Progress towards effective treatment of epileptic seizures has seen much improvement in the past decade. In particular, the emergence of phenomenological models of epileptic seizures specifically designed to capture the electrical seizure dynamics in the Epileptor model is inspiring new approaches to predicting and controlling seizures. These new models present in various forms and contain important but unmeasurable variables that control the occurrence of seizures. These models have been used mostly as nodes in large networks to study the complex brain behaviour of seizures. In order to use this model for the purposes of seizure forecasting or to control seizures through deep brain stimulation, the states of the model will need to be estimated. Although devices such as EEG electrodes can be related to some of the states of the model, most remain unmeasured and would require an observer (as defined in control theory) for their estimation. Additionally, we would like to consider the case for large nodes of systems where the number of electrodes is far smaller than the number of nodes being estimated. In this paper, we provide methods towards obtaining the full states of these phenomenological models using nonlinear observers. In particular, we explore the effectiveness of the Extended Kalman Filter for small networks of nodes of a smoothed sixth order Epileptor model. We show that observer design is possible for this family of systems and identify the difficulties in doing so.Clinical relevance—The methods presented here can be applied with an individual epileptic patient’s EEG to reveal previously hidden biomarkers of epilepsy for seizure forecasting.

The paper presents a PyDigitizer application designed to extract numerical coordinates of existing curves from image format. The application is created in the Python programming language and offers the possibility of manual extraction of curve coordinates, intersection of curves with user-specified abscissa or ordinate, generation of polynomial regression equations of curves. All generated information (coordinates, intersection points, regression curves) can be exported to Microsoft Excel. Also, point coordinates of Excel curves can be loaded into PyDigitizer to obtain polynomial regression curves or intersections.

During the operation of each machine, the deformation and stress state of its supporting structure is directly related to the load. The load intensity ranges from the minimum to the maximum value and is a function of nominal force, torque, and kinematic-dynamic values of moving and executive assemblies during the machine operation process. The intensity of deformations is also a function of the shape and type of the supporting structure. However, although the supporting structure is reliable, which refers to its integrity, the production of a quality workpiece (product) does not have to be reliable. Therefore, it is important that the deformation states of the supporting structure be in the appropriate tolerance field, regardless of the intensity of the load. If the intensity of deformations is outside a certain field, it will directly affect the quality of the workpiece that is made on the subject machine. It is known that load-bearing structures can be of open and closed types, load-bearing structures of closed type are used for higher loads and larger workpiece dimensions. By installing sensors on the elements of the supporting structure with accompanying measuring chains in real-time, the deformation state of certain elements or places on the supporting structure can be monitored, based on which the reliable quality of the workpiece can be influenced.

Introduction: The paper aims to research how the Covid-19 infection affects BPH patients, whether their PSA, prostate volume, residual urine, and quality of life have changed. Additionally, to examine whether any of these variables are a predictive factor for acute urinary retention (AUR). Methodology: The study comprised 80 patients with clinical manifestations of LUTS, an aggravation of previously diagnosed BPH, and who recovered from COVID-19. IPSS, QoL, PSA, prostate volume, and postmicturition residual urine were studied before and after COVID-19. Results: The IPSS score, PSA, prostate volume, and residual urine were signicantly higher after recovering from COVID-19. Additionally, greater IPSS-QoL scores were discovered. Nine patients (mostly older than 60) suffered acute retention during or after the COVID-19 infection. Residual urine was found to be a signicant predictor of AUR. Conclusion: COVID-19 infection is caused by aggravating LUTS symptoms associated with BPH. Consequently, the increase postmicturition residual urine can be considered a predictive factor for the occurrence of AUR

