Recovery and resilience plan (RRP) approved by the European Commission fosters the development of lifelong learning programs to upgrade employees’ skills and knowledge for digital and green transitions. Within higher education, the field of information and communication technology (ICT) is also a priority area, so we compared the demographic variables of students enrolled in formal first-cycle higher education programs in ICT with those enrolled in lifelong ICT programs within the framework of the Advanced Computer Skills project funded by the RRP in Slovenia. The results show that formal first-cycle higher education in the field of ICT remains strongly male-dominated, whereas, among participants in lifelong learning, the percentage of females stands out. Bachelor programs in ICT are primarily enrolled by young people aged up to 24 years, while shorter university-based lifelong learning programs attract mostly older participants with higher completed formal education and from a broader range of prior educational backgrounds. Finally, when all three variables (gender, age and level of prior formal education) are considered, participants in lifelong learning are much more similar to part-time students than full-time bachelor ICT students, although the percentage of men in formal education is still predominant even in part-time studies. The research findings highlight the need for further efforts to offer lifelong learning in ICT to enable individuals to improve their employment prospects, progress in the workplace or even change their field of work.

Every sector must possess the ability to identify potential dangers, assess associated risks, and mitigate them to a controllable extent. The mining industry inherently faces significant hazards due to the intricate nature of its systems, processes, and procedures. Effective risk control management and hazard assessment are essential to identify potential adverse events that might lead to hazards, analyze the processes by which these occurrences may transpire, and estimate the extent, importance, and likelihood of negative consequences. (1) The stage of industrial hazard analysis assesses the capability of a risk assessment process by acknowledging that hidden hazards have the potential to generate dangers that are both unknown and beyond control. (2) To mitigate hazards in mines, it is imperative to identify and assess all potentially dangerous circumstances. (3) Upon conducting an analysis and evaluation of the safety risks associated with identified hazards, the acquired knowledge has the potential to assist mine management in making more informed and effective decisions. (4) Frequently employed methods of data collection include interrogation of victims/witnesses and collection of information directly from the accident site. (5) After conducting a thorough analysis and evaluation of the safety hazards associated with hazard identification, the dataset has the potential to assist mine management in making more informed decisions. The study highlights the critical role of management in promoting a strong safety culture and the need for active participation in health and safety systems. By addressing both feared and unknown risks, educating workers, and utilizing safety-related data more effectively, mining companies can significantly improve their risk management strategies and ensure a safer working environment.

The human brain has been described as a complex system. Its study by means of neurophysiological signals has revealed the presence of linear and nonlinear interactions. In this context, entropy metrics have been used to uncover brain behavior in the presence and absence of neurological disturbances. Entropy mapping is of great interest for the study of progressive neurodegenerative diseases such as Alzheimer’s disease. The aim of this study was to characterize the dynamics of brain oscillations in such disease by means of entropy and amplitude of low frequency oscillations from Bold signals of the default network and the executive control network in Alzheimer’s patients and healthy individuals, using a database extracted from the Open Access Imaging Studies series. The results revealed higher discriminative power of entropy by permutations compared to low-frequency fluctuation amplitude and fractional amplitude of low-frequency fluctuations. Increased entropy by permutations was obtained in regions of the default network and the executive control network in patients. The posterior cingulate cortex and the precuneus showed differential characteristics when assessing entropy by permutations in both groups. There were no findings when correlating metrics with clinical scales. The results demonstrated that entropy by permutations allows characterizing brain function in Alzheimer’s patients, and also reveals information about nonlinear interactions complementary to the characteristics obtained by calculating the amplitude of low frequency oscillations.

Given the heavy workload faced by teachers, automatic speaking scoring systems provide essential support. This study aims to consolidate technological configurations of automatic scoring systems for spontaneous L2 English, drawing from literature published between 2014 and 2024. The focus will be on the architecture of the automatic speech recognition model and the scoring model, as well as on features used to evaluate phonological competence, linguistic proficiency, and task completion. By synthesizing these elements, the study seeks to identify potential research areas, as well as provide a foundation for future research and practical applications in software engineering.

Natural forests and abandoned agricultural lands are increasingly replaced by monospecific forest plantations that have poor capacity to support biodiversity and ecosystem services. Natural forests harbour plants belonging to different mycorrhiza types that differ in their microbiome and carbon and nutrient cycling properties. Here we describe the MycoPhylo field experiment that encompasses 116 woody plant species from three mycorrhiza types and 237 plots, with plant diversity and mycorrhiza type diversity ranging from one to four and one to three per plot, respectively. The MycoPhylo experiment enables us to test hypotheses about the plant species, species diversity, mycorrhiza type, and mycorrhiza type diversity effects and their phylogenetic context on soil microbial diversity and functioning and soil processes. Alongside with other experiments in the TreeDivNet consortium, MycoPhylo will contribute to our understanding of the tree diversity effects on soil biodiversity and ecosystem functioning across biomes, especially from the mycorrhiza type and phylogenetic conservatism perspectives.