Monitoring of risk of multidimensional stochastic system as tools for a research of sustainable development of regions

New approach for a research of sustainable development of regions and cities is offered. It is based on the risk model of multidimensional stochastic system. In article the risk model of multidimensional stochastic system with interdependent factors is described. The hypothesis which consists that the risk can be managed by changing probabilistic properties of a component of multidimensional stochastic system is the cornerstone of the offered risk model. At the same time the multidimensional stochastic system is modeled in the form of a random vector which components in generally are mutually correlated. The questions of formation of multidimensional areas of dangerous states and calculation of risk are described. The representation of risk function is shown. For regions of the Ural Federal District on group of risk factors numerical characteristics of a multidimensional Gaussian random variable - a covariance matrix and a vector of mathematical expectations are found. Results of calculation of probability of a dangerous outcome and risk depending on the found numerical characteristics are given. © 2018 Institute of Physics Publishing. All rights reserved.Present study was carried out under financial support of the Russian Fund of Fundamental Research grant No. 17-01-00315 “Development of models and methods of monitoring, forecasting and control optimization of multidimensional regional socio-economic systems based on entropy and minimax approaches”

Enhancing the performance of the exact algorithm for implementing the method of least absolute deviations when estimating the parameters of linear regression models

An algorithm for finding the exact solution of the problem of estimating the parameters of linear regression models by the method of least absolute deviations is described. This algorithm significantly wins in comparison with the known search algorithm. Comparative characteristics of the proposed and known algorithms are given. An example of practical implementation of the algorithm is described.Описан алгоритм нахождения точного решения задачи оценивания параметров линейных регрессионных моделей методом наименьших модулей. Данный алгоритм значительно выигрывает по сравнению с известным переборным алгоритмом. Приведены сравнительные характеристики предложенного и известного алгоритмов. Описан пример практической реализации алгоритма.Исследование выполнено при поддержке РФФИ, грант № 16-06-00048а

Systems monitoring based on robust estimation of stochastic time series models

The problem of system monitoring under conditions of stochastic data heterogeneity based on time series models is considered. The stability of monitoring is proposed to be ensured through the use of convex-concave loss functions. An algorithm for estimating the variance of the main error distribution is proposed. This allows using robust procedures for estimating the parameters of stochastic time series models without a priori information about the variance value of the main error distribution. Using the Monte Carlo statistical test method, the estimates of the proposed robust methods are compared with the known methods of least squares, least modules, and Huber. It is shown that the introduced robust estimates of the parameters of stochastic models of time series win in accuracy and allow increasing the reliability of monitoring the state of systems. © Published under licence by IOP Publishing Ltd.Russian Foundation for Basic Research, РФФИ, (20-41-660008)The study was carried out with the financial support of the RFBR grant, project No. 20-41-660008

Interrelation between Supply and Demand Factors in Regional Labor Markets

Annotation. The article presents the author's approach to the analysis of matching the demand for labor and its supply. The essence of the approach lies in the dynamic assessment the closeness of the relationship between two sets of indicators describing each of the factors. The proposed model for calculating the coefficient characterizing the closeness of the relationship allowed us to consider simultaneously the factors of the formation of demand for labor and its supply, as well as to make quantitative estimates. The approach was tested using the data from the subjects of the Russian Federation situated in the Ural Federal District. The results of the assessment showed that during the period from 2000 to 2019 the closeness of relationship between the indicators of supply and demand factors in the labor market increased. The most significant contribution to the coordination between supply and demand in the regional labor markets is made by the demographic factor, i.e. the share of the population of working age. In addition, in some subjects of the Russian Federation, the functioning of the labor market is quite significantly affected by the retail turnover, the amount of investment in fixed assets and the graduation of specialists. The use of the coefficient of closeness of the relationship allowed us to consider simultaneously all the indicators of the factors of supply and demand in the labor market and make quantitative estimates. Such a unique approach makes it possible to avoid the objectively existing restrictions in the statistical accounting of employment and unemployment. © 2022 Economic Research Institute, Far Eastern Branch, Russian Academy of Sciences. All rights reserved.Russian Foundation for Basic Research, РФФИ: 20-41-660008Acknowledgements. This work has been carried out with the financial support of the Russian Foundation for Basic Research grant, project No. 20-41-660008

