10 research outputs found
ΠΠΎΠ΄ΠΈΡΠΈΠΊΠ°ΡΠΈΡ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ Π΄Π»Ρ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-Π·Π½Π°ΡΠΈΠΌΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ (Π½Π° ΠΏΡΠΈΠΌΠ΅ΡΠ΅ Ρ ΡΠΎΠ½ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π²ΠΈΡΡΡΠ½ΠΎΠ³ΠΎ Π³Π΅ΠΏΠ°ΡΠΈΡΠ° Π‘)
Purpose of the study: to develop, evaluate the effectiveness and applicability of an epidemiological model for the development of chronic viral hepatitis C, with the ability to predict the number of people who need to be tested for the presence of the virus.Materials and methods. In our study, we used official data for the Republic of Bashkortostan on the spread of chronic viral hepatitis C (annual dynamics of cases) in the period from 2005 to 2020, which were provided at our request by the Republican Clinical Infectious Diseases Hospital. Demographic indicators for births and deaths were taken from the annual statistical report of Bashkortostanstat. The study considered 2 mathematical models: 1) Model SIR considers three groups: susceptible (those who have not yet become infected), infected and dropouts (those who have recovered or died). 2) The STIRD model is the SIR model, improved by the author, which takes into account five population groups: susceptible (those who have not yet become infected), tested (those who have been in contact with the infected people and require a test to clarify the diagnosis), infected, dropouts (those who recovered) and deceased.Results: from 2015 to 2017, the model provided representative data on the forecast of the infected people, the error was about 1.5-4%, but after this period, starting from 2018, the error rate became critical and the model lost its representativeness. To explain this phenomenon, there are 2 reasons: the first is the easy availability of drugs for the treatment of chronic hepatitis C, the second is the need to use Markov models in the model, since the calculation does not take into account the dynamics of changes in the coefficients of the model. As a result of the coronavirus pandemic in 2020, the error was more than 166%, this is due to a decrease in contacts between people and, as a result, a sharp decrease in the incidence of chronic hepatitis C.Conclusion. The complete epidemiological STIRD model proposed by the author (taking into account the demographic change in the structure of the population) has shown itself well in medium-term forecasting up to three years. A significant advantage of this model specification compared to other epidemiological models is the ability to predict the number of