Convergence of economic growth and digitalization of households: spatial analysis of interrelation with regional panel data

Objective: to assess the relationship between the digital infrastructure of households and the average rate of economic growth in the regions, taking into account short- and long-term spatial dependencies.Methods: global Moran and Geary spatial correlation indices, local Moran spatial correlation index, econometric model with spatial autoregression lag, econometric model with spatial interaction in errors, maximum likelihood method.Results: a positive spatial relationship for the gross regional product per capita and the share of the population using the Internet was shown; the positive influence of neighboring regions on economic growth in the given region was confirmed; local spatial clusters of regions by the share of the population using the Internet were found; conditional β-convergence of the average growth rates of the gross regional product both short- and long-term was revealed; Solow’s conclusion about the decreasing return of the excess factor of production was confirmed; a positive impact was found of the number of active subscribers of mobile broadband access to the Internet per 100 inhabitants on the average growth rate of gross regional product, on the share of households having personal computer, on the proportion of households having access to the Internet, and on the average growth rate of gross regional product.Scientific novelty: for the first time, the article uses Russian regional panel data for the period from 2014 to 2017 to measure the relationship between the digital infrastructure of households and the average rate of economic growth, taking into account spatial dependencies.Practical significance: the main conclusions of the article can be used in scientific and practical activities to develop measures to increase the rate of regional economic growth by stimulating investment and consumer demand of households

Measurement of cognitive growth factors of regional economy based on panel data

© MCSER-Mediterranean Center of Social and Educational Research. The article seeks to demonstrate the need for improved mesoeconomical measurement by separating the sphere of production and dissemination of knowledge and formulate an approach to the measurement of cognitive factors in the economic growth of the regional economy. This suggests presenting a classification of growth factors, theoretical principles of knowledge management, knowledge base and the methods of multivariate data analysis: crossed classification and panel data. The study intends to provide a method for measuring changes in the economy of the region under the influence of new knowledge by means of an econometric analysis of the knowledge indicators system - predictors of the cognitive factors of economic growth in the region. The author applies a multidisciplinary approach to the study, carrying out a synthesis of scientific publications on the problems of economic growth, knowledge management, and accumulation of knowledge in the information space of the region, applied analysis. It is emphasized that there is the need for multivariate statistical methods in the analysis of stochastic information. It is proposed to measure and simulate the spatial heterogeneity of the innovation economy based on panel data. The article stresses the need for and the importance of measuring cognitive growth factors for the innovation regional economy. The result is a methodical approach to the calculation of integral indices on the basis of a system of knowledge indicators in the regional economy. The article presents the more conceptual judgments and general recommendations. Therefore, future studies can perform more detailed calculations and experimental development. The presented methodical approach can be useful for improving the monitoring in the system of the state strategic planning to increase the efficiency of innovation and gain competitive advantages of the region's economy

Effect of digitalization on unemployment among the elderly population in EAEU countries

Objective: to identify current trends in the labor market under digitalization and the growing risks and global instability in the world and national markets in the EAEU countries.Methods: panel data analysis models, graphical method, least squares method, generalized feasible least squares method.Results: the data of the EAEU countries from 2016 to 2020 show the synchronization of unemployment indicators; a slight increase in the share of unemployed aged 55 and older in all countries except Russia; a decrease in value added produced within the “Information and Communication” type of activity, with the exception of Kazakhstan; during the pandemic, a decrease in the integral indicator of unemployment and the number of unemployed aged 55 and older was found under the influence of the gross value added within the “Information and Communication” type of activity, as well as a decrease in unemployment among elder citizens under the influence of the share of the population using the Internet.Scientific novelty: the current trends of unemployment are reflected, under digitalization and the growing risks and global instability in the world and national markets in the EAEU countries.Practical significance: the main conclusions of the article can be an argument in favor of the competitive advantages of the older population in the labor market under digitalization and uncertainty of economy

TRITIUM IN EMISSIONS FROM A RESEARCH NUCLEAR REACTOR

The paper presents methods for determining tritium in emissions, and the contribution of various sources of radioactive tritium emissions during the normal operation of the IVV-2M research reactor

Протективные технологии современных методов респираторной поддержки в неонатальной практике

