The prerequisites for this research included the rapid development and constant modernization of massive open online courses (MOOCs) and their dissemination in higher education, in particular, in the preparation of medical practitioners of various specialties. The present investigation was conducted among two groups of students of I.M. Sechenov First Moscow State Medical University (experimental and control, 48 and 46 people respectively). For the control group, a standard MOOC with a training design characteristic of the vast majority of similar courses was proposed. The experimental group took the MOOC with additional learning strategies. Results showed the introduction of collaborative learning and decision-making assignments in e-education could overcome the challenges of MOOCs or at least significantly reduce their negative impact on the learning process. The share of experimental group participants who completed the training course and passed all the tests was 78.26%, while in the control group, their part was only 39.58%. The study findings can be widely applied when designing new MOOC curricula or improving the existing courses.

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Organizing students' independent work at universities for professional competencies formation and personality development.

Considering features of hydrological conditions for hydro-chemical system, this paper analyses the performance of the hydro-ecological status of the Kuban river basin.. The results of the study on water chemical composition depending on the distance from the source are presented. By comparing the results with the reference values of water quality, increased aluminium, zinc, and copper content was established. Respective dendrograms of hydro-ecological studies obtained according to performed analysis for the Kuban River and its tributaries are presented. The relevance of the findings received is p<0.0005 and the correlation coefficient corresponds to 0.935...1. The results of multivariate cluster analysis showed that the Kuban basin has an increased content of particular heavy metals such as aluminium, copper, and zinc.

This paper draws on the methods of analysis and synthesis to study the regulatory framework governing the modern operating mechanism of the EU single market. Statistical analysis made it possible to reflect the market dynamics with reference to the pre-and post-COVID crisis periods. Consolidation was applied to merge data on the trade of goods and servicesthe key elements of the EU Member States' trade indicators. Finally, the method of comparative analysis was employed to compare the single market environment of the EU with markets of other countries. The functioning of the single market depends on shared responsibility between the EU's centralized management and the many policies of its Member States. There are barriers within the single market system that limit the free movement of goods, services, people and capital and lead to an imbalance. These are sanitary and phytosanitary standards, tariff measures, and technical and quantitative barriers.

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This paper presents the results of modeling the distribution process of industrial emission components at specified distances from the emission source along the normal. The model uses a system of differential diffusion equations to compute the concentration profiles of aerosols, industrial gases, and fine particles in the atmosphere. In order to investigate the regularity of the emitter propagation into the atmosphere, a theory of impurity dispersion was developed. The model is constrained by the effect of particle interactions. The partial derivative equations are presented to calculate the concentrations of aerosols and fine particles under the turbulent airflow in the atmosphere, dispersion of inert impurities, and distribution of chemically active compounds. The adequacy of the mathematical model for a series of theoretical calculations was checked by contrasting the data of the atmospheric air monitoring for the cities of Almaty, Ust-Kamenogorsk, Pavlodar, Atyrau, Krasnodar, Chelyabinsk, Beijing, and Shanghai. Air monitoring data included PM10, SO2, and NO2 levels. The mathematical model solutions for the relative values of the emitter concentration in the direction along the normal of the pollution source at the surface were obtained. Graphical interpretation of the calculation results over the 0…200 m distance for time intervals ranging from 3 to 600 min was provided. According to the multiple factor cluster analysis, the critical values of SO2 concentrations in Atyrau exceeded MPC in 26.2% of cases. The level of NO2 for Shanghai was 15.6%, and those for PM10 concentrations in Almaty and Atyrau amounted to 16.4%. A comparison of theoretical values and results obtained from official sources showed arithmetic mean of 49.4 mg/m3 and maximum value of 823.0 mg/m3. Standard deviation comprised 48.9 mg/m3. Results were considered statistically significant at p≤0.005. The mathematical model developed in this study can be used to predict the status of atmospheric air.