350 research outputs found
Mechanism of phase transitions and the electronic density of states in (La,Sm)FeAsOF from ab initio calculations
The structure and electronic density of states in layered
LnFeAsOF (Ln=La,Sm; =0.0, 0.125, 0.25) are investigated using
density functional theory. For the =0.0 system we predict a complex
potential energy surface, formed by close-lying single-well and double-well
potentials, which gives rise to the tetragonal-to-orthorhombic structural
transition, appearance of the magnetic order, and an anomaly in the specific
heat capacity observed experimentally at temperatures below 140--160 K.
We propose a mechanism for these transitions and suggest that these phenomena
are generic to all compounds containing FeAs layers. For 0.0 we demonstrate
that transition temperatures to the superconducting state and their dependence
on correlate well with the calculated magnitude of the electronic density
of states at the Fermi energy.Comment: 4 pages, 3 figures, 1 tabl
Investment and Growth in Rich and Poor Countries
This paper revisits the association between investment and growth. The empirical findings highlight substantial heterogeneity for the effect of investment on growth and suggest a possible negative association. Results based on a battery of cross-sectional and time-series regressions show that the link between investment and growth has weakened over time and that investment in high-income countries is more likely to have a negative effect on growth. The adverse effect for high-income countries appears to have increased over time. An implication is that uphill capital flows could be associated with negative or zero returns. The result is robust to the presence of control variables that are commonly included in growth studies.
Rural youth in search of social lift: opportunities and risks
Π Π΄ΠΎΠΊΠ»Π°Π΄Π΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Ρ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΡΠΎΡΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ ΡΠ΅Π»ΡΡΠΊΠΎΠΉ ΠΌΠΎΠ»ΠΎΠ΄Π΅ΠΆΠΈ ΠΡΠ°ΡΠ½ΠΎΠ΄Π°ΡΡΠΊΠΎΠ³ΠΎ ΠΏΡΠΈ ΠΏΠΎΠΌΠΎΡΠΈ Π³Π»ΡΠ±ΠΈΠ½Π½ΠΎΠ³ΠΎ ΠΈΠ½ΡΠ΅ΡΠ²ΡΡ. ΠΠ½Π°Π»ΠΈΠ·ΠΈΡΡΡΡΡΡ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΡΡ
ΠΏΠ΅ΡΠ΅ΠΌΠ΅ΡΠ΅Π½ΠΈΠΉ ΠΌΠΎΠ»ΠΎΠ΄ΡΡ
ΡΠ΅Π»ΡΡΠ°Π½ Π² ΡΡΠ»ΠΎΠ²ΠΈΡΡ
ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΡΠ°Π³Π½Π°ΡΠΈΠΈ ΡΠ΅Π»ΡΡΠΊΠΎΠΉ ΠΌΠ΅ΡΡΠ½ΠΎΡΡΠΈ.This report presents the results of the survey of contemporary rural youth Krasnodar using in-depth interviews. Analyzes the characteristics of the social movements of young villagers in terms of socio-economic stagnation countryside
ΠΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ Π°Π²ΠΈΠ°ΠΏΠ°ΡΡΠ°ΠΆΠΈΡΡΠΊΠΈΡ ΠΏΠ΅ΡΠ΅Π²ΠΎΠ·ΠΎΠΊ Π ΠΎΡΡΠΈΠΈ
