1,361 research outputs found
Balance of protein supplements according to the criterion of convertible protein
The main sources of vegetable protein are seeds of legumes and oilseeds, which differ as by total content as by the quality. One of the least expensive and most rapid method of assessing the quality of protein is a chemical method, based on a comparative analysis of its amino acid composition, in particular, essential amino acids (EAA), and "ideal" protein. A widespread indicator of the proximity of the protein to the ideal is the minimum period, which shows how much of it can be used by the body for plastic needs (the main exchange and ensuring of body weight gain). Obviously, the more of this (convertible) protein in the product, the better (but not more than the daily value). One of the methods of obtaining a grain product with an increased convertible protein is blending, i.e. mixing in a certain proportion of different types of protein raw materials. In this case, the content of the converted mixture may be greater than in the components, and the excess less. The article presents a methodology for calculating the proportion of convertible protein in the product, as well as a new approach to the formation of effective mixtures. On the basis of this method, the results of the calculation of such mixtures on the example of a grain product with the use of collapsed white lupine, linseed cake and ginger seeds as components are shown. In all cases, there are rational proportions of the mixture, in which its convertible protein exceeds this figure in the component. The accuracy of the calculations largely depends on the accuracy of the total protein content and EAA.The main sources of vegetable protein are seeds of legumes and oilseeds, which differ as by total content as by the quality. One of the least expensive and most rapid method of assessing the quality of protein is a chemical method, based on a comparative analysis of its amino acid composition, in particular, essential amino acids (EAA), and "ideal" protein. A widespread indicator of the proximity of the protein to the ideal is the minimum period, which shows how much of it can be used by the body for plastic needs (the main exchange and ensuring of body weight gain). Obviously, the more of this (convertible) protein in the product, the better (but not more than the daily value). One of the methods of obtaining a grain product with an increased convertible protein is blending, i.e. mixing in a certain proportion of different types of protein raw materials. In this case, the content of the converted mixture may be greater than in the components, and the excess less. The article presents a methodology for calculating the proportion of convertible protein in the product, as well as a new approach to the formation of effective mixtures. On the basis of this method, the results of the calculation of such mixtures on the example of a grain product with the use of collapsed white lupine, linseed cake and ginger seeds as components are shown. In all cases, there are rational proportions of the mixture, in which its convertible protein exceeds this figure in the component. The accuracy of the calculations largely depends on the accuracy of the total protein content and EAA