diagnostic laboratory tests needed to detect a virus in humans. This is important, since the diagnosis and treatment of chronic hepatitis C is covered from compulsory medical insurance and regional budgets. Epidemiological modeling opens up great opportunities for developing scenarios for combating viral hepatitis C, especially with its chronic form, because, according to WHO, each country has the opportunity to completely get rid of this socially significant infection by 2030.Π¦Π΅Π»ΡΡ Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠ²Π»ΡΠ΅ΡΡΡ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ°, ΠΎΡΠ΅Π½ΠΊΠ° ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΠΈ ΠΏΡΠΈΠΌΠ΅Π½ΠΈΠΌΠΎΡΡΠΈ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΡ Ρ
ΡΠΎΠ½ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π²ΠΈΡΡΡΠ½ΠΎΠ³ΠΎ Π³Π΅ΠΏΠ°ΡΠΈΡΠ° Π‘, Ρ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡΡ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π° ΡΠ΅Π»ΠΎΠ²Π΅ΠΊ, ΠΊΠΎΡΠΎΡΡΠΌ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎ ΠΏΡΠΎΠ²Π΅ΡΡΠΈ ΡΠ΅ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ Π½Π° Π½Π°Π»ΠΈΡΠΈΠ΅ Π²ΠΈΡΡΡΠ°.ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. Π ΡΠ²ΠΎΠ΅ΠΌ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ Π±ΡΠ»ΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Ρ ΠΎΡΠΈΡΠΈΠ°Π»ΡΠ½ΡΠ΅ Π΄Π°Π½Π½ΡΠ΅ ΠΏΠΎ Π Π΅ΡΠΏΡΠ±Π»ΠΈΠΊΠ΅ ΠΠ°ΡΠΊΠΎΡΡΠΎΡΡΠ°Π½ ΠΏΠΎ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΡ Ρ
ΡΠΎΠ½ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π²ΠΈΡΡΡΠ½ΠΎΠ³ΠΎ Π³Π΅ΠΏΠ°ΡΠΈΡΠ° Π‘ (Π΅ΠΆΠ΅Π³ΠΎΠ΄Π½Π°Ρ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠ° Π·Π°Π±ΠΎΠ»Π΅Π²ΡΠΈΡ
) Π² ΠΏΠ΅ΡΠΈΠΎΠ΄ Ρ 2005 ΠΏΠΎ 2020 Π³Π³., ΠΊΠΎΡΠΎΡΡΠ΅ Π±ΡΠ»ΠΈ ΠΏΡΠ΅Π΄ΠΎΡΡΠ°Π²Π»Π΅Π½Ρ ΠΏΠΎ Π·Π°ΠΏΡΠΎΡΡ ΠΊ Π Π΅ΡΠΏΡΠ±Π»ΠΈΠΊΠ°Π½ΡΠΊΠΎΠΉ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΎΠ½Π½ΠΎΠΉ Π±ΠΎΠ»ΡΠ½ΠΈΡΠ΅. ΠΠ΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ ΠΏΠΎ ΡΠΎΠΆΠ΄Π°Π΅ΠΌΠΎΡΡΠΈ ΠΈ ΡΠΌΠ΅ΡΡΠ½ΠΎΡΡΠΈ Π±ΡΠ»ΠΈ Π²Π·ΡΡΡ ΠΈΠ· Π΅ΠΆΠ΅Π³ΠΎΠ΄Π½ΠΎΠ³ΠΎ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΎΡΡΠ΅ΡΠ° ΠΠ°ΡΠΊΠΎΡΡΠΎΡΡΠ°Π½ΡΡΠ°ΡΠ°. Π ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ Π±ΡΠ»ΠΈ ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½Ρ 2 ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ: 1) ΠΠΎΠ΄Π΅Π»Ρ SIR. Π Π°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅Ρ ΡΡΠΈ Π³ΡΡΠΏΠΏΡ: Π²ΠΎΡΠΏΡΠΈΠΈΠΌΡΠΈΠ²ΡΠ΅ (ΡΠ΅, ΠΊΡΠΎ Π΅ΡΠ΅ Π½Π΅ Π·Π°ΡΠ°Π·ΠΈΠ»ΡΡ), ΠΈΠ½ΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΡΠ΅ ΠΈ Π²ΡΠ±ΡΠ²ΡΠΈΠ΅ (ΡΠ΅, ΠΊΡΠΎ Π²ΡΠ·Π΄ΠΎΡΠΎΠ²Π΅Π» ΠΈΠ»ΠΈ ΡΠΌΠ΅Ρ). 