The use of economic and mathematical methods of forecasting the results of activities of civil aviation organisations, and in particular assessment of the volume of air passenger traffic is quite relevant due to the importance of operational planning of air transport processes, development of strategic directions, technological and technical renewal of air enterprises.The objective of the study is to plan the traffic flow of air passengers using a regression model, considering the results of multifactorial selection of determinants, particularly distinguishing fundamental macro indicators are distinguished, as well as significant indicators of the aviation market.The study of passenger air transportation was carried out using methods of system analysis, methods of mathematical statistics and econometrics. Modelling of the process of passenger transportation has identified the main determinants that positively or negatively affect the dynamics of air passenger traffic. The multiple regression of the study of the processes of connectivity and synchronicity of changes in development of passenger traffic and selected macro indicators in a generalised form is the sum of vectors of influencing variables adjusted for the calculated coefficients.Six-, four- and three-factor regression models were developed. The three-factor model turned to be more reliable with values most close to actual data. Nevertheless, while applying regression model for forecasting air traffic it is necessary to consider not only theoretical aspects, data of official forecasts of macro indicators but expert opinions as well.ΠΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΎ-ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² Π΄Π΅ΡΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΠΉ Π³ΡΠ°ΠΆΠ΄Π°Π½ΡΠΊΠΎΠΉ Π°Π²ΠΈΠ°ΡΠΈΠΈ ΠΈ, Π² ΡΠ°ΡΡΠ½ΠΎΡΡΠΈ, ΠΎΠ±ΡΡΠΌΠΎΠ² Π°Π²ΠΈΠ°ΠΏΠ°ΡΡΠ°ΠΆΠΈΡΡΠΊΠΈΡ
ΠΏΠ΅ΡΠ΅Π²ΠΎΠ·ΠΎΠΊ Π² ΡΠΈΠ»Ρ Π²Π°ΠΆΠ½ΠΎΡΡΠΈ ΠΎΠΏΠ΅ΡΠ°ΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΠΏΠ»Π°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² Π°Π²ΠΈΠ°ΡΡΠ°Π½ΡΠΏΠΎΡΡΠ°, ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ ΡΡΡΠ°ΡΠ΅Π³ΠΈΡΠ΅ΡΠΊΠΈΡ
Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½ΠΈΠΉ Π΅Π³ΠΎ ΡΠ°Π·Π²ΠΈΡΠΈΡ, ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈ ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΎΠ±Π½ΠΎΠ²Π»Π΅Π½ΠΈΡ Π°Π²ΠΈΠ°ΠΏΡΠ΅Π΄ΠΏΡΠΈΡΡΠΈΠΉ Π΄ΠΎΡΡΠ°ΡΠΎΡΠ½ΠΎ Π°ΠΊΡΡΠ°Π»ΡΠ½ΠΎ.Π¦Π΅Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠΎΡΡΠΎΠΈΡ Π² ΠΏΠ»Π°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΠΈ Π°Π²ΠΈΠ°ΠΏΠΎΡΠΎΠΊΠ° ΠΏΠ°ΡΡΠ°ΠΆΠΈΡΠΎΠ² ΠΏΠΎ ΡΠ΅Π³ΡΠ΅ΡΡΠΈΠΎΠ½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ Ρ ΡΡΡΡΠΎΠΌ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² ΠΌΠ½ΠΎΠ³ΠΎΡΠ°ΠΊΡΠΎΡΠ½ΠΎΠ³ΠΎ ΠΎΡΠ±ΠΎΡΠ° Π΄Π΅ΡΠ΅ΡΠΌΠΈΠ½Π°Π½Ρ, ΡΡΠ΅Π΄ΠΈ ΠΊΠΎΡΠΎΡΡΡ