ΠΠ»Π΅ΠΌΠ΅Π½ΡΠ°ΡΠ½ΠΎΠ΅ ΠΌΡΠ·ΠΈΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΠΎ ΡΠΈΡΡΠ΅ΠΌΠ΅ Π. ΠΡΡΠ° ΠΏΡΠΈ ΠΎΠ±ΡΡΠ΅Π½ΠΈΠΈ Π΄Π΅ΡΠ΅ΠΉ ΠΈΠ³ΡΠ΅ Π½Π° ΡΠ»Π΅ΠΉΡΠ΅
ΠΠ½Π°Π»ΠΈΠ· ΡΠ°ΠΊΡΠΎΡΠΎΠ², Π²Π»ΠΈΡΡΡΠΈΡ Π½Π° Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΡ ΡΠ΅Π½ Π½Π° ΠΆΠΈΠ»ΡΡ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΡ Π² Π ΠΎΡΡΠΈΠΈ
In this paper, we have constructed a VAR model to identify and assess the impact of real interest rate shocks, real estate demand, oil prices, uncertainty, and aggregate business activity on residential real estate prices in Russia. The relevance of the research is due to the following: the dynamics of real estate prices determines the consumer and investment behavior of households, and serious fluctuations in real estate prices lead to adverse consequences in many areas of life, so more and more researchers are asking questions about the presence of bubbles in the real estate market, which can be dangerous to the stability of the economy. In addition, a sharp increase in the cost of housing in Russia in 2020 is an open question for researchers. Our goal is to determine what factors caused the rise in real estate prices in Russia in the time interval from the Q1 of 2000 to the Q2 of 2022. A VAR model with a Cholesky decomposition was used for the evaluation. Several specifications were considered with the inclusion of the real oil price as an exogenous variable and a set of endogenous variables: real GDP, real interest rate, uncertainty index and housing price index. The main conclusion of the paper is that the housing market is sensitive to identified macroeconomic shocks, and a decrease in the interest rate leads to an increase in demand and real estate prices. The estimate of the long-term elasticity of housing prices for oil prices was 0.35, the dynamics of oil prices explained a significant proportion of the variation in real estate prices, but the predominant role in housing price fluctuations is given to housing demand shocks. The housing demand shocks in Russia itself had a negligible impact on GDP.Π Π΄Π°Π½Π½ΠΎΠΉ ΡΠ°Π±ΠΎΡΠ΅ ΠΌΡ ΠΏΠΎΡΡΡΠΎΠΈΠ»ΠΈ VAR ΠΌΠΎΠ΄Π΅Π»Ρ Π΄Π»Ρ ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΠΈ ΠΎΡΠ΅Π½ΠΊΠΈ Π²Π»ΠΈΡΠ½ΠΈΡ ΡΠΎΠΊΠΎΠ² ΡΠ΅Π°Π»ΡΠ½ΠΎΠΉ ΠΏΡΠΎΡΠ΅Π½ΡΠ½ΠΎΠΉ ΡΡΠ°Π²ΠΊΠΈ, ΡΠΏΡΠΎΡΠ° Π½Π° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΡ, ΡΠ΅Π½ Π½Π° Π½Π΅ΡΡΡ, Π½Π΅ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΠΎΡΡΠΈ ΠΈ Π°Π³ΡΠ΅Π³ΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ Π΄Π΅Π»ΠΎΠ²ΠΎΠΉ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ Π½Π° ΡΠ΅Π½Ρ ΠΆΠΈΠ»ΠΎΠΉ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ Π² Π ΠΎΡΡΠΈΠΈ. ΠΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΎΠ±ΡΡΠ»ΠΎΠ²Π»Π΅Π½Π° ΡΠ»Π΅Π΄ΡΡΡΠΈΠΌ: Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠ° ΡΠ΅Π½ Π½Π° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΡ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ΅Ρ ΠΏΠΎΡΡΠ΅Π±ΠΈΡΠ΅Π»ΡΡΠΊΠΎΠ΅ ΠΈ ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΈΠΎΠ½Π½ΠΎΠ΅ ΠΏΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠ΅ Π΄ΠΎΠΌΠΎΡ
