Introduction: It is an undeniable fact that antidepressants can cause side effects. Antidepressants generally have a similar effect but they differ in their application safety, as well as their side effects. Aim: To determine differences in the frequency and intensity of antidepressant induced side effects in patients treated in primary care. Methods: The research was designed as a prospective, cross-sectional study, conducted on a voluntary and anonymous basis, and it included depression patients treated with antidepressant medications during 2013-2015 in Zenica-Doboj Canton using the Hamilton Depression Rating Scale and Toronto Side Effects Scale. Results: The total sample included 508 subjects. As a significant problem, abdominal pain was felt by 14% of subjects, indigestion by 19% of subjects, nausea by 15% of subjects, diarrhea by 9% of subjects, and constipation by 11% of subjects. 29% of subjects suffered from sweating, 20% suffered from a sudden heat stroke, 10% suffered from swelling, and 23% of them reported suffering from dry mouth as a significant problem. The prevalence of side effects in relation to how do they affect life and daily activities of subjects is statistically significant (P <0.000). Statistically significant side effects of SSRI antidepressants correlate with the duration of our subject’s treatment: perception of increased sleep (0.039) as well as decreased sleep (P = 0.009), sweating (P <0.001), sudden heat stroke (P <0.001), being without orgasm (P = 0.004), decreased libido (P <0.001), weight loss (P = 0.045). Conclusion: It is necessary to educate the patients about the nature and features of the depressive disorder, and to notify the patients of the expected course of recovery, as well as the need to adhere to the recommended therapy and the possible side effects of the medication.

To meet the demand for new functional foods in line with the trend of sustainable development, a novel probiotic yogurt fortified with 1%, 3%, and 5% apple pomace flour (APF) added immediately after inoculation with Lactobacillus acidophilus, Streptococcus thermophilus, and Bifidobacterium bifidum was developed. Upon fermentation in the presence of APF, a number of probiotic strains remained within the required range, while the syneresis of enriched yogurts was reduced up to 1.8 times in comparison to the control. Supernatants (i.e., extracted whey) obtained from yogurts with 1%, 3%, and 5% APF respectively had 1.4-, 1.8-, and 2.3-fold higher total phenolic content (TPC) than the control, 3.3-, 4.7-, and 8.0-fold higher radical scavenging (DPPH), and 1.3-, 1.6-, and 1.7-fold higher reducing activity (FRAP). Also, probiotic yogurt supernatants (3% and 5%) inhibited colon cancer cells’ viability (HCT 116, 12% and 17%; SW-620, 13% and 19%, respectively). The highest firmness, cohesiveness, and viscosity index values, and the highest scores for color and taste, were obtained for yogurt with 3% APF, indicating that this is the optimal APF amount for the production of novel yogurt with functional properties.

Abstract Acute kidney damage associated with pregnancy occurs in 1/20.000 pregnancies. In developing countries, the main cause of the development of acute kidney damage is septic abortion, and preeclampsia in the developed countries of the world. Preeclampsia is defined as newly developed hypertension, proteinuria and swelling in pregnant women after the 20th week of gestation. It occurs due to disorders in the development of placenta and systemic disorders of the function of the endothelium of the mother. It is treated with methyldopa, magnesium sulfate and timely delivery. Urgent delivery is indicated if the age of gestation is ≥ 34 weeks. HELLP syndrome is a difficult form of preeclampsia. Its main characteristics are decreased platelet count, microangiopathic hemolysis anemia, increased concentration of aminotransferase in the serum and acute kidney damage. Severe HELLP syndrome is treated with emergency delivery, antihypertensives, magnesium sulfate, and in some cases plasmapheresis and hemodialysis. Acute fatty liver in pregnancy occurs because of decreased activity of the LCHAD enzyme of the fetus. Due to the reduced beta oxidation of fatty acids in the hepatocytes of the fetus, long chain fatty acids that cause damage to the mother’s hepatocytes are released. Swansea criteria are used for diagnosis, and the difficult form of the disease is treated with plasmapheresis and extracorporeal liver support. Atypical HUS is due to a reduced protein activity that regulates the activity of the alternative pathway of the complement system. Its main features are thrombocytopenia, microangiopathic hemolytic anemia and acute kidney damage. It is treated with plasmapheresis, and in case of resistance with eculizumab. Thrombotic thrombocytopenic purpura is due to decreased activity of the ADAMTS13 enzyme. It is characterized by thrombocytopenia, microangiopathic hemolytic anemia, high temperature, nervous system disorders and acute kidney damage. It is treated with plasmapheresis, and severe form of disease with corticosteroids and azathioprine. Early detection and timely treatment of acute kidney damage provides a good outcome for the mother and fetus.

Introduction: Infection with human papillomavirus is the main cause of cervical carcinoma. In Bosnia and Herzegovina (BIH) 556 cases of cervical carcinoma are diagnosed annually, and 141 women die from it. Aim: To determine the most common HPV type found in ASCUS and LSIL and progression, regression and persistence of lesions. Methods: In a retrospective study, 11 051 PAP tests, performed in several private gynecological practices located in Tuzla Canton from January 2016 to December 2019, were analyzed. In processing of data , X2 – statistical method was used. Results: 11051 PAP test were inspected. Normal findings were found in 90.48% (N-10002) and pathological findings in 9.49% (N- 049). ASCUS was present in 4.9% (N-544), LSIL in 3.04% (N-337), HSIL in 0.74% (N-84), ASC-H in 0.27% (N-30) and AGC in 0.49% (N-55) of cases. The most common is HPV 16, found in 50.5% (N-44) of ASCUS and LSIL. Monoinfection with HPV 16 was found in 40.9% (N-18) ASCUS (N-3) and LSIL (N-15), and a combination of HPV 16 with other types like HPV 18, 31, 33, 39 in 59% (N-26). Progression of ASCUS lesion in HSIL 1.6% (N-2), and LSIL 9.6% (N-12). Progression of LSIL to HSIL was found in 9.0% (N-10). HSIL progresses significantly more frequent from LSIL (p<0.05) than from ASCUS changes. Lesions that progress into higher grade HSIL are HPV 16 positive. Progression into HSIL is not found in patients with low-risk HPV 6 and 11 infection. Conclusion: Women infected with HPV 16 have more a frequent progression of a lesion into higher grade HSIL. They should be intensively monitored because of the increased risk for development of cervical carcinoma.

