The economic efficiency of intensive livestock farming on an industrial basis depends on the rational housing of animals, which is largely determined by the presence of an optimal microclimate in the premises. Whatever breed and pedigree qualities the animals may have, without creating the necessary microclimate conditions they are unable to maintain their health and show their potential productive capabilities due to heredity. Between 2018 and 2020, 11 farms in Perm Region were surveyed for respiratory and digestive diseases, skin diseases, and in some cases stress was observed in the animals. The costs of heating livestock buildings are, as a rule, much lower than the losses due to mortality, loss of productivity and overconsumption of feed. The physical properties of the air environment are factors that are not constant and are subject to large fluctuations. To optimize the microclimate in a livestock building, a program algorithm has been developed for a computer. That will create a system, which provides optimal conditions for the maintenance and service of animals and increase the life safety on livestock farms. In this regard, in order to improve conditions for keeping calves and cows, a project for a device to control the parameters of the microclimate in farms in the Perm region has been developed. The microclimate control system is developed on the basis of: Order of the Ministry of Agriculture of the Russian Federation from October 21, 2000 № 622 “On approval of Veterinary rules of keeping cattle for its reproduction, rearing and realization” and Set of rules 106.13330.2012 “Cattle - breeding, poultry - breeding and beast - breeding buildings and premises”. At the heart of the monitoring is an automated analysis and regulation of microclimate parameters. Hardware-software implementation is made on PLC Omron.
In the new millennium, humanity is faced with infectious diseases that no one previously knew about. In the end of 2019, an outbreak of a new coronavirus infection occurred in the People’s Republic of China (PRC) with an epicenter in the city of Wuhan (Hubei Province). On February 11, 2020, the International Committee on the Taxonomy of Viruses assigned an official name to the infectious agent - SARS-CoV-2. According to the results of serological and phylogenetic analysis, coronaviruses are divided into four genera: Alphacoronavirus, Betacoronavirus, Gammacoronavirus and Deltacoronavirus. Currently, four seasonal coronaviruses (HCoV-229E, - OC43, -NL63 and -HKU1) are circulating among the world’s population, which are present year-round in the structure of ARI, and, as a rule, cause damage to the upper respiratory tract of mild and moderate severity, as well as two highly pathogenic coronaviruses-Middle East respiratory syndrome virus (MERS) and new coronavirus infection COVID-19. To develop a model of human resistance to the disease caused by the coronavirus family, the elements, links and ways of protecting the Human-Virus-Environment system were identified. The destructive functions of sixteen proteins of the SARS-CoV-2 strain are considered. Deterministic and statistical models of cells infection risk development have been developed. A parameterized system of human protection against coronavirus infection is proposed.
The histology is carried out for studying of fabrics of different bodies and systems. The histologic research helps to define existence of pathological cells and new growths with high precision. Modern examinations of an organism are conducted in the different ways: surveys, analyses, ultrasonography, but not always these methods allow to make precisely the diagnosis or to find pathological processes at the cellular level. This method is often applied in various fields of medicine and veterinary science. We conducted pilot laboratory studies patholologically of the changed cells with use of a technique of the histologic analysis. Qualitative and quantitative characteristics pathologists of the changed cells, with identification of indicators are defined. The module of support of decision-making for the preliminary diagnosis of pathologies is developed. The table of the validity of communication of indicators and group of pathologies is developed. With use of the theory of finite-state machines minimization of disjunctive normal form is carried out. On the basis of the received logical equations ladder charts for programming of logical matrixes of the microcontroller of OMRON are constructed. Experiments on reliability of results of the automatic machine - the recognizer of pathology of cells, the shown satisfactory results are made.
The histological method of research based on nanotechnology, allows to study cells and tissues, the effect of herbal supplements on the quality of meat products. Histology is performed to study the tissues of various organs and systems. Histological examination helps with high accuracy to determine the presence of pathologically altered cells and damage to the structure of tissues in products. The difference of this research method from others, for example, examinations, laboratory tests, is an increased accuracy of obtaining results. Currently, studies are conducted manually, and therefore, there is a need to automate the process of histological analysis. Based on the method of histological analysis, a technological map of the stages of histological research has been developed. Developed a functional diagram and logical equations of the equipment. The software and hardware of the automated histological analysis system is implemented on the Omron controller.
Much attention is now being paid to the development of automated devices for rapid disease diagnosis in veterinary medicine and medicine in general. One of the directions in medical instrumentation designing is the development of methods for automated disease diagnosis. This article is devoted to the automatization of pathology detection in histological analysis. The topology of pathologies of morphostructural changes in cells may have a tree-like structure, which makes the development of methods, software and hardware implementation of tools relevant for determination of the disease pathology. The three-level pathology system of structural changes in cell tissues obtained by histological analysis has been studied. It was suggested to use sequential logic, based on the Mealy machine, for the development of automated system for pathology indicators detection. Hartley binary measure for this topology of structural changes in tissues has been calculated and the indicator encoding has been given. The method of automated diagnosis based on the analysis of pathology indicators has been developed. An example of building an automatic recognition machine of pathology indicators on hard logics considered. It is relevant when using programmable logic device. The logical equations implemented in the combination scheme of the device are obtained. Simulation modeling to identify pathology indicators is performed. It is suggested to use the developed method of determining the disease indicators when designing the automated histological analyzer.
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