2) ΠΠΎΠ΄Π΅Π»Ρ STIRD β ΡΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½Π½Π°Ρ Π°Π²ΡΠΎΡΠΎΠΌ ΠΌΠΎΠ΄Π΅Π»Ρ SIR, ΠΊΠΎΡΠΎΡΠ°Ρ ΡΡΠΈΡΡΠ²Π°Π΅Ρ ΠΏΡΡΡ Π³ΡΡΠΏΠΏ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ: Π²ΠΎΡΠΏΡΠΈΠΈΠΌΡΠΈΠ²ΡΠ΅ (ΡΠ΅, ΠΊΡΠΎ Π΅ΡΠ΅ Π½Π΅ Π·Π°ΡΠ°Π·ΠΈΠ»ΡΡ), ΡΠ΅ΡΡΠΈΡΡΠ΅ΠΌΡΠ΅ (ΡΠ΅, ΠΊΡΠΎ ΠΊΠΎΠ½ΡΠ°ΠΊΡΠΈΡΠΎΠ²Π°Π» Ρ ΠΈΠ½ΡΠΈΡΠΈΡΡΠ΅ΠΌΡΠΌΠΈ ΠΈ ΡΡΠ΅Π±ΡΡΡΠΈΠ΅ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ ΡΠ΅ΡΡΠ° Π΄Π»Ρ ΡΡΠΎΡΠ½Π΅Π½ΠΈΡ Π΄ΠΈΠ°Π³Π½ΠΎΠ·Π°), ΠΈΠ½ΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΡΠ΅, Π²ΡΠ±ΡΠ²ΡΠΈΠ΅ (ΡΠ΅, ΠΊΡΠΎ Π²ΡΠ·Π΄ΠΎΡΠΎΠ²Π΅Π») ΠΈ ΡΠΌΠ΅ΡΡΠΈΠ΅.Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. Π‘ 2015 Π΄ΠΎ 2017 Π³ΠΎΠ΄Π° ΠΌΠΎΠ΄Π΅Π»Ρ Π΄Π°Π²Π°Π»Π° ΡΠ΅ΠΏΡΠ΅Π·Π΅Π½ΡΠ°ΡΠΈΠ²Π½ΡΠ΅ Π΄Π°Π½Π½ΡΠ΅ ΠΏΠΎ ΠΏΡΠΎΠ³Π½ΠΎΠ·Ρ ΠΈΠ½ΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
, ΠΎΡΠΈΠ±ΠΊΠ° ΡΠΎΡΡΠ°Π²Π»ΡΠ»Π° ΠΎΠΊΠΎΠ»ΠΎ 1,5β4%, Π½ΠΎ ΠΏΠΎΡΠ»Π΅ ΡΡΠΎΠ³ΠΎ ΠΏΠ΅ΡΠΈΠΎΠ΄Π°, Π½Π°ΡΠΈΠ½Π°Ρ Ρ 2018Π³., ΠΏΡΠΎΡΠ΅Π½Ρ ΠΎΡΠΈΠ±ΠΊΠΈ ΡΡΠ°Π» ΠΊΡΠΈΡΠΈΡΠ½ΡΠΌ ΠΈ ΠΌΠΎΠ΄Π΅Π»Ρ ΠΏΠΎΡΠ΅ΡΡΠ»Π° ΡΠ²ΠΎΡ ΡΠ΅ΠΏΡΠ΅Π·Π΅Π½ΡΠ°ΡΠΈΠ²Π½ΠΎΡΡΡ. Π§ΡΠΎΠ±Ρ ΠΎΠ±ΡΡΡΠ½ΠΈΡΡ ΡΡΠΎ ΡΠ²Π»Π΅Π½ΠΈΠ΅, Π΅ΡΡΡ 2 ΠΏΡΠΈΡΠΈΠ½Ρ: ΠΏΠ΅ΡΠ²ΠΎΠ΅, ΡΡΠΎ Π»Π΅Π³ΠΊΠΎΠ΄ΠΎΡΡΡΠΏΠ½ΠΎΡΡΡ ΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΠΎΠ² Π΄Π»Ρ Π»Π΅ΡΠ΅Π½ΠΈΡ Π₯ΠΠΠ‘, Π²ΡΠΎΡΠΎΠ΅, Π² ΠΌΠΎΠ΄Π΅Π»ΠΈ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°ΡΡ ΠΌΠ°ΡΠΊΠΎΠ²ΡΠΊΠΈΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ, ΡΠ°ΠΊ ΠΊΠ°ΠΊ ΠΏΡΠΈ ΡΠ°ΡΡΠ΅ΡΠ΅ Π½Π΅ ΡΡΠΈΡΡΠ²Π°Π΅ΡΡΡ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠ° ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠΎΠ² ΠΌΠΎΠ΄Π΅Π»ΠΈ. Π ΠΈΡΠΎΠ³Π΅, Π² ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ΅ ΠΊΠΎΡΠΎΠ½Π°Π²ΠΈΡΡΡΠ½ΠΎΠΉ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ Π² 2020 Π³ΠΎΠ΄Ρ ΠΎΡΠΈΠ±ΠΊΠ° ΡΠΎΡΡΠ°Π²ΠΈΠ»Π° Π±ΠΎΠ»Π΅Π΅ 166%, ΡΡΠΎ ΡΠ²ΡΠ·Π°Π½ΠΎ ΡΠΎ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΠ΅ΠΌ ΠΊΠΎΠ½ΡΠ°ΠΊΡΠΎΠ² ΠΌΠ΅ΠΆΠ΄Ρ Π»ΡΠ΄ΡΠΌΠΈ ΠΈ ΠΊΠ°ΠΊ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠΌ, ΡΠ΅Π·ΠΊΠΈΠΌ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΠ΅ΠΌ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π΅ΠΌΠΎΡΡΠΈ Π₯ΠΠΠ‘.ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅. ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π½Π°Ρ Π°Π²ΡΠΎΡΠΎΠΌ ΠΏΠΎΠ»Π½Π°Ρ (Ρ ΡΡΠ΅ΡΠΎΠΌ Π΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΡΡΡΠΊΡΡΡΡ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ) ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠ°Ρ ΠΌΠΎΠ΄Π΅Π»Ρ STIRD Ρ
ΠΎΡΠΎΡΠΎ ΡΠ΅Π±Ρ ΠΏΠΎΠΊΠ°Π·Π°Π»Π° ΠΏΡΠΈ ΡΡΠ΅Π΄Π½Π΅ΡΡΠΎΡΠ½ΠΎΠΌ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΠΈ Π΄ΠΎ ΡΡΠ΅Ρ
