Both the reduction in operating and maintenance (O&M) costs and improved reliability have become top priorities in wind turbine maintenance strategies. O&M costs typically account for 20% to 25% of the total levelized cost of electricity (LCOE) of current wind power systems. This paper provides a general review of the state of the art of research conducted on wind farm maintenance in recent years. It shows the new methods and techniques, focusing on trends and future challenges. In addition to this, this work includes a review of the following items: (i) operation and maintenance, (ii) failure rate, (iii) reliability, (iv) condition monitoring, (v) maintenance strategies, (vi) maintenance and life cycle and (vii) maintenance optimization As for offshore wind turbines, it is crucial to limit the maximum faults, since the maintenance of these wind farms is more complex both technically and logistically. Research into wind farm maintenance increased by 87% between 2007 and 2019, with more than 38,000 papers (Scopus) including “wind energy” as the main topic and some keywords related to O&M costs. The LCOE in onshore wind projects has decreased by 45%, while in offshore projects it has decreased by 28%. The O&M costs of onshore wind projects fell 52%, while in the case of offshore projects, they have declined 45%. Thus, the results obtained in this paper suggest that there is a change in research on wind farm operation and maintenance, as in recent years, scientific interest in failure has been increasing, while interest in the various techniques of wind farm maintenance and operation has been decreasing.

Nuclear energy is presented as a real option in the face of the current problem of climate change and the need to reduce CO2 emissions. The nuclear reactor design with the greatest global impact throughout history and which has the most ambitious development plans is the Pressurized Water Reactor (PWR). Thus, a global review of such a reactor design is presented in this paper, utilizing the analysis of (i) technical aspects of the different variants of the PWR design implemented over the past eight years, (ii) the level of implementation of PWR nuclear power plants in the world, and (iii) a life extension scenario and future trends in PWR design based on current research and development (R&D) activity. To develop the second analysis, a statistical study of the implementation of the different PWR variants has been carried out. Such a statistical analysis is based on the operating factor, which represents the relative frequency of reactors operating around the world. The results reflect the hegemony of the western variants in the 300 reactors currently operating, highlighting the North American and French versions. Furthermore, a simulation of a possible scenario of increasing the useful life of operational PWRs up to 60 years has been proposed, seeing that in 2050 the generation capacity of nuclear PWRs power plants will decrease by 50%, and the number of operating reactors by 70%.

The integration of artificial intelligence (AI) into project management (PM) transforms how projects are planned, executed, and monitored. The main objective of this study is to provide a comprehensive bibliometric analysis exploring trends, thematic areas, and future directions in AI applications in project management by examining publications from the last decade. This research uncovers dominant themes such as machine learning, decision making, information management, and resource optimization. The findings highlight the growing use of AI to enhance efficiency, accuracy, and innovation in PM processes, with recent trends favoring data-driven approaches and emerging technologies like generative AI. Geographically, China, India, and the United States lead in publications, while the United Kingdom and Australia show a high citation impact. The research landscape, including AI-enhanced decision-making frameworks and cost analysis, demonstrates the diversity of AI applications in PM. An increased interest in the use of generative AI and its impact on PM and project managers was observed. This analysis contributes to the field by offering a structured overview of research trends, defining the challenges and opportunities for integrating AI into project management practices and offering perspectives on emerging technologies.

Today, soft skills (transversal competencies) are increasingly appreciated by employers as essential skills for professional success. Likewise, these competencies are necessary to be able to operate as individuals in today’s society. In view of this situation, in the future post-COVID-19 educational model it is necessary to design training programs that promote both hard skills (specific competencies) and soft skills. This fact brings to the table the need for university teachers to have an optimal level of soft skills so that their students can acquire them. Given this situation, this paper aims to analyze the degree of acquisition of this type of competencies in American university teachers from different regions: (i) North America; (ii) Central America, and (iii) Southern Cone. To achieve this objective, it has been necessary to develop a questionnaire on the self-concept of soft skills, based on several variables: (i) gender, (ii) age range, (iii) geographic area, (iv) area of knowledge, (v) years of teaching experience, and (vi) university tenure (public-private). The questionnaire developed was based on the soft skills included in the Bochum Inventory of Personality and Competences (BIP). Results, obtained by descriptive and inferential statistical analysis of the means and deviations of the data collected from a sample of 473 participants, reflect that, in general, the American university teachers have a high self-concept about their degree of soft skills development. Although results show significant differences depending on each variable considered in this study, it can be suggested that the American university teachers are prepared to face a mixed university educational model, which promotes equally both hard skills and soft skills.

This paper conducts quantitative research on the influence of the COVID-19 pandemic on the adaptation to digital learning environments (DLE) of a group of 908 university professors. We compared the perceptions of participants who were digital natives (born before 1980) with those of digital immigrants (born after 1980). For this purpose, a validated survey was used and the obtained responses statistically analyzed. The results show a negative correlation between pandemic stress and the digital competence of professors and their adaptation skills to digital environments, which although weak for both of the two groups compared are stronger for digital immigrants. Both self-confidence and digital competence show a positive influence on the perception of adaptation of skills to DLE, and this is weaker in digital natives. Gaps were identified by gender and area of knowledge of the participants; consequently, the need to carry out training actions for university faculty on skills linked to their digital competence in teaching is clear.