Given the high mortality rate from cardiovascular diseases and the need to transfer medicine to a more high-tech level of development, the authors propose the use of digital twin technology for the diagnosis and treatment of heart diseases. As a digital twin of the human heart, it is proposed to use the combination of an equivalent electric heart generator and the of D. Noble computer heart model within the subsystem for supporting medical decision-making. The use of such digital twin will make it possible to reliably conduct non-invasive cardiodiagnosis to select drugs within the treatment regimen.
The connection between the state of the territorial technosphere and the ecological well-being of man is obvious. Modern research is aimed at studying the effect of pollutants on individual natural systems and do not take into account their complex effects. The assessment is carried out according to individual parameters, not combined into generalizing indicators characterizing the state of the territorial technosphere as a whole and not taking into account the contribution of each. A method for processing measurement information is proposed, which makes it possible to evaluate the contribution of each impact to the final coagulation index. This index characterizes the state of the territorial technosphere taking into account the current aspects and the analyzed criteria and allows, using the method of hierarchy analysis, to determine the weighting coefficients for each aspect. A feature of the proposed method implementation is the lack of subjectivity in the ranking of the analyzed criteria due to the use of not subjective expert assessments, but quantitative values enshrined in regulatory legal acts. The results of such an analysis are important for setting priorities for the implementation of environmental measures and ensuring the ecological well-being of man.
This article proposes a smart system of measurement of and control over a local technosphere’s condition. A basic element of this system, which allows for minimizing control errors, is a smart sensor which gives an opportunity to measure, transform, and automatically detect and correct measurement results. In order to minimize control errors within threshold values of parameters, we suggest transforming the sensitivity of a smart sensor using the Monte Carlo method. Structural schemes of a smart measurement and control system and an intelligent sensor are proposed, as well as an algorithm for transforming the sensitivity of an intelligent sensor based on the Monte Carlo method.
Uncertainties of the results of quantitative determinations in gas chromatography using the methods based on the absolute peak areas (including the external standard method) are rather “sensitive” to the reproducibility of injections. The effective way to compensate for such errors is to introduce the additional standards into the samples, followed by replacing the absolute peak areas by their ratios to peak areas of the standards. It is important to underline that any constituents of the samples can be used as additional standards, including the solvents. Solvents can be used for these purposes even if the heights of their peaks are restricted when the analytical signals exceed the amplifier limits. Using the relative peak areas does not require any extra sample processing besides the registration of peak areas for solvents. Comparing the commonly known and modified methods of external standard demonstrates that using the relative peak areas instead of the absolute ones does not influence the overall precision of determinations (according to the criterion “introduced-determined”) but improve the reproducibility by 2-3 times. The problem of increasing the reliability of such statistical evaluations of results is discussed and to solve it, it is proposed to change the “design” of the experiments. Instead of series of successive analyses of similar origin samples, the use of parallel determinations is preferable. This can be realized, for example, during the fulfillment of student’s practical works.
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