In this study, we compared the effectiveness of AR-based homework, traditional homework, and mixed-approach homework in learning about circular motion. To that end, we conducted a pretest-posttest quasi-experiment involving 135 first-year students enrolled in an introductory physics course at the University of Zagreb, Faculty of Chemical Engineering and Technology, Croatia. The students in the experimental group completed augmented reality (AR)-based homework assignments. In these assignments, their learning about circular motion was supported by a meticulously designed worksheet that included four AR-supported activities. In the mixed-approach group, students were given a homework assignment that included three AR-supported activities and one quantitative textbook problem, whereas the traditional group’s homework consisted of four quantitative textbook problems covering the same content. Findings from our study suggest that the post-treatment scores for all groups were significantly higher than the pretreatment scores, with the largest pre-post gains observed in the mixed-approach group. We conclude that combining carefully selected quantitative problems with key AR activities is the most promising approach.

Hydropower is the world's most exploited renewable energy source. It provides a substantial, flexible, and reliable source of renewable energy, complementing other renewables like solar and wind power. Besides conventional hydropower potentials and technologies, the development of technologies for the exploitation of hidden hydropower potentials is an ongoing process. This paper presents the current state of hidden hydropower technologies and links them with possible applications in different hydropower potentials. Technologies and potential applications are structured within three main groups (pressurized systems, hydro storage, unpressurized systems), with their mutual interconnections analysed and displayed throughout the paper. The opportunity for the application of hidden hydropower technologies in different roles within the energy system is recognized through the concepts of off- and on-grid roles, the prosumer concept, and on-site measurement powering. This paper shows that hidden hydropower technologies could emerge as significant contributors to a smoother energy transition, especially with the prosumer and off-grid concepts.

BACKGROUND The childhood immunization coverage in Serbian communities in Kosovo after the 1999 armed conflict has not been investigated. The study purpose was to evaluate the trend of immunization coverage with vaccines from the national childhood immunization program in Serbian communities in Kosovo and Metohija from 2003 to 2022. METHODS Data were retrieved from the annual reports of the Public Health Institute of Kosovska Mitrovica received through notifications from the primary health centers where vaccines are being administered. Data were analyzed using the linear regression and join-point regression models. RESULTS In the examined period, a significant decrease in vaccination coverage was observed for the following diseases: diphtheria, tetanus and pertussis (DTP), polio, as well as measles, mumps and rubella vaccines (MMR), then, the first revaccination for DTP and polio, the second revaccination against diphtheria and tetanus for children (DT) and polio, and the third revaccination against diphtheria and tetanus for adults (dT), as well as the second dose of the MMR vaccine. During the COVID-19 pandemic, a significant decrease in coverage was observed for primary vaccination against: DTP, polio and hepatitis B, first and second doses of the MMR vaccine, as well as the first and second revaccination for DTP and polio, and the third revaccination for dT. CONCLUSION A decline in coverage with DTP, MMR, polio and hepatitis B vaccines was observed between 2003 and 2022. This was even more pronounced during the COVID-19 pandemic. Further research on individual-level factors contributing to lower vaccination coverage is warranted.

Simple Summary This study investigates lung cancer detection by combining metabolomics and advanced machine learning to identify small cell lung cancer (SCLC) with high accuracy. We analyzed 461 serum samples from publicly available data to create a stacking-based ensemble model that can distinguish between SCLC, non-small cell lung cancer (NSCLC), and healthy controls. The model has 85.03% accuracy in multi-class classification and 88.19% accuracy in binary classification (SCLC vs. NSCLC). This innovation relies on sophisticated feature selection techniques to identify significant metabolites, particularly positive ions. SHAP analysis identifies key predictors such as benzoic acid, DL-lactate, and L-arginine, shedding new light on cancer metabolism. This non-invasive approach presents a promising alternative to traditional diagnostic methods, with the potential to transform early lung cancer detection. By combining metabolomics and machine learning, the study paves the way for faster, more accurate, and patient-friendly cancer diagnostics, potentially improving treatment outcomes and survival rates.

In this article we investigate topography and electrical properties of potassium blue bronze thin films by the means of atomic force microscopy. Thin films were prepared by pulsed laser depositions on two types of substrates (Al2O3 and SrTiO3) at different substrate temperatures and partial oxygen pressures. On the basis of topography measurements, granular nature of the films was revealed. Surface roughness, as well as the size and the orientation of grains was determined. Films deposited on SrTiO3 substrates are quite homogeneous and the grains display ordering in preferential directions. Films on Al2O3 contain randomly oriented grains. Roughness of the films increases with the increase of the deposition temperature. Electrical measurements provided qualitative information regarding the electrical properties of the films.

Abstract This paper investigates the impact of artificial intelligence (hereinafter AI) on the accounting profession, emphasizing the need to adapt educational programs and business practices due to the emergence and development of AI technologies. A qualitative method with the help of a semi-structured interview was used to collect primary data. The participants were professionals in the accounting and information technology field who have the relevant knowledge and experience to consider this topic. The research aimed to discover the main problems that may arise when implementing artificial intelligence in the accounting profession, to determine how AI technologies affect the quality of financial reports, and whether education reform in accounting is needed due to the emergence of AI technologies. The results of the conducted research showed that AI technology will find its application in the accounting profession, that the quality of the financial report generated based on AI technology depends on the quality of the entered data, i.e. that the control function of accountants is of crucial importance, and that it is necessary to reform curricula in the context of exploiting the benefits of AI technologies.

