Abstract
Phasor Measurement Unit (PMU) provides beneficial information for dynamic power system stability, analysis and control. One main application of such useful information is data-driven control. This paper is devoted to presenting an approach for optimal signal selection in PMU-based power system stabilizer (PSS) design. In this paper, for selecting the optimal input and output signals for PSS, an algorithm is suggested in which the combination of clustering the generators and the buses of the system with ICA, modal analysis and PCA techniques is used. The solution for optimal PSS input-output selection is found to increase the observability and damping of the power system. This method is simulated on a 68 buses system with 16 machines. To compare the results with the previous methods, the system is simulated and the results of two previously-developed algorithms are compared with the proposed approach. The results show the benefit of the suggested method in reducing the required signals, which lowers the number of required PMUs while the system damping is not deteriorated.

Abstract
The COVID-19 crisis exposed the vulnerability and poor resilience of the global supply chains. The objective of this research is to reflect on the possible impacts of the Coronavirus crisis in the global supply chains and provide some recommendations to overcome the present situation, offering suggestions for future research: (1) What are the contingency factors affecting Supply Chains in the complex COVID-19 operating environment? (2) How do these factors affect post-COVID-19 operating performance? After a contextualization of the COVID-19 pandemic crisis and its impacts, theoretical background on Supply Chains and Supply Chain Management are presented, and a summary of the main scenarios for the post-COVID-19 crisis are discussed. The propositions regarding the contingency factors and their impact on the Supply Chain operating performance in post-COVID-19 suggest that successful companies will focus on creating a new kind of operational performance and minimize risks. To that end, companies will aim to improve their operations' resilience (ability to resist, hold on, and recover from shocks) and accelerate the end-to-end digital transformation. Consumers will have to adapt to the contact-free economy, less low-cost supply chains, and put additional emphasis on service levels. Governments will reinforce the focus in the health sector supply chain and increase spending in the health and social care sectors. Furthermore, the longer, the more concentrated, the less transparent, and the more price sensitivity is the supply chain, the more challenging the adaptation to the new pos pandemic realities. Suggestions for future research are also provided.

Abstract
The science and technology (S&T) binomial is often considered in the literature as an innovation system per se. Different theoretical frameworks, such as the 'national innovation systems', 'regional innovation systems' and the 'triple helix', were put forward in order to conceptualising the role of a diversity of agents in innovation processes underpinning knowledge-driven economies. More recently, the conceptual framework of smart specialisation has reinforced the importance of innovation and its diffusion in the entrepreneurial sector. Universities are still deemed as having a potentially pivotal role to play, not only in knowledge production but also in innovation delivery. The goal of this research is to discuss the importance of universities as sources of knowledge for innovative activities in Portugal. A panel comprising three waves of the CIS was built to estimate a hurdle model, the discussion of the estimation results attempt to provide some policy recommendations on the role of universities in knowledge production and diffusion and its connection to innovative firms. © 2020 Inderscience Enterprises Ltd.

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.