Π²ΡΠ΄Π΅Π»ΡΡΡ ΡΡΠ½Π΄Π°ΠΌΠ΅Π½ΡΠ°Π»ΡΠ½ΡΠ΅ ΠΌΠ°ΠΊΡΠΎΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ, Π° ΡΠ°ΠΊΠΆΠ΅ Π·Π½Π°ΡΠΈΠΌΡΠ΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ Π°Π²ΠΈΠ°ΡΡΠ½ΠΊΠ°.ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΠ°ΡΡΠ°ΠΆΠΈΡΡΠΊΠΈΡ
Π°Π²ΠΈΠ°ΠΏΠ΅ΡΠ΅Π²ΠΎΠ·ΠΎΠΊ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΎΡΡ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΡΠΈΡΡΠ΅ΠΌΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π°, ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ ΠΈ ΡΠΊΠΎΠ½ΠΎΠΌΠ΅ΡΡΠΈΠΊΠΈ. ΠΡΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠ° ΠΏΠ°ΡΡΠ°ΠΆΠΈΡΡΠΊΠΈΡ
ΠΏΠ΅ΡΠ΅Π²ΠΎΠ·ΠΎΠΊ Π²ΡΠ΄Π΅Π»Π΅Π½Ρ ΠΎΡΠ½ΠΎΠ²Π½ΡΠ΅ Π΄Π΅ΡΠ΅ΡΠΌΠΈΠ½Π°Π½ΡΡ, ΠΏΠΎΠ»ΠΎΠΆΠΈΡΠ΅Π»ΡΠ½ΠΎ ΠΈΠ»ΠΈ ΠΎΡΡΠΈΡΠ°ΡΠ΅Π»ΡΠ½ΠΎ Π²Π»ΠΈΡΡΡΠΈΠ΅ Π½Π° Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΡ Π°Π²ΠΈΠ°ΠΏΠ°ΡΡΠ°ΠΆΠΈΡΠΎΠΏΠΎΡΠΎΠΊΠ°. ΠΠ½ΠΎΠΆΠ΅ΡΡΠ²Π΅Π½Π½Π°Ρ ΡΠ΅Π³ΡΠ΅ΡΡΠΈΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² ΡΠ²ΡΠ·Π°Π½Π½ΠΎΡΡΠΈ ΠΈ ΡΠΈΠ½Ρ
ΡΠΎΠ½Π½ΠΎΡΡΠΈ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΏΠ°ΡΡΠ°ΠΆΠΈΡΠΎΠΏΠΎΡΠΎΠΊΠ° ΠΈ ΠΎΡΠΎΠ±ΡΠ°Π½Π½ΡΡ
ΠΌΠ°ΠΊΡΠΎΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ Π² ΠΎΠ±ΠΎΠ±ΡΡΠ½Π½ΠΎΠΌ Π²ΠΈΠ΄Π΅ ΡΠ²Π»ΡΠ΅ΡΡΡ ΡΡΠΌΠΌΠΎΠΉ Π²Π΅ΠΊΡΠΎΡΠΎΠ² Π²Π»ΠΈΡΡΡΠΈΡ
ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
Ρ ΠΏΠΎΠΏΡΠ°Π²ΠΊΠΎΠΉ Π½Π° ΡΠ°ΡΡΡΠΈΡΠ°Π½Π½ΡΠ΅ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΡ.Π ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ΅ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Ρ ΡΠ΅ΡΡΠΈ-, ΡΠ΅ΡΡΡΡΡ
- ΠΈ ΡΡΡΡ
- ΡΠ°ΠΊΡΠΎΡΠ½ΡΠ΅ ΡΠ΅Π³ΡΠ΅ΡΡΠΈΠΎΠ½Π½ΡΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ, ΠΈΠ· ΠΊΠΎΡΠΎΡΡΡ
ΠΏΠΎΡΠ»Π΅Π΄Π½ΡΡ ΠΎΠ±Π»Π°Π΄Π°Π΅Ρ Π½Π°ΠΈΠ±ΠΎΠ»ΡΡΠ΅ΠΉ Π΄ΠΎΡΡΠΎΠ²Π΅ΡΠ½ΠΎΡΡΡΡ Ρ Π΄ΠΎΡΡΠ°ΡΠΎΡΠ½ΠΎ Π±Π»ΠΈΠ·ΠΊΠΈΠΌΠΈ ΠΊ ΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈΠΌ Π·Π½Π°ΡΠ΅Π½ΠΈΡΠΌ Π΄Π°Π½Π½ΡΠΌΠΈ. ΠΡΠΈ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΠΈ ΠΏΠ°ΡΡΠ°ΠΆΠΈΡΠΎΠΏΠΎΡΠΎΠΊΠ° ΠΏΠΎ ΡΠ΅Π³ΡΠ΅ΡΡΠΈΠΎΠ½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎ ΡΡΠΈΡΡΠ²Π°ΡΡ Π½Π΅ ΡΠΎΠ»ΡΠΊΠΎ ΡΠ΅ΠΎΡΠ΅ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π°ΡΠΏΠ΅ΠΊΡΡ, Π΄Π°Π½Π½ΡΠ΅ ΠΎΡΠΈΡΠΈΠ°Π»ΡΠ½ΡΡ
ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΎΠ² ΠΌΠ°ΠΊΡΠΎΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ, Π½ΠΎ ΠΈ ΠΌΠ½Π΅Π½ΠΈΠ΅ ΡΠΊΡΠΏΠ΅ΡΡΠΎΠ²
ΠΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠ΅Π½ Π°Π²ΠΈΠ°ΠΏΠ΅ΡΠ΅Π²ΠΎΠ·ΠΎΠΊ ΠΏΠ°ΡΡΠ°ΠΆΠΈΡΠΎΠ²
