Science is built upon the continuous re-evaluation of evidence and empirical research driven by the desire for success and the fear of failure, while religion is based on the unconditional acceptance of original dogmatic traditions and fundamental principles of belief in God and eternal reward, coupled with the fear of divine punishment. Metaphysics, as the foundation of philosophical scientific thought, examines the nature of reality and existence, asking questions about what exists, why, in which time, space, and causality. Disaster risk management is an exact scientific discipline established on metaphysical examinations of causes and phenomena, along with mathematical models of prediction and consequence analysis. This paper explores the intriguing correlation between the logical relationships of metaphysical principles and disaster risk management. By delving into the philosophical realm of metaphysics, we analyze concepts such as uncertainty, causality, and the nature of reality. Drawing correlative connections, we examine the development of a logical matrix of cause and effect to better understand metaphysical principles that can timely alert decision-makers and improve their risk management strategies. Researching the interconnections of fundamental principles in the domains of risk, impact, and response capacity to crises offers a fresh perspective on addressing uncertainty and making informed decisions in complex situations. Conclusions will be defined using analytical-deductive and synthetic methods, comparing the relationship between metaphysics and applied science within the framework of the multimillennial challenges faced by humanity, from the time of Noah's flood to contemporary crises and approaches to resolving them. The paper will scientifically determine risks, impacts, and capacities for more effective responses to climatic and socio-political crises, challenging the professionalscientific community to proactively offer answers to the question: Can the acceptance and understanding of the 3D logical model of integrated application of metaphysics and risk management contribute to reducing the vulnerability of humankind?

Introduction/purpose: The paper presents the multi-criteria Fuzzy DIBR-Fuzzy DIBR II-EWAA-BM-DEXi-Fuzzy LMAW model for choosing a location for crossing water obstacles by fording in a defense operation. After the identification of the criteria by experts in this field, the mentioned model was applied and the optimal point was determined. In order to test the consistency of the results and the validity of the model, experts were consulted again, and the sensitivity analysis and the comparative analysis were performed. Methods: The Fuzzy DIBR and Fuzzy DIBR II methods were used to determine the weighting coefficients of the identified criteria, while the aggregation of the expert opinions and the obtained values was performed using the EWAA and BM operators. To select the optimal location, the Fuzzy LMAW method was applied, while the linguistic descriptors were determined using the DEXi decision support system. Results: The proposed methodology made it possible to identify all the criteria that determine the choice of a location and the choice of the optimal point for crossing a water obstacle in a defense operation. The testing of the model by experts, the analysis of the sensitivity of the output results to changes in the weights of the criteria and the comparison of the obtained results with the results of other methods indicated the fact that the model is valid and that it gives consistent results. Conclusion: It was concluded that the multi-criteria model provides the necessary help to decision makers in conditions of imprecise and unspecified information and that it is applicable in real situations. Also, the proposed model takes into consideration all the aspects that must be considered when making such a complex decision and helps less experienced officers in the decision-making process, reducing the possibility of errors, which can result in human casualties. Finally, directions for further research in the field of overcoming water obstacles and multicriteria decision making are suggested.

Distributed generation (DG) especially energy acquired from renewable energy sources (RES) plays a significant role in modern power sector due to high carbon emissions around the globe. Its emerging potential is feasible by implementing microgrids as they are beneficial for networks in terms of increasing flexibility and stability, providing frequency and voltage support, power factor compensation etc. This makes the investment into microgrid incorporating RESs attractive, while at the same time reducing overall investment in the grid. Higher cost and stochastic nature of intermittent RES are complications for the implementation and operation of such solutions. This paper will analyse economic feasibility of hybrid power system (HPS) implementation consisting of a wind generator (WG), a photovoltaic system (PVS), gas combined heat and power plant (CHP) and storage batteries. Each of the elements is optimized according to power demand and RES’s potential. Technical analysis of the grid integration, parallel operation of the system and the grid is analysed with an example of a real medium-voltage distribution network operating in Bosnia and Herzegovina by using quasi-dynamic load flow simulation of one-week time-period. Finally, different operating mechanisms and strategies will be proposed, following the minimal power form the grid premise to satisfy maximum usability of RES’s potential. It is shown that implementing such HPS would be beneficial in terms of both economy and, ecology, as well as in reducing energy losses. Besides, it will reduce power supplying costs and energy losses, as well as and secure better exploitation and utilization of natural renewable energy sources. These technologies positively affect power network by decreasing the risk of network-components overloading, better exploiting the power-generation facilities based on renewable resources and positively impacting voltage profiles. Similar places, situated on remote locations, may use this analysis as an example to follow, to reduce their costs of electricity, acquire more reliable and sustainable power supply, and embrace green future.