The article  presents  an analysis of literature data  on modern  protective regimens  for invasive respiratory support  in premature newborns  with respiratory distress  syndrome. We have considered positive and negative  aspects of the used methods  of invasive ventilation of the lungs, which are currently widely used as a method  of respiratory therapy  in obstetric hospitals  at any level, even in the category  of children  with extremely and very low birth weight. Modern  protective mechanical ventilation provides for 2 main directions for reducing ventilator-induced lung damage: a decrease in tidal volume (Vt) and the principle  of tolerable  (permissive) hypercapnia. The use of the technique of permissive hypercapnia and regimens with a target volume can reduce the likelihood of ventilator-induced lung injury in newborns. Despite the limited indications for mechanical ventilation in modern neonatology and the widespread use of non-invasive ventilation, for patients who really need mechanical ventilation, the use of volume-targeted regimens offers the best chance of reducing  ventilation complications.Представлен анализ литературы по применению современных протективных режимов инвазивной респираторной поддержки недоношенных новорожденных с респираторным дистресс-синдромом. Рассмотрены положительные и отрицательные стороны используемых методов инвазивной вентиляции легких, которые в настоящее время нашли широкое применение в качестве метода респираторной терапии в акушерских стационарах любого уровня, в том числе у категории детей с экстремально и очень низкой массой тела при рождении. Современная протективная ИВЛ предусматривает два основных направления снижения вентилятор-индуцированного повреждения легких: уменьшение дыхательного  объема (Vt) и принцип  допустимой  (пермиссивной) гиперкапнии. Применение методики  пермиссивной гиперкапнии и режимов с целевым объемом позволяет  снизить вероятность вентилятор-индуцированного повреждения легких у новорожденных детей. Несмотря на ограничение показаний к ИВЛ в современной неонатологии и широкому применению неинвазивной вентиляции, для пациентов, действительно нуждающихся в ИВЛ, применение режимов с целевым объемом дает лучшие шансы на уменьшение осложнений вентиляции

Диагностика вируса, вызывающего COVID-19, методом ПЦР в реальном времени

Aim: the study was aimed to develop a reagent kit for the real-time RT-PCR diagnostics of virus causing COVID-19.Materials and Methods. Three target sites were chosen in the genome SARS-CoV-2. The testing included 220 samples, 48 artificially created positive samples (made from patients’ biomaterial) and 172 clinical samples (scrapes from nasal and pharyngeal cavities, bronchoalveolar lavage, expectoration, endotracheal/nasopharyngeal aspirate, feces, post-mortem material), obtained from two medical centers. Preliminary, the obtained biomaterial was analyzed with a reagent kit of comparison. The evaluation was performed with a confidential interval CI 95%. The calculation of CI for the sensitivity and specificity was made based on the distribution of χ2.Results. The authors developed a technology of novel coronavirus infection (COVID-19) real-time RT-PCR diagnostics for the application in practical healthcare and proposed the variants of testing at all the stages (preanalytical, analytical, and post-analytical, including automated results processing). The proposed reagent kit meets the requirements of the World Health Organization and the Ministry of Healthcare of the Russian Federation. The study results demonstrated high sensitivity and specificity. The sensitivity was 100% (95% CI) 95.6–100%; the specificity was 100% (95% CI) 96.7–100%.Conclusion. The proposed reagent kit was registered in the RF as a medical product; the registration certificate No. RZN 2020/9948 dated 01.04.2020. The application of the reagent kit in network laboratories will provide patients with access to testing for the virus causing COVID-19 and contribute to quick differential diagnostics, improvement of pandemic control, and accurate statistics on the spread of the virus. Цель – разработка набора реагентов для диагностики вируса, вызывающего COVID-19, методом ПЦР в реальном времени.Материалы и методы. В качестве мишеней были выбраны три участка генома SARS-CoV-2. Тестирование выполнено на 220 образцах – 48 положительных образцах, искусственно созданных из биоматериала пациентов, и 172 клинических образцах (соскобы из полости носа и зева, бронхоальвеолярный лаваж, мокрота, эндотрахеальный/назофарингеальный аспират, фекалии, аутопсийный материал) из двух медицинских центров. Предварительно биоматериал был проанализирован с использованием набора сравнения. Оценка проводилась с доверительным интервалом 95%. Расчет доверительных интервалов для чувствительности и специфичности осуществлялся на основании распределения χ2.Результаты. Для использования в практическом здравоохранении разработана технология диагностики новой коронавирусной инфекции (COVID-19) методом ПЦР в реальном времени, предложены конкретные варианты проведения всех этапов тестирования – преаналитического, аналитического и постаналитического, включая автоматизированную обработку результата. Исследуемый набор реагентов соответствует рекомендациям ВОЗ и МЗ РФ. Испытания продемонстрировали высокую чувствительность и специфичность: чувствительность составила 100% (95%-й доверительный интервал) 95,6–100%; специфичность составила 100% (95%-й доверительный интервал) 96,7–100%.Заключение. Набор реагентов зарегистрирован в РФ как медицинское изделие, регистрационное удостоверение № РЗН 2020/9948 от 01.04.2020. Использование его сетевыми лабораториями позволит обеспечить массовый доступ пациентов к тестированию на вирус, вызывающий COVID-19, способствуя быстрому получению результата дифференциальной диагностики, улучшению контроля над пандемией, получению корректной статистики распространения вируса.

