Abstract
One of the main advantages of Prolog is its potential for the implicit exploitation of parallelism and, as a high-level language, Prolog is also often used as a means to explicitly control concurrent tasks. Tabling is a powerful implementation technique that overcomes some limitations of traditional Prolog systems in dealing with recursion and redundant subcomputations. Given these advantages, the question that arises is if tabling has also the potential for the exploitation of concurrency/parallelism. On one hand, tabling still exploits a search space as traditional Prolog but, on the other hand, the concurrent model of tabling is necessarily far more complex, since it also introduces concurrency on the access to the tables. In this paper, we summarize Yap's main contributions to concurrent tabled evaluation and we describe the design and implementation challenges of several alternative table space designs for implicit and explicit concurrent tabled evaluation that represent different tradeoffs between concurrency and memory usage. We also motivate for the advantages of using fixed-size and lock freedata structures, elaborate on the key role that the engine's memory allocator plays on such environments, and discuss how Yap's mode-directed tabling support can be extended to concurrent evaluation. Finally, we present our future perspectives toward an efficient and novel concurrent framework which integrates both implicit and explicit concurrent tabled evaluation in a single Prolog engine.

Abstract
Skeletal muscle dispersion and optical clearing (OC) kinetics were studied experimentally to prove the existence of the refractive index (RI) matching mechanism of OC. Sample thickness and collimated transmittance spectra were measured during treatments with glucose (40%) and ethylene glycol (EG; 99%) solutions and used to obtain the time dependence of the RI of tissue fluids based on the proposed theoretical model. Calculated results demonstrated an increase of RI of tissue fluids and consequently proved the occurrence of the RI matching mechanism. The RI increase was observed for the wavelength range between 400 and 1000 nm and for the 2 probing molecules explored. We found that for 30 min treatment with 40% glucose and 99% EG, RI of sarcoplasm plus interstitial fluid was increased at 800 nm from 1.328 to 1.348 and from 1.328 to 1.369, respectively.

Abstract
The general increase in life expectancy and the consequent ageing of the general population impose major challenges to modern societies. Most elderly people experience the typical problems related to old age, such as chronic health problems, as well as sensory and cognitive impairments. In addition, in today’s modern societies, where families have less and less time to look after their older relatives, the isolation of the elderly is a real concern and a highly recurrent problem, which is enhanced when they live alone. To solve, or at least minimize, these problems, a smart home monitoring system was developed, as presented and described in this paper. This solution is implemented based on a sensory network which detects anomalous behaviors, immediately triggering a warning to the caregiver or family. A strong concern when developing a project of this kind is the physical security of the elderly. Houses tend to have hazardous objects and characteristics that may inflict serious injuries to their occupants or, in extrema, even death. As time goes by, the elderly start losing muscle mass and osteoporosis may appear, as well as vision and hearing impairments, which increase the likelihood of falling. Several other serious accidents may also occur, such as gas leaks, floods and fire outbreaks. Therefore, this population would strongly benefit from a solution which helps predict and even prevent accidents before they happen. © Springer International Publishing AG, part of Springer Nature 2018.

Abstract
Research datasets include all kinds of objects, from web pages to sensor data, and originate in every domain. Concerns with data generated in large projects and well-funded research areas are centered on their exploration and analysis. For data in the long tail, the main issues are still how to get data visible, satisfactorily described, preserved, and searchable. Our work aims to promote data publication in research institutions, considering that researchers are the core stakeholders and need straightforward workflows, and that multi-disciplinary tools can be designed and adapted to specific areas with a reasonable effort. For small groups with interesting datasets but not much time or funding for data curation, we have to focus on engaging researchers in the process of preparing data for publication, while providing them with measurable outputs. In larger groups, solutions have to be customized to satisfy the requirements of more specific research contexts. We describe our experience at the University of Porto in two lines of enquiry. For the work with long-tail groups we propose general-purpose tools for data description and the interface to multi-disciplinary data repositories. For areas with larger projects and more specific requirements, namely wind infrastructure, sensor data from concrete structures and marine data, we define specialized workflows. In both cases, we present a preliminary evaluation of results and an estimate of the kind of effort required to keep the proposed infrastructures running.  The tools available to researchers can be decisive for their commitment. We focus on data preparation, namely on dataset organization and metadata creation. For groups in the long tail, we propose Dendro, an open-source research data management platform, and explore automatic metadata creation with LabTablet, an electronic laboratory notebook. For groups demanding a domain-specific approach, our analysis has resulted in the development of models and applications to organize the data and support some of their use cases. Overall, we have adopted ontologies for metadata modeling, keeping in sight metadata dissemination as Linked Open Data.

