27 research outputs found
ΠΠ± ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠΈ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ° ΠΠΆΠΈΠ½ΠΈ Π² ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΎ-ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡΡ
Frequent cases of incorrect use of the Gini index in economic and statistical studies have forced the authors to express their opinion. This refers to those calculations that consider average and relative (per capita) rates rather than divide total rates into groups. A right choice and a correct use of statistical tools play a crucial role in statistical research for an analysis of valid and reliable statistical data. Even the simplest and most widely known method of statistical data processing requires competent use depending on the original data. The data provided in the article demonstrates possibilities and conditions of the Gini index use, which is popular among researchers. The concentration index (often referred to as the Gini index in the literature) was originally proposed by the Italian statistician K. Gini to assess the degree of uneven distribution ofwealth (income) within a population. The authors proceed from the fact that the concentration index can be used for characterizing inequalities of many other indicators. The article contains description of key provisions of the statistical theory of measuring such properties units collectively as Β«concentrationΒ» and well-known formulas for calculating the Gini index. The authors emphasize the important condition of this indicator application: raw data must consider the possibility of distribution allocated to the group together, i. e. it must be necessarily presented as group totals, not as indicators per capita or average values.ΠΠ±ΡΡΠΎΡΡΠ΅Π»ΡΡΡΠ²ΠΎ, ΠΏΠΎΠ±ΡΠ΄ΠΈΠ²ΡΠ΅Π΅ Π°Π²ΡΠΎΡΠΎΠ² ΡΡΠ°ΡΡΠΈ Π²ΡΡΠΊΠ°Π·Π°ΡΡ ΡΠ²ΠΎΠ΅ ΠΌΠ½Π΅Π½ΠΈΠ΅, - ΡΡΠ°ΡΡΠΈΠ²ΡΠΈΠ΅ΡΡ ΡΠ»ΡΡΠ°ΠΈ Π½Π΅ΠΊΠΎΡΡΠ΅ΠΊΡΠ½ΠΎΠ³ΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ° ΠΠΆΠΈΠ½ΠΈ Π² ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΎ-ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡΡ
, ΠΊΠΎΠ³Π΄Π° Π΄Π°Π½Π½ΡΠΉ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½Ρ ΡΠ°ΡΡΡΠΈΡΡΠ²Π°Π΅ΡΡΡ Π½Π΅ ΠΏΡΠΈΠΌΠ΅Π½ΠΈΡΠ΅Π»ΡΠ½ΠΎ ΠΊ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΡΡΠΌΠΌΠ°ΡΠ½ΡΡ
(ΠΎΠ±ΡΠ΅ΠΌΠ½ΡΡ
) ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΠΏΠΎ Π³ΡΡΠΏΠΏΠ°ΠΌ, Π° Π΄Π»Ρ ΡΡΠ΅Π΄Π½ΠΈΡ
ΠΈ ΠΎΡΠ½ΠΎΡΠΈΡΠ΅Π»ΡΠ½ΡΡ
(ΡΠ°ΡΡΡΠΈΡΠ°Π½Π½ΡΡ