ΠΎΠ·ΡΠΉΡΡΠ², Π° ΡΠ΅ΡΡΠ΅Π·Π½ΡΠ΅ ΠΊΠΎΠ»Π΅Π±Π°Π½ΠΈΡ ΡΠ΅Π½ Π½Π° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΡ ΠΏΡΠΈΠ²ΠΎΠ΄ΡΡ ΠΊ Π½Π΅Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΡΠΌ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΠ²ΠΈΡΠΌ Π²ΠΎ ΠΌΠ½ΠΎΠ³ΠΈΡ
ΡΡΠ΅ΡΠ°Ρ
ΠΆΠΈΠ·Π½ΠΈ, ΠΏΠΎΡΡΠΎΠΌΡ Π²ΡΠ΅ Π±ΠΎΠ»ΡΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»Π΅ΠΉ Π·Π°Π΄Π°ΡΡΡΡ Π²ΠΎΠΏΡΠΎΡΠ°ΠΌΠΈ Π½Π°Π»ΠΈΡΠΈΡ ΠΏΡΠ·ΡΡΠ΅ΠΉ Π½Π° ΡΡΠ½ΠΊΠ΅ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΠΈ, ΠΊΠΎΡΠΎΡΡΠ΅ ΠΌΠΎΠ³ΡΡ Π±ΡΡΡ ΠΎΠΏΠ°ΡΠ½Ρ Π΄Π»Ρ ΡΡΠ°Π±ΠΈΠ»ΡΠ½ΠΎΡΡΠΈ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ. Π ΡΠΎΠΌΡ ΠΆΠ΅ ΡΠ΅Π·ΠΊΠΈΠΉ ΡΠΎΡΡ ΡΡΠΎΠΈΠΌΠΎΡΡΠΈ ΠΆΠΈΠ»ΡΡ Π² Π ΠΎΡΡΠΈΠΈ Π² 2020 Π³. β ΠΎΡΠΊΡΡΡΡΠΉ Π²ΠΎΠΏΡΠΎΡ Π΄Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»Π΅ΠΉ. ΠΠ°ΡΠ° ΡΠ΅Π»Ρ - ΠΎΠΏΡΠ΅Π΄Π΅Π»ΠΈΡΡ, ΠΈΠ·-Π·Π° ΠΊΠ°ΠΊΠΈΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ² ΠΏΡΠΎΠΈΡΡ
ΠΎΠ΄ΠΈΠ» ΡΠΎΡΡ ΡΠ΅Π½ Π½Π° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΡ Π² Π ΠΎΡΡΠΈΠΈ Π½Π° Π²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΌ ΠΏΡΠΎΠΌΠ΅ΠΆΡΡΠΊΠ΅ Ρ I ΠΊΠ²Π°ΡΡΠ°Π»Π° 2000 ΠΏΠΎ II ΠΊΠ²Π°ΡΡΠ°Π» 2022 Π³. ΠΠ»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ Π±ΡΠ»Π° ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Π° VAR ΠΌΠΎΠ΄Π΅Π»Ρ Ρ ΡΠ°Π·Π»ΠΎΠΆΠ΅Π½ΠΈΠ΅ΠΌ ΠΏΠΎ Π₯ΠΎΠ»Π΅ΡΠΊΠΎΠΌΡ. Π Π°ΡΡΠΌΠΎΡΡΠ΅Π½Ρ Π½Π΅ΡΠΊΠΎΠ»ΡΠΊΠΎ ΡΠΏΠ΅ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΉ Ρ Π²ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅ΠΌ ΡΠ΅Π°Π»ΡΠ½ΠΎΠΉ ΡΠ΅Π½Ρ Π½Π° Π½Π΅ΡΡΡ Π² ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ ΡΠΊΠ·ΠΎΠ³Π΅Π½Π½ΠΎΠΉ ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ ΠΈ Π½Π°Π±ΠΎΡΠ° ΡΠ½Π΄ΠΎΠ³Π΅Π½Π½ΡΡ
ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
: ΡΠ΅Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΠΠ, ΡΠ΅Π°Π»ΡΠ½ΠΎΠΉ ΠΏΡΠΎΡΠ΅Π½ΡΠ½ΠΎΠΉ ΡΡΠ°Π²ΠΊΠΈ, ΠΈΠ½Π΄Π΅ΠΊΡΠ° Π½Π΅ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΠΎΡΡΠΈ ΠΈ ΠΈΠ½Π΄Π΅ΠΊΡΠ° ΡΠ΅Π½ Π½Π° ΠΆΠΈΠ»ΡΠ΅. ΠΡΠ½ΠΎΠ²Π½ΠΎΠΉ Π²ΡΠ²ΠΎΠ΄ ΡΠ°Π±ΠΎΡΡ β ΡΡΠ½ΠΎΠΊ ΠΆΠΈΠ»ΡΡ ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»Π΅Π½ ΠΊ ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΡΠΌ ΠΌΠ°ΠΊΡΠΎΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΠΌ ΡΠΎΠΊΠ°ΠΌ, Π° ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΠ΅ ΠΏΡΠΎΡΠ΅Π½ΡΠ½ΠΎΠΉ ΡΡΠ°Π²ΠΊΠΈ ΠΏΡΠΈΠ²ΠΎΠ΄ΠΈΡ ΠΊ ΡΠΎΡΡΡ ΡΠΏΡΠΎΡΠ° ΠΈ ΡΠ΅Π½ Π½Π° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΡ. ΠΡΠ΅Π½ΠΊΠ° Π΄ΠΎΠ»Π³ΠΎΡΡΠΎΡΠ½ΠΎΠΉ ΡΠ»Π°ΡΡΠΈΡΠ½ΠΎΡΡΠΈ ΡΠ΅Π½ ΠΆΠΈΠ»ΡΡ ΠΏΠΎ ΡΠ΅Π½Π°ΠΌ Π½Π° Π½Π΅ΡΡΡ ΡΠΎΡΡΠ°Π²ΠΈΠ»Π° 0,35, Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠ° ΡΠ΅Π½ Π½Π° Π½Π΅ΡΡΡ ΠΎΠ±ΡΡΡΠ½ΡΠ»Π° ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΡ Π΄ΠΎΠ»Ρ Π²Π°ΡΠΈΠ°ΡΠΈΠΈ ΡΠ΅Π½ Π½Π° Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡΡ, ΠΎΠ΄Π½Π°ΠΊΠΎ ΠΏΡΠ΅Π²Π°Π»ΠΈΡΡΡΡΠ°Ρ ΡΠΎΠ»Ρ Π² ΠΊΠΎΠ»Π΅Π±Π°Π½ΠΈΡΡ
