Regional Economic Policy: Structured Approach and Tools (The Oretical Formulation

The subject matter of the article is the development of a doctrine of coordinated regional development and the study of the structural quality of development of regional systems based on the theoretical analysis of institutional factors (parameters) that determine the technological efficiency of the regional economy. The purpose is to show possibilities of technological changes and the shift of economic growth in a particular regional system, with strict limits for accelerated development, with emphasis on industrial regions. For this purpose, we generated a number of structural models, analyzed the impact of technological factors on parameters of growth of the regional economy and determined conditions for development of industrial regions. We applied correlative and regression analysis to establish a statistically significant correlation between relevant parameters, used econometric models to show the possibility to estimate parameters of growth through control parameters, including technological factor. The structural aspect of regional economic growth is measured by dividing investments into two classes: old and new technologies. It is possible to increase the technological efficiency of the regional economy by improving results with regard to used (old) technologies and applying new technologies. This approach fundamentally refines the priority queue algorithm for regional development, provides a choice of a strategy of regional technological development. When resources are directed only to the latest technologies, the disproportion in development of the regional economic system can dramatically increase, and parameters related to diversion of resources and creation of a new resource will determine the growth rate of the region. The behavior of investment in old technologies has a major impact on the rate of regional economic growth in Russia, while investments in new technologies are minor and did not have an equivalent impact on the economic growth rate compared with old technologies. Institutional corrections that define parameters of resource diversion from old technologies and creation of a new resource for development, will determine the quality of new economic growth

Инвестиционная функция экономического роста России

The intensification of investment dynamics is a determining factor in the new growth model of the Russian economy. The Covid crisis has greatly limited the opportunities to use this factor and made restoring growth dynamics an urgent task. The aim of the study is to determine the investment function of the Russian economy before the Covid crisis in order to identify the main instruments of the investment policy of growth in the post-crisis period. The research methods are macroeconomic and regression analysis based on software Gretl 2020b, which helped to choose the investment function according to the instrument-factors. Solving the problem of collinearity of multiple regression factors makes it possible to select the best models for GDP and investment in fixed assets of the Russian economy. The research result is selected multivariate models of gross product and investment that allow considering the impact of the following instruments on the goal’s function: monetization level, key interest rate, exchange rate, risk, profitability, oil prices, financial investments, inflation. The author concludes that an increase in the monetization of the economy, a decrease in the key interest rate, and a controlled devaluation generally had a positive effect on the amount of investment in fixed assets. The investment growth increased the risk of economic activity; the decrease in profitability relatively decreased investment and increased Russia’s GDP with an increased risk over the considered time interval. When implementing investment policy, one should consider these features along with the specified macro-aggregates, the structure of investment distribution between sectors and types of investments, for example, in financial and non-financial assets. The paper shows the significance of this condition, which affects the effectiveness of the investment policy, when the shift in investment towards financial assets accompanies the slowdown in economic growth. The prospect of further research is an assessment of the equalization of sectoral risks affecting the distribution of investments and investment dynamics.Активизация инвестиционной динамики является определяющим фактором новой модели роста российской экономики. «Ковидный кризис» серьезно сузил возможности использования этого фактора, актуализировав задачу восстановления ростовой динамики. Цель исследования — определить инвестиционную функцию российской экономики до «ковидного кризиса», чтобы выявить основные инструменты инвестиционной политики роста в посткризисный период. Методологию исследования составляет макроэкономический и регрессионный анализ, проведенный на базе программного модуля Gretl 2020b, при помощи которого осуществлен подбор инвестиционной функции в зависимости от инструментов-факторов. Разрешение проблемы коллинеарности факторов множественной регрессии позволяет отобрать лучшие модели для ВВП и инвестиций в основной капитал российской экономики. Результатом исследования выступают отобранные многофакторные модели валового продукта и величины инвестиций, позволяющие рассмотреть картину влияния следующих инструментов на функции цели: уровня монетизации, ключевой процентной ставки, валютного курса, риска, рентабельности, цены на нефть, финансовых инвестиций, инфляции. Автор делает вывод, что увеличение монетизации экономики, снижение ключевой процентной ставки и управляемая девальвация в целом положительно влияли на величину инвестиций в основной капитал. Рост инвестиций сопровождался ростом риска ведения экономической деятельности, а снижение рентабельности сопровождалось относительным снижением инвестиций и ростом ВВП России с увеличением риска на рассматриваемом интервале времени. Эти выявленные особенности требуют учета при реализации инвестиционной политики наравне с указанными макроагрегатами, структуры распределения инвестиций между секторами и видами инвестиций, например в финансовые и нефинансовые активы. Показана значимость данного условия, влияющего на результативность проводимой инвестиционной политики, когда смещение инвестиций в сторону финансовых активов сопровождает торможение экономического роста. Перспективу дальнейшего исследования составляет оценка выравнивания секторальных рисков, сказывающихся на распределении инвестиций и инвестиционной динамике