Π»Π΅Ρ. Π‘ΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΌ ΠΏΡΠ΅ΠΈΠΌΡΡΠ΅ΡΡΠ²ΠΎΠΌ Π΄Π°Π½Π½ΠΎΠΉ ΡΠΏΠ΅ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΏΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ Ρ Π΄ΡΡΠ³ΠΈΠΌΠΈ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ ΠΌΠΎΠ΄Π΅Π»ΡΠΌΠΈ ΡΠ²Π»ΡΠ΅ΡΡΡ Π½Π°Π»ΠΈΡΠΈΠ΅ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ ΠΏΠΎΡΡΡΠΎΠΈΡΡ ΠΏΡΠΎΠ³Π½ΠΎΠ· ΠΏΠΎ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Ρ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΡΡ
Π΄Π»Ρ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
Π»Π°Π±ΠΎΡΠ°ΡΠΎΡΠ½ΡΡ
ΡΠ΅ΡΡΠΎΠ² Π½Π° Π²ΡΡΠ²Π»Π΅Π½ΠΈΠ΅ Π²ΠΈΡΡΡΠ° Ρ ΡΠ΅Π»ΠΎΠ²Π΅ΠΊΠ°. ΠΡΠΎ Π²Π°ΠΆΠ½ΠΎ, ΡΠ°ΠΊ ΠΊΠ°ΠΊ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΈ Π»Π΅ΡΠ΅Π½ΠΈΠ΅ Π₯ΠΠΠ‘ ΠΏΠΎΠΊΡΡΠ²Π°Π΅ΡΡΡ ΠΈΠ· ΡΡΠ΅Π΄ΡΡΠ² ΠΠΠ‘ ΠΈ ΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
Π±ΡΠ΄ΠΆΠ΅ΡΠΎΠ². ΠΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΎΡΠΊΡΡΠ²Π°Π΅Ρ ΡΠΈΡΠΎΠΊΠΈΠ΅ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ Π΄Π»Ρ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ ΡΡΠ΅Π½Π°ΡΠΈΠ΅Π² Π±ΠΎΡΡΠ±Ρ Ρ Π²ΠΈΡΡΡΠ½ΡΠΌ Π³Π΅ΠΏΠ°ΡΠΈΡΠΎΠΌ Π‘, ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎ Ρ Π΅Π³ΠΎ Ρ
ΡΠΎΠ½ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠΎΡΠΌΠΎΠΉ, Π²Π΅Π΄Ρ ΠΏΠΎ Π΄Π°Π½Π½ΡΠΌ ΠΠΠ Ρ ΠΊΠ°ΠΆΠ΄ΠΎΠΉ ΡΡΡΠ°Π½Ρ Π΅ΡΡΡ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ ΠΊ 2030 Π³. ΠΏΠΎΠ»Π½ΠΎΡΡΡΡ ΠΈΠ·Π±Π°Π²ΠΈΡΡΡΡ ΠΎΡ Π΄Π°Π½Π½ΠΎΠΉ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-Π·Π½Π°ΡΠΈΠΌΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ
Bottom topography, length, chamber structure of timergazin canyon-like valley and problems of oil and gas exploration in basement
In this article there are specified: a sub-latitudinal valley bottom topography of South Tatar arch, valley length and a position of directive pallial-crustal first order fracture. The valley bottom chamber was considered as continental rift structure with fracture-block tectonics in plan. The possible contribution of the valley to hydrocarbon transit from deep formations is estimated. The Subkhankulovsky swell is specified as possible hydrocarbon deposit within the basement. Β© 2009
Using E-Learning Tools to Enhance Students- Mathematiciansβ Competences in the Context of International Academic Mobility Programmes
Introduction. The article is concerned with the use of special electronic teaching tools to increase the studentsβ understanding of the subject and adaptation to the professional language environment of the host country, taking into account the mathematical education. Our purpose is to develop a methodology of multilingual support of mathematical courses in the host country to improve the effectiveness of studentsβ academic mobility using e-learning tools.
