BACKGROUND Regional wall motion abnormality (RWMA) is considered a sensitive and specific marker of ischemia during stress echocardiography (SE). However, ischemia is a multifaceted entity associated with either coronary artery disease (CAD) or angina with normal coronary arteries (ANOCA), a distinction difficult to make using a single sign. We aimed to evaluate the diagnostic potential of the ABCDE-SE protocol for CAD detection. METHODS From the 2016-2022 SE-2030 study data bank, we selected 3229 patients (age= 66±12 years, 2089, 65% males), with known CAD (n=1792) or ANOCA (n= 1437). All patients were studied with both ABCDE-SE protocol and with coronary angiography, within 3 months. Step A assesses RWMA; step B, B-lines/diastolic function; step C, left ventricular contractile reserve; step D, coronary flow velocity reserve (CFVR) in the left anterior descending artery; step E, heart rate reserve. RESULTS SE response ranged from score 0 (all steps normal) to score 5 (all steps abnormal) . In CAD, the rate of abnormal results was 347 for A (19.4%), 547 (30.5%) for B, 720 (40.2%) for C, 615 (34.3%) for D, and 633 (35.3%) for E step. In ANOCA, the rate of abnormal results was 81 (5.6%) for A, 429 (29.9%) for B, 432 (30.1%) for C, 354 (24.6%) for D, and 445 (31.0%) for E step. The dominant "solitary phenotype" was step B in 109 (9.1%) patients. CONCLUSION Stress-induced ischemia presents with a wide range of diagnostic phenotypes, highlighting its complex nature. Utilizing a comprehensive approach such as the advanced ABCDE score, which combines multiple markers, proves to be more valuable than relying on a single marker in isolation.

SUMMARY The aim of the study was to determine changes in body mass index (BMI) and in the prevalence of overweight and obesity in Serbian adult population. Data for this study were obtained from three National Health Interview Surveys, carried out as cross-sectional, nationally representative surveys in 2000, 2006 and 2013. The values of p for trends of sociodemographic and health related behavioral characteristics, of BMI distribution, and of overweight and obesity prevalence were determined by univariate and multivariate linear and logistic regression analyses, with year of survey as a continuous variable. The mean values of BMI and standard deviations in surveys were 26.09±3.92, 26.28±4.02 and 26.87±4.33 in men, and 25.91±5.25, 25.77±5.22 and 26.35±5.58 in women, respectively (trend p<0.001 both). The prevalence of obesity was 14.3%, 16.5% and 21.4% in men, and 20.0%, 19.7% and 23.3% in women, respectively (trend p<0.001 both). The prevalence of overweight did not change significantly during the observed period. In conclusion, the prevalence of obesity showed an increasing trend in both men and women, demanding targeted public health interventions.

This paper investigates the application of Adaptive Fuzzy PID Control in the context of car control using a bilateral teleoperator. A bilateral teleoperator allows the operator to operate a remote car using his own controls and at the same time receive feedback on the car’s condition. The goal of the research is the analysis and comparison of different control methods, including PID controller, Adaptive Fuzzy PID controller, and the use of energy and wave variables of the bilateral teleoperator. The paper presents a car control model by means of a bilateral teleoperator, which was implemented in a simulation environment. Then performance comparisons of different control methods were made. The PID controller was used as the basic method, while the Adaptive Fuzzy PID controller was additionally included to achieve system adaptivity. Also, the use of energy and wave variables of the bilateral teleoperator was additionally investigated. The results of the comparison show that the use of bilateral teleoperator wave variables gave the best response of the control system. The analysis of signal waveforms and frequencies enabled more precise monitoring of the car’s condition and the detection of possible problems or instability in the system. This knowledge can be of great importance for improving the performance of car control by means of a bilateral teleoperator.

Drug-induced nephrotoxicity is still a significant obstacle in pharmacotherapy of various diseases and it accounts for around 25 % of serious side-effects reported after drug administration. Furthermore, some groups of drugs such as nonsteroidal anti-inflammatory drugs, antibiotics, antiviral drugs, antifungal drugs, immunosuppressants, and chemotherapeutic drugs have the "preference" for damaging the kidney and are often referred to as the kidney's "silent killer". Clinically, the onset of acute kidney injury associated with drug administration is registered in approximately 20 % of patients and many of them develop chronic kidney disease vulnerability. However, current knowledge about the mechanisms underlying this dangerous phenomenon is still insufficient with many unknowns. Hence, the valuable use of these drugs in clinical practice is significantly limited. The main aim of this study is to draw attention to commonly prescribed nephrotoxic drugs by clinicians or drugs bought over the counter. In addition, the complex relationship between immunological, vascular and inflammatory events that promote kidney damage is discussed. The practical use of this knowledge could be implemented in the engineering of novel biomarkers for early detection of drug-associated kidney damage such as Kidney Injury Molecule (KIM-1), lipocalin associated with neutrophil gelatinase (NGAL) and various microRNAs. In addition, the utilization of artificial intelligence (AI) for the development of computer algorithms that could detect kidney damage at an early stage should be further explored. Therefore, this comprehensive review provides a new outlook on drug nephrotoxicity that opens the door for further clinical research of novel potential drugs or natural products for the prevention of drug-induced nephrotoxicity and accessible education.

