Abstract
The paper introduces the Active and Permanent Information System Management Model (MGSI-AP). It results from an investigation that discussed concepts and perspectives about Information Management, positioning it as a transversal and applied area within Information Science, focused on info communicational flow, in a complex institutional context the Portuguese public University and related information services. The University is assumed in a complex and systemic double facet, between the formal organized system and the loosely coupled combinatory system. Here is presented one of the operationalization axes of the performed research and model. It highlights the close connection between Information Management and the area of studies of Information Production, framed by a theoretical-methodological proposal and operational modeling, which converge to an Information Management definition and the design of a Matrix of Components and Variables under analysis.

Abstract
In the last few decades, the alkali-silica reaction (ASR) has been reported as one of the major concrete concerns regarding durability, leading to high maintenance and reconstruction costs. The occurrence of ASR in numerous concrete infrastructures all over the world points to the need for research regarding measures for its detection in an initial stage (and further mitigation) either in new or existing structures. Furthermore, the chemical and physical mechanisms for ASR remain poorly understood. This lack of knowledge leads to incapacity to assess risk, cost-effectively predict service life, and efficiently mitigate the deterioration process due to ASR in concrete structures. This manuscript aims to review the most recent and relevant achievements and the existing knowledge concerning the reaction mechanisms of ASR. Additionally, this manuscript is focused on the conditioning factors, diagnostic and prognostic methodologies, preventive measures and test methods (including their limitations) of ASR conducted at an academic level. The perspectives for future research challenges are also identified and debated.

Abstract
Mobile robotic applications are increasing in several areas not only in industries but also service robots. The Industry 4.0 promoted even more the digitalization of factories that opened space for smart-factories implementation. Robotic competitions are a key to improve research and to motivate learning. This paper addresses a new competition proposal, the Robot@Factory Lite, in the scope of the Portuguese Robotics Open. Beyond the competition, a reference robot with all its components is proposed and a simulation environment is also provided. To minimize the gap between the simulation and the real implementation, an Hardware-in-the-loop technique is proposed that allows to control the simulation with a real Arduino board. Results show the same code, and hardware, can control both simulation model and real robot.

Abstract
Concept drift describes unforeseeable changes in the underlying distribution of streaming data over time. Concept drift research involves the development of methodologies and techniques for drift detection, understanding, and adaptation. Data analysis has revealed that machine learning in a concept drift environment will result in poor learning results if the drift is not addressed. To help researchers identify which research topics are significant and how to apply related techniques in data analysis tasks, it is necessary that a high quality, instructive review of current research developments and trends in the concept drift field is conducted. In addition, due to the rapid development of concept drift in recent years, the methodologies of learning under concept drift have become noticeably systematic, unveiling a framework which has not been mentioned in literature. This paper reviews over 130 high quality publications in concept drift related research areas, analyzes up-to-date developments in methodologies and techniques, and establishes a framework of learning under concept drift including three main components: concept drift detection, concept drift understanding, and concept drift adaptation. This paper lists and discusses 10 popular synthetic datasets and 14 publicly available benchmark datasets used for evaluating the performance of learning algorithms aiming at handling concept drift. Also, concept drift related research directions are covered and discussed. By providing state-of-the-art knowledge, this survey will directly support researchers in their understanding of research developments in the field of learning under concept drift.

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