is estimated to provide the largest amount of novel information is selected, and the system moves to that location, where a new exploration step begins. The exploration session is terminated when there are no more unknown regions in the scene or when those that exist cannot be observed by the system. The experimental setup consisted of a robotic manipulator with an RGB-D sensor assembled on its end-effector, all managed by a Robot Operating System (ROS) based architecture. The manipulator provides movement, while the sensor collects information about the scene. Experimental results span over three test scenarios designed to evaluate the performance of the proposed system. In particular, the exploration performance of the proposed system is compared against that of human subjects. Results show that the proposed approach is able to carry out the exploration of a scene, even when it starts from scratch, building up knowledge as the exploration progresses. Furthermore, in these experiments, the system was able to complete the exploration of the scene in less time when compared to human subjects.

Abstract
The key contribution of this paper is the proposal of a novel conceptual model for the social business value proposition. This research was about making sense out of the body of knowledge underlying social business concepts and perspectives, stemming from the social entrepreneurship literature, and building on the so-called business model ontology that underlies the widely used business model canvas. The developed constructs were built in the scope of a design science approach to research, supported by an assessment process that involved several steps comprising the interaction with well-known academicians and practitioners in the area of social business, culminating with a case-study for final validation and assessment. Interviews with the experts from the field helped in the iterative development process of the ontology and its assessment, further supported by informed arguments and a continuous review of the literature.

Abstract
Film consumers are continuously online and active in various social platforms. This phenomenon has led over-the-top (OTT) providers - empowered by social computing technologies - to establish a social media presence and incorporate elements drawn from social media into their services. However, little is known about existing OTT interfaces and their key social features. This study sought to provide a structured categorisation of the most salient social media features of the best-known applications in the OTT video business. In addition, a new social content network model, Avids, was proposed to connect individuals socially through films. Avids reaches beyond more fixed, functionality-based approaches applied in the development of OTT video sites and focuses on components related to sociality. This approach ensures a unified system in which the overall social media setting is embedded in every functional area of the platform's architecture, thereby allowing applications to trigger and support social behaviours absent from traditional OTT providers. A purpose-built international online survey was administered to 479 film lovers to assess how Avids' main features compare with traditional OTT video providers. The questionnaire was based on the technology acceptance model. The results confirm the critical role of sociality in film viewing-related activities.

Abstract
Portugal is a country with a large coastal extension and a fishing and sea tradition which place it on the top of fresh, salty and deep-frozen fish consumption in the European Union. The incapacity by consumers to evaluate the degree of freshness and quality of fish for consumption may cause health problems, such as food poisoning, hence the preference of consumers for deep-frozen products instead of healthier fish that is sold fresh. In this project we intend to contribute to an improvement in the evaluation by the final consumer of the quality of fresh fish sold to them through creating a reference table of fish degradation (at this experimental stage for mackerel and sardine) and the development of a mobile application allowing, in a near future, for users to determine the rate of freshness of fish they wish to acquire. The reference table creation is based on the degradation/dehydration of the fish’s eye as well as a respective coloration (opaqueness), which changes according to the time since the fish was caught. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.

Abstract
In clinical practice and in particular in the diagnostic process, the assessment of cardiac and respiratory functions is supported by electrocardiogram and auscultation. These exams are non-invasive, quick and inexpensive to perform and easy to interpret. For these reasons, this type of assessment is a constant in the daily life of a clinician and the information obtained is central to the decision making process. Therefore, it is essential that during their training, students of health-related subjects acquire skills in the acquisition and evaluation of the referred physiological signals. Simulation, considering the technological possibilities of today, is an excellent preparation tool since it exposes trainees to near real contexts but without the associated risks. Hence, the simulation of physiological signals plays an important role in the education of healthcare professionals, bioengineering professionals and also in the development and calibration of medical devices. This paper describes a project to develop synchronized electrocardiogram (ECG), phonocardiogram (PCG) and breathing sounds simulators that aims to improve an existing phantom simulator. The developed system allows, in an integrated way, to generate normal and pathological signals, being contemplated several distinct pathologies. For engineering education, it is also possible to simulate the introduction of signal disturbances or hardware malfunctions. A graphical interface allows changing operating parameters in real time.