We investigate a discrete counterpart of planar dynamical system of nonlinear differential equations induced by kinetic differential equations for a two-species chemical reaction. Chemical reactions exhibit a wide range of dynamical behavior. We show how the theoretical analysis provides insight into the potential behavior of chemical reaction systems, determining the areas of parametric space which indicate scenarios for local stability, then for one type of bifurcation co-dimension one and one type of bifurcation co-dimension two. Precisely, we prove the existence of period-doubling bifurcation and 1:2 resonance bifurcation also, by using the center manifold theorem and the technique of normal forms. All mathematical investigations are illustrated with numerical examples, bifurcation diagrams, Lyapunov exponents and phase portraits.

In this study, the selection of suppliers within an alternative food supply network for fruits and vegetables, specifically Box Schemes, was conducted using multi-criteria decision-making methods. The Entropy-MABAC method was used as the multi-criteria decision-making approach, and the research focused on five suppliers from the city of Novi Sad. Eleven socioeconomic criteria were chosen for the research to identify the most favourable supplier. The results indicate that the criterion "product character," i.e., whether the final agricultural product is organic or conventional, was rated the highest, and the first supplier was selected as the most favourable. These results provide a solid foundation for future research, which should focus on further examining the impact of supply methods on end consumers of agricultural products within the alternative food network and developing new methods to aid in selecting the most favourable supplier.

Background: The organizational climate is defined as the perception of events within the work environment (relationships, values, actions) among organization members that are psychologically meaningful. It also includes the influence of the surroundings on employee motivation and behavior. This concept is studied within the field of industrial and organizational psychology, particularly focusing on healthcare institutions. Objective: The study aims to explain the concept, definition, and history of organizational climate, with a specific focus on healthcare institutions. It also aims to examine the factors influencing the work environment and the extent to which they can improve it. Methods: The research utilizes both quantitative and qualitative methods. The quantitative approach is presented through a non-standardized survey method. Qualitative research was conducted using case studies of healthcare institutions in Sarajevo Canton. The integration of these methods allowed for a comprehensive examination of the organizational climate. Results: The survey provided detailed insights into the organizational climate within healthcare institutions in Sarajevo Canton. It identified key factors that influence the work environment and highlighted areas for potential improvement. Discussion: The findings underscore the importance of strategic management of human resources and potential in creating a positive organizational climate. The study suggests that improving organizational climate is a long-term, multi-layered process involving doctors, managers, and all organizational members working towards common goals. Further research is needed to explore specific interventions that can enhance organizational climate in healthcare settings. Conclusion: This underscores the need for healthcare institutions to focus on fostering a supportive organizational climate and nurturing positive interpersonal interactions to enhance overall job satisfaction among employees.

Physical inactivity, unhealthy diet, fast-paced lifestyle, as well as genetic predispositions lead to the appearance of diabetes mellitus, and with it many other complications, of which diabetic foot syndrome is very common. In order to avoid complications with the diabetic foot, one of the forms of prevention is wearing specially designed footwear that protects and reduces the pressure on the foot and thus the risk of ulcers. Insoles also play a big role in preventing complications. The paper will present a conceptual solution of a model of footwear for patients with diabetes mellitus and a prototype of an insole made of knitwear, which was previously printed with medical clay, honey and extracts of the plants Rosmarinus officinalis and Zingiber officinale. Samples of knitwear that were printed with a paste containing Rosmarinus officinalis extract showed exceptional antimicrobial activity against Staphylococcus aureus bacteria. Replaceable insoles for footwear are intended for the prevention of complications from Diabetes mellitus.

AI-driven data analysis methods have garnered attention in enhancing the performance of wireless networks. One such application is the prediction of downlink throughput in mobile cellular networks. Accurate throughput predictions have demonstrated significant application benefits, such as improving the quality of experience in adaptive video streaming. However, the high degree of variability in cellular link behaviour, coupled with device mobility and diverse traffic demands, presents a complex problem. Numerous published studies have explored the application of machine learning to address this problem, displaying potential when trained and evaluated with traffic traces collected from operational networks. The focus of this paper is an empirical investigation of machine learning-based throughput prediction that runs in real-time on a smartphone, and its evaluation with video streaming in a range of real-world cellular network settings. We report on a number of key challenges that arise when performing prediction “in the wild”, dealing with practical issues one encounters with online data (not traces) and the limitations of real smartphones. These include data sampling, distribution shift, and data labelling. We describe our current solutions to these issues and quantify their efficacy, drawing lessons that we believe will be valuable to network practitioners planning to use such methodologies in operational cellular networks.