Materials and Methods. The basis of the research was methods of system analysis and descriptive and analytical methods, primarily experimental. To identify advantages of the proposed approach the methods of empirical research were used (observation and comparison). To prove the efficiency, classical methods of measurement were used.
Results. We analyzed the existing electronic learning environments and defined an e-learning environment Math-Bridge that allows for creating mathematical courses in several languages in parallel. For example, the e-training course βOptimization Methodsβ was developed in three languages for training Russian-speaking Master programme students. The comparative analysis of the target and control studentβs groups showed that 100 % of the students in the target group achieved an excellent level of mastering competencies, while the control group has only 75 %. For the control group, the degree of motivation to mathematical studying has not virtually changed (increase by 0,86 %). In the target group the level of student interest to the mathematics increased from 0,9 % to 8,9 % (mean 2.21 %).
Discussion and Conclusion. The results described in the article will be useful for the staff of international departments, administrations and deans, as well as teachers of those universities that participate in the studentsβ international academic mobility programmes
ΠΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ΅ Π±ΡΠ΅ΠΌΡ Ρ ΡΠΎΠ½ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π²ΠΈΡΡΡΠ½ΠΎΠ³ΠΎ Π³Π΅ΠΏΠ°ΡΠΈΡΠ° Π‘
Background. The spread of chronic viral hepatitis C (CVHC) among the population entails significant costs for society, both direct, associated with the treatment of such patients, and indirect, associated with the shortfall in fiscal payments to the budget, due to the disability of this category of patients. Therefore, an important task remains to assess the global economic burden of the disease, taking into account the pathological conditions of the human body associated with it.Objective: to systematize studies of published sources devoted to assessing the global economic burden of chronic viral hepatitis C.Material and methods. A feature of the proposed review design is paying attention not only to the objects of assessment under study, but also to the instrumental (including mathematical) means of scenario assessment of the global burden. The study analyzed 29 sources published between 2014 and 2020 and dedicated to assessing and forecasting the global economic burden