Π½Π° Π΄ΡΡΡ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ) ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ. Π ΠΌΠ΅ΠΆΠ΄Ρ ΡΠ΅ΠΌ ΠΈΡΠΊΠ»ΡΡΠΈΡΠ΅Π»ΡΠ½ΡΡ ΡΠΎΠ»Ρ Π² ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΌ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ ΠΈΠ³ΡΠ°Π΅Ρ ΠΏΡΠ°Π²ΠΈΠ»ΡΠ½ΡΠΉ Π²ΡΠ±ΠΎΡ ΠΈ ΠΊΠΎΡΡΠ΅ΠΊΡΠ½ΠΎΠ΅ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΡΠΈΡ Π΄Π»Ρ Π°Π½Π°Π»ΠΈΠ·Π° Π² ΠΏΡΠΈΠ½ΡΠΈΠΏΠ΅ Π΄ΠΎΡΡΠΎΠ²Π΅ΡΠ½ΡΡ
ΠΈ Π½Π°Π΄Π΅ΠΆΠ½ΡΡ
Π΄Π°Π½Π½ΡΡ
. ΠΠ°ΠΆΠ΅ ΡΠ°ΠΌΡΠΉ ΠΏΡΠΎΡΡΠΎΠΉ ΠΈ ΡΠΈΡΠΎΠΊΠΎ ΠΈΠ·Π²Π΅ΡΡΠ½ΡΠΉ ΠΌΠ΅ΡΠΎΠ΄ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
Π΄Π°Π½Π½ΡΡ
ΡΡΠ΅Π±ΡΠ΅Ρ Π³ΡΠ°ΠΌΠΎΡΠ½ΠΎΠ³ΠΎ Π΅Π³ΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ Π² Π·Π°Π²ΠΈΡΠΈΠΌΠΎΡΡΠΈ ΠΎΡ Π½Π°Π»ΠΈΡΠΈΡ ΡΠΎΠΉ ΠΈΠ»ΠΈ ΠΈΠ½ΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ. Π ΡΡΠ°ΡΡΠ΅ Π½Π° ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΡΡ
ΠΏΡΠΈΠΌΠ΅ΡΠ°Ρ
ΠΏΡΠΎΠ΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΠΎΠ²Π°Π½Ρ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ ΠΈ ΡΡΠ»ΠΎΠ²ΠΈΡ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΠΏΠΎΠΏΡΠ»ΡΡΠ½ΠΎΠ³ΠΎ ΡΡΠ΅Π΄ΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»Π΅ΠΉ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ° ΠΠΆΠΈΠ½ΠΈ. ΠΠ²ΡΠΎΡΡ ΠΈΡΡ
ΠΎΠ΄ΡΡ ΠΈΠ· ΡΠΎΠ³ΠΎ ΡΠ°ΠΊΡΠ°, ΡΡΠΎ ΠΈΠ½Π΄Π΅ΠΊΡ ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΠΈ, ΡΠ°ΡΠ΅ ΠΈΠΌΠ΅Π½ΡΠ΅ΠΌΡΠΉ Π² Π»ΠΈΡΠ΅ΡΠ°ΡΡΡΠ΅ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠΎΠΌ ΠΠΆΠΈΠ½ΠΈ ΠΈ ΠΏΠ΅ΡΠ²ΠΎΠ½Π°ΡΠ°Π»ΡΠ½ΠΎ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΡΠΉ ΠΈΡΠ°Π»ΡΡΠ½ΡΠΊΠΈΠΌ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΎΠΌ Π. ΠΠΆΠΈΠ½ΠΈ Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ ΡΡΠ΅ΠΏΠ΅Π½ΠΈ Π½Π΅ΡΠ°Π²Π½ΠΎΠΌΠ΅ΡΠ½ΠΎΡΡΠΈ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ Π±ΠΎΠ³Π°ΡΡΡΠ²Π° (Π΄ΠΎΡ
ΠΎΠ΄ΠΎΠ²) Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ, ΠΌΠΎΠΆΠ΅Ρ Π±ΡΡΡ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ Π΄Π»Ρ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠΈ Π½Π΅ΡΠ°Π²Π½ΠΎΠΌΠ΅ΡΠ½ΠΎΡΡΠΈ, Π½ΠΎ ΡΠΆΠ΅ ΠΏΡΠΈΠΌΠ΅Π½ΠΈΡΠ΅Π»ΡΠ½ΠΎ ΠΊ Π΄ΡΡΠ³ΠΈΠΌ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΡΠΌ. Π‘ΡΠ°ΡΡΡ ΡΠΎΠ΄Π΅ΡΠΆΠΈΡ ΠΈΠ·Π»ΠΎΠΆΠ΅Π½ΠΈΠ΅ ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠ΅ΠΎΡΠΈΠΈ ΠΈΠ·ΠΌΠ΅ΡΠ΅Π½ΠΈΡ ΡΠ°ΠΊΠΎΠ³ΠΎ ΡΠ²ΠΎΠΉΡΡΠ²Π° Π΅Π΄ΠΈΠ½ΠΈΡ ΡΠΎΠ²ΠΎΠΊΡΠΏΠ½ΠΎΡΡΠΈ, ΠΊΠ°ΠΊ ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΡ, ΠΈ ΡΠΈΡΠΎΠΊΠΎ ΠΈΠ·Π²Π΅ΡΡΠ½ΡΡ
ΡΠΎΡΠΌΡΠ» ΡΠ°ΡΡΠ΅ΡΠ° ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ° ΠΠΆΠΈΠ½ΠΈ. ΠΠ²ΡΠΎΡΡ Π°ΠΊΡΠ΅Π½ΡΠΈΡΡΡΡ Π²Π½ΠΈΠΌΠ°Π½ΠΈΠ΅ Π½Π° Π²Π°ΠΆΠ½ΠΎΠΌ ΡΡΠ»ΠΎΠ²ΠΈΠΈ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΡΠΎΠ³ΠΎ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Ρ: ΠΈΡΡ
