The paper presents the results of studying the development of calcite neoformations on the surfaces of modern buildings within the city of Tyumen. The objects of the study were carbonate crusts and stalactite-like bodies formed on the surfaces of five representative buildings in the city center. Research methods included visual diagnostics, optical microscopy, scanning electron microscopy with energy dispersive X-ray spectroscopy, confocal laser scanning microscopy and semi-quantitative determination of the mineral composition by X-ray diffraction analysis. The results of the study show that calcite is the main component of all carbonate crusts, while other minerals were found in small quantities. The microscopic studies revealed the differences in morphology of crusts developing on horizontal and vertical surfaces. The mycelium of fungi (presumably of the Penicillium group), represented by filamentous and often hollow hyphae covered with calcite, as well as relics of bacterial colonies were found in all studied samples. It was noted that the mycelium forms the structural frame of carbonate crusts and stalactites. Studies have shown that the prokaryotic–eukaryotic communities are responsible for the high rate of the urban speleothem growth and play the main role in calcite precipitation at the initial stages of their development.
This study shows that the use of a submersible digital holographic camera as part of a multifunctional hardware and software complex allows carrying out in situ measurements of plankton, automating the process of obtaining data on plankton, as well as classifying plankton species up to an order within the specified taxonomic groups. Such automation ensures monitoring expeditionary or stationary research of species diversity and spatial and temporal organization of zooplankton in conjunction with the hydrophysical parameters of the medium. This paper presents the full-scale results of vertical profiles and daily measurements of plankton made with the use of the submersible digital holographic camera as well as the classification of plankton in laboratory and field conditions in the automatic mode. It is shown that, within the accomplished version, the classification algorithm using the morphological parameter makes it possible to solve the problem quickly (the time required to obtain the result is less than 1 s and depends on the number of plankton particles and the frame size of a restored image); however, the classification accuracy by orders varies within 50-60%.
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