The pricing policy of airlines is developed based on a retrospective analysis of the price dynamics of air transportation and forecasting the market situation of supply and demand. The price dynamics of passenger air transportation has a certain structure and patterns, the identification of which helps to develop a competitive price offer for consumers.The objective of the work is to determine the structure of price dynamics and identify patterns of price fluctuations in passenger air transportation from 2008 to 2022, which is important to consider when developing the pricing policy of airlines and the range of tariffs. Studies of the price dynamics of airline tickets by econometric methods allowed to identify the structure of the time series of prices and develop several models.The study of the price dynamics structure, first, identified and analysed the seasonal component of the dynamics of airline ticket prices. Its calculation was carried out using additive and multiplicative models. The range of seasonal changes was -8,5% to +12,5%. The autocorrelation function of the dynamics of average monthly prices showed that the time series of airline ticket prices contained a trend. In addition to trend and seasonal components, cyclical fluctuations were identified in the price dynamics, the modelling of which was carried out based on regression analysis. Cyclical changes in the dynamics of air ticket prices, identified from 2008 to the present, are not sustainable.Analysed dynamics revealed several medium-term cycles with a duration of 4β6 years. The cyclical dynamics of air transportation prices largely coincides with the general economic medium-term cycles, but there are time lags or lagging growth and decline rates.Thus, the change in prices for civil air transportation has a natural trend-cyclical character shaped under the influence of fundamental macroeconomic factors and new determinants, the effect of which may result in a stronger change but with shorter impact or lag effect. Additive and multiplicative models will help predict average annual prices.Π¦Π΅Π½ΠΎΠ²Π°Ρ ΠΏΠΎΠ»ΠΈΡΠΈΠΊΠ° Π°Π²ΠΈΠ°ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΠΉ ΡΠ°Π·ΡΠ°Π±Π°ΡΡΠ²Π°Π΅ΡΡΡ Π½Π° ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠΈ ΡΠ΅ΡΡΠΎΡΠΏΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΡΠ΅Π½ΠΎΠ²ΠΎΠΉ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ Π°Π²ΠΈΠ°ΠΏΠ΅ΡΠ΅Π²ΠΎΠ·ΠΎΠΊ ΠΈ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΡΠ½ΠΎΡΠ½ΠΎΠΉ ΡΠΈΡΡΠ°ΡΠΈΠΈ ΡΠΏΡΠΎΡΠ° ΠΈ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΈΡ. Π¦Π΅Π½ΠΎΠ²Π°Ρ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠ° ΠΏΠ°ΡΡΠ°ΠΆΠΈΡΡΠΊΠΈΡ
Π°Π²ΠΈΠ°ΠΏΠ΅ΡΠ΅Π²ΠΎΠ·ΠΎΠΊ ΠΈΠΌΠ΅Π΅Ρ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ½Π½ΡΡ ΡΡΡΡΠΊΡΡΡΡ ΠΈ Π·Π°ΠΊΠΎΠ½ΠΎΠΌΠ΅ΡΠ½ΠΎΡΡΠΈ, Π²ΡΡΠ²Π»Π΅Π½ΠΈΠ΅ ΠΊΠΎΡΠΎΡΡΡ