ΠΎΠ΄Π½ΡΠ΅ Π΄Π°Π½Π½ΡΠ΅ Π΄ΠΎΠ»ΠΆΠ½Ρ Π΄ΠΎΠΏΡΡΠΊΠ°ΡΡ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΏΠΎ Π²ΡΠ΄Π΅Π»ΡΠ΅ΠΌΡΠΌ Π³ΡΡΠΏΠΏΠ°ΠΌ ΡΠΎΠ²ΠΎΠΊΡΠΏΠ½ΠΎΡΡΠΈ, ΡΠΎ Π΅ΡΡΡ Π΄ΠΎΠ»ΠΆΠ½Ρ Π±ΡΡΡ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Ρ ΠΎΠ±ΡΠ·Π°ΡΠ΅Π»ΡΠ½ΠΎ ΡΡΠΌΠΌΠ°ΡΠ½ΡΠΌΠΈ ΠΈΡΠΎΠ³Π°ΠΌΠΈ ΠΏΠΎ Π³ΡΡΠΏΠΏΠ°ΠΌ, Π° Π½Π΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΡΠΌΠΈ Π½Π° Π΄ΡΡΡ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ ΠΈΠ»ΠΈ ΡΡΠ΅Π΄Π½ΠΈΠΌΠΈ Π²Π΅Π»ΠΈΡΠΈΠ½Π°ΠΌΠΈ
On the cooling of a free thin film at the presence of the van der waals forces
The cooling of a hot free thin viscous film attached to a rectangular colder frame is considered. The film is under the action of capillary and van der Waals forces and is symmetric with respect to a middle plane. The one@dimensional case of the corresponding nonβstationary nonlinear thermoβdynamic problem is solved numerically by a finite difference scheme. The numerical results for the film shape, longitudinal velocity and temperature are obtained for different Reynolds numbers, dimensionless Hamaker constants and radiation numbers.
Apie laisvosios plonosios plΔvelΔs atvΔsinimΔ
, atsiΕΎvelgiant Δ― Van der Valso jΔgΕ³ poveikΔ―
Santrauka
Nagrinejamas karΕ‘tosios laisvosios plonosios klampiosios pleveles, prikabintos prie staΔiakampio Ε‘altesnio remo, atvesinimas. Plevele yra veikiama kapiliariniu ir Van der Valso jegu ir yra simetriΕ‘ka vidurio plokΕ‘tumos atΕΎvilgiu. Atitinkama nestaβcionari netiesine termodinamine problema vienmaΔiu atveju yra skaitiΕ‘kai iΕ‘spresta baigtiniu skirtumu schemos pagalba. Yra gauti skaitiniai rezultatai pleveles formai, iΕ‘ilginiam greiΔiui ir temperatΕ«rai skirtingiems Reinoldso skaiΔiams, bedimensinems Hamakerio konstantoms ir radiacijos parametrams.
First Published Online: 14 Oct 201
Numerical modelling of free thin film dynamics
The dynamics of a free thin film attached to a rectangular frame surrounded by an ambient gas is studied theoretically. The mathematical model is described by evolutionary nonlinear system for the longitudinal velocity components and film thickness. The 1D form of the nonstationary problem is solved by a finite difference scheme. The film shape evolution in time is tracked at different Reynolds numbers,Β Re. The steady state solutions are reached asymptotically in time for a large range ofΒ Re.
Laisvosios plonosios plΔvelΔs dinamikos skaitinis modeliavimas
Santrauka
NagrinΔjamas svarbus dujΕ³ dinamikai plonosios plΔvelΔs judΔjimo matematinio modeliavimo uΕΎdavinys. Atlikta diferencialiniΕ³ lygΔiΕ³ asimptotinΔ analizΔ. PasiΕ«lyta skirtuminΔ schema skaiΔiavimams atlikti ir pateikti skaitiniΕ³ eksperimentΕ³ rezultatai.
First Published Online: 14 Oct 201
Recent declines in reported syphilis rates in eastern Europe and central Asia: are the epidemics over?