of CVHC both in individual countries and continents as a whole, and in individual regions of countries. The main criterion for the selection of studies was the availability of an estimate of the global burden of CVHC, taking into account the use of direct antiviral drugs for the treatment of hepatitis C. The search was conducted in PubMed/MEDLINE and eLibrary databases, and in the ResearchGate network.Results. Of the 29 analyzed sources, 40% of the works consider the burden for CVHC only of certain genotypes; in the overwhelming number of articles (80%), when assessing the burden, the distribution of patients by the degree of liver fibrosis is taken into account. In 50% of the studies reviewed, quality of life adjustment tools (QALY or DALY) were used to estimate the global economic burden. A third of the publications took into account both the direct costs of treating CVHC and indirect costs, including those associated with a shortfall in the contribution to the gross national product due to temporary or permanent disability of this category of patients.Conclusion. The analysis showed that interest in assessing the global burden of CVHC began to appear in recent years, when expensive directacting antivirals for the treatment appeared. This is explained by the emergence of a question about the cost of implementing a scenario in which by a certain year it will be possible to completely exclude the spread of the disease. The results of this work may be useful in conducting such studies, including the determining of their design and the use of modern mathematical modeling tools.ΠΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ. Π Π°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΠ΅ Ρ
ΡΠΎΠ½ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π²ΠΈΡΡΡΠ½ΠΎΠ³ΠΎ Π³Π΅ΠΏΠ°ΡΠΈΡΠ° Π‘ (Π₯ΠΠΠ‘) ΡΡΠ΅Π΄ΠΈ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ Π²Π»Π΅ΡΠ΅Ρ Π·Π° ΡΠΎΠ±ΠΎΠΉ Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΡΠ΅ Π·Π°ΡΡΠ°ΡΡ Π΄Π»Ρ ΠΎΠ±ΡΠ΅ΡΡΠ²Π° β ΠΊΠ°ΠΊ ΠΏΡΡΠΌΡΠ΅, ΡΠ²ΡΠ·Π°Π½Π½ΡΠ΅ Ρ Π»Π΅ΡΠ΅Π½ΠΈΠ΅ΠΌ, ΡΠ°ΠΊ ΠΈ ΠΊΠΎΡΠ²Π΅Π½Π½ΡΠ΅, ΡΠ²ΡΠ·Π°Π½Π½ΡΠ΅ Ρ Π½Π΅Π΄ΠΎΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΠ΅ΠΌ ΡΠΈΡΠΊΠ°Π»ΡΠ½ΡΡ
ΠΏΠ»Π°ΡΠ΅ΠΆΠ΅ΠΉ Π² Π±ΡΠ΄ΠΆΠ΅Ρ ΠΈΠ·-Π·Π° Π½Π΅ΡΡΡΠ΄ΠΎΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ ΡΠ°ΠΊΠΈΡ
Π±ΠΎΠ»ΡΠ½ΡΡ
. ΠΠΎΡΡΠΎΠΌΡ Π²Π°ΠΆΠ½ΠΎΠΉ Π·Π°Π΄Π°ΡΠ΅ΠΉ ΠΎΡΡΠ°Π΅ΡΡΡ ΠΎΡΠ΅Π½ΠΊΠ° Π³Π»ΠΎΠ±Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π±ΡΠ΅ΠΌΠ΅Π½ΠΈ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ Ρ ΡΡΠ΅ΡΠΎΠΌ Π°ΡΡΠΎΡΠΈΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
