We have prepared a composite thin coating by incorporation of CuFe₂O₄/Cu₂O/CuO nanoparticles in polymethyl methacrylate (PMMA) matrix by using the solution casting method. The electrical explosion of two twisted wires (EETW) was used to obtain multicomponent CuFe₂O₄/Cu₂O/CuO nanoparticles with an average particle size of 20–70 nm. The microscopic studies showed that the nanoparticles in the composite coatings are evenly distributed. However, nanoparticles are strongly agglomerated as the powder concentration in the coating increases to 5 wt.% and 10 wt.%, as the size of particle agglomerates increases to 50 and 100 μm, respectively. Therefore, nanoparticles were pre-treated with ultrasound when introduced into the PMMA matrix. The thermal stability of the composite coating does not change with the introduction of CuFe₂O₄/Cu₂O/CuO nanoparticles in the amount of 5 wt.%. The inclusion of nanoparticles in the PMMA matrix significantly enhances its antibacterial activity. The addition of 5 wt.% nanoparticles inhibited the growth of E. coli by 100% and the growth of MRSA by 99.94% compared to pure PMMA already after 3 h of exposure of bacteria on the surface of the composites. This research provides an easy-to-manufacture and cost-efficient method for producing a CuFe₂O₄/Cu₂O/CuO/PMMA composite coating with a broad application as an antibacterial material.

Cyclonic activity in the midlatitudes is a form of general atmospheric circulation, and the most intense cyclones are the cause of hydrometeorological anomalies that lead to economic damage, casualties and human losses. This paper examines the features of variability of intense cyclonic activity in the Black Sea region and the examples of their regional manifestations in the storm types. Based on 6-hourly NCEP/NCAR reanalysis data on 1000 hPa geopotential height fields with 2° × 2° spatial resolution and using the methodology by M.Yu. Bardin, objective data were obtained for the identification and estimation of the frequency of deep cyclones (reaching 0.75 and 0.95 quantiles by intensity and depth—intense and extreme cyclones, respectively) for the Black Sea region during the period 1951–2017. Additionally, a specific methodology of more precise cyclone identification based on spherical spline interpolation was successfully applied, and then the two methodologies were compared. The key point of the study is the following: In the background of negative significant linear trends and interdecadal variability (period of about 35 years), typical scales of their interannual variability on the periods of about 2.5–3.5 and 6–8 years were identified. These periods coincide with the time scales of the North Atlantic Oscillation and El Nino–Southern Oscillation, providing an outlook for further study of the patterns of their connection. Besides, seasonal forecasts of frequency of intense cyclones in the Black Sea region were successfully modeled using an artificial neural network technique. Finally, the case studies of regional manifestations of deep cyclones in the types of storms in the northern Black Sea coast revealed substantial differences in the location of deep centers of cyclones and storm tracks associated with the large-scale pressure fields.

Equations for the mass conservation law and the molecular parameters observed in spectroscopic experiments have been derived for non-covalent, non-cooperative, one-dimensional self-assembly in systems containing two types of interacting molecules (hetero-association), taking into account “reflected” complexes and “edge effects.”