Abstract Microstructure of austenitic stainless steel is primarily monophasic, i.e. austenitic. However, precipitation of the δ-ferrite in the austenite matrix is possible depending on the chemical composition of steel. δ-Ferrite is stable on room temperature but it transforms into σ-phase, carbides and austenite during heat treatment. In this work, the results of analysis of influence of temperature and time on decomposition of δ-ferrite are presented. Magnetic induction method, microstructure and hardness analyses were used for testing the degree of decomposition of the δ-ferrite. Analysis of results showed that increase in temperature and time increases the degree of decomposition of δ-ferrite.

This paper investigates the relationship of information communication technology (ICT) and virtual reality (VR), and tourism, or specifically its interrelations and links to tourism sustainability. As a consumer technology, VR is still a relatively new concept, although it has been researched and used in the tourism industry for marketing purposes. The aim is to understand the different aspects of VR and ICTs and potentially link them to sustainability and perspectives on mass tourism, as well as to the potential future developments related to the ability of ICT and tourism to meet the tourists’ needs to a greater extent in the future. By use of the systematic mapping methodology, the insights into these concepts and their relations to each other are provided. The study reveals the evolution and links between the investigated concepts, the existing challenges and solutions, and the remaining gaps. The present findings indicate that VR as a trend in the tourism industry still needs significant work and improvement until it is ready to fully immerse itself into the tourism sector and especially involve itself into the issues concerning tourism and the potential of sustainability concept within the industry. Many of the concerns and conflicts still exist, but the potential of its right implementation is enormous.

Neural networks are important method of machine learning that can be used to predict air quality with high accuracy. Using NARX-SP neural network type, several neural network models are developed to predict concentration of air pollutants in Sarajevo for two prediction cases, for 24th and 48th hour ahead, with different combinations of inputs and outputs. The data used in this paper contain hourly values of meteorological parameters (air humidity, pressure and temperature, wind speed and direction) and concentrations of SO2, PM10, NO2, O3 and CO from 2016 to 2018. Optimal models are selected for both prediction cases. It is concluded that the optimal models have very good performances and can be used to predict concentration of pollutants in Sarajevo with great accuracy and contribute to improve quality of life. By adequate application of optimal models, concentration of air pollutants can be predicted for each hour over the next 48 hours.

Quantum computing has the power to break current cryptographic systems, disrupting online banking, shopping, data storage and communications. Quantum computing also has the power to support stronger more resistant technologies. In this paper, we describe a digital cash scheme created by Dmitry Gavinsky, which utilises the capability of quantum computing. We contribute by setting out the methods for implementing this scheme. For both the creation and verification of quantum coins we convert the algebraic steps into computing steps. As part of this, we describe the methods used to convert information stored on classical bits to information stored on quantum bits.

Noninvasive contactless methods for electric power line monitoring based on magnetic field measurement have become an interesting topic for researchers and the electric power industry since introduction of the Smart Grid concept. By measuring and analyzing magnetic field originating from currents in power line conductors, it is possible to detect faults in the network. In medium voltage distribution networks, where a variety of different pole geometries are present, different criteria for fault detection have to be employed for each geometry, which complicates detection and influences accuracy. This paper proposes a novel approach for fault detection in medium voltage distribution networks which is based on processing of signals measured by low cost contactless magnetic field sensors. In order to create a generalized method for fault detection, a sequence of mathematical transformations of the measured magnetic field components is applied. A novel geometric transformation which eliminates influence of pole geometry is introduced, providing signals from which steady-state symmetrical components of the rotating magnetic field are computed. Those components are used as general fault detection criteria. The proposed approach is confirmed to be applicable for different fault types by a set of experiments on three-phase overhead power line model scaled to laboratory conditions.

Recent work has shown how predictive modeling can endow agents with rich knowledge of their surroundings, improving their ability to act in complex environments. We propose question-answering as a general paradigm to decode and understand the representations that such agents develop, applying our method to two recent approaches to predictive modeling -action-conditional CPC (Guo et al., 2018) and SimCore (Gregor et al., 2019). After training agents with these predictive objectives in a visually-rich, 3D environment with an assortment of objects, colors, shapes, and spatial configurations, we probe their internal state representations with synthetic (English) questions, without backpropagating gradients from the question-answering decoder into the agent. The performance of different agents when probed this way reveals that they learn to encode factual, and seemingly compositional, information about objects, properties and spatial relations from their physical environment. Our approach is intuitive, i.e. humans can easily interpret responses of the model as opposed to inspecting continuous vectors, and model-agnostic, i.e. applicable to any modeling approach. By revealing the implicit knowledge of objects, quantities, properties and relations acquired by agents as they learn, question-conditional agent probing can stimulate the design and development of stronger predictive learning objectives.