Since the early 1990s, major syphilis epidemics have occurred in the Newly Independent States (NIS) of the former Soviet Union. The new and rapidly changing societal and economic conditions in these countries challenge their traditional approaches to the control of sexually transmitted infections (STI). Nevertheless, following a steady increase until 1997, reported syphilis incidence has declined during the past 3 years in most parts of the region. We examine these trends against a background of ongoing changes in service delivery, care seeking behaviour, and case finding practices.
National syphilis surveillance data reported to the WHO Regional Office for Europe were compiled and analysed, and supplemented with information presented at recent expert meetings and with results from ongoing research.
Since 1997, reported syphilis incidence either stabilised or declined in many locations in the NIS, but further increased in others, especially in rural areas. Congenital syphilis continued to increase in all countries, except Latvia. The proportion of self presenting cases versus cases detected through screening declined, and so did notifications of early compared with late forms of syphilis. Patients increasingly seek care in the private formal and informal healthcare sectors which hardly participate in case reporting.
Recent declines in syphilis notifications in the NIS are at least partially a reflection of a reduced intensity of active case finding and of changes in reporting completeness because of a shift in service utilisation from the public to the private/informal sectors. Syphilis rates are still high, indicating that both public and private sectors have to respond more efficiently to the needs of many people at risk of STI. The collection of serial STI prevalence data is recommended to be able to validate trends in notifications
Simulation of Heat Removal from Fuel Rods in a Turbulent Flow
Numerical simulations of flow and heat transfer around of transverse arrangement of fuel rods of the gas-cooled nuclear reactor by a new 3D code is presented
ΠΡΠ΅ ΡΠ°Π· ΠΎ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ΅ ΠΠΆΠΈΠ½ΠΈ ΠΊΠ°ΠΊ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΠΈ
This article is a continuation of the discussion that started with the publication in Β«Voprosy statistikiΒ» of the article Β«On the use of the Gini index in economic and statistical studiesΒ» by G.l. Gromyko, I.N. Matyukhina (issue β9 for 2015) and continued in the issue No. 2 for 2016, with the article by K.P. Gluschenko Β«On the issue of application of the Gini coefficient and other inequality indicesΒ». Both papers expressed opposing views on the application area for the widely recognized Gini coefficient. In the present article the authors include response to critical feedback from the authors of the second article, along with criticism of their main key points. The difference in authorsβ approaches manifest in the following issues: application area for the Gini coefficient as a concentration index, directly associated with the Lorenz curve and intended to evaluate the uneven distribution of the studied index by groups; interpretation of Β«distributionΒ» and Β«concentrationΒ» concepts in statistics; selection of a grouping variable when constructing variational series of distribution; meaningful interpretations of concentration and differentiation (difference) indicators and etc.ΠΠ° ΡΡΡΠ°Π½ΠΈΡΠ°Ρ
