350 research outputs found

    Mechanism of phase transitions and the electronic density of states in (La,Sm)FeAsO1βˆ’x_{1-x}Fx_x from ab initio calculations

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    The structure and electronic density of states in layered LnFeAsO1βˆ’x_{1-x}Fx_x (Ln=La,Sm; xx=0.0, 0.125, 0.25) are investigated using density functional theory. For the xx=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 ∼\sim140--160 K. We propose a mechanism for these transitions and suggest that these phenomena are generic to all compounds containing FeAs layers. For x>x>0.0 we demonstrate that transition temperatures to the superconducting state and their dependence on xx 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

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    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

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    Π’ Π΄ΠΎΠΊΠ»Π°Π΄Π΅ прСдставлСны Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ социологичСского исслСдования соврСмСнной сСльской ΠΌΠΎΠ»ΠΎΠ΄Π΅ΠΆΠΈ ΠšΡ€Π°ΡΠ½ΠΎΠ΄Π°Ρ€ΡΠΊΠΎΠ³ΠΎ ΠΏΡ€ΠΈ ΠΏΠΎΠΌΠΎΡ‰ΠΈ Π³Π»ΡƒΠ±ΠΈΠ½Π½ΠΎΠ³ΠΎ ΠΈΠ½Ρ‚Π΅Ρ€Π²ΡŒΡŽ. ΠΠ½Π°Π»ΠΈΠ·ΠΈΡ€ΡƒΡŽΡ‚ΡΡ особСнности ΡΠΎΡ†ΠΈΠ°Π»ΡŒΠ½Ρ‹Ρ… ΠΏΠ΅Ρ€Π΅ΠΌΠ΅Ρ‰Π΅Π½ΠΈΠΉ ΠΌΠΎΠ»ΠΎΠ΄Ρ‹Ρ… ΡΠ΅Π»ΡŒΡ‡Π°Π½ Π² условиях ΡΠΎΡ†ΠΈΠ°Π»ΡŒΠ½ΠΎ-экономичСской стагнации сСльской мСстности.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

    ΠœΠΎΠ΄Π΅Π»ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ авиапассаТирских ΠΏΠ΅Ρ€Π΅Π²ΠΎΠ·ΠΎΠΊ России

