Although there is clear dose-dependence of pulmonary toxicity caused by inhalation of normobaric oxygen in animal studies, the threshold of toxicity in humans remains largely unknown. The aim of this systematic review of published clinical studies was to establish threshold in terms of total oxygen dose administered under normal pressure by inhalation that causes first clinical signs of toxicity. MEDLINE, EBSCO, The Cochrane Central Register of Controlled Trials (Central), SCIndeks, Scopus, Google Scholar, and ClinicalTrials.gov were searched from their foundation to April 2022. The systematic review was performed according to the pre-registered protocol at PROSPERO. The studies were included if describing toxic effects of normobaric oxygen therapy in humans. In total 11 human studies of poor quality were found, with either experimental or observational design. In none of the analyzed studies did oxygen therapy cause toxic effects on the respiratory tract if the concentration of oxygen in the inhaled air was below 50%, regardless of the rate of administration. The toxic consequences of inhaling oxygen at a concentration of more than 50% occurred only after oxygen was administered for more than 6 hours, at a rate of more than 7 L/min, and were mainly reflected in inflammation of the tracheobronchial mucosa, with epithelial erosions. Normobaric oxygen therapy can have toxic effects in humans if the oxygen concentration in the inhaled air is higher than 50%, if the administration rate is above 7 L/min, and if the application lasts at least 6 hours.

Understanding the level of economic freedom is an important indicator for investors and policymakers. The index of economic freedom, which the Heritage Foundation releases annually, is the most significant of the methods used to measure this indicator in practice, as this index evaluates the degree of market openness over the degree of fiscal and regulatory restraint. The research presented in this paper was conducted in order to establish the level of economic freedom in the Balkan countries. For this purpose, a multi-criteria ranking of Balkan countries based on economic freedom criteria was used. The weight of the criteria was determined using the Entropy method, and the countries were ranked using the CRADIS (Compromise Ranking of Alternatives from Distance to ideal Solution) method. These methods employed a double normalisation approach, and according to the results of this application, Bulgaria has the best indicators of economic freedom, while Montenegro has the worst, with sensitivity analysis and validation of the results confirming these findings. The approach of using double normalisation contributes to decision-making stability since the results of different methods are uniform when compared to the use of the classical approach in the case of multi-criteria analysis methods.

This research is focused to identifying the most suitable plum variety for establishing a new orchard, aiming to achieve optimal outcomes. To accomplish this goal, multi-criteria decision-making model has been developed striving to support decision-making process. The gained results are based on experience of experts engaged in assessment of certain plum varieties. The analysis of collected expert ratings has involved mutual use of 3 methods, where the FUll COnsistency Method (FUCOM) and CRiteria Importance Through Intercriteria Correlation (CRITIC) methods were applied to determine the weights of selected criteria. The results of applying these methods demonstrated that the Maretability criterion is of highest importance. Besides, the fuzzy MARCOS method (Measurement Alternatives and Ranking according to Compromise Solution) has been applied to rank the plum varieties according to expert ratings. Derived results revealed that the ?Cacanska rodna? and ?Stanley? varieties were ranked as the most favorable, while the ?Prezident? variety was assessed as the most unfavorable. Further, gained research outcomes were corroborated by the sensitivity analysis and results validation. This research contributes to improvement of fruit growing in BiH by previous adequate selection of available plum varieties towards the establishing of new orchards and yielding optimal outcomes.

According to applied TOPSIS multi-criteria decision-making method (Technique for Order of Preference by Similarity to Ideal Solution), in paper was selected adequate sales distribution channel in one enterprise active within the agro-food sector at the territory of Semberija (BiH). Decision makers, in this case represented by employed management in enterprise, have been evaluated five sales distribution channels in enterprise in line to previously defined criteria, i.e. products' characteristics, company's financial situation, consumer habits, production costs, geographic concentration, and products' assortment. The main goal of research was to create a model for optimal selection of sales channels, while derived results have been showed that the model "producer - seller (retailer) - consumer" is the most adequate towards the predefined selection criteria. In addition to the justified role of used method in selection of offered alternatives, article also represents a base that will serve in further research, whose focus would be on modernizing of existing and searching for new distribution channels in agricultural enterprises.

Methods for automatic analysis of user interfaces are essential for a wide range of applications in computer science and software engineering. These methods are used in software security, document archiving, human-computer interaction, software engineering, and data science. Even though these methods are essential, no single research systematically lists most of the methods and their characteristics. This paper aims to give an overview of different solutions and their applications in the separate processes of automatic analysis of user interfaces. The main focus is on the techniques that analyze web page layouts and web page structure. Web pages’ style, type of content, and even structure constantly (often drastically) change, as do methods that analyze them. The fact that most methods use very different datasets and web pages of various complexities are some of the reasons that the direct comparison of methods is difficult, if not impossible. Another fact is that the vast applications of methods practically solve similar problems. With these facts in mind, in the paper, we surveyed relevant scientific articles, categorized them, and provided an overview of how these methods have developed over time.