Comparative structural analysis of economic growth in countries of the Eurasian Economic Union

Relevance. The development of the Eurasian Union means economic integration between its member countries (Armenia, Belarus, Kazakhstan, Kyrgyzstan, and Russia). For more efficient coordination of this process, it is necessary to analyze national models of economic growth and adjust the Union’s economic policy accordingly.Research objective. The study aims to identify the national models of economic growth by applying the structural analysis method and building regression models of GDP growth.Data and methods. The study relies on the structural analysis of GDP growth and regression analysis of the impact of macroeconomic policy instruments.Results. The study provides an overview of the research literature on the factors affecting economic growth (e.g. the financial structure, government expenditures. Based on the results of the structural analysis, a classification of the models of economic growth in terms of expenditures and sectors is proposed. This classification can be used to devise measures stimulating cooperation and integration within the Eurasian Union.Conclusions. The study has revealed the differences between the national models of economic growth by looking at each country’s reaction to the crises of 2009 and 2015. These differences correspond to the peculiarities of each country’s economic policy and need to be taken into account in the Union’s policy-making

Gating-by-tilt of mechanosensitive membrane channels

We propose an alternative mechanism for the gating of biological membrane channels in response to membrane tension that involves a change in the slope of the membrane near the channel. Under biological membrane tensions we show that the energy difference between the closed (tilted) and open (untilted) states can far exceed kBT and is comparable to what is available under simple ilational gating. Recent experiments demonstrate that membrane leaflet asymmetries (spontaneous curvature) can strong effect the gating of some channels. Such a phenomenon would be more easy to explain under gating-by-tilt, given its novel intrinsic sensitivity to such asymmetry.Comment: 10 pages, 2 figure

Identification of the thermostable enterotoxin of Escherichia coli in calves with colibacteriosis

IFA test-sistem is developed for identification of the heat stable (ST) enterotoxin of Escherichia coli in the calves faeces at different stages of colibacteriosis. The range of its titre makes ≥ 250 ng/ml at the hyperacute stage, at the acute stage – ≥ 500 ng/ml, and at the subacute one– ≥ 1 000 ng/ml. The registered enterotoxin titres can be considered as the diagnostic indices

Determining Optimal Mining Work Size on the OpenCL Platform for the Ethereum Cryptocurrency

In terms of cryptocurrency, mining is a process of creating a new transaction block to add it to the blockchain. The cryptocurrency protocol should ensure the reliability of new transaction blocks. One of the popular mining protocols is the Proof-of-Work protocol, which requires the miner to perform a certain work to verify its right to add a new block into the blockchain. To perform this work, high-performance hardware is used, such as GPU. On the program level, hardware needs special computing framework, for example, CUDA or OpenCL. In this article, we discuss Ethereum cryptocurrency mining using the OpenCL standard. The Ethereum cryptocurrency is the most popular cryptocurrency with GPU-based mining. There are several open-source implementations of the Ethereum cryptocurrency miners. The host-part of the OpenCL-miner is considered, which makes the research results independent of the mining algorithm and allows using the results of the research in the mining of other cryptocurrencies. During the research, we have found the problems, which lead to mining productivity loss, and we are looking for the ways to resolve these problems and thus increase mining performance. As part of solving these problems, we have developed the algorithm for the functioning of the miner and proposed the methodology of determining the optimal size of OpenCL work, which allows to reduce the impact of problems found and achieve maximum mining productivity using OpenCL framework