ΠΏΠΎΠΌΠΎΠ³Π°Π΅Ρ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°ΡΡ ΠΊΠΎΠ½ΠΊΡΡΠ΅Π½ΡΠΎΡΠΏΠΎΡΠΎΠ±Π½ΠΎΠ΅ ΡΠ΅Π½ΠΎΠ²ΠΎΠ΅ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΈΠ΅ Π΄Π»Ρ ΠΏΠ°ΡΡΠ°ΠΆΠΈΡΠΎΠ².Π¦Π΅Π»Ρ ΡΠ°Π±ΠΎΡΡ Π·Π°ΠΊΠ»ΡΡΠ°Π΅ΡΡΡ Π² ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ ΡΡΡΡΠΊΡΡΡΡ ΡΠ΅Π½ΠΎΠ²ΠΎΠΉ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ Ρ 2008 Π³ΠΎΠ΄Π° ΠΏΠΎ 2022 Π³ΠΎΠ΄ ΠΈ Π²ΡΡΠ²Π»Π΅Π½ΠΈΠΈ Π·Π°ΠΊΠΎΠ½ΠΎΠΌΠ΅ΡΠ½ΠΎΡΡΠ΅ΠΉ Π΄Π²ΠΈΠΆΠ΅Π½ΠΈΡ ΡΠ΅Π½ Π½Π° ΠΏΠ°ΡΡΠ°ΠΆΠΈΡΡΠΊΠΈΠ΅ Π°Π²ΠΈΠ°ΠΏΠ΅ΡΠ΅Π²ΠΎΠ·ΠΊΠΈ, ΡΡΠΎ Π²Π°ΠΆΠ½ΠΎ ΡΡΠΈΡΡΠ²Π°ΡΡ ΠΏΡΠΈ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠΈ ΡΠ΅Π½ΠΎΠ²ΠΎΠ³ΠΎ ΠΊΡΡΡΠ° ΠΈ Π΄ΠΈΠ°ΠΏΠ°Π·ΠΎΠ½Π° ΡΠ΅Π½ ΡΠ°ΡΠΈΡΠΎΠ². ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠ΅Π½ΠΎΠ²ΠΎΠΉ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ Π°Π²ΠΈΠ°Π±ΠΈΠ»Π΅ΡΠΎΠ² ΡΠΊΠΎΠ½ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ ΠΌΠ΅ΡΠΎΠ΄Π°ΠΌΠΈ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΈ Π²ΡΡΠ²ΠΈΡΡ ΡΡΡΡΠΊΡΡΡΡ Π²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠ³ΠΎ ΡΡΠ΄Π° ΡΠ΅Π½ ΠΈ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°ΡΡ ΡΡΠ΄ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ.ΠΡΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ ΡΡΡΡΠΊΡΡΡΡ ΡΠ΅Π½ΠΎΠ²ΠΎΠΉ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ Π² ΠΏΠ΅ΡΠ²ΡΡ ΠΎΡΠ΅ΡΠ΅Π΄Ρ Π±ΡΠ»Π° Π²ΡΠ΄Π΅Π»Π΅Π½Π° ΠΈ ΠΏΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Π° ΡΠ΅Π·ΠΎΠ½Π½Π°Ρ ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠ°, ΡΠ°ΡΡΡΡ ΠΊΠΎΡΠΎΡΠΎΠΉ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΡΡ ΠΏΠΎ Π°Π΄Π΄ΠΈΡΠΈΠ²Π½ΡΠΌ ΠΈ ΠΌΡΠ»ΡΡΠΈΠΏΠ»ΠΈΠΊΠ°ΡΠΈΠ²Π½ΡΠΌ ΠΌΠΎΠ΄Π΅Π»ΡΠΌ. ΠΠΈΠ°ΠΏΠ°Π·ΠΎΠ½ ΡΠ΅Π·ΠΎΠ½Π½ΡΡ
ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ ΡΠΎΡΡΠ°Π²Π»ΡΠ΅Ρ -8,5 % Π΄ΠΎ +12,5 %. ΠΠ²ΡΠΎΠΊΠΎΡΡΠ΅Π»ΡΡΠΈΠΎΠ½Π½Π°Ρ ΡΡΠ½ΠΊΡΠΈΡ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ ΡΡΠ΅Π΄Π½Π΅ΠΌΠ΅ΡΡΡΠ½ΡΡ
ΡΠ΅Π½ ΠΏΠΎΠΊΠ°Π·Π°Π»Π°, ΡΡΠΎ Π²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ ΡΡΠ΄ ΡΠ΅Π½ Π½Π° Π°Π²ΠΈΠ°Π±ΠΈΠ»Π΅ΡΡ ΡΠΎΠ΄Π΅ΡΠΆΠΈΡ ΡΡΠ΅Π½Π΄. ΠΡΠΎΠΌΠ΅ ΡΡΠ΅Π½Π΄ΠΎΠ²ΡΡ
ΠΈ ΡΠ΅Π·ΠΎΠ½Π½ΡΡ
ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½Ρ Π² Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠ΅ ΡΠ΅Π½ Π²ΡΠ΄Π΅Π»Π΅Π½Ρ ΡΠΈΠΊΠ»ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΊΠΎΠ»Π΅Π±Π°Π½ΠΈΡ, ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΊΠΎΡΠΎΡΡΡ
ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΎΡΡ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΠ΅Π³ΡΠ΅ΡΡΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π°. Π¦ΠΈΠΊΠ»ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ ΡΠ΅Π½ Π½Π° Π°Π²ΠΈΠ°Π±ΠΈΠ»Π΅ΡΡ, Π²ΡΡΠ²Π»Π΅Π½Π½ΡΡ
Ρ 2008 Π³ΠΎΠ΄Π° ΠΏΠΎ Π½Π°ΡΡΠΎΡΡΠ΅Π΅ Π²ΡΠ΅ΠΌΡ, Π½Π΅ ΠΈΠΌΠ΅ΡΡ ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎΠ³ΠΎ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠ°.Π Π°Π½Π°Π»ΠΈΠ·ΠΈΡΡΠ΅ΠΌΠΎΠΉ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠ΅ Π²ΡΠ΄Π΅Π»Π΅Π½ΠΎ Π½Π΅ΡΠΊΠΎΠ»ΡΠΊΠΎ ΡΡΠ΅Π΄Π½Π΅ΡΡΠΎΡΠ½ΡΡ
