Abstract
This paper presents the perspectives of the immersive learning research network community on the relevance of various challenges to the adoption of immersive learning technology, along three dimensions: access, content production, and deployment. Using a previously validated questionnaire, we surveyed this community of 622 researchers and practitioners during the summer of 2018, attaining 54 responses. By ranking the challenges individually and within each dimension, the results point towards higher relevance being placed on aspects that link immersive environments with learning management systems and pedagogical tasks, alongside aspects that empower non-technical users (educational actors) to produce interactive stories, objects, and characters.

Abstract
In order to avoid voltage problems derived from the connection of large amounts of renewable-based generation to the electrical distribution system, new advanced tools need to be developed that are able to exploit the presence of Distributed Energy Resources (DER). This paper describes the approach proposed for a predictive voltage control algorithm to be used in Low Voltage (LV) distribution networks in order to make use of available flexibilities from domestic consumers via their Home Energy Management System (HEMS) and more traditional resources from the Distribution System Operator (DSO), such as transformers with On-Load Tap Changer (OLTC) and storage devices. The proposed algorithm-the Low Voltage Control (LVC)-is detailed in this paper. The algorithm was tested through simulation using a real Portuguese LV network and real consumption and generation data, in order to evaluate its performance in preparation for a field-trial validation in a Portuguese smart grids pilot.

Abstract
Autonomous driving is currently a widely researched topic worldwide. With a large research effort being taken by industrial research units in the automotive sector, it is no longer exclusive to academic research labs. Essential to this ongoing effort towards level-5 vehicle autonomy, are the sensors used for tracking and detection, mainly lasers, radars and cameras. Most of the cameras for automotive application systems use wide-angle or fish-eye lens, which present high distortion levels. Cameras need to be calibrated for correct perception, particularly for capturing geometry features, or for distance-based calculations. This paper describes a case-study concerning monocular camera calibration for a small scale autonomous driving vehicle vision system. It describes the fundamentals on camera calibration and implementation, with results given for different lenses and distortion models. The aim of the paper is not only to provide a detailed and comprehensive review on the application of these calibration methods, but to serve also as a reference document for other researchers and developers starting to use monocular vision in their robotic applications.

Abstract
STEAM Education is nowadays a key element for our current digital society. Integrating STEAM and developing competences such as Computational Thinking is highly demanded by the industry and higher education institutions. In order to do so new methodological approaches are required. RoboSTEAM project is an Erasmus+ project defined to address these topics by using of physical devices and robotics employing Challenge Based Learning methodology. One of the first steps in the project development is the definition of current landscape in the research field. Which means to carry out a literature mapping that considers previous applications of Challenge Based Learning in STEAM education and use of robots and physical devices to do so. This paper shows the mapping review process and the main results obtained. The mapping analyze 242 candidate works from the most relevant bibliographic sources and selected 54. Form them it was possible to see that there are not many initiatives on STEM Education related to Challenge base learning and the most of them are specially focused on the application of specific tools and in the development of concrete competences.

Abstract
In a recent paper (10.1007/s11192-020-03386-9) we proposed a model to estimate the citations of an article in a database (Scopus/Web of Science) in which it is not indexed using the percentile rank of the database (Web of Science/Scopus) in which it is indexed. In this study we supplement the previous work with three advances: (1) by using 15 different research fields, corresponding to over 1 million papers, since we previously used only four fields; (2) by measuring the agreement between the percentile ranks in both databases using Lin's concordance correlation coefficient, since this coefficient has not been used previously to measure this agreement, but as a test with a sample of 15,400 papers to compare the actual and estimated number of citations; and (3) by using a robust data cleaning procedure. The results revealed a substantial concordance between percentile ranks of papers indexed in these two databases in all the research fields studied, and that this concordance is even stronger for high percentile values. This level of concordance suggests that we can consider the percentile of a paper in a database in which it is not indexed as being equal to the percentile of this paper in a database in which it is indexed. In other words, we increased the reliability of our previous conclusions that the percentile rank can be used as a citation database-normalization. The results of this study contribute to improve the use of citation counts in bibliometric studies, and to calculate research indicators when we need to use both bibliographic databases.

Abstract
The problem of the consumption or provision of common and public goods is a well known and well studied problem in economic sciences. The nature of the problem is the existence of non-excludable externalities which gives rise to incentives to free-riding behaviour. There are several economical frameworks trying to deal with the problem such as coalition theory or mechanism design and implementation theory to ensure a Pareto efficient consumption or provision of such good. Baliga and Maskin considered an environmental game where several communities face a problem of pollution reduction. They show that all communities except one of them have incentives to act as a free-rider, i.e. only one community is willing to face the costs that air cleaning implies, namely the one with greatest preference for the good. In this work we introduce an adaptive evolutionary dynamics for the generalization of the Baliga-Maskin model to quasi-linear utility functions. We show that the Baliga-Maskin equilibrium is the only asymptotically stable dynamical equilibrium, all others being unstable. This result reasserts the problem of free-riding and externalities for the case of a common good in a dynamically/evolutionary setting, and reiterates the relevance of mechanism design and coalition formation in the context of dynamical models.