Abstract
Today we use the Web for almost everything, even to program. There are several specialized code editors gravitating on the Web and emulating most of the features inherited from traditional IDEs, such as, syntax highlight, code folding, autocompletion and even code refactorization. One of the techniques to speed the code development is the use of snippets as predefined code blocks that can be automatically included in the code. Although several Web editors support this functionality, they come with a limited set of snippets, not allowing the contribution of new blocks of code. Even if that would be possible, they would be available only to the code's owner or to the editors' users through a private cloud repository. This paper describes the design and implementation of Sni'per, a RESTful API that allows public access for multi-language programming code-blocks ordered by popularity. Besides being able to access code snippets from other users and score them, we can also contribute with our own snippets creating a global network of shared code. In order to make coding against this API easier, we create a client library that reduces the amount of code required to write and make the code more robust. © Ricardo Queirós and Alberto Simões;licensed under Creative Commons License CC-BY.

Abstract
Mesenchymal Stromal/Stem Cells (MSC) are currently being explored in diverse clinical applications, including regenerative therapies. Their contribution to regeneration of bone fractures is dependent on their capacity to proliferate, undergo osteogenesis and induce angiogenesis. This study aimed to uncover microRNAs capable of concomitantly regulate these mechanisms. Following microRNA array results, we identified miR-195 and miR-497 as downregulated in human primary MSC under osteogenic differentiation. Overexpression of miR-195 or miR-497 in human primary MSC leads to a decrease in osteogenic differentiation and proliferation rate. Conversely, inhibition of miR-195 increased alkaline phosphatase expression and activity and cells proliferation. Then, miR-195 was used to study MSC capacity to recruit blood vessels in vivo. We provide evidence that the paracrine effect of MSC on angiogenesis is diminished when cells over-express miR-195. VEGF may partially mediate this effect, as its expression and secreted protein levels are reduced by miR195, while increased by anti-miR-195, in human MSC. Luciferase reporter assays revealed a direct interaction between miR-195 and VEGF 3'-UTR in bone cancer cells. In conclusion, our results suggest that miR-195 regulates important mechanisms for bone regeneration, specifically MSC osteogenic differentiation, proliferation and control of angiogenesis; therefore, it is a potential target for clinical bone regenerative therapies.

Abstract
This chapter presents the architecture and design of enki, an Integrated Development Environment (IDE) for learning programming languages on massive open online courses (moocs). this environment can be used as a tool by a learning management system (lms) and a typical lms such as moodle can launch it using the learning tool interoperability (lti) api. student authentication tokens are passed via lti, thus integrating enki in the single sign-on domain of the academic institution. the proposed tool has a web user interface similar to those of reference ides, where the learner has access to different integrated tools, from viewing tutorial videos, to solving programming exercises that are automatically evaluated. enki uses several gamification strategies to engage learners, including generic gamifications services provided by odin and the sequencing of educational resources. the course content (videos, pdfs, programming exercises) is progressively disclosed to the learner as he successfully completes exercises. this is similar to what happens in a game, where new levels are unlocked as the previous are completed, thus contributing to the sense of achievement.

Abstract
Many errors in spreadsheet formulas can be avoided if spreadsheets are built automatically from higher-level models that can encode and enforce consistency constraints in the generated spreadsheets. Employing this strategy for legacy spreadsheets is difficult, because the model has to be reverse engineered from an existing spreadsheet and existing data must be transferred into the new model-generated spreadsheet. We have developed and implemented a technique that automatically infers relational schemas from spreadsheets. This technique uses particularities from the spreadsheet realm to create better schemas. We have evaluated this technique in two ways: first, we have demonstrated its applicability by using it on a set of real-world spreadsheets. Second, we have run an empirical study with users. The study has shown that the results produced by our technique are comparable to the ones developed by experts starting from the same (legacy) spreadsheet data. Although relational schemas are very useful to model data, they do not fit spreadsheets well, as they do not allow expressing layout. Thus, we have also introduced a mapping between relational schemas and ClassSheets. A ClassSheet controls further changes to the spreadsheet and safeguards it against a large class of formula errors. The developed tool is a contribution to spreadsheet (reverse) engineering, because it fills an important gap and allows a promising design method (ClassSheets) to be applied to a huge collection of legacy spreadsheets with minimal effort.

Abstract
To cluster a data stream is a more challenging task than its regular batch version, having stricter performance constraints. In this paper an approach to this problem is presented, based on WiSARD, a memory-based artificial neural network (ANN) model. This model functioning was reviewed and improved, in order to adapt it to this task. The experimental results obtained support the use of this system for the analysis of data streams in an informative way. © 2016 ACM.

Abstract