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The constant developments in the area of accounting information systems unlock a wide area for contributing to the existing theory in the field of accounting information systems. Particularly in the case of the Federation of Bosnia and Herzegovina, where the benefits that the use of AIS brings with it, are not yet well recognized. The purpose of this research is to analyze the overall situation in the FBiH regarding the use of AIS in companies and its impact on strategic decisionmaking. Data is collected through surveys that were distributed to the companies in FBIH. Multinomial logistic regression was used to analyze the data. Research findings indicate that the industry sector and satisfaction with AIS are found to be statistically significant predictors of the probability of decision-making based on AIS and that accounting information is indispensable in the process of strategic decision-making, especially when it comes to the company's growth, investments, and borrowing.

The hotel industry is undergoing significant change as a result of technological advancements and shifting guest preferences. Artificial intelligence (AI) is playing an increasingly important role in this transformation, allowing hotels to provide personalized, efficient, and sustainable experiences that meet the needs of modern travelers. This paper provides an overview of the role and application of AI in the hotel industry, highlighting its benefits and challenges as well as presenting case studies that show how hotels are currently utilizing AI technology. According to the review of literature, AI technology can be used to optimize hotel operations, improve the guest experience, and boost sustainability efforts. However, the use of AI technology in the hotel industry raises concerns about data privacy and security, job displacement, and the need for human supervision to ensure ethical and responsible deployment. Finally, the paper discusses the future directions of AI in the hotel industry, highlighting the emergence of voice technology and augmented reality as potential areas for future innovation. This paper adds to the growing body of literature on the use of AI in the hotel industry and provides useful insights for hotel managers, technology providers, and researchers.

This paper investigates the absolute and conditional convergence process of the Western Balkan states toward the EU-27+1. The analyzed period is 2004–2018; therefore, we include the United Kingdom in the analysis. To test the effects of the 2008/2009 financial crisis on the absolute and conditional convergence process, we include three subperiods in this research: the precrisis period, the crisis period

Background: The pathophysiology and therapy of coronavirus disease-19 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), are a dilemma for scientists and health professionals, and the fact that patients show different symptoms and severity of the clinical picture also contributes to that. Objective: This paper aims to evaluate the effectiveness of therapeutic protocols (the use of immunomodulators) in the treatment of COVID-19 patients of various severity of the clinical picture by monitoring inflammatory markers (ESR and CRP), as well as the impact of the type and number of comorbidities patients had on these markers. Methods: A total of 200 patients with a mild (n=76), moderate (n=70) or severe (n=54) clinical picture was included. Inflammatory markers [ESR (erythrocyte sedimentation rate), CRP (C-reactive protein)] were examined on three occasions: twice during hospitalization and once after hospital discharge. Immunomodulators used intrahospital were corticosteroids (methylprednisolone, dexamethasone, methylprednisolone + dexamethasone), tocilizumab or metenkefalin/tridecactide. Posthospital, patients were taking either methylprednisolone or did not use any immunomodulators. For statistical analysis, SPSS 26.0 and Microsoft Excel 2019 were used, with a level of significance of α=0.05. Nonparametric tests (Kruskal-Wallis and Wilcoxon Signed-Rank) were applied and effect size (ES) was calculated. Results: Three corticosteroid therapies used intrahospital caused a significant decrease in both inflammatory markers, especially in patients with a severe clinical picture, but the ES was the biggest with methylprednisolone + dexamethasone, then dexamethasone, and lastly methylprednisolone. Posthospital, methylprednisolone caused a significant decrease in both inflammatory markers, especially in patients with a severe clinical picture. The most common comorbidity in all patients, as well as in patients with a severe clinical picture, was hypertension. There was no statistically significant impact of the number of comorbidities patients had on ESR and CRP, but the highest number of comorbidities was in patients with a severe clinical picture. Conclusion: The use of immunomodulators, especially methylprednisolone + dexamethasone intrahospital and methylprednisolone posthospital, is justified in most COVID-19 cases as there is a significant correlation between this disease’s pathophysiology and the immune response. There is also a positive correlation between the number of comorbidities patients have and the severity of the clinical picture.

The primary objective of this research paper is to investigate the potential impact of emergency remote teaching on the academic performance of undergraduate students, while also assessing the consistency of academic outcomes across various courses during the emergency transition to distance learning. The research methodology involves the collection of students' accomplishments and course passing rates spanning four consecutive academic years, from 2018/2019 to 2021/2022. The study identifies three distinct teaching environments: traditional, distance learning, and hybrid. The academic year 2018/2019 is designated as a pre-pandemic reference point. The subsequent years mark a transition from distance learning to a hybrid teaching model and a return to the traditional in-class environment. The analytical framework includes descriptive and correlation analyses, supplemented by an analysis of variance to derive meaningful insights. It is essential to highlight that the results obtained are further validated by the passing rates for the academic year 2022/2023, reinforcing the contemporary relevance and credibility of the research findings.