Abstract
A few years back organizations were rushing into social media environments following the worldwide trend to create a social presence in multiple channels and / or to explore their potential. Currently, after having gone through a period of experimentation and consolidation of that presence, it is important to understand and to report on how the performance and communication efficiency of organizations has evolved. On previous studies, where we focused on the public higher education sector, we have identified a set of organizations that presented behaviour which was typical from yearly social media adopters, with very low relative performance and communication efficiency. Using data and text mining tools, and techniques, we showed that these organizations revealed very low frequency of publication of messages and very low engagement among their audiences. At the time, the analysis of this sector posed challenges to the confirmation of whether these content strategies were representative enough and if they were a result of an effective and permanent organizational behaviour on social media, or just a result of a stage of social media adoption. In this paper, we present a longitudinal study that portrays the evolution of the organizational behaviour of these organizations on social media, concerning their relative performance and their communication efficiency after a four-year period. Our analysis is based on how and if they have evolved from that stage by fine-tuning their social media communications. We also present findings concerning the content strategy structure evolution along the past four years, concerning the type of content used in higher education institutions' social media strategies, to obtain the best possible return on engagement from the publics (fans), demonstrating how these organizations have either dropped Facebook or optimized their type of content to foster higher return. Thus, on this longitudinal study we present and benchmark the current state of performance of public higher education institutions, concerning the path they undertook in the past four years.

Abstract
Computer-based modelling tools allow students to express their theories in models that can be simulated. In this way, students can use their theories operationally, confronting themselves with the consequences of their ideas. The ability of students to form and express a mental model will be expanded if they are given an opportunity to become aware of their own mental model by expressing this same model and comparing it to other models, like a consensus model. The building of numerical models of biophysical phenomena, such as the mechanics of breathing, or blood circulation, has the potential for student motivation as well as long-term learning. Our theory is that by re-building well known numerical models of physiological phenomena students will have the opportunity to change their perceptions about the relevance of the contents addressed, simultaneously improving their learning in the topics covered and increasing their motivation in the basic science disciplines in their curricula. For the implementation of computer numerical models historically it was necessary to use some programming language, such as MATLAB, BASIC, C++, JAVA. With the development of computer science, it is now possible to these students "construct" models of physical phenomena expressed through dedicated computer tools without necessarily having to do so in a programming language. As for example we have STELLA, MODELLUS, or STARLOGO. There is also the possibility of using a spreadsheet such as Microsoft EXCEL, Open Office CALC, Google SHEETS, or others, as tools that allow students to express physical models. The current spreadsheets, even those available for free, are very powerful, having many integrated tools, in terms of calculation, and we can count on several other features, such as graphs of various types, buttons and other tools that allow interaction with the model, and databases that can be integrated into the spreadsheet. There are several advantages of using spreadsheets in science education due to its general access, through smartphones, tablet's and computers, ease of implementation for the basic operations, and ease of the "debug" process, relative to other types of software. Also, it does not require prior knowledge of programming languages, or about complex mathematical software, which would an obstacle to the learning in itself. There is also the positive side effect of learning how to use a spreadsheet that is a plus in itself for the future professional's. This paper will have a review of the state of the art of using spreadsheets in Modelling Based Learning. Also, it will be presented a study with first year undergraduate students of a health care course, using Biophysical models historically very important in the physiology and medicine development.