ΡΠ΅Π½ ΠΆΠΈΠ»ΡΡ ΠΎΡΠ²ΠΎΠ΄ΠΈΡΡΡ ΡΠΎΠΊΠ°ΠΌ ΡΠΏΡΠΎΡΠ° Π½Π° ΠΆΠΈΠ»ΡΠ΅. Π‘Π°ΠΌΠΈ ΠΆΠ΅ ΡΠΎΠΊΠΈ ΡΠΏΡΠΎΡΠ° Π½Π° ΠΆΠΈΠ»ΡΠ΅ Π² Π ΠΎΡΡΠΈΠΈ ΠΎΠΊΠ°Π·ΡΠ²Π°Π»ΠΈ Π½Π΅Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΠΎΠ΅ Π²Π»ΠΈΡΠ½ΠΈΠ΅ Π½Π° ΠΠΠ
Development of regression model of proteins attackability process in meat food (in vitro)
In the presented article the authors consider the issues of development of regression model for process of food digestion by proteolytic enzymes in human body. The authors use correlation analysis. They analyze the main nutritional values and physical and chemical properties of meat products, the modes of heat treatment of semi-finished lamb products. The essential parameters and features are determined to find the dependence between the factor values and efficient values of the basic raw material, which affect the quality of the technological processes and, in general, the finished product. The regression model equation is mathematically calculated by methods of solving K. Gauss linear equations. The standard deviations of parameters are calculated, the initial data are normalized; the matrices of the pair correlation coefficients, lower and upper limits of their values are compiled. Equations of the mathematical regression model of meat proteins attackability by proteolytic enzymes β in vitro (pepsin, trypsin) are developed. It is proved that the obtained equation represents a regression model of the process of meat food proteins attackability by enzymes (pepsin, trypsin and chymotrypsin), depending on the determined 3 essential factors (weight of a meat piece, duration of frying, collagen content in lamb meat). Also this equation reflects the process of lamb digestibility in a digestive tract of a human body
Russian Demographic Data Sheet 2016
The Russian Demographic Datasheet 2016 shows key demographic data, population trends and projections until 2035. It covers fertility, mortality, migration, population structure including population ageing and their changes. The datasheet combines data for the national level, all regions and districts, and features maps, population pyramids, rankings, graphs and a glossary. It pays special attention to the importance of alternative indicators of population ageing for the current and future population changes across Russia. All information is provided in both languages, Russian and English. The project is a collaboration between IIASA, the Russian Presidential Academy of National Economy and Public Administration (RANEPA), and the Russian Federal State Statistics Service (Rosstat)
Active shielding of magnetic field with circular space-time characteristic