ΠΆΡΡΠ½Π°Π»Π° Π² Π΄Π²ΡΡ
Π΅Π³ΠΎ Π½ΠΎΠΌΠ΅ΡΠ°Ρ
ΠΎΠΏΡΠ±Π»ΠΈΠΊΠΎΠ²Π°Π½Ρ Π΄Π²Π΅ ΡΡΠ°ΡΡΠΈ, ΠΏΠΎΡΠ²ΡΡΠ΅Π½Π½ΡΠ΅ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ° ΠΠΆΠΈΠ½ΠΈ: Β«ΠΠ± ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠΈ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ° ΠΠΆΠΈΠ½ΠΈ Π² ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΎ-ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡΡ
Β» (Π°Π²ΡΠΎΡΡ: Π.Π. ΠΡΠΎΠΌΡΠΊΠΎ, Π.Π. ΠΠ°ΡΡΡ
ΠΈΠ½Π°) Π² β 9 Π·Π° 2015 Π³. ΠΈ Β«Π Π²ΠΎΠΏΡΠΎΡΡ ΠΎ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠΈ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ° ΠΠΆΠΈΠ½ΠΈ ΠΈ Π΄ΡΡΠ³ΠΈΡ
ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ Π½Π΅ΡΠ°Π²Π΅Π½ΡΡΠ²Π°Β» (Π°Π²ΡΠΎΡ: Π.Π. ΠΠ»ΡΡΠ΅Π½ΠΊΠΎ) Π² β 2 Π·Π° 2016 Π³. ΠΠ²ΡΠΎΡΡ ΡΡΠ°ΡΠ΅ΠΉ Π²ΡΡΠΊΠ°Π·ΡΠ²Π°ΡΡ ΡΠ°Π·Π»ΠΈΡΠ½ΡΠ΅ ΡΠΎΡΠΊΠΈ Π·ΡΠ΅Π½ΠΈΡ Π½Π° ΠΎΠ±Π»Π°ΡΡΡ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΠΈΡΠΎΠΊΠΎ ΠΈΠ·Π²Π΅ΡΡΠ½ΠΎΠ³ΠΎ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ° ΠΠΆΠΈΠ½ΠΈ. ΠΠ°Π½Π½Π°Ρ ΡΡΠ°ΡΡΡ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΏΡΠΎΠ΄ΠΎΠ»ΠΆΠ΅Π½ΠΈΠ΅ΠΌ ΡΠ°Π·Π²Π΅ΡΠ½ΡΠ²ΡΠ΅ΠΉΡΡ Π΄ΠΈΡΠΊΡΡΡΠΈΠΈ ΠΈ ΡΠΎΠ΄Π΅ΡΠΆΠΈΡ ΠΊΠ°ΠΊ ΠΎΡΠ²Π΅Ρ Π°Π²ΡΠΎΡΠΎΠ² ΠΏΠ΅ΡΠ²ΠΎΠΉ ΡΡΠ°ΡΡΠΈ Π½Π° ΠΊΡΠΈΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π·Π°ΠΌΠ΅ΡΠ°Π½ΠΈΡ, ΠΈΠ·Π»ΠΎΠΆΠ΅Π½Π½ΡΠ΅ Π²ΠΎ Π²ΡΠΎΡΠΎΠΉ ΡΡΠ°ΡΡΠ΅, ΡΠ°ΠΊ ΠΈ ΠΊΡΠΈΡΠΈΠΊΡ ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
Π΅Π΅ ΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΠΉ. Π Π°Π·Π»ΠΈΡΠΈΡ Π² ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Π°Ρ
Π°Π²ΡΠΎΡΠΎΠ² ΠΎΠ±Π½Π°ΡΡΠΆΠΈΠ²Π°ΡΡΡΡ ΠΏΠΎ ΡΡΠ΄Ρ Π²ΠΎΠΏΡΠΎΡΠΎΠ²: ΠΎΠ±Π»Π°ΡΡΡ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ° ΠΠΆΠΈΠ½ΠΈ ΠΊΠ°ΠΊ ΠΈΠ½Π΄Π΅ΠΊΡΠ° ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΠΈ, Π½Π΅ΠΏΠΎΡΡΠ΅Π΄ΡΡΠ²Π΅Π½Π½ΠΎ ΡΠ²ΡΠ·Π°Π½Π½ΠΎΠ³ΠΎ Ρ ΠΊΡΠΈΠ²ΠΎΠΉ ΠΠΎΡΠ΅Π½ΡΠ° ΠΈ ΠΏΡΠ΅Π΄Π½Π°Π·Π½Π°ΡΠ΅Π½Π½ΠΎΠ³ΠΎ Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ Π½Π΅ΡΠ°Π²Π½ΠΎΠΌΠ΅ΡΠ½ΠΎΡΡΠΈ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΈΡΡΠ»Π΅Π΄ΡΠ΅ΠΌΠΎΠ³ΠΎ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Ρ ΠΏΠΎ Π³ΡΡΠΏΠΏΠ°ΠΌ; ΡΡΠ°ΠΊΡΠΎΠ²ΠΊΠ° ΠΏΠΎΠ½ΡΡΠΈΠΉ Β«ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅Β» ΠΈ Β«ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΡΒ» Π² ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠ΅; Π²ΡΠ±ΠΎΡ Π³ΡΡΠΏΠΏΠΈΡΠΎΠ²ΠΎΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΈΠ·Π½Π°ΠΊΠ° ΠΏΡΠΈ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΠΈ Π²Π°ΡΠΈΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΡΠ΄ΠΎΠ² ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ; ΡΠΎΠ΄Π΅ΡΠΆΠ°ΡΠ΅Π»ΡΠ½Π°Ρ ΠΈΠ½ΡΠ΅ΡΠΏΡΠ΅ΡΠ°ΡΠΈΡ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΠΈ ΠΈ Π΄ΠΈΡΡΠ΅ΡΠ΅Π½ΡΠΈΠ°ΡΠΈΠΉ (ΡΠ°Π·Π»ΠΈΡΠΈΠΉ) ΠΈ Π΄Ρ