UAV technologies provide a time- and cost-efficient framework for a variety of environmental monitoring domains. It also increases data resolution and provides new insights into observed objects and phenomena, especially within the difficult-to-access and complex for monitoring aquatic habitats. The objective of this study was to develop UAV-based acquisition and GIS-based image processing guidelines for aquatic macrophyte detection and monitoring in large temperate rivers. According to the European standard CEN EN -14184:2014, the assessment of aquatic macrophytes should be performed using the transect approach. Large rivers, such as the Danube, represent an exception and should be evaluated using 1km transects. Therefore, seven transects of the Middle Danube in Serbia were simultaneously surveyed using traditional field methods and novel UAV technology. UAV images were acquired using RGB and multispectral cameras carried by a fixed-wing drone. The images were processed and orthomosaics were classified using Object Based Image Analysis (OBIA), to create digital GIS maps of the river transects. During the traditional monitoring approach, the relative abundance of 22 macrophyte species was recorded along the transects. Using the UAV technology and OBIA approach eight macrophyte classes were distinguished based on dominant macrophyte taxa or plant life form traits. Aquatic macrophytes were 'almost perfectly' distinguished from the orthomosaics, achieving a high classification accuracy of 96 % / 88 % / 0.84 for RGB and 94 % / 97 % / 0.95 Producers /Users accuracy/Kappa index for the multispectral approach. Individual macrophyte classes accuracy varied between 0.5 and 1 Kappa and were generally higher for the multispectral imagery approach. Although the resolution of the taxonomic data is lower, UAV monitoring provided the necessary spatial context of macrophytes distribution and absolute area occupied by macrophytes. It also provided information on the diversity and distribution of habitats along the river. Therefore, the UAV-assisted monitoring approach described in this study can be effectively integrated into macrophyte monitoring during large river expeditions such as the JDS.

This paper analyses whether there have been any changes in the behavior and patterns of tourist travel after the outbreak of the COVID-19 pandemic. The convenience sample included 265 respondents. The results of the study show that the most important factors in choosing to travel during the COVID-19 pandemic are: cleanliness, safety, comfort, costs, and social distance. The results of the study show a statistically significant difference in the factors that influence choosing to travel during COVID-19 with regard to employment, i.e., occupation, whereby the most factors when deciding on travel during COVID-19 are considered by pensioners and the least by students. When choosing a destination, as well as the image of the destination from the perspective of tourists, the study showed that owning a car is a statistically significant factor. The study also shows that there is a positive relationship that is statistically significant between the factors that influence choosing to travel during COVID-19 and the factors when choosing a destination from the perspective of tourists and the image of the destination, so those respondents who take into account more factors when choosing to travel during COVID-19, also take into account several factors when choosing a destination from the perspective of tourists and the image of the destination.  

The mobility of factors of production from the very beginnings of the theory of the optimal currency area (OCA) stands out as one of the primary mechanisms for achieving a balance of payments, i.e. sustainability of the monetary union (Mundell criterion). However, there is a significant qualitative difference between the monetary union of countries with similar income levels and the one with different development stages Namely, in the first case, labor mobility, as a rule, has short-term economic effects, while it has a longer-term (more negative) impact – especially on the long-run aggregate supply (LRAS). Many Eastern European countries, which expressed a desire to become part of European integration and the monetary union after the communist ruin, experienced this. In a previous paper, the authors set the thesis about “Impossible Trinity of Developing Countries”. In this paper, the aspiration is to confirm the validity of this theory by analyzing Greece within the period 1999-2020, specifically observing the impact of three variables (fiscal policy, social development level, and level of economic freedom) on the emigration of the population under conditions of monetary union and labor force mobility. The results obtained in this research indicate that the fiscal policy in the observed period was the most significant factor in explaining migration trends. The implications for developing countries that are currently entering (such as Croatia) or intend to enter the monetary union with more developed countries in the future are particularly significant.

Leachate water from sanitary landfills represents one of the most complex global environmental problems. This paper examines the possibility of using aluminosilicate material, pyrophyllite, from the Parsovići deposit, as an adsorbent. It was researched the influence of two granulations of pyrophyllite (0-53 μm and 0-100 μm) on the degree of adsorption of heavy metals (Fe, Ni, Mn) from leachate water from the municipal landfill "Desetine", Tuzla. The adsorption experiment was performed using the Batch method, depending on the contact time between the adsorbent and the adsorbate, the mixing speed, and the mass of the adsorbent, pyrophyllite, through two treatments. The results indicate a higher efficiency of the finer fraction of pyrophyllite, and in the competition of the three examined metals, iron is completely removed in the first treatment with both granulations and then nickel with finer granulation and manganese with coarser. After the first treatment, the unpleasant smell was removed, which is certainly a consequence of the removal of ammonia compounds as the most abundant compounds in leachate water. In these pioneering researches, pyrophyllite proved to be effective, and at the same time, it is a cheap, easily available, and environmentally friendly material for leachate water purification.