Ρ Π½ΠΈΠΌ ΠΏΠ°ΡΠ°Π»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠΎΡΡΠΎΡΠ½ΠΈΠΉ ΠΎΡΠ³Π°Π½ΠΈΠ·ΠΌΠ° ΡΠ΅Π»ΠΎΠ²Π΅ΠΊΠ°.Π¦Π΅Π»Ρ: ΡΠΈΡΡΠ΅ΠΌΠ°ΡΠΈΠ·Π°ΡΠΈΡ ΠΎΠΏΡΠ±Π»ΠΈΠΊΠΎΠ²Π°Π½Π½ΡΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ, ΠΏΠΎΡΠ²ΡΡΠ΅Π½Π½ΡΡ
ΠΎΡΠ΅Π½ΠΊΠ΅ Π³Π»ΠΎΠ±Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π±ΡΠ΅ΠΌΠ΅Π½ΠΈ Ρ
ΡΠΎΠ½ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π²ΠΈΡΡΡΠ½ΠΎΠ³ΠΎ Π³Π΅ΠΏΠ°ΡΠΈΡΠ° Π‘.ΠΠ°ΡΠ΅ΡΠΈΠ°Π» ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. ΠΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΡΡ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΠΎΠ³ΠΎ Π΄ΠΈΠ·Π°ΠΉΠ½Π° ΠΎΠ±Π·ΠΎΡΠ° ΡΠ²Π»ΡΠ΅ΡΡΡ ΡΠ΄Π΅Π»Π΅Π½ΠΈΠ΅ Π²Π½ΠΈΠΌΠ°Π½ΠΈΡ Π½Π΅ ΡΠΎΠ»ΡΠΊΠΎ ΠΈΡΡΠ»Π΅Π΄ΡΠ΅ΠΌΡΠΌ ΠΎΠ±ΡΠ΅ΠΊΡΠ°ΠΌ ΠΎΡΠ΅Π½ΠΊΠΈ, Π½ΠΎ ΠΈ ΠΏΡΠΈΠΌΠ΅Π½ΡΠ΅ΠΌΡΠΌ ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°Π»ΡΠ½ΡΠΌ (Π² Ρ.Ρ. ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΌ) ΡΡΠ΅Π΄ΡΡΠ²Π°ΠΌ ΡΡΠ΅Π½Π°ΡΠ½ΠΎΠΉ ΠΎΡΠ΅Π½ΠΊΠΈ Π³Π»ΠΎΠ±Π°Π»ΡΠ½ΠΎΠ³ΠΎ Π±ΡΠ΅ΠΌΠ΅Π½ΠΈ. ΠΡΠΎΠ²Π΅Π΄Π΅Π½ Π°Π½Π°Π»ΠΈΠ· 29 ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠΎΠ², ΠΎΠΏΡΠ±Π»ΠΈΠΊΠΎΠ²Π°Π½Π½ΡΡ
Π² ΠΏΠ΅ΡΠΈΠΎΠ΄ Ρ 2014 ΠΏΠΎ 2020 Π³Π³. ΠΈ ΠΏΠΎΡΠ²ΡΡΠ΅Π½Π½ΡΡ
ΠΎΡΠ΅Π½ΠΊΠ΅ ΠΈ ΠΏΡΠΎΠ³Π½ΠΎΠ·Ρ Π³Π»ΠΎΠ±Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π±ΡΠ΅ΠΌΠ΅Π½ΠΈ Π₯ΠΠΠ‘ ΠΊΠ°ΠΊ Π² ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΡ
ΡΡΡΠ°Π½Π°Ρ
ΠΈ Π½Π° ΠΊΠΎΠ½ΡΠΈΠ½Π΅Π½ΡΠ°Ρ
Π² ΡΠ΅Π»ΠΎΠΌ, ΡΠ°ΠΊ ΠΈ Π² ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΡΡ
ΡΠ΅Π³ΠΈΠΎΠ½Π°Ρ
ΡΡΡΠ°Π½. ΠΡΠ½ΠΎΠ²Π½ΡΠΌ ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅ΠΌ ΠΎΡΠ±ΠΎΡΠ° ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ Π±ΡΠ»ΠΎ Π½Π°Π»ΠΈΡΠΈΠ΅ ΠΎΡΠ΅Π½ΠΊΠΈ Π³Π»ΠΎΠ±Π°Π»ΡΠ½ΠΎΠ³ΠΎ Π±ΡΠ΅ΠΌΠ΅Π½ΠΈ Π₯ΠΠΠ‘ Ρ ΡΡΠ΅ΡΠΎΠΌ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ Π΄Π»Ρ Π»Π΅ΡΠ΅Π½ΠΈΡ Π³Π΅ΠΏΠ°ΡΠΈΡΠ° Π‘ ΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΠΎΠ² ΠΏΡΡΠΌΠΎΠ³ΠΎ ΠΏΡΠΎΡΠΈΠ²ΠΎΠ²ΠΈΡΡΡΠ½ΠΎΠ³ΠΎ Π΄Π΅ΠΉΡΡΠ²ΠΈΡ. ΠΠΎΠΈΡΠΊ ΠΎΡΡΡΠ΅ΡΡΠ²Π»ΡΠ»ΠΈ ΠΏΠΎ Π±Π°Π·Π°ΠΌ PubMed/MEDLINE ΠΈ eLibrary, Π° ΡΠ°ΠΊΠΆΠ΅ Π² ΡΠ΅ΡΠΈ ResearchGate.Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΠ· 29 ΠΏΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠΎΠ² Π² 40% ΡΠ°Π±ΠΎΡ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ Π±ΡΠ΅ΠΌΡ Π΄Π»Ρ Π₯ΠΠΠ‘ Π»ΠΈΡΡ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΡΡ
Π³Π΅Π½ΠΎΡΠΈΠΏΠΎΠ², Π² ΠΏΠΎΠ΄Π°Π²Π»ΡΡΡΠ΅ΠΌ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ (80%) ΠΏΡΠΈ ΠΎΡΠ΅Π½ΠΊΠ΅ Π±ΡΠ΅ΠΌΠ΅Π½ΠΈ ΡΡΠΈΡΡΠ²Π°Π΅ΡΡΡ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ Π±ΠΎΠ»ΡΠ½ΡΡ
