The failure of uncovered interest rate parity (UIP) is a well-known phenomenon of the last thirty years. UIP failure is more prominent in advanced economies than in emerging market economies. Typically, UIP estimation for an advanced economy generates a negative coefficient, meaning that a higher interest rate in advanced economy A will result in the appreciation of economy A's exchange rate. For emerging market economies, higher interest rates usually correspond to future depreciation, although this depreciation is not sufficient for UIP to hold. This paper shows that UIP holds in Russia better than in other emerging market economies when the UIP equation accounts for a constant risk premium. Consequently, there is no forward premium puzzle for Russian data for 2001-2014. To determine the results for Russia and to compare them with the results for other countries, we estimate UIP first for Russia and then for advanced and emerging market economies using seemingly unrelated regressions and panel data analysis. By comparing the profitability of static and dynamic carry trade strategies, we also confirm that in emerging market economies, risk premiums are often constant, whereas in advanced economies, risk premiums are almost always volatile. This may explain why UIP holds better in emerging market economies. It also enables us to formulate a hypothesis that macroeconomic policies of emerging market economies (e.g., the accumulation of large foreign exchange reserves) stabilize risk premiums.

Fuel power plants are one of the main sources of pollutant emissions, so special attention should be paid to improving the efficiency of the fuel combustion process. The mathematical modeling of processes in the combustion chamber makes it possible to reliably predict and find the best dynamic characteristics of the operation of a power plant, in order to quantify the emission of harmful substances, as well as the environmental and technical and economic efficiency of various regime control actions and measures, and the use of new types of composite fuels. The main purpose of this article is to illustrate how machine learning methods can play an important role in modeling and predicting the performance and control of the combustion process. The paper proposes a mathematical model of an unsteady turbulent combustion process, presents a model of a combustion chamber with a combined burner, and performs a numerical study using the STAR-CCM+ multidisciplinary platform. The influence of various input indicators on the efficiency of burner devices, which is evaluated by several parameters at the output, is investigated. In this case, three possible states of the burners are assumed: optimal, satisfactory and unsatisfactory.

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The non-stiff Initial Value Problem is a wider subject classified in Mathematics.Here, we consider an interesting subclass. Namely, the Linear Inhomogeneous system that shares constant coefficients. Runge-Kutta pairs of high orders are chosen in order to achieve stringent accuracies when solving these systems numerically. It is theoretically interesting to equip these methods with large stability intervals for addressing the problems at hand. Thus, at first, we present an explicit algorithm for deriving the coefficients of such pairs of orders eight and seven. Then we adjust this in an optimization precess for extending the stability region and simultaneously keep the principal truncation error as low as possible. The resulting pair outperforms other standard pairs in a series of relevant problems.

An increasing number of countries are now shifting their economies to low-carbon development, which has an impact on the energy sector. The goal of the transition to low -carbon development is to reduce the negative environmental impact. This article presents a simulation of the combustion process of a fuel-air mixture based on natural gas with the proposed organization of flue gas recirculation in the a power-generating boiler of the TGMT-464 type, using the Ansys Fluent software package. The article presents graphs of the distribution of the NO x content in the active combustion zone when the proportion of flue gas recirculation changes from 0 to 22 %. In the proposed process of organizing the flue gas recirculation on a power-generating boiler of the type TGME-464, the reduction in the emission of harmful substances is explained by a decrease in the peak temperature in the active combustion zone, which is the main indicator of the formation of thermal NO x . The article is intended for postgraduates, doctoral students interested in the development of methods for suppressing the formation of NO x in the combustion products of TPP boilers.