Aim. The synthesis of two degree of freedom robust two circuit system of active shielding of magnetic field with circular spacetime characteristic, generated by overhead power lines with "triangle" type of phase conductors arrangements for reducing the magnetic flux density to the sanitary standards level and to reducing the sensitivity of the system to plant parameters uncertainty. Methodology. The synthesis is based on the multi-criteria game decision, in which the payoff vector is calculated on the basis of the Maxwell equations quasi-stationary approximation solutions. The game decision is based on the stochastic particles multiswarm optimization algorithms. The initial parameters for the synthesis by system of active shielding are the location of the overhead power lines with respect to the shielding space, geometry and number of shielding coils, operating currents, as well as the size of the shielding space and magnetic flux density normative value, which should be achieved as a result of shielding. The objective of the synthesis is to determine their number, configuration, spatial arrangementand and shielding coils currents, setting algorithm of the control systems as well as the resulting of the magnetic flux density value at the shielding space. Results. Computer simulation and field experimental research results of two degree of freedom robust two circuit system of active shielding of magnetic field, generated by overhead power lines with Β«triangleΒ» type of phase conductors arrangements are given. The possibility of initial magnetic flux density level reducing and system sensitivity reducing to the plant parameters uncertainty is shown. Originality. For the first time the synthesis, theoretical and experimental research of two degree of freedom robust two -circuit t system of active shielding of magnetic field generated by single-circuit overhead power line with phase conductors triangular arrangements carried out. Practical value. Practical recommendations from the point of view of the practical implementation on reasonable choice of the spatial arrangement of two shielding coils of robust two -circuit system of active shielding of the magnetic field with circular space-time characteristic generated by single-circuit overhead power line with phase conductors triangular arrangements are given.Π¦Π΅Π»Ρ. Π‘ΠΈΠ½ΡΠ΅Π· ΠΊΠΎΠΌΠ±ΠΈΠ½ΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ ΡΠΎΠ±Π°ΡΡΠ½ΠΎΠΉ Π΄Π²ΡΡ
ΠΊΠΎΠ½ΡΡΡΠ½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ Π°ΠΊΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΡΠΊΡΠ°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΌΠ°Π³Π½ΠΈΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ»Ρ Ρ ΠΊΡΡΠ³ΠΎΠ²ΠΎΠΉ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎ-Π²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠΎΠΉ, Π³Π΅Π½Π΅ΡΠΈΡΡΠ΅ΠΌΠΎΠ³ΠΎ ΠΎΠ΄Π½ΠΎΠΊΠΎΠ½ΡΡΡΠ½ΠΎΠΉ Π²ΠΎΠ·Π΄ΡΡΠ½ΠΎΠΉ Π»ΠΈΠ½ΠΈΠ΅ΠΉ ΡΠ»Π΅ΠΊΡΡΠΎΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ Ρ ΡΡΠ΅ΡΠ³ΠΎΠ»ΡΠ½ΡΠΌ ΠΏΠΎΠ΄Π²Π΅ΡΠΎΠΌ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΎΠ² Π΄Π»Ρ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΡ ΠΈΠ½Π΄ΡΠΊΡΠΈΠΈ ΠΌΠ°Π³Π½ΠΈΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ»Ρ Π΄ΠΎ ΡΡΠΎΠ²Π½Ρ ΡΠ°Π½ΠΈΡΠ°ΡΠ½ΡΡ