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    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.ΠŸΡ€ΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ экономико-матСматичСских ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² прогнозирования Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² Π΄Π΅ΡΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ ΠΎΡ€Π³Π°Π½ΠΈΠ·Π°Ρ†ΠΈΠΉ граТданской Π°Π²ΠΈΠ°Ρ†ΠΈΠΈ ΠΈ, Π² частности, ΠΎΠ±ΡŠΡ‘ΠΌΠΎΠ² авиапассаТирских ΠΏΠ΅Ρ€Π΅Π²ΠΎΠ·ΠΎΠΊ Π² силу ваТности ΠΎΠΏΠ΅Ρ€Π°Ρ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ планирования процСссов авиатранспорта, Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚ΠΊΠΈ стратСгичСских Π½Π°ΠΏΡ€Π°Π²Π»Π΅Π½ΠΈΠΉ Π΅Π³ΠΎ развития, тСхнологичСского ΠΈ тСхничСского обновлСния авиапрСдприятий достаточно Π°ΠΊΡ‚ΡƒΠ°Π»ΡŒΠ½ΠΎ.ЦСль исслСдования состоит Π² ΠΏΠ»Π°Π½ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠΈ Π°Π²ΠΈΠ°ΠΏΠΎΡ‚ΠΎΠΊΠ° пассаТиров ΠΏΠΎ рСгрСссионной ΠΌΠΎΠ΄Π΅Π»ΠΈ с ΡƒΡ‡Ρ‘Ρ‚ΠΎΠΌ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² ΠΌΠ½ΠΎΠ³ΠΎΡ„Π°ΠΊΡ‚ΠΎΡ€Π½ΠΎΠ³ΠΎ ΠΎΡ‚Π±ΠΎΡ€Π° Π΄Π΅Ρ‚Π΅Ρ€ΠΌΠΈΠ½Π°Π½Ρ‚, срСди ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… Π²Ρ‹Π΄Π΅Π»ΡΡŽΡ‚ Ρ„ΡƒΠ½Π΄Π°ΠΌΠ΅Π½Ρ‚Π°Π»ΡŒΠ½Ρ‹Π΅ ΠΌΠ°ΠΊΡ€ΠΎΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»ΠΈ, Π° Ρ‚Π°ΠΊΠΆΠ΅ Π·Π½Π°Ρ‡ΠΈΠΌΡ‹Π΅ ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»ΠΈ Π°Π²ΠΈΠ°Ρ€Ρ‹Π½ΠΊΠ°.ИсслСдованиС пассаТирских Π°Π²ΠΈΠ°ΠΏΠ΅Ρ€Π΅Π²ΠΎΠ·ΠΎΠΊ ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΎΡΡŒ с использованиСм ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² систСмного Π°Π½Π°Π»ΠΈΠ·Π°, ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² матСматичСской статистики ΠΈ экономСтрики. ΠŸΡ€ΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠΈ процСсса пассаТирских ΠΏΠ΅Ρ€Π΅Π²ΠΎΠ·ΠΎΠΊ Π²Ρ‹Π΄Π΅Π»Π΅Π½Ρ‹ основныС Π΄Π΅Ρ‚Π΅Ρ€ΠΌΠΈΠ½Π°Π½Ρ‚Ρ‹, ΠΏΠΎΠ»ΠΎΠΆΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎ ΠΈΠ»ΠΈ ΠΎΡ‚Ρ€ΠΈΡ†Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎ Π²Π»ΠΈΡΡŽΡ‰ΠΈΠ΅ Π½Π° Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΡƒ авиапассаТиропотока. ΠœΠ½ΠΎΠΆΠ΅ΡΡ‚Π²Π΅Π½Π½Π°Ρ рСгрСссия исслСдования процСссов связанности ΠΈ синхронности ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ развития пассаТиропотока ΠΈ ΠΎΡ‚ΠΎΠ±Ρ€Π°Π½Π½Ρ‹Ρ… ΠΌΠ°ΠΊΡ€ΠΎΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»Π΅ΠΉ Π² ΠΎΠ±ΠΎΠ±Ρ‰Ρ‘Π½Π½ΠΎΠΌ Π²ΠΈΠ΄Π΅ являСтся суммой Π²Π΅ΠΊΡ‚ΠΎΡ€ΠΎΠ² Π²Π»ΠΈΡΡŽΡ‰ΠΈΡ… ΠΏΠ΅Ρ€Π΅ΠΌΠ΅Π½Π½Ρ‹Ρ… с ΠΏΠΎΠΏΡ€Π°Π²ΠΊΠΎΠΉ Π½Π° рассчитанныС коэффициСнты.Π’ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Π΅ Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚Π°Π½Ρ‹ ΡˆΠ΅ΡΡ‚ΠΈ-, Ρ‡Π΅Ρ‚Ρ‹Ρ€Ρ‘Ρ…- ΠΈ Ρ‚Ρ€Ρ‘Ρ…- Ρ„Π°ΠΊΡ‚ΠΎΡ€Π½Ρ‹Π΅ рСгрСссионныС ΠΌΠΎΠ΄Π΅Π»ΠΈ, ΠΈΠ· ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… послСдняя ΠΎΠ±Π»Π°Π΄Π°Π΅Ρ‚ наибольшСй Π΄ΠΎΡΡ‚ΠΎΠ²Π΅Ρ€Π½ΠΎΡΡ‚ΡŒΡŽ с достаточно Π±Π»ΠΈΠ·ΠΊΠΈΠΌΠΈ ΠΊ фактичСским значСниям Π΄Π°Π½Π½Ρ‹ΠΌΠΈ. ΠŸΡ€ΠΈ ΠΏΡ€ΠΎΠ³Π½ΠΎΠ·ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠΈ пассаТиропотока ΠΏΠΎ рСгрСссионной ΠΌΠΎΠ΄Π΅Π»ΠΈ Π½Π΅ΠΎΠ±Ρ…ΠΎΠ΄ΠΈΠΌΠΎ ΡƒΡ‡ΠΈΡ‚Ρ‹Π²Π°Ρ‚ΡŒ Π½Π΅ Ρ‚ΠΎΠ»ΡŒΠΊΠΎ тСорСтичСскиС аспСкты, Π΄Π°Π½Π½Ρ‹Π΅ ΠΎΡ„ΠΈΡ†ΠΈΠ°Π»ΡŒΠ½Ρ‹Ρ… ΠΏΡ€ΠΎΠ³Π½ΠΎΠ·ΠΎΠ² ΠΌΠ°ΠΊΡ€ΠΎΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»Π΅ΠΉ, Π½ΠΎ ΠΈ ΠΌΠ½Π΅Π½ΠΈΠ΅ экспСртов