ΡΠΈΠΊΠ»ΠΎΠ² ΠΏΡΠΎΠ΄ΠΎΠ»ΠΆΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΡΡ 4β6 Π»Π΅Ρ. Π¦ΠΈΠΊΠ»ΠΈΡΠ½ΠΎΡΡΡ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ ΡΠ΅Π½ Π½Π° Π°Π²ΠΈΠ°ΠΏΠ΅ΡΠ΅Π²ΠΎΠ·ΠΊΠΈ Π²ΠΎ ΠΌΠ½ΠΎΠ³ΠΎΠΌ ΡΠΎΠ²ΠΏΠ°Π΄Π°Π΅Ρ Ρ ΠΎΠ±ΡΠ΅ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ ΡΡΠ΅Π΄Π½Π΅ΡΡΠΎΡΠ½ΡΠΌΠΈ ΡΠΈΠΊΠ»Π°ΠΌΠΈ, Π½ΠΎ ΠΏΡΠΈΡΡΡΡΡΠ²ΡΡΡ Π²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠ΅ Π»Π°Π³ΠΈ Π·Π°ΠΏΠ°Π·Π΄ΡΠ²Π°Π½ΠΈΡ ΠΈΠ»ΠΈ ΠΎΡΡΡΠ°Π²Π°Π½ΠΈΠ΅ ΡΠ΅ΠΌΠΏΠΎΠ² ΡΠΎΡΡΠ° ΠΈΠ»ΠΈ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΡ.Π’Π°ΠΊΠΈΠΌ ΠΎΠ±ΡΠ°Π·ΠΎΠΌ, ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΡΠ΅Π½ Π½Π° Π³ΡΠ°ΠΆΠ΄Π°Π½ΡΠΊΠΈΠ΅ Π°Π²ΠΈΠ°ΠΏΠ΅ΡΠ΅Π²ΠΎΠ·ΠΊΠΈ ΠΈΠΌΠ΅Π΅Ρ Π·Π°ΠΊΠΎΠ½ΠΎΠΌΠ΅ΡΠ½ΡΠΉ ΡΡΠ΅Π½Π΄ΡΠΈΠΊΠ»ΠΈΡΠ΅ΡΠΊΠΈΠΉ Ρ
Π°ΡΠ°ΠΊΡΠ΅Ρ, ΡΠΎΡΠΌΠΈΡΡΡΡΠΈΠΉΡΡ ΠΏΠΎΠ΄ Π΄Π΅ΠΉΡΡΠ²ΠΈΠ΅ΠΌ ΡΡΠ½Π΄Π°ΠΌΠ΅Π½ΡΠ°Π»ΡΠ½ΡΡ
ΠΌΠ°ΠΊΡΠΎΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ² ΠΈ Π½ΠΎΠ²ΡΡ
Π΄Π΅ΡΠ΅ΡΠΌΠΈΠ½Π°Π½Ρ, Π΄Π΅ΠΉΡΡΠ²ΠΈΠ΅ ΠΊΠΎΡΠΎΡΡΡ
ΠΌΠΎΠΆΠ΅Ρ Π²ΡΠ·ΡΠ²Π°ΡΡ Π±ΠΎΠ»Π΅Π΅ ΡΠΈΠ»ΡΠ½ΠΎΠ΅ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠ΅, Π½ΠΎ Ρ ΠΊΡΠ°ΡΠΊΠΈΠΌ ΠΏΠ΅ΡΠΈΠΎΠ΄ΠΎΠΌ Π²ΠΎΠ·Π΄Π΅ΠΉΡΡΠ²ΠΈΡ, ΠΈΠ»ΠΈ Π»Π°Π³ΠΎΠ²ΠΎΠ΅ Π²Π»ΠΈΡΠ½ΠΈΠ΅. ΠΠ΄Π΄ΠΈΡΠΈΠ²Π½ΡΠ΅ ΠΈ ΠΌΡΠ»ΡΡΠΈΠΏΠ»ΠΈΠΊΠ°ΡΠΈΠ²Π½ΡΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΏΠΎΠΌΠΎΠ³ΡΡ ΡΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°ΡΡ ΡΡΠ΅Π΄Π½Π΅Π³ΠΎΠ΄ΠΎΠ²ΡΠ΅ ΡΠ΅Π½Ρ Π°Π²ΠΈΠ°ΡΠ°ΡΠΈΡΠΎΠ²
First order transition and phase separation in pyrochlores with colossal-magnetoresistance
TlMnO pyrochlores present colossal magnetoresistance (CMR)
around the long range ferromagnetic ordering temperature (T). The
character of this magnetic phase transition has been determined to be first
order, by purely magnetic methods, in contrast to the second order character
previously reported by Zhao et al. (Phys. Rev. Lett. 83, 219 (1999)). The
highest CMR effect, as in TlCdMnO, corresponds to a
stronger first order character. This character implies a second type of
magnetic interaction, besides the direct superexchange between the Mn
ions, as well as a phase coexistence. A model is proposed, with a complete
Hamiltonian (including superexchange and an indirect interaction), which
reproduce the observed phenomenology.Comment: 6 pages. Figures include
Quality of life of school and university students with acne
Acne may have severe negative impact on different aspects of patient health-related quality of life (HRQoL). Prevalence of acne in university and school students is high, and the HRQoL of students with acne from different countries was studied. There is a lack of studies on direct comparison of HRQoL impairment of university and school students with acne. The Cardiff Acne Disability Index (CADI) was used to assess the HRQOL in university and school students with