Sustainable Development Indicators in Benchmarks of Russia's Regional Policy

We have considered the problem concerning the substantiation of sustainable development indicators and the improvement of the standard of living of the population in Russian regions. To quantify the standard of living of the population, we have used a common indicator such as the Human Development Index. The authors present an approach to managing the region in the form of optimization problems aimed at improving the standard of living of the region's population by increasing the probability of its classification as a region with a higher standard of living. The optimization problem is solved based on the identified relationship between the standard of living of the region's population and its socioeconomic indicators. © 2020 Published under licence by IOP Publishing Ltd.This work has been performed with the support of the Russian Foundation for Basic Research, Grant No. 18-010-00493

Assessment of the differential entropy of random vectors

Hereby, the features of assessment of differential realization of random vectors for practical use are considered. The question of the stability of the assessment procedure for the presence of anomalous observations in the samples was investigated. The possibility of using differential entropy for samples of random vectors is considered, some components of which are presented in grouped form as discrete quantities. Examples are given of differential entropy assessment with the help of the proposed algorithms.Рассмотрены особенности оценивания дифференциальной реализации случайных векторов для практического использования. Исследован вопрос устойчивости процедуры оценивания к присутствию в выборках аномальных наблюдений. Рассмотрена возможность использования дифференциальной энтропии для выборок случайных векторов, некоторые компоненты которых представлены в сгруппированном виде как дискретные величины. Приведены примеры оценивания дифференциальной энтропии с помощью предложенных алгоритмов.Исследование выполнено при поддержке РФФИ, грант № 17-01-00315а

Entropy-probabilistic modeling as a tool for forming key competencies of a doctor

The possibility of using modern digital educational technologies in the formation of key competencies of a doctor is shown on the example of the entropy-probability model, which is a synthesis of the system-entropy approach and multidimensional risk analysis of stochastic systems. Examples of practical application of this model in preventive medicine are given: Analysis of population entropy in the prevention of noncommunicable diseases, comprehensive assessment of the effectiveness and safety of medicines, quantitative assessment of population health with the determination of the contribution of individual risk factors, and systematic analysis of population changes in monitoring risk factors. The introduction of entropy-probabilistic modeling in the educational process will help in the formation of the doctor's basic universal, professional competencies and systematic clinical thinking. © Published under licence by IOP Publishing Ltd.The work was supported by the RFBR (grant 20-51-00001 Bel_a)

CD28 between tolerance and autoimmunity: The side effects of animal models [version 1; referees: 2 approved]

Regulation of immune responses is critical for ensuring pathogen clearance and for preventing reaction against self-antigens. Failure or breakdown of immunological tolerance results in autoimmunity. CD28 is an important co-stimulatory receptor expressed on T cells that, upon specific ligand binding, delivers signals essential for full T-cell activation and for the development and homeostasis of suppressive regulatory T cells. Many in vivo mouse models have been used for understanding the role of CD28 in the maintenance of immune homeostasis, thus leading to the development of CD28 signaling modulators that have been approved for the treatment of some autoimmune diseases. Despite all of this progress, a deeper understanding of the differences between the mouse and human receptor is required to allow a safe translation of pre-clinical studies in efficient therapies. In this review, we discuss the role of CD28 in tolerance and autoimmunity and the clinical efficacy of drugs that block or enhance CD28 signaling, by highlighting the success and failure of pre-clinical studies, when translated to humans

Mathematical model of diagnostics of perinatal damage of the central nervous system in infants in the neonatal period

Questions of relevance and timeliness of diagnostics of perinatal disturbances of the central nervous system in newborns are considered in the article. Research objective was to determine the reliable recognition of the development of newborn encephalopathy at the age of the first two weeks of life according to neurological examination and neurosonography parameters with Doppler study of cerebral vessels. Features of the neurology status and data of ultrasonic examination of brain with Doppler study of cerebral vessels in 58 newborns with pathology of the nervous system and 23 healthy newborns are investigated. 10 sings of the neurological status and 10 parameters of ultrasonic examination are analyzed. By results of the obtained findings, prognostic rule is developed, governed by application of discriminant analysis of the studied signs, allowing to diagnose encephalopathy in newborn with sensitivity and specificity of 95% in the first week of life. Its application promotes timely identification and the beginning of therapy at infants from risk group of development of severe neurological dysfunction and preventing the growth of disability among infants. © 2017 Team of Authors