Π½ΠΎΡΠΌ ΠΈ Π΄Π»Ρ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΡ ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ ΡΠΈΡΡΠ΅ΠΌΡ ΠΊ Π½Π΅ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΠΎΡΡΠΈ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΎΠ² ΠΎΠ±ΡΠ΅ΠΊΡΠ° ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ. ΠΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡ. Π‘ΠΈΠ½ΡΠ΅Π· ΠΎΡΠ½ΠΎΠ²Π°Π½ Π½Π° ΡΠ΅ΡΠ΅Π½ΠΈΠΈ ΠΌΠ½ΠΎΠ³ΠΎΠΊΡΠΈΡΠ΅ΡΠΈΠ°Π»ΡΠ½ΠΎΠΉ ΡΡΠΎΡ
Π°ΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ³ΡΡ, Π² ΠΊΠΎΡΠΎΡΠΎΠΉ Π²Π΅ΠΊΡΠΎΡΠ½ΡΠΉ Π²ΡΠΈΠ³ΡΡΡ Π²ΡΡΠΈΡΠ»ΡΠ΅ΡΡΡ Π½Π° ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠΈ ΡΠ΅ΡΠ΅Π½ΠΈΠΉ ΡΡΠ°Π²Π½Π΅Π½ΠΈΠΉ ΠΠ°ΠΊΡΠ²Π΅Π»Π»Π° Π² ΠΊΠ²Π°Π·ΠΈΡΡΠ°ΡΠΈΠΎΠ½Π°ΡΠ½ΠΎΠΌ ΠΏΡΠΈΠ±Π»ΠΈΠΆΠ΅Π½ΠΈΠΈ. Π Π΅ΡΠ΅Π½ΠΈΠ΅ ΠΈΠ³ΡΡ Π½Π°Ρ
ΠΎΠ΄ΠΈΡΡΡ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π°Π»Π³ΠΎΡΠΈΡΠΌΠΎΠ² ΡΡΠΎΡ
Π°ΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΡΠ»ΡΡΠΈΠ°Π³Π΅Π½ΡΠ½ΠΎΠΉ ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΠΈ ΠΌΡΠ»ΡΡΠΈΡΠΎΠ΅ΠΌ ΡΠ°ΡΡΠΈΡ. ΠΡΡ
ΠΎΠ΄Π½ΡΠΌΠΈ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠ°ΠΌΠΈ Π΄Π»Ρ ΡΠΈΠ½ΡΠ΅Π·Π° ΡΠΈΡΡΠ΅ΠΌΡ Π°ΠΊΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΡΠΊΡΠ°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠ²Π»ΡΡΡΡΡ ΡΠ°ΡΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΠ΅ Π²ΡΡΠΎΠΊΠΎΠ²ΠΎΠ»ΡΡΠ½ΠΎΠΉ
Π»ΠΈΠ½ΠΈΠΉ ΡΠ»Π΅ΠΊΡΡΠΎΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ ΠΏΠΎ ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΡ ΠΊ ΡΠΊΡΠ°Π½ΠΈΡΡΠ΅ΠΌΠΎΠΌΡ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Ρ, Π³Π΅ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ°Π·ΠΌΠ΅ΡΡ, ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²ΠΎ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΎΠ² ΠΈ ΡΠ°Π±ΠΎΡΠΈΠ΅ ΡΠΎΠΊΠΈ Π»ΠΈΠ½ΠΈΠΈ ΡΠ»Π΅ΠΊΡΡΠΎΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΠ°Π·ΠΌΠ΅ΡΡ ΡΠΊΡΠ°Π½ΠΈΡΡΠ΅ΠΌΠΎΠ³ΠΎ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π° ΠΈ Π½ΠΎΡΠΌΠ°ΡΠΈΠ²Π½ΠΎΠ΅ Π·Π½Π°ΡΠ΅Π½ΠΈΠ΅ ΠΈΠ½Π΄ΡΠΊΡΠΈΠΈ ΠΌΠ°Π³Π½ΠΈΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ»Ρ, ΠΊΠΎΡΠΎΡΠΎΠ΅ Π΄ΠΎΠ»ΠΆΠ½ΠΎ Π±ΡΡΡ Π΄ΠΎΡΡΠΈΠ³Π½ΡΡΠΎ Π² ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ΅ ΡΠΊΡΠ°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ. ΠΠ°Π΄Π°ΡΠ΅ΠΉ ΡΠΈΠ½ΡΠ΅Π·Π° ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π°, ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠ°ΡΠΈΠΈ, ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠ°ΡΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΡ ΠΈ ΡΠΎΠΊΠΎΠ² ΡΠΊΡΠ°Π½ΠΈΡΡΡΡΠΈΡ
ΠΎΠ±ΠΌΠΎΡΠΎΠΊ, Π°Π»Π³ΠΎΡΠΈΡΠΌΠ° ΡΠ°Π±ΠΎΡΡ ΡΠΈΡΡΠ΅ΠΌΡ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠΈΡΡΡΡΠ΅Π³ΠΎ Π·Π½Π°ΡΠ΅Π½ΠΈΡ ΠΈΠ½Π΄ΡΠΊΡΠΈΠΈ ΠΌΠ°Π³Π½ΠΈΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ»Ρ Π² ΡΠΊΡΠ°Π½ΠΈΡΡΠ΅ΠΌΠΎΠΌ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΡΠΈΠ²ΠΎΠ΄ΡΡΡΡ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΡΠ΅ΠΎΡΠ΅ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈ ΠΏΠΎΠ»Π΅Π²ΡΡ
ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ°Π»ΡΠ½ΡΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ ΠΊΠΎΠΌΠ±ΠΈΠ½ΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ ΡΠΎΠ±Π°ΡΡΠ½ΠΎΠΉ Π΄Π²ΡΡ
ΠΊΠΎΠ½ΡΡΡΠ½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ Π°ΠΊΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΡΠΊΡΠ°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΌΠ°Π³Π½ΠΈΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ»Ρ, Π³Π΅Π½Π΅ΡΠΈΡΡΠ΅ΠΌΠΎΠ³ΠΎ Π²ΠΎΠ·Π΄ΡΡΠ½ΠΎΠΉ Π»ΠΈΠ½ΠΈΠ΅ΠΉ ΡΠ»Π΅ΠΊΡΡΠΎΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ Ρ ΡΡΠ΅ΡΠ³ΠΎΠ»ΡΠ½ΡΠΌ ΠΏΠΎΠ΄Π²Π΅ΡΠΎΠΌ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΎΠ². ΠΠΎΠΊΠ°Π·Π°Π½Π° Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΡ ΡΡΠΎΠ²Π½Ρ ΠΈΠ½Π΄ΡΠΊΡΠΈΠΈ ΠΈΡΡ
ΠΎΠ΄Π½ΠΎΠ³ΠΎ ΠΌΠ°Π³Π½ΠΈΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ»Ρ Π²Π½ΡΡΡΠΈ ΡΠΊΡΠ°Π½ΠΈΡΡΠ΅ΠΌΠΎΠ³ΠΎ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π° ΠΈ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΡ ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ ΡΠΈΡΡΠ΅ΠΌΡ ΠΊ Π½Π΅ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΠΎΡΡΡΠΌ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΎΠ² ΠΎΠ±ΡΠ΅ΠΊΡΠ° ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ. ΠΡΠΈΠ³ΠΈΠ½Π°Π»ΡΠ½ΠΎΡΡΡ. ΠΠΏΠ΅ΡΠ²ΡΠ΅ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Ρ ΡΠΈΠ½ΡΠ΅Π·, ΡΠ΅ΠΎΡΠ΅ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΈ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ°Π»ΡΠ½ΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΊΠΎΠΌΠ±ΠΈΠ½ΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ ΡΠΎΠ±Π°ΡΡΠ½ΠΎΠΉ Π΄Π²ΡΡ
ΠΊΠΎΠ½ΡΡΡΠ½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ Π°ΠΊΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΡΠΊΡΠ°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΌΠ°Π³Π½ΠΈΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ»Ρ, Π³Π΅Π½Π΅ΡΠΈΡΡΠ΅ΠΌΠΎΠ³ΠΎ ΠΎΠ΄Π½ΠΎΠΊΠΎΠ½ΡΡΡΠ½ΠΎΠΉ Π²ΠΎΠ·Π΄ΡΡΠ½ΠΎΠΉ Π»ΠΈΠ½ΠΈΠ΅ΠΉ ΡΠ»Π΅ΠΊΡΡΠΎΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ Ρ ΡΡΠ΅ΡΠ³ΠΎΠ»ΡΠ½ΡΠΌ ΠΏΠΎΠ΄Π²Π΅ΡΠΎΠΌ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΎΠ². ΠΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠ°Ρ ΡΠ΅Π½Π½ΠΎΡΡΡ. ΠΡΠΈΠ²ΠΎΠ΄ΡΡΡΡ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°ΡΠΈΠΈ ΠΏΠΎ ΠΎΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½Π½ΠΎΠΌΡ Π²ΡΠ±ΠΎΡΡ Ρ ΡΠΎΡΠΊΠΈ Π·ΡΠ΅Π½ΠΈΡ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠ°ΡΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΡ Π΄Π²ΡΡ
ΡΠΊΡΠ°Π½ΠΈΡΡΡΡΠΈΡ
ΠΎΠ±ΠΌΠΎΡΠΎΠΊ Π΄Π²ΡΡ