Measurement of cognitive growth factors of regional economy based on panel data

© MCSER-Mediterranean Center of Social and Educational Research. The article seeks to demonstrate the need for improved mesoeconomical measurement by separating the sphere of production and dissemination of knowledge and formulate an approach to the measurement of cognitive factors in the economic growth of the regional economy. This suggests presenting a classification of growth factors, theoretical principles of knowledge management, knowledge base and the methods of multivariate data analysis: crossed classification and panel data. The study intends to provide a method for measuring changes in the economy of the region under the influence of new knowledge by means of an econometric analysis of the knowledge indicators system - predictors of the cognitive factors of economic growth in the region. The author applies a multidisciplinary approach to the study, carrying out a synthesis of scientific publications on the problems of economic growth, knowledge management, and accumulation of knowledge in the information space of the region, applied analysis. It is emphasized that there is the need for multivariate statistical methods in the analysis of stochastic information. It is proposed to measure and simulate the spatial heterogeneity of the innovation economy based on panel data. The article stresses the need for and the importance of measuring cognitive growth factors for the innovation regional economy. The result is a methodical approach to the calculation of integral indices on the basis of a system of knowledge indicators in the regional economy. The article presents the more conceptual judgments and general recommendations. Therefore, future studies can perform more detailed calculations and experimental development. The presented methodical approach can be useful for improving the monitoring in the system of the state strategic planning to increase the efficiency of innovation and gain competitive advantages of the region's economy

Measurement of cognitive growth factors of regional economy based on panel data

© MCSER-Mediterranean Center of Social and Educational Research. The article seeks to demonstrate the need for improved mesoeconomical measurement by separating the sphere of production and dissemination of knowledge and formulate an approach to the measurement of cognitive factors in the economic growth of the regional economy. This suggests presenting a classification of growth factors, theoretical principles of knowledge management, knowledge base and the methods of multivariate data analysis: crossed classification and panel data. The study intends to provide a method for measuring changes in the economy of the region under the influence of new knowledge by means of an econometric analysis of the knowledge indicators system - predictors of the cognitive factors of economic growth in the region. The author applies a multidisciplinary approach to the study, carrying out a synthesis of scientific publications on the problems of economic growth, knowledge management, and accumulation of knowledge in the information space of the region, applied analysis. It is emphasized that there is the need for multivariate statistical methods in the analysis of stochastic information. It is proposed to measure and simulate the spatial heterogeneity of the innovation economy based on panel data. The article stresses the need for and the importance of measuring cognitive growth factors for the innovation regional economy. The result is a methodical approach to the calculation of integral indices on the basis of a system of knowledge indicators in the regional economy. The article presents the more conceptual judgments and general recommendations. Therefore, future studies can perform more detailed calculations and experimental development. The presented methodical approach can be useful for improving the monitoring in the system of the state strategic planning to increase the efficiency of innovation and gain competitive advantages of the region's economy

Measurement of cognitive growth factors of regional economy based on panel data

© MCSER-Mediterranean Center of Social and Educational Research. The article seeks to demonstrate the need for improved mesoeconomical measurement by separating the sphere of production and dissemination of knowledge and formulate an approach to the measurement of cognitive factors in the economic growth of the regional economy. This suggests presenting a classification of growth factors, theoretical principles of knowledge management, knowledge base and the methods of multivariate data analysis: crossed classification and panel data. The study intends to provide a method for measuring changes in the economy of the region under the influence of new knowledge by means of an econometric analysis of the knowledge indicators system - predictors of the cognitive factors of economic growth in the region. The author applies a multidisciplinary approach to the study, carrying out a synthesis of scientific publications on the problems of economic growth, knowledge management, and accumulation of knowledge in the information space of the region, applied analysis. It is emphasized that there is the need for multivariate statistical methods in the analysis of stochastic information. It is proposed to measure and simulate the spatial heterogeneity of the innovation economy based on panel data. The article stresses the need for and the importance of measuring cognitive growth factors for the innovation regional economy. The result is a methodical approach to the calculation of integral indices on the basis of a system of knowledge indicators in the regional economy. The article presents the more conceptual judgments and general recommendations. Therefore, future studies can perform more detailed calculations and experimental development. The presented methodical approach can be useful for improving the monitoring in the system of the state strategic planning to increase the efficiency of innovation and gain competitive advantages of the region's economy

The hedonic model of the land for agricultural purposes market value

© 2019, Research Trend. All rights reserved. The authors identified and evaluated the key hedonic factors of agricultural land in the Arsk municipal district of the Republic of Tatarstan of the Russian Federation market value. The authors studied the composition of hedonic characteristics included in the specification of the model, taking into account the characteristics of the terms of the transaction. In order to identify the observed factors determining the value of land plots, a linear specification of the regression hedonic model of market value according to the data on 35 land plots in the Arsk municipal district in 2019 is constructed. The empirical estimates of the specifications presented in the article confirmed the hypothesis of the relationship between the market value of the land plot with its area and the availability of access roads with hard surface. The relationship of the land market value with the distance to the city, the population in the locality in which the land is located, the configuration of the site in the linear specification of the regression hedonic model was not confirmed. The quality of the results was tested using the coefficient of determination, Fisher test and Student test, the results of the official monitoring of prices for agricultural land in the municipal districts of the Republic of Tatarstan. The results of empirical estimates confirmed the feasibility of this approach practical use to the assessment of land market value