    ΠœΠΎΠ΄Π΅Π»ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ Ρ†Π΅Π½ Π°Π²ΠΈΠ°ΠΏΠ΅Ρ€Π΅Π²ΠΎΠ·ΠΎΠΊ пассаТиров

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    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 4–6 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.ЦСновая ΠΏΠΎΠ»ΠΈΡ‚ΠΈΠΊΠ° Π°Π²ΠΈΠ°ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΠΉ разрабатываСтся Π½Π° основании рСтроспСктивного Π°Π½Π°Π»ΠΈΠ·Π° Ρ†Π΅Π½ΠΎΠ²ΠΎΠΉ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ Π°Π²ΠΈΠ°ΠΏΠ΅Ρ€Π΅Π²ΠΎΠ·ΠΎΠΊ ΠΈ прогнозирования Ρ€Ρ‹Π½ΠΎΡ‡Π½ΠΎΠΉ ситуации спроса ΠΈ прСдлоТСния. ЦСновая Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠ° пассаТирских Π°Π²ΠΈΠ°ΠΏΠ΅Ρ€Π΅Π²ΠΎΠ·ΠΎΠΊ ΠΈΠΌΠ΅Π΅Ρ‚ ΠΎΠΏΡ€Π΅Π΄Π΅Π»Ρ‘Π½Π½ΡƒΡŽ структуру ΠΈ закономСрности, выявлСниС ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… ΠΏΠΎΠΌΠΎΠ³Π°Π΅Ρ‚ Ρ„ΠΎΡ€ΠΌΠΈΡ€ΠΎΠ²Π°Ρ‚ΡŒ конкурСнтоспособноС Ρ†Π΅Π½ΠΎΠ²ΠΎΠ΅ ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΈΠ΅ для пассаТиров.ЦСль Ρ€Π°Π±ΠΎΡ‚Ρ‹ Π·Π°ΠΊΠ»ΡŽΡ‡Π°Π΅Ρ‚ΡΡ Π² исслСдовании структуры Ρ†Π΅Π½ΠΎΠ²ΠΎΠΉ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ с 2008 Π³ΠΎΠ΄Π° ΠΏΠΎ 2022 Π³ΠΎΠ΄ ΠΈ выявлСнии закономСрностСй двиТСния Ρ†Π΅Π½ Π½Π° пассаТирскиС Π°Π²ΠΈΠ°ΠΏΠ΅Ρ€Π΅Π²ΠΎΠ·ΠΊΠΈ, Ρ‡Ρ‚ΠΎ Π²Π°ΠΆΠ½ΠΎ ΡƒΡ‡ΠΈΡ‚Ρ‹Π²Π°Ρ‚ΡŒ ΠΏΡ€ΠΈ ΠΎΠΏΡ€Π΅Π΄Π΅Π»Π΅Π½ΠΈΠΈ Ρ†Π΅Π½ΠΎΠ²ΠΎΠ³ΠΎ курса ΠΈ Π΄ΠΈΠ°ΠΏΠ°Π·ΠΎΠ½Π° Ρ†Π΅Π½ Ρ‚Π°Ρ€ΠΈΡ„ΠΎΠ². ИсслСдования Ρ†Π΅Π½ΠΎΠ²ΠΎΠΉ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ Π°Π²ΠΈΠ°Π±ΠΈΠ»Π΅Ρ‚ΠΎΠ² экономСтричСскими ΠΌΠ΅Ρ‚ΠΎΠ΄Π°ΠΌΠΈ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΈ Π²Ρ‹ΡΠ²ΠΈΡ‚ΡŒ структуру Π²Ρ€Π΅ΠΌΠ΅Π½Π½ΠΎΠ³ΠΎ ряда Ρ†Π΅Π½ ΠΈ Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚Π°Ρ‚ΡŒ ряд ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ.ΠŸΡ€ΠΈ исслСдовании структуры Ρ†Π΅Π½ΠΎΠ²ΠΎΠΉ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ Π² ΠΏΠ΅Ρ€Π²ΡƒΡŽ ΠΎΡ‡Π΅Ρ€Π΅Π΄ΡŒ Π±Ρ‹Π»Π° Π²Ρ‹Π΄Π΅Π»Π΅Π½Π° ΠΈ ΠΏΡ€ΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡ€ΠΎΠ²Π°Π½Π° сСзонная ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½Ρ‚Π°, расчёт ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠΉ проводился ΠΏΠΎ Π°Π΄Π΄ΠΈΡ‚ΠΈΠ²Π½Ρ‹ΠΌ ΠΈ ΠΌΡƒΠ»ΡŒΡ‚ΠΈΠΏΠ»ΠΈΠΊΠ°Ρ‚ΠΈΠ²Π½Ρ‹ΠΌ модСлям. Π”ΠΈΠ°ΠΏΠ°Π·ΠΎΠ½ сСзонных ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ составляСт -8,5 % Π΄ΠΎ +12,5 %. АвтокоррСляционная функция Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ срСднСмСсячных Ρ†Π΅Π½ ΠΏΠΎΠΊΠ°Π·Π°Π»Π°, Ρ‡Ρ‚ΠΎ Π²Ρ€Π΅ΠΌΠ΅Π½Π½ΠΎΠΉ ряд Ρ†Π΅Π½ Π½Π° Π°Π²ΠΈΠ°Π±ΠΈΠ»Π΅Ρ‚Ρ‹ содСрТит Ρ‚Ρ€Π΅Π½Π΄. ΠšΡ€ΠΎΠΌΠ΅ Ρ‚Ρ€Π΅Π½Π΄ΠΎΠ²Ρ‹Ρ… ΠΈ сСзонных ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½Ρ‚ Π² Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠ΅ Ρ†Π΅Π½ Π²Ρ‹Π΄Π΅Π»Π΅Π½Ρ‹ цикличСскиС колСбания, ΠΌΠΎΠ΄Π΅Π»ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΎΡΡŒ Π½Π° основС рСгрСссионного Π°Π½Π°Π»ΠΈΠ·Π°. ЦикличСскиС измСнСния Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ Ρ†Π΅Π½ Π½Π° Π°Π²ΠΈΠ°Π±ΠΈΠ»Π΅Ρ‚Ρ‹, выявлСнных с 2008 Π³ΠΎΠ΄Π° ΠΏΠΎ настоящСС врСмя, Π½Π΅ ΠΈΠΌΠ΅ΡŽΡ‚ устойчивого Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€Π°.Π’ Π°Π½Π°Π»ΠΈΠ·ΠΈΡ€ΡƒΠ΅ΠΌΠΎΠΉ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠ΅ Π²Ρ‹Π΄Π΅Π»Π΅Π½ΠΎ нСсколько срСднСсрочных Ρ†ΠΈΠΊΠ»ΠΎΠ² ΠΏΡ€ΠΎΠ΄ΠΎΠ»ΠΆΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΡŒΡŽ 4–6 Π»Π΅Ρ‚. Π¦ΠΈΠΊΠ»ΠΈΡ‡Π½ΠΎΡΡ‚ΡŒ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ Ρ†Π΅Π½ Π½Π° Π°Π²ΠΈΠ°ΠΏΠ΅Ρ€Π΅Π²ΠΎΠ·ΠΊΠΈ Π²ΠΎ ΠΌΠ½ΠΎΠ³ΠΎΠΌ совпадаСт с общСэкономичСскими срСднСсрочными Ρ†ΠΈΠΊΠ»Π°ΠΌΠΈ, Π½ΠΎ ΠΏΡ€ΠΈΡΡƒΡ‚ΡΡ‚Π²ΡƒΡŽΡ‚ Π²Ρ€Π΅ΠΌΠ΅Π½Π½Ρ‹Π΅ Π»Π°Π³ΠΈ запаздывания ΠΈΠ»ΠΈ отставаниС Ρ‚Π΅ΠΌΠΏΠΎΠ² роста ΠΈΠ»ΠΈ сниТСния.Π’Π°ΠΊΠΈΠΌ ΠΎΠ±Ρ€Π°Π·ΠΎΠΌ, ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ Ρ†Π΅Π½ Π½Π° граТданскиС Π°Π²ΠΈΠ°ΠΏΠ΅Ρ€Π΅Π²ΠΎΠ·ΠΊΠΈ ΠΈΠΌΠ΅Π΅Ρ‚ Π·Π°ΠΊΠΎΠ½ΠΎΠΌΠ΅Ρ€Π½Ρ‹ΠΉ трСндцикличСский Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€, Ρ„ΠΎΡ€ΠΌΠΈΡ€ΡƒΡŽΡ‰ΠΈΠΉΡΡ ΠΏΠΎΠ΄ дСйствиСм