Abstract
The combined adoption of Agile and DevOps enables organizations to cope with the increasing complexity of managing customer requirements and requests. It fosters the emergence of a more collaborative and Agile framework to replace the waterfall models applied to software development flow and the separation of development teams from operations. This study aims to explore the benefits of the combined adoption of both models. A qualitative methodology is adopted by including twelve case studies from international software engineering companies. Thematic analysis is employed in identifying the benefits of the combined adoption of both paradigms. The findings reveal the existence of twelve benefits, highlighting the automation of processes, improved communication between teams, and reduction in time to market through process integration and shorter software delivery cycles. Although they address different goals and challenges, the Agile and DevOps paradigms when properly combined and aligned can offer relevant benefits to organizations. The novelty of this study lies in the systematization of the benefits of the combined adoption of Agile and DevOps considering multiple perspectives of the software engineering business environment.

Abstract
Research into teaching and learning methodologies is intense and demonstrates the academic community's unrelenting need to understand how people learn in a continuous effort to improve efficiency in the transmission of knowledge. Teachers are dealing with a growing disengagement of students in recent decades. In part, this is due to the increase in the spread of ICT technologies outside the classroom, particularly those supporting social networking and video games. New trends, such as gamification and flipped classroom, are emerging to try to find ways to stimulate increased student engagement and motivation. In this chapter, the authors present a critical reflection and field experiences, around the potential of joint implementation of gamification with flipped classroom, demonstrating possibilities of positive increment of efficiency and effectiveness of teaching and learning processes.

Abstract
Covid19 pandemic has stimulated both the discussion on the use of IT related teaching tools and the exposure of the student population to vulnerabilities linked to cybersecurity literacy. The study presented is based on the assumption that the use of gamification as an element or tool that promotes learning within digital environments may be feasible, and more specifically may function as a teaching element on issues related to cybersecurity for students, especially for higher education students. In order to quantify the openness of students to such a tool path, quantitative methodology was used, and a survey was carried out in two Polytechnic Institutions (PI), achieving a sample of 95 students, and seeking perceptions on positive impacts resulting from the creation of a game scenario for better learning. The statistical analysis conducted tested hypotheses regarding representations and practices about gamification and cybersecurity. Results show that students, regardless of their higher education course, clearly understand what Gamification is and its goals, and also that students adopt good cybersecurity practices according to their higher education course. This last result goes accordingly with the supposition that gamification can and should be used in cybersecurity literacy.

Abstract
There are Optimization Problems that are too complex to be solved efficiently by deterministic methods. For these problems, where deterministic methods have proven to be inefficient, if not completely unusable, it is common to use approximate methods, that is, optimization methods that solve the problems quickly, regardless of their size or complexity, even if they do not guarantee optimal solutions. In other words, methods that find acceptable solutions, efficiently. One particular type of approximate method, which is particularly effective in complex problems, are metaheuristics. Particle Swarm Optimization is a population-based metaheuristic, which has been particularly successful. In order to broaden the application and overcome the limitation of Particle Swarm Optimization, a discrete version of the metaheuristics is proposed. The Discrete Particle Swarm Optimization, DPSO, will change the PSO algorithm so it can be applied to discrete optimization problems. This alteration will focus on the velocity update equation. The DPSO was tested in an instance of the Traveling Salesman Problem, att48, 48 points problems proposed by Padberg and Rinaldi, which showed some promising results.

Abstract
There are different clean energy production technologies, including wind energy production. This type of energy, among renewable energies, is one of the least predictable due to the unpredictability of the wind. The wind prediction has been a deeply analysed field since has a considerable share on the green energy production, and the investments on this sector are growing. The efficiency and stability of power production can be increased with a better prediction of the main source of energy, in our case the wind. In this paper, some techniques inspired by Biological Inspired Optimization Techniques applied to wind forecast are compared. The wind forecast is very important to be able to estimate the electric energy production in the wind farms. As you know, the energy balance must be checked in the electrical system at every moment. In this study we are going to analyse different methodologies of wind and power prediction for wind farms to understand the method with best results.

Abstract
The need for sustainable power production has led to the development of more innovative approaches to production and storage. In light of this hydrogen production through wind power has emerged as sufficient in ensuring that the objectives of the Paris Agreement are made. This paper discusses the state-of-art models and controls used in ensuring that greater efficiency is achieved in the processes of energy to hydrogen transformation. The paper concludes with a comparison of the models and determination of one which suffices in ensuring that hydrogen/energy transformation is more efficient.