This study analyzed 16 bisphenols (BPs) in wastewater and sludge samples collected from different stages at a municipal wastewater treatment plant based on sequencing batch reactor technology. It also describes developing an analytical method for determining BPs in the solid phase of activated sludge based on solid-phase extraction and gas chromatography-mass spectrometry. Obtained concentrations are converted into mass flows, and the biodegradation of BPs and adsorption to primary and secondary sludge are determined. Ten of the sixteen BPs were present in the influent with concentrations up to 434 ng L−1 (BPS). Only five BPs with concentrations up to 79 ng L−1 (BPA) were determined in the plant effluent, accounting for 8 % of the total BPs determined in the influent. Eleven per cent of the total BPs were adsorbed on primary and secondary sludge. Overall, BPs biodegradation efficiency was 81%. The highest daily emissions via effluent release (1.48 g day−1) and sludge disposal (4.63 g day−1) were for BPA, while total emissions reached 2 g day−1 via effluent and 6 g day−1 via sludge disposal. The data show that the concentrations of BPs in sludge are not negligible, and their environmental emissions should be monitored and further studied.

In the present-day environment pertaining to digitalisation, increasing competition on the market and changes in industries, the CRM as a system is an essential tool for success. The issue of CRM system application in higher education institutions is insufficiently researched, especially in the parts that should indicate a clear connection between participants in higher education and CRM in higher education institutions, and factors that decision makers should pay attention to when making decisions about CRM implementation. Therefore, the aim of the paper is to research the functionality, application and advantages of CRM in the higher education sector, and to determine the features that will facilitate effective decision-making on the implementation of CRM. As a result of the research, a proposal for a conceptual model/framework of CRM was presented. The proposal is presented for the purpose of making appropriate decisions for higher education institutions when it comes to developing their own or purchasing a ready-made CRM solution. From the scientific aspect, the paper contributes to the existing literature by providing decision makers with an insight into the structure of the CRM system, its elements, connections and functionalities, as well as a description of the model with the information they need to pay attention to when making decisions.

In the present study, vortex-assisted matrix solid-phase dispersion (VA-MSPD) extraction was used to isolate the major bioactive compounds from H. arenarium. To reduce the negative environmental impact of the conventionally used organic solvents, four different choline chloride-based natural deep eutectic solvents (NADES) were investigated as possible eluents. The most influential VA-MSPD extraction parameters: stationary phase (adsorbent), adsorbent/sample ratio, vortex time, and volume of extraction solvent were systematically optimized. Ultrasound-assisted extraction with 80% MeOH was used as the standard method for the comparison of results. The stability of the obtained extracts was studied over a period of 0 to 60 days at three different temperatures (−18 °C, 4 °C, and 25 °C). All extracts were evaluated both spectrophotometrically (determination of total phenolic content (TPC) and antioxidant activity by ABTS and FRAP assay) and chromatographically (HPLC-UV). NADES based on choline chloride and lactic acid (ChCl-LA) was selected as the most effective extractant, with a determined TPC value of its extract of 38.34 ± 0.09 mg GA/g DW (27% higher than the methanolic VA-MSPD extract) and high antioxidant activity. The content of individual phenolic compounds (chlorogenic acid, dicaffeoylquinic acid isomers, naringenin isomers, and chalcones) in the ChCl-LA extract, determined by HPLC-UV, was comparable to that of the conventionally obtained one. Moreover, the stabilization effect of ChCl-LA was confirmed for the studied compounds: chlorogenic acid, naringenin-4′-O-glucoside, tomoroside A, naringenin-5-O-glucoside, isosalipurposide, and naringenin. The optimum VA-MSPD conditions for the extraction of H. arenarium polyphenols were: florisil/sample ratio of 0.5/1, a vortex time of 2 min, and an elution volume of ChCl-LA of 10 mL.