Abstract Tourist boards, through their social activities, can make a tourist destination, tourist attractions and tourist products attractive, unique, and special. Through relevant scientific knowledge, using the tools and techniques of destination management as well as modern forms of communication, tourist boards can make the entire area of a tourist destination very interesting and desirable for tourist visits throughout the year by promoting the specificity, authenticity and originality of the tourist offer and tourist products. Keywords: tourist board; tourism promotion through sports and sports recreation competitions; tourism promotion through social networks, tourism

Museum development is a side effect of tourism development since museums are significant components of cultural and tourist infrastructure, and tourism encourages infrastructure development in general. In Bosnia and Herzegovina, where tourism is a critical sector of the economy with a decades-long flow, the pattern of comparative development of tourism and museums has been recognized. The study provides a comparative review of the country's tourism and museum development, showcasing the multiple benefits of tourism and museums. Museums are one of the most important socio-cultural benefits of tourism because they preserve and present heritage, improve science, education, and cultural profiling, encourage employment and visitation, provide a better stay, generate income, and contribute to environmental urbanization and higher living standards. The identification of museums and museum resources revealed that, during the past three decades, approximately thirty museums of a predominantly thematic character have been established, particularly in the country's most visited destination (Sarajevo). Furthermore, an open-air museum (ethno-village) trend has begun. Museum visitation is increasing in tandem with tourist trips to the country, despite a lack of adequate monitoring (incomplete figures that are inconsistent with the situation in the field). Despite the fact that the global crisis disrupted tourism and museum development (COVID-19), both areas are key drivers of economic revitalization, as evidenced by new ideas and projects in this field. However, in addition to the benefits of increased museum activity, the study highlighted certain issues (e.g., lower engagement of professional staff and women etc.), which will encourage future research to provide more sustainable strategies for museum development.

Abstract Voltage unbalance is common issue encountered in low voltage distribution networks, caused by uneven allocation of single-phase customers among phases. This paper analyses part of real low voltage distribution network in Bosnia and Herzegovina. The impact of single-phase customers and single-phase connected micro photovoltaic power plants (MPPP-s) were analysed. To reduce unbalance and improve voltage profiles, Phase Balance Optimization toolbox in DIgSILENT PowerFactory software was performed in six scenarios with different distribution of customers and different percentage of penetration of MPPS-s. The aim was to find method with least number of changes in customer and photovoltaic phase connection that fits within defined limits of voltage variations and voltage unbalance of European standard for power quality (EN 50160). Conclusion is that MPPP-s cause voltage increases in the network, as well as an increase in voltage unbalance, but these effects can be mitigated by proper distribution of customer loads and MPPS-s among phases.

This paper is about the parameter identification of an energy based hysteresis model from measurements by employing automatic differentiation and neural networks. We first introduce the energy based hysteresis model and the parameters which are to be identified. Then we show how the model can benefit from automatic differentiation. After that we incorporate a parametrization of the energy based hysteresis model via distribution functions and identify the parameters of the distribution function. Then, the hysteresis model is sampled and the generated datasets are used to train neural networks to predict the hysteresis parameters. The described methods are tested and verified on synthetic as well as measurement data.

Abstract In the dynamic field of power systems, integrating distributed generation (DG) sources like solar photovoltaic (PV) plants is crucial for enhancing reliability and fostering sustainability. However, this integration poses voltage profile management challenges in electrical grids. This study investigates voltage profile optimization in Bosnia and Herzegovina’s Gračanica network, focusing on a medium voltage feeder with 68 buses. Using DIgSILENT PowerFactory software, six scenarios with different configurations of solar plants are analyzed for their impact on voltage profiles and power losses. Results show that while DG integration offers benefits, incorrect sizing or placement can increase power losses. Optimal DG benefits are linked to specific sizes and locations. This research emphasizes the need for balancing PV generation with load demands and provides insights for optimal PV plant size and output to minimize negative impacts. These findings aid energy planners and policymakers in implementing distributed solar PV in medium voltage networks.

