In this study, we utilized a convolutional neural network (CNN) trained on microscopic images encompassing the SARS-CoV-2 virus, the protozoan parasite “plasmodium falciparum” (causing of malaria in humans), the bacterium “vibrio cholerae” (which produces the cholera disease) and non-infected samples (healthy persons) to effectively classify and predict epidemics. The findings showed promising results in both classification and prediction tasks. We quantitatively compared the obtained results by using CNN with those attained employing the support vector machine. Notably, the accuracy in prediction reached 97.5% when using convolutional neural network algorithms.

Human capital, which is a key resource of every organization, is characterized by high sensitivity to social, cultural and other factors that are not necessarily economic in nature. In the process of managing this capital, employee satisfaction becomes key, resulting from various reasons. In this study, we attempted to examine the level of satisfaction of university employees. The aim of this study was to gather information on the level of employee satisfaction with their job positions and to examine the relationships between selected, identified factors influencing their job satisfaction. The paper used multivariate statistical analysis, mainly Wilcoxon tests and Spearman rank correlation. Analysis of the survey results confirmed significant relationships between factors such as work atmosphere, appreciation of work effects, proper division of responsibilities and possible help in the team.

Currently, important efforts are being made to improve governability and governance by combining the monopoly of state decisions with the collaboration of diverse actors in public practice. Based on the above, the purpose of this article is to analyze the evolution of conceptual approaches to both terms over the last 23 years, examining scientific production by author authors, journals, and countries. The methodology was based on a bibliometric analysis: First, the WoS and Scopus databases were searched. Subsequently, scientometric techniques and the Science Tree methodology were used to identify patterns, structures, and trends, to understand the progress and behavior of scientific production, and to measure the quantity and quality of research that has addressed these issues from different perspectives. This study examined governability and governance publications and their annual citations to assess their impact and analyzed the total output of both datasets to identify similarities and differences in governability and governance research. The findings reveal that the number of publications and citations in this field is increasing, with the United States being the most academically influential country and the journal Marine Policy being the most prominent in ranking. These data provide key information for decision-makers, researchers, and academics for future debate and discussion toward operationalizing the concepts at the practical level of action, management, and the functioning of government structures.