Numerical and pseudo data for pion electroproduction from four reaction channels, p(γ*, π0)p, p(γ*, π+)n, n(γ*, π−)p, and n(γ*, π0)n, from threshold up to W = 1.575 GeV are used to perform a single energy partial wave analysis. As a constraint, higher partial waves are taken from the MAID07 model and lower partial waves are fitted. It is demonstrated that truncated partial wave analysis in a full isospin can be obtained with this procedure. The results for photon virtuality Q2 = 0.5 GeV2 are presented. Electromagnetic Eℓ±, Mℓ±, and longitudinal Lℓ± multipoles are presented and discussed. In the first step, numerical data are generated, and the optimal number of lower partial waves required for a good data fit is determined. In the second step, the same procedure is applied using generated pseudo data.

The river channel cut into an alluvial substrate constantly adapts to changes in water flow and sediment transport. This paper presents a new approach to determine the magnitude of channel deformation based on the definition of dimensionless spatial parameters of channel deformation. The new approach’s applicability is evaluated by experimental studies on the Željeznica River in the Sarajevo Field in central Bosnia and Herzegovina. The morphological changes of the channel over a period of ten years were analyzed using dimensionless parameters of the channel geometry. A numerical analysis of changes in the channel of the Željeznica River was carried out using a mathematical model and a selected equation for sediment transport. Sensitivity analysis of the model parameters for channel deformation and statistical reliability analysis of the numerical model showed a good agreement between the modeled and observed values of channel deformation parameters during the analyzed period.

Abstract This study seeks to examine pull factors of capital inflows, offering an empirical analysis based on a panel study of eleven Southeast European countries (Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Greece, Montenegro, North Macedonia, Kosovo, Romania, Serbia, and Türkiye) over the period of 2004 – 2021. Methodologically, the study utilizes a fixed effects (FE) regression model with robust Driscoll-Kraay standard errors to address issues of heteroskedasticity, autocorrelation, and potential cross-country correlation. The study finds that several pull factors can be relevant in driving capital inflows as follows: market size, inflation, financial and trade openness. The empirical analysis confirms that the forces of trade liberalization, financial liberalization, market size, real interest rates and inflation stability are the elements that encourage capital inflows. On the other hand, the estimated effects of current account balance and real economic growth are not very convincing. Finally, we stress that more study is required to fully understand the pull variables' ultimate macroeconomic implications at the national level. The overall influence of these positive (or negative) inflows may be moderated by several characteristics, even if certain countries may be extremely susceptible to these factors.

The aim of the research was to determine the psychometric properties of the Multidimensional Scale of Perceived Social Support in individuals with disabilities in Bosnia and Herzegovina. The research included a total sample of 232 participants, with an average chronological age of 44.21±19.31 years, of which 121 (52.2%) were male and 111 (47.8%) were female. The study was conducted among individuals with motor impairments, visual and hearing impairments, speech and language disorders, and combined disabilities. To achieve the research objective, the Multidimensional Scale of Perceived Social Support was applied, consisting of 12 assessment variables scaled from 1 to 7. The research data were processed using parametric and non-parametric statistical methods. A multivariate method of exploratory factor analysis was applied to identify factors in a given domain when the number and structure of factors are not previously known, along with confirmatory factor analysis using the maximum likelihood algorithm. Following factorization, the internal consistency coefficient (Cronbach's alpha) was calculated, and the reliability of the variables was assessed through inter-item statistics. Based on the obtained research results, it can be concluded that the Multidimensional Scale of Perceived Social Support has satisfactory reliability and internal consistency for use among individuals with disabilities in Bosnia and Herzegovina. The results of both exploratory and confirmatory factor analysis indicate a suitable three-dimensional model and confirm the original structure of the scale, which can be applied to individuals with disabilities in Bosnia and Herzegovina. Keywords: Social support, disability, validity, reliability, factor analysis.

Leisure time in contemporary society is increasingly becoming a crucial factor in shaping the personalities of children and youth. Alongside family, schools play a central role in organizing and shaping students' leisure time. The aim of this paper is to examine the role of schools in the pedagogical structuring of students’ leisure time and to explore differences in the perception of leisure time between students in urban and rural schools. The research was conducted on a sample of 140 seventh-grade students from elementary schools in the Tuzla Canton. The study analyzed students' ways of spending leisure time, the involvement and support of schools in organizing leisure time, and the perception of societal support for students' leisure activities. The results of the research indicate that students most frequently spend their leisure time in activities without significant pedagogical influence. Most students occasionally participate in school clubs, with significant differences observed between urban and rural schools in the type and number of activities available. Teachers and parents are the primary sources of support in organizing leisure time, while the broader community offers limited support. The findings suggest that schools play an important role in the organization of leisure time but that there are significant disparities in the activities available to students in different environments. Although activities such as sports and cultural clubs remain popular, students are increasingly gravitating towarddigital content, which may reduce the pedagogical value of leisure time. Schools should continue to develop and adapt leisure activities to meet students’ needs, with greater involvement from the broader community and support in fostering healthy and constructive patterns of leisure time usage. Keywords:school, children, education, leisure time.

Cancer progression is an evolutionary process driven by the selection of cells adapted to gain growth advantage. We present a formal study on the adaptation of gene expression in subclonal evolution. We model evolutionary changes in gene expression as stochastic Ornstein-Uhlenbeck processes, jointly leveraging the evolutionary history of subclones and single-cell expression data. Applying our model to sublines derived from single cells of a mouse melanoma revealed that sublines with distinct phenotypes are underlined by different patterns of gene expression adaptation, indicating non-genetic mechanisms of cancer evolution. Sublines previously observed to be resistant to anti-CTLA4 treatment showed adaptive expression of genes related to invasion and non-canonical Wnt signaling, whereas sublines that responded to treatment showed adaptive expression of genes related to proliferation and canonical Wnt signaling. Our results suggest that clonal phenotypes emerge as the result of specific adaptivity patterns of gene expression. A record of this paper's transparent peer review process is included in the supplemental information.