Background: MRI techniques of the lumbar spine have not provided data on the effect of gravity on the spine and on the relationship of anatomic structures during its action. Because conventional MRI examinations of the spine are usually performed in the supine position these are often exacerbated by standing upright and are not evident in the supine position the loading conditions differ from those known to cause symptoms in patients with lumbar instability. Axial loading imaging may improve diagnostics in the clinical management of LBP and lead to appropriate treatment decisions. Objective: The aim of this study is to determine the significance of alMRI in detecting the morphologic changes of the lumbar spine caused by axial loading and to compare it with conventional MRI images of the lumbar spine without loading. Methods: The study was conducted as a prospective, descriptive clinical trial. Imaging was performed with a MRI 1.5 T in the head-first supine position. Imaging was performed in two acts: without load and under load. Loading for alMRI was performed with the DynaWell L-Spine device. The onset of loading was 10 minutes before the start of alMRI. The loading continued throughout the imaging procedure. The height of the IV, AP and LL diameters of IV, IV disk surface area, DSCA and width of the IV foraminas before and under load was measured. Results: After evaluating the changes in the height and size of the lumbar disks, the size of the DSCA, and the narrowing of the intervertebral foramina significant differences were found between the images before and after axial loading. Conclusion: alMRI provides information on morphological changes of all segments of the lumbar spine. This data represents significant information that can lead to more accurate and effective treatment of LBP.

Abstract Simulation of unsteady flow of SF6 gas in a simplified high-voltage circuit breaker model describing the nozzle, contacts and their nearest surrounding is presented. SF6 is considered as viscous, compressible, real gas described by Redlich-Kwong model. Heat transfer is taken into account due to the gas compressibility. The heat source, triggered by the electric arc between the contacts, was out of the scope of the current research, thus it was not included in the simulations presented. Turbulence, caused by the gas viscosity, is described using realizable k-ε model. In the simulation model, one of the contact sides – electrodes, is considered as moving at prescribed velocity. The part of the space ‘swept’ by the moving electrode is considered as the gas with imposed artificially increased viscosity in order to imitate the rigid body behaviour. Thus, no moving parts of the computational mesh are used in the model. The conservation equations of mass, momentum and energy, given in integral form, are solved using a finite-volume method on unstructured computational grids.

Background: The COVID-19 pandemic has generated significant symptoms of stress, anxiety, and depression among health care workers, which can negatively affect the health and well-being of individuals. Although the WHO stressed the importance of nurturing mental health in the context of the COVID-19 pandemic, a more significant response focused on this area was still lacking in most countries. Objective: The aim of the study was to examine the differences in the levels of depression, anxiety, and stress in healthcare professionals in relation to exposure to contact with COVID-19 positive patients, as well as to examine the differences and correlation of sociodemographic characteristics of health workers in the experience of symptoms of depression, anxiety and stress. Methods: The research included 266 respondents, and it used a socio-demographic questionnaire and the DASS-21 scale. Mann-Whitney U tests, Kruskal-Wallis test and Spearman correlation coefficient were used in data processing. Results: The prevalence of high to extremely high symptoms of depression was reported in 45.49% of employees, anxiety 63.91% and stress 23.22%. Those who have been in continuous contact with COVID-19 positive patients, or 27.07%, report experiencing high or extremely high symptoms of depression, 36.60%, high to extremely high symptoms of anxiety, and 22.18% high to extremely high symptoms of stress. Discussion: The degree of self-care and family care, education level, and work experience were found to be a statistically significant factor in experiencing symptoms of depression, anxiety, and stress. Workers who were more in contact with COVID19 patients reported a higher degree of symptom on the DASS-21 scale. Those employees with more work experience had previously encountered similar situations of uncertainty and pressure, had better developed defense mechanisms, and showed less pronounced symptoms. A higher level of education often implies a higher degree of involvement in active treatment around each patient, which results in more responsibility and pressure in a given situation. Conclusion: High levels of stress, anxiety and depression in healthcare workers can lead to repercussions in their work with patients. Therefore, the mental health of health workers should be put in focus, as a very important part of the public health problem during the COVID19 pandemic.

Lightning parameters are needed in different engineering applications. For the prediction of the severity of transient voltages in power systems, an accurate knowledge of the parameters of lightning currents is essential. All relevant standards and technical brochures recommend that lightning characteristics should be classified according to geographical regions instead of assuming that these characteristics are globally uniform. Many engineers and scientists suggest that better methods for lightning current measurements and analyses need to be developed. A system for direct lightning current measurements installed on Mount Lovćen is described in this paper. Observed data were analyzed, and statistical data on parameters that are of interest for engineering applications were obtained, as well as correlations between various lightning parameters. Furthermore, a novel approach for classifying and analyzing lightning data from direct measurements based on empirical mode decomposition (EMD) is proposed. Matlab was used as a tool for signal processing and statistical analysis. The methodology implemented in this work opens possibilities for automated analysis of large data sets and expressing lightning parameters in probabilistic terms from the data measured on site.