Ρ„ΡƒΠ½Π΄Π°ΠΌΠ΅Π½Ρ‚Π°Π»ΡŒΠ½Ρ‹Ρ… макроэкономичСских Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠ² ΠΈ Π½ΠΎΠ²Ρ‹Ρ… Π΄Π΅Ρ‚Π΅Ρ€ΠΌΠΈΠ½Π°Π½Ρ‚, дСйствиС ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… ΠΌΠΎΠΆΠ΅Ρ‚ Π²Ρ‹Π·Ρ‹Π²Π°Ρ‚ΡŒ Π±ΠΎΠ»Π΅Π΅ сильноС ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠ΅, Π½ΠΎ с ΠΊΡ€Π°Ρ‚ΠΊΠΈΠΌ ΠΏΠ΅Ρ€ΠΈΠΎΠ΄ΠΎΠΌ воздСйствия, ΠΈΠ»ΠΈ Π»Π°Π³ΠΎΠ²ΠΎΠ΅ влияниС. АддитивныС ΠΈ ΠΌΡƒΠ»ΡŒΡ‚ΠΈΠΏΠ»ΠΈΠΊΠ°Ρ‚ΠΈΠ²Π½Ρ‹Π΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΏΠΎΠΌΠΎΠ³ΡƒΡ‚ ΡΠΏΡ€ΠΎΠ³Π½ΠΎΠ·ΠΈΡ€ΠΎΠ²Π°Ρ‚ΡŒ срСднСгодовыС Ρ†Π΅Π½Ρ‹ Π°Π²ΠΈΠ°Ρ‚Π°Ρ€ΠΈΡ„ΠΎΠ²

    First order transition and phase separation in pyrochlores with colossal-magnetoresistance

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    Tl2_{2}Mn2_{2}O7_{7} pyrochlores present colossal magnetoresistance (CMR) around the long range ferromagnetic ordering temperature (TC_{C}). 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 Tl1.8_{1.8}Cd0.2_{0.2}Mn2_{2}O7_{7}, corresponds to a stronger first order character. This character implies a second type of magnetic interaction, besides the direct superexchange between the Mn4+^{4+} 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

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    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&lt;0.05). Total CADI scores negatively correlated with the age of university students (r=-0.16; P&lt;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&lt;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&lt;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

    Get PDF
    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&lt;0.05). Total CADI scores negatively correlated with the age of university students (r=-0.16; P&lt;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&lt;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&lt;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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