self-assessed acne. The CADI results from 159 university and 99 school students with self-reported acne were obtained. Mean age of university and school students was 20.99Β±1.47 (mean Β± Standard Deviation) and 14.10Β±0.51 years, respectively. Reported impact on QoL of university students was significantly higher (3.33Β±2.26 and 2.76Β±2.42, P<0.05). Total CADI scores negatively correlated with the age of university students (r=-0.16; P<0.05). Analysis of gender differences of university students showed that negative correlation of HRQoL with age was present in women (r=-0.22; P<0.05) but absent in male students (r=0.05; P=0.77). Female university students reported more severe impact of acne on their life (2.55Β±2.31 in male and 3.59Β±2.20 in female students, P<0.01). Our results showed that university students experience higher impact of acne on their life than school students. The highest is the impact on young female university students. We recommend paying more attention to the psychological aspects of young female students with acne during consultations.Β </p
Quality of life of school and university students with acne
Acne may have severe negative impact on different aspects of patient health-related quality of life (HRQoL). Prevalence of acne in university and school students is high, and the HRQoL of students with acne from different countries was studied. There is a lack of studies on direct comparison of HRQoL impairment of university and school students with acne. The Cardiff Acne Disability Index (CADI) was used to assess the HRQOL in university and school students with self-assessed acne. The CADI results from 159 university and 99 school students with self-reported acne were obtained. Mean age of university and school students was 20.99Β±1.47 (mean Β± Standard Deviation) and 14.10Β±0.51 years, respectively. Reported impact on QoL of university students was significantly higher (3.33Β±2.26 and 2.76Β±2.42, P<0.05). Total CADI scores negatively correlated with the age of university students (r=-0.16; P<0.05). Analysis of gender differences of university students showed that negative correlation of HRQoL with age was present in women (r=-0.22; P<0.05) but absent in male students (r=0.05; P=0.77). Female university students reported more severe impact of acne on their life (2.55Β±2.31 in male and 3.59Β±2.20 in female students, P<0.01). Our results showed that university students experience higher impact of acne on their life than school students. The highest is the impact on young female university students. We recommend paying more attention to the psychological aspects of young female students with acne during consultations.Β </p
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