ΠΊΠΎΠ½ΡΡΡΠ½ΠΎΠΉ ΡΠΎΠ±Π°ΡΡΠ½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ Π°ΠΊΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΡΠΊΡΠ°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΌΠ°Π³Π½ΠΈΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ»Ρ Ρ ΠΊΡΡΠ³ΠΎΠ²ΠΎΠΉ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎ-Π²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠΎΠΉ, ΡΠΎΠ·Π΄Π°Π²Π°Π΅ΠΌΠΎΠ³ΠΎ ΠΎΠ΄Π½ΠΎΠΊΠΎΠ½ΡΡΡΠ½ΠΎΠΉ Π²ΠΎΠ·Π΄ΡΡΠ½ΠΎΠΉ Π»ΠΈΠ½ΠΈΠ΅ΠΉ ΡΠ»Π΅ΠΊΡΡΠΎΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ Ρ ΡΡΠ΅ΡΠ³ΠΎΠ»ΡΠ½ΡΠΌ ΠΏΠΎΠ΄Π²Π΅ΡΠΎΠΌ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΎΠ²
Innovative technologies of management of social work in the Russian Federation
The purpose of studying innovative technologies of social service of elderly people in the Russian Federation is to analyse and synthesize the best regional practices on the organization of social work with elderly people.
It is particular importance during political and economic crisis when elderly people become the most wounded group of the population.
As a result of this research it has been revealed that the main document organizing social work with elderly people is "Road map" at the regional level.
It is described as the basic principles of increase in efficiency and quality of services in the sphere of social service of the population in the Novgorod region for 2013 - 2018. The training, medical-correctional, social and psychological, health saving and spare time of work are revealed with citizens of elderly age.peer-reviewe
Assessment of Womenβs Early-stage Entrepreneurial Activity in 2018
The analysis of the regularities characterizing the existing rate of female early-stage entrepreneurial activity, as well as the identification of reserves for female entrepreneurship growth is relevant nowadays. The purpose of the work is to assess the rates of entrepreneurial activity of women, their motivational preferences, and comparative analysis of female and male early-stage entrepreneurial activities. The study is based on the economic analysis of the data on 48 countries, presented in the Global Entrepreneurship Monitor report for 2018. Normal distribution density functions are used in the modeling process. The research reveals features of female entrepreneurship and the barriers to its development. The paper defines countries with high and low values of the considered indicators. The study estimates the existing rates of opportunity and necessity motivation of female entrepreneurs, presents the analysis of the ratio of female to male participation in early- stage entrepreneurial activity, and proves the hypothesis on substantial differentiation of these indicators across countries. The obtained knowledge can be used in future scientific research, in the educational process of bachelors and masters training. The scientific novelty lies in the study of the distribution of indicators characterizing female entrepreneursβ motivation and the existing gender gap in early-stage entrepreneurship. The study proposes new methods and tools for the analysis and presents a comparative analysis of the development of female and male early-stage entrepreneurship
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