Introduction. Controlling microclimates in the cabin of mobile energy vehicles is an important factor for ensuring operator comfort and productivity. Failure to conform to the microclimate standard values, resulting from uneven heat input from the cab enclosing surfaces and outside can negatively impact the operator health and performance. Therefore, it is necessary to develop an adaptive algorithm of climate control system operation for forecasting the changes in heat input into the cabin and preadjusting cooling capacity. Aim of the Study. The study is aimed at developing an adaptive algorithm for the climate control system operation in the cabins of mobile energy vehicles. Materials and Methods. The theoretical analysis of heat balance formation was used to study the creating process of microclimate conditions in the cabins of mobile energy vehicles, including the dependence of temperature changes in the tractor cabin. There was also used an experimental method involved temperature measurements in the cabin of a T-150K tractor. The exponential smoothing method was used as a forecasting method in the cabins of mobile energy vehicles. Results. As a result of the study, an adaptive algorithm for climate control system has been developed. There has been found an equation for forecasting the air temperature and cooling capacity of a climate control system. An adaptive algorithm for the operation of a climate control system using the exponential smoothing method has been theoretically substantiated and tested in practice. Discussion and Conclusion. The developed adaptive algorithm makes it possible to predict temperature changes in the range of one minute, while the discrepancy between theoretical and experimental values is 2%. When forecasting changes in the cooling capacity of the climate control system, the discrepancy between theoretical and experimental values was 5%. The theoretical basis of the algorithm includes a heat balance equation using the exponential smoothing method to forecast cabin air temperature. An experimental test carried out in the T-150K tractor showed a low prediction error that allows the use of an adaptive algorithm for the operation of climate control systems.
The purpose of the research is to assess the economic efficiency of the production of bakery products enriched with powders from recycled phytomaterials and to make recommendations for reducing their cost. The scientific work was carried out in 2024-2025 on the basis of the Tver State Agricultural Academy. The economic assessment of the production of products was carried out taking into account the calculation of current wholesale prices for raw materials, the cost of resources, services and other items. As a result, the economic efficiency of bakery products enriched with powdered products from secondary plant resources (cakes) of raspberries, sea buckthorn, strawberries, carrots, beets, pumpkins, jerusalem artichokes, apples, pears and cherries in a ratio of 90% (wheat flour) was calculated : 10% (phytopowder). It has been established that the cost of introducing enriching additives into the formulation schemes of wheat bread is usually compensated by the higher selling price of the manufactured products, formed in particular due to the growth of competitive and consumer characteristics of products due to a functional increase in their nutritional value and improved sensory properties. The profitability of the production of functional wheat bread ranges on average from 66 to 84%. An effective way to optimize the cost structure of raw materials in the production of enriched products is to create our own laboratory and production site for powdered products from recycled phytochemicals, which is on average 6-7 times cheaper than ready-made powders. The organization of the site also makes it possible to ensure the uninterrupted supply of technological lines with materials and significantly increase the ability to maneuver the product range. The amount of capital investments in the creation of the site will be about 1333 thousand rubles. The results of this work can be successfully used by enterprises of the bakery and food industries, as well as public catering, to expand the range of products and optimize the cost structure of baked goods.
The problem of assessing the quality of the educational process is one of the key issues in the activities of an educational organization. Its relevance is determined by the growing complexity of the tasks solved at the educational institution. To monitor quality, regular monitoring of all components of the educational process is carried out. This verification is carried out by external governing bodies, the educational organization itself, and experts. State accreditation is of the greatest importance in assessing the activities of a university. To successfully pass it, the educational organization must prepare thoroughly. To do this, it is necessary to assess the risks associated with passing the accreditation. The most convenient way to assess the risks is through mathematical modeling. The impact of numerous different, hard‑to‑control factors on the quality indicators of the educational process determines the stochastic nature of these indicators. This necessitates the use of probabilities of meeting the standard indicators. The probability values are determined with the help of expert specialists. The aim of this article is to build a mathematical model of accreditation based on Bayesian estimation. To achieve this aim, accreditation indicators have been identified, alternative hypotheses have been put forward, and a method for calculating the posterior probabilities of the hypotheses has been presented. Bayesian risks based on regret coefficients are used to make a decision about the possibility of undergoing accreditation. To illustrate the developed method, a specific numerical example is examined. The developed model can be used not only to evaluate an educational institution but also to determine the quality of operation of other organizational management institutions.
The article considers the role of predatory fish species: pike and pike perch in improving the ichthyofauna of the Ivankovo reservoir and the ecologization of the reservoir as a whole. Ivankovo reservoir, located in the Tver region, the average depth is two meters. Bream-type reservoir. Of the predators, the main ones are pike and walleye. Fish sampling was carried out in all molds of the reservoir in a seasonal aspect at six sections covering both channel and shallow water zones. Carp species of fish are exposed to mass disease, the percentage of their morbidity is growing annually. The disease of the fish of the Ivankovo reservoir is associated with both natural and anthropogenic influence. Fluctuations in the level regime of the reservoir, wastewater discharge, mass development of the coastal zone of the reservoir, the absence of commercial fishing create conditions for the development of invasive and fungal diseases. The disease of bream ligulosis from 2 to 2012 increased from 2020 to 1,5%, roach postodiplostomatosis from 6,2 to 2,7%, and thickers to 15,6%. Pike and pike perch are not susceptible to these diseases, due to other feed preferences.
