Abstract
The technological advances in Unmanned Aerial Vehicles (UAV) related to energy power structure inspection are gaining visibility in the past decade, due to the advantages of this technique compared with traditional inspection methods. In the particular case of power pylon structure and components, autonomous UAV inspection architectures are able to increase the efficacy and security of these tasks. This kind of application presents technical challenges that must be faced to build real-world solutions, especially the precise positioning and path following for the UAV during a mission. This paper aims to evaluate a novel architecture applied to a power line pylon inspection process, based on the machine learning techniques to process and identify the signal obtained from a UAV-embedded planar Light Detection and Ranging - LiDAR sensor. A simulated environment built on the GAZEBO software presents a first evaluation of the architecture. The results show an positive detection accuracy level superior to 97% using the vertical scan data and 70% using the horizontal scan data. This accuracy level indicates that the proposed architecture is proper for the development of positioning algorithms based on the LiDAR scan data of a power pylon.

Abstract
Recent studies show that many real-world software faults are due to slight modifications (mutations) to the program. Thus, analyzing transformations made by a developer and associating them with well-known mutation operators can help pinpoint and repair the root cause of failures. This paper proposes a mutation operator inference technique: given the original program and one of its subsequent forms, it infers which mutation operators would transform the original and produce such a version. Moreover, we implemented this technique as a tool called Morpheus, which analyzes faulty Java programs. We have also validated both the technique and tool by analyzing a repository with 1753 modifications for 20 different programs, successfully inferring mutation operators 78% of times. Furthermore, we also show that several program versions result from not just a single mutation operator but multiple ones. In the end, we resort to real-world case studies to demonstrate the advantages of this approach regarding program repair.

Abstract
To identify the most frequently developed topics in the area of Big Data and Digital Marketing, a quantitative analysis was developed in December 2020. This analysis was focused on 750 publications and later on 67 publications on Big Data and Digital Marketing from the Scopus database. A bibliometric analysis was developed using the VOSviewer software and the technique of term co-occurrence and author co-authorship. Clusters were found for each of the analyzed situations. © 2021 AISTI.

Abstract
The growth in social media use has given rise to concerns about the impacts it may have on users' psychological well-being. This paper's main objective is to shed light on the effect of social media use on psychological well-being. Building on contributions from various fields in the literature, it provides a more comprehensive study of the phenomenon by considering a set of mediators, including social capital types (i.e., bonding social capital and bridging social capital), social isolation, and smartphone addiction. The paper includes a quantitative study of 940 social media users from Mexico, using structural equation modeling (SEM) to test the proposed hypotheses. The findings point to an overall positive indirect impact of social media usage on psychological well-being, mainly due to the positive effect of bonding and bridging social capital. The empirical model's explanatory power is 45.1%. This paper provides empirical evidence and robust statistical analysis that demonstrates both positive and negative effects coexist, helping to reconcile the inconsistencies found so far in the literature.

Abstract
Despite the significant increase in the use of digital devices, and the access to e-books by younger ages, the printed book still remains very important. Nowadays, although many communication processes and information exchanges have a digital support, the importance of using printed paper is acknowledged in many contexts. Both the paper and the digital media have unique advantages: digital media integrate with audiovisual and interactive resources, and the paper book supports interactions such as tactile and kinesthetic feedback given to both hands. In recent years there have been several commercial products designated as "augmented books", using augmented reality technologies to provide the reader with more layers of information, thereby fostering the use of the book in new ways. So, in this concept paper we describe part of the research and outcomes of project CHIC – C3, aimed at designing and developing a platform for managing the production of digital content connected with printed books. Furthermore, we propose a model for the gamification of digital content based on the printed book, mainly aimed at educational purposes. A proof of concept for the model was built in the form of a companion platform, supported by the Moodle LMS, fully integrated with the main CHIC website. Readers are able to access the platform, engage in several content related games, and interact with other readers.

Abstract
Purpose - The ex-post literature, which evaluates the real impact of renewable generation, is scarce. Most studies are simulations and therefore are not based on real data. This study aims to further this goal using a unique database of the Portuguese spot market, where there are powerful incentives for renewable electricity. Design/methodology/approach - This paper analyses ex-post the impact of energy produced in special regime on the wholesale hourly spot market prices of Portuguese electricity during the period 2009-2016. This paper uses standard, two stage least squares and generalized method of moments multivariate regressions and other energy econometrics techniques. Findings - It is found that special regime generation has a negative impact on the wholesale price. This impact is higher than that found in other markets. This paper also concludes that using special regime generation to supply the future growth of demand will decrease wholesale electricity spot prices more intensively than using other technologies. Originality/value - This paper uses a unique database based on ex-post for the Portuguese spot market. The Portuguese case is particularly interesting, not only because of its strong incentives policy on renewable energy but also because its spot market is interconnected with the Spanish market. This paper contributes to the debate about the sustainability of current renewable electricity support schemes. The decreasing trend in electricity prices, with the introduction of new renewable capacity, can be incompatible with the required payments for non-renewable producers. This paper also shows that even if the price reduction on spot markets is transferred to final consumers, given that it is relatively small (8% spot price which represents 45% of the final price), compared with the cost of incentives (35% of the final price), consumers probably will not be able to support a new investment pipeline with a similar framework.