A Study on Green Economy Indicators and Modeling: Russian Context

This article aims to assess and forecast the dynamics of a regional green economy. The research relevance is determined by the need to develop theoretical and methodological basis of the green economy for the transition period and to identify criteria basis for assessing the state and regional level of it. The authors applied the modern methods, which allowed to model criteria considering data uncertainty and both static and dynamic criteria. The research process involved the methods of scientific analysis, comparison and synthesis, the theory of fuzzy sets, and fuzzy modeling. The main principles and methodology of the criteria evaluation for a regional green economy are proposed. The principal methodological approach in this research combines the current state and dynamics of the green economy in evaluating and forecasting the conditions of data uncertainty. The research results form a theoretical, methodological, and practical basis for assessing the current state and level of a regional green economy development, determining the effectiveness of environmental and economic programs, optimizing financial management, conducting environmental monitoring, and developing state plans.The research was funded by the grant of the Ministry of Education and Science of the Russian Federation to Perm National Research Polytechnic University # 26.6884.2017/8.9 "Sustainable development of urban areas and the improvement of the human environment.

A Study on Green Economy Indicators and Modeling: Russian Context

This article aims to assess and forecast the dynamics of a regional green economy. The research relevance is determined by the need to develop theoretical and methodological basis of the green economy for the transition period and to identify criteria basis for assessing the state and regional level of it. The authors applied the modern methods, which allowed to model criteria considering data uncertainty and both static and dynamic criteria. The research process involved the methods of scientific analysis, comparison and synthesis, the theory of fuzzy sets, and fuzzy modeling. The main principles and methodology of the criteria evaluation for a regional green economy are proposed. The principal methodological approach in this research combines the current state and dynamics of the green economy in evaluating and forecasting the conditions of data uncertainty. The research results form a theoretical, methodological, and practical basis for assessing the current state and level of a regional green economy development, determining the effectiveness of environmental and economic programs, optimizing financial management, conducting environmental monitoring, and developing state plans.The research was funded by the grant of the Ministry of Education and Science of the Russian Federation to Perm National Research Polytechnic University # 26.6884.2017/8.9 "Sustainable development of urban areas and the improvement of the human environment.

Explicit Solution of the Time Domain Volume Integral Equation Using a Stable Predictor-Corrector Scheme

An explicit marching-on-in-time (MOT) scheme for solving the time domain volume integral equation is presented. The proposed method achieves its stability by employing, at each time step, a corrector scheme, which updates/corrects fields computed by the explicit predictor scheme. The proposedmethod is computationally more efficient when compared to the existing filtering techniques used for the stabilization of explicit MOT schemes. Numerical results presented in this paper demonstrate that the proposed method maintains its stability even when applied to the analysis of electromagnetic wave interactions with electrically large structures meshed using approximately half a million discretization elements

The role of human resources on the economy: a study of the Balkan eu member states

In this paper we analyze the impact of the quality of human capital on the main economic indicators of South-Eastern Europe countries [SEE] at the NUTS 2 level. The subjects of this research are the human capital indicators of regional competitiveness. The quality of human capital depends largely on the age structure of the population and the quality of education. Those regions, which have the highest percentage of the working-age population and highly educated people, are able to achieve higher productivity and gain a competitive advantage over other regions. As main indicators of the quality of human capital we identified: population; persons aged 25-64 with tertiary education attainment; students in tertiary education and participation of adults aged 25-64 in education and training and human resources in science and technology. As main economic indicators, we identified: regional gross domestic product; employment and income of households. The aim of this paper is to determine whether there is a correlation between the indicators of the quality of human capital and economic indicators. As a main methodology we have used the correlation coefficient which shows interdependence of the analyzed indicators. As part of our analysis, we consider only EU member states that belong to the SEE countries: Slovenia, Croatia, Romania, Bulgaria and Greece. We conclude that in all countries there is a high multiple correlation coefficient between the indicators human resources in science and technology, number of students and employment.This paper is the result of the project No. 47007 III funded by the Ministry for Education, Science and Technological Development of Republic of Serbia

Technical Note: High-resolution mineralogical database of dust-productive soils for atmospheric dust modeling

Dust storms and associated mineral aerosol transport are driven primarily by meso- and synoptic-scale atmospheric processes. It is therefore essential that the dust aerosol process and background atmospheric conditions that drive dust emissions and atmospheric transport are represented with sufficiently well-resolved spatial and temporal features. The effects of airborne dust interactions with the environment determine the mineral composition of dust particles. The fractions of various minerals in aerosol are determined by the mineral composition of arid soils; therefore, a high-resolution specification of the mineral and physical properties of dust sources is needed. <br></br> Several current dust atmospheric models simulate and predict the evolution of dust concentrations; however, in most cases, these models do not consider the fractions of minerals in the dust. The accumulated knowledge about the impacts of the mineral composition in dust on weather and climate processes emphasizes the importance of including minerals in modeling systems. Accordingly, in this study, we developed a global dataset consisting of the mineral composition of the current potentially dust-producing soils. In our study, we (a) mapped mineral data to a high-resolution 30 s grid, (b) included several mineral-carrying soil types in dust-productive regions that were not considered in previous studies, and (c) included phosphorus

Modified group projectors: tight binding method

Modified group projector technique for induced representations is a powerful tool for calculation and symmetry quantum numbers assignation of a tight binding Hamiltonian energy bands of crystals. Namely, the induced type structure of such a Hamiltonian enables efficient application of the procedure: only the interior representations of the orbit stabilizers are to be considered. Then the generalized Bloch eigen functions are obtained naturally by the expansion to the whole state space. The method is applied to the electronic pi-bands of the single wall carbon nanotubes: together with dispersion relations, their complete symmetry assignation by the full symmetry (line) groups and the corresponding symmetry-adapted eigen function are found.Comment: 10 pages 1 figur

Combines Work Quality in Maize Silage Production

The paper presents testing results of three silage combines employed in maize silage preparation in Toplica region. It is focused on determination of technical working parameters of tested machines. Achieved results verified the superiority of silage combine John Deere 5820, which produced the chopped mass having particle lengths of the smallest deviation with respect to the preset cutting length. In this case, the average length of chopped mass was 9.9 mm, having 69 % mass in the range up to 8 mm. The other two silage combines produced lower mass percentage of this fraction and larger variations of particle lengths with respect to the preset length. Minimum mass flow rate was evidenced for the silage combine Fortschrit E-286: 7.3 kg s-1 (26.3 t h-1) and the surface productivity of 0.83 ha h-1, at the average speed of 4.0 km h-1. Maximum production rate was achieved with silage combine John Deere 5820: 10.9 kg s-1 (39.1 t h-1) at average working velocity of 4.7 km h-1 and surface efficiency of 1.21 ha h-1