Open access implies the idea of scientific information dissemination over the Internet that is free to the end user. The higher education and university libraries’ mission is to connect people and information, and the goals of open access help librarians respond to users' information queries more quickly. This paper presents the basic concepts of open access with an emphasis on creating an open access journal through ten steps. The open access portal at the University of Sarajevo is also presented within the paper, as well.

The aim of this study was to investigate the mechanical behavior of beech and fir finger joints under laboratory conditions. The samples were manufactured using a 9 mm finger joint with glued surfaces, in accordance with the EN 14 080 standard. Polyurethane adhesive of class D3, commonly used for the production of exterior wooden structures in Bosnia and Herzegovina, was applied to the samples. The specimens were subjected to destructive four-point bending tests according to the BAS EN 408 standard, and the achieved bending strength was statistically evaluated and compared to the results of unglued samples.

Timber structures have been a popular choice for construction due to their natural and aesthetic appeal. However, with the increasing focus on sustainability and eco-friendliness, alternative building materials are gaining popularity. One such material that has gained attention is coconut wood. Coconut wood is a by-product of the coconut industry and has several unique properties that make it an excellent choice for timber structures. This paper reviews the properties and applications of coconut wood in timber structures and discusses its advantages, limitations, and challenges. We discussed the physical and chemical properties and durability of coconut wood. The average density of coconut palm wood ranges from 0.41-1.11g/cm3, while its moisture content ranges from 50% to 400%. Coconut wood has low shrinkage and swelling rates, reducing the risk of cracking or warping. The holocellulose content is about 67% while the lignin content is approximately 25%. Chemical and natural products, are effective in protecting coconut wood against decay and insect attack. Understanding such characteristics of coconut wood is critical for its optimal utilization in various industries. By employing appropriate preservation techniques and utilizing this versatile and sustainable resource, coconut wood can continue to provide significant benefits for communities and industries around the world.

Preschool wheezing and childhood asthma create a heavy disease burden which is only exacerbated by the complexity of the conditions. Preschool wheezing exhibits both “curricular” and “aetiological” heterogeneity: that is, heterogeneity across patients both in the time‐course of its development and in its underpinning pathological mechanisms. Since these are not fully understood, but clinical presentations across patients may nonetheless be similar, current diagnostic labels are imprecise—not mapping cleanly onto underlying disease mechanisms—and prognoses uncertain. These uncertainties also make a identifying new targets for therapeutic intervention difficult. In the past few decades, carefully designed birth cohort studies have collected “big data” on a large scale, incorporating not only a wealth of longitudinal clinical data, but also detailed information from modalities as varied as imaging, multiomics, and blood biomarkers. The profusion of big data has seen the proliferation of what we term “modern data approaches” (MDAs)—grouping together machine learning, artificial intelligence, and data science—to make sense and make use of this data. In this review, we survey applications of MDAs (with an emphasis on machine learning) in childhood wheeze and asthma, highlighting the extent of their successes in providing tools for prognosis, unpicking the curricular heterogeneity of these conditions, clarifying the limitations of current diagnostic criteria, and indicating directions of research for uncovering the etiology of the diseases underlying these conditions. Specifically, we focus on the trajectories of childhood wheeze phenotypes. Further, we provide an explainer of the nature and potential use of MDAs and emphasize the scope of what we can hope to achieve with them.

The 2020 earthquakes that hit the Croatian capital city Zagreb and Petrinja revealed the (un)preparedness of the country once exposed to strong earthquake motion. Three years after, numerous buildings out of 25,000 that have been heavily damaged and destroyed still have not been reconstructed. The effect of the earthquake was felt as well in the bordering cities and towns in Bosnia and Herzegovina (BIH). Seismic assessment of the existing buildings in BIH is done by individual researchers and there is no defined methodology not policy for such activities. This paper aims to present the work that has been done in this field up to now and to give guidelines for the further work that needs to be conducted. The starting point was the calculation of the earthquake risk for the entire Bosnia and Herzegovina based on the rapid assessment taking into account the vulnerability of buildings, seismic hazard, and population exposure. A more detailed assessment was conducted for the three largest cities in BIH, specifically Sarajevo, Banja Luka, and Tuzla. Typical residential masonry structures were identified, and detailed calculations were conducted, leading to the need for their strengthening. To have a more detailed picture much work has to be conducted.