With the advent of new sources and technologies for obtaining data on the location and mutual location of objects and systems in general, as well as their integration into real – time control methods and algorithms, conditions have been created for more modern and high-quality use of computer technologies in the management of complex distributed systems (SRS). The components of such SRS are themselves complex distributed systems and have (or can potentially have), among other things, a negative impact on each other, that is, they represent or form a threat to each other. One of the most urgent tasks of our time is to develop various, usually highly computerized, tools and methods for parrying threats based on monitoring and forecasting the development of processes (including physical ones) that form the basis of these threats. This article discusses the problem of parrying one of the types of threats – flood. The issues of using various types of information coming from various sources – sensors for monitoring and forecasting the water level and associated flooding of the corresponding territories are considered. The system of using real-time automatically measured SRS parameters and their further application for digital decision support for parrying threats is a complex highly computerized technical system belonging to the class of the Internet of things. At the same time, it is one of the digital subsystems of the SRS that have a positive impact on other components of the SRS as a whole. All this information comes from various (technically and departmental) heterogeneous sources, so for its rapid and high-quality storage and use for monitoring, forecasting and parrying threats to the SRS, it needs specialized methods of analysis, structuring and distributed storage.

Исследовали влияние синтетических аналогов моноядерных динитрозильных комплексов железа (ДНКЖ) с функциональными серусодержащими лигандами (донорами NO) на активность миелопероксидазы (МПО). Обнаружили, что МПО является молекулярной мишенью действия катионных ДНКЖ. С помощью флуоресцентного анализа установили, что шесть соединений ДНКЖ ингибируют активность МРО, а одно активирует.

A method for predicting threats in complex distributed systems is proposed, based on the intelligent analysis of large data arrays on the results of monitoring changes in water level in water bodies and air temperature at the measurement point, which makes it possible to increase the efficiency of planning and implementing measures to fend off such and similar threats. The method is based on general approaches and mathematical models previously used by the authors to develop adaptive algorithms for controlling gas turbine engines, which is especially relevant in the context of the increasingly widespread introduction of automatic means for monitoring the state of complex distributed systems and the exponential growth in the number of data used to support decision-making. The choice of the future value of the water level at the measurement point is carried out based on the results of processing the data accumulated for all previous flood periods on the compliance of the water level and its changes per day with the values of air temperature and its changes for the same day. The results of an experimental assessment of the accuracy of predicting the water level in the water bodies of the Republic of Bashkortostan in the flood period of 2021 are presented, which confirm the applicability of the proposed forecasting method to support decision-making to fend off threats in complex distributed systems from a sharp rise in water.

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