ΠΏΠΎ ΡΡΠ΅ΠΏΠ΅Π½ΠΈ ΡΠΈΠ±ΡΠΎΠ·Π° ΠΏΠ΅ΡΠ΅Π½ΠΈ. Π 50% ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½Π½ΡΡ
ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΠΉ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π»ΠΈΡΡ ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΡ Ρ ΠΏΠΎΠΏΡΠ°Π²ΠΊΠΎΠΉ Π±ΡΠ΅ΠΌΠ΅Π½ΠΈ Π½Π° ΠΊΠ°ΡΠ΅ΡΡΠ²ΠΎ ΠΆΠΈΠ·Π½ΠΈ: QALY (Π°Π½Π³Π». quality-adjusted life year) ΠΈΠ»ΠΈ DALY (Π°Π½Π³Π». disability-adjusted life year). Π 1/3 ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ ΡΡΠΈΡΡΠ²Π°Π»ΠΈΡΡ ΠΊΠ°ΠΊ ΠΏΡΡΠΌΡΠ΅ ΠΈΠ·Π΄Π΅ΡΠΆΠΊΠΈ Π½Π° Π»Π΅ΡΠ΅Π½ΠΈΠ΅ Π₯ΠΠΠ‘, ΡΠ°ΠΊ ΠΈ ΠΊΠΎΡΠ²Π΅Π½Π½ΡΠ΅ Π·Π°ΡΡΠ°ΡΡ, Π² Ρ.Ρ. ΡΠ²ΡΠ·Π°Π½Π½ΡΠ΅ Ρ Π½Π΅Π΄ΠΎΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΠ΅ΠΌ Π²ΠΊΠ»Π°Π΄Π° Π² Π²Π°Π»ΠΎΠ²ΠΎΠΉ Π½Π°ΡΠΈΠΎΠ½Π°Π»ΡΠ½ΡΠΉ ΠΏΡΠΎΠ΄ΡΠΊΡ Π·Π° ΡΡΠ΅Ρ Π²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ Π»ΠΈΠ±ΠΎ ΡΡΠΎΠΉΠΊΠΎΠΉ Π½Π΅ΡΡΡΠ΄ΠΎΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ ΡΡΠΎΠΉ ΠΊΠ°ΡΠ΅Π³ΠΎΡΠΈΠΈ Π±ΠΎΠ»ΡΠ½ΡΡ
.ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅. ΠΠ½Π°Π»ΠΈΠ· ΠΏΠΎΠΊΠ°Π·Π°Π», ΡΡΠΎ ΠΈΠ½ΡΠ΅ΡΠ΅Ρ ΠΊ ΠΎΡΠ΅Π½ΠΊΠ΅ Π³Π»ΠΎΠ±Π°Π»ΡΠ½ΠΎΠ³ΠΎ Π±ΡΠ΅ΠΌΠ΅Π½ΠΈ Π₯ΠΠΠ‘ Π²ΠΎΠ·Π½ΠΈΠΊ Π² ΠΏΠΎΡΠ»Π΅Π΄Π½ΠΈΠ΅ Π³ΠΎΠ΄Ρ, ΠΊΠΎΠ³Π΄Π° ΠΏΠΎΡΠ²ΠΈΠ»ΠΈΡΡ Π΄ΠΎΡΠΎΠ³ΠΎΡΡΠΎΡΡΠΈΠ΅ ΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΡ ΠΏΡΡΠΌΠΎΠ³ΠΎ ΠΏΡΠΎΡΠΈΠ²ΠΎΠ²ΠΈΡΡΡΠ½ΠΎΠ³ΠΎ Π΄Π΅ΠΉΡΡΠ²ΠΈΡ. ΠΡΠΎ ΠΎΠ±ΡΡΡΠ½ΡΠ΅ΡΡΡ Π²ΠΎΠ·Π½ΠΈΠΊΠ½ΠΎΠ²Π΅Π½ΠΈΠ΅ΠΌ Π²ΠΎΠΏΡΠΎΡΠ° ΠΎ ΡΡΠΎΠΈΠΌΠΎΡΡΠΈ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΡΡΠ΅Π½Π°ΡΠΈΡ, ΠΏΡΠΈ ΠΊΠΎΡΠΎΡΠΎΠΌ ΠΊ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΠΎΠΌΡ Π³ΠΎΠ΄Ρ ΠΏΠΎΠ»Π½ΠΎΡΡΡΡ ΠΌΠΎΠΆΠ½ΠΎ Π±ΡΠ΄Π΅Ρ ΠΈΡΠΊΠ»ΡΡΠΈΡΡ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΠ΅ Π±ΠΎΠ»Π΅Π·Π½ΠΈ. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ Π΄Π°Π½Π½ΠΎΠΉ ΡΠ°Π±ΠΎΡΡ Π±ΡΠ΄ΡΡ ΠΏΠΎΠ»Π΅Π·Π½Ρ Π² ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠΈ ΠΏΠΎΠ΄ΠΎΠ±Π½ΡΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ, Π² Ρ.Ρ. Π΄Π»Ρ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΈΡ
Π΄ΠΈΠ·Π°ΠΉΠ½Π° ΠΈ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠΎΠ² ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ
Bottom topography, length, chamber structure of timergazin canyon-like valley and problems of oil and gas exploration in basement
In this article there are specified: a sub-latitudinal valley bottom topography of South Tatar arch, valley length and a position of directive pallial-crustal first order fracture. The valley bottom chamber was considered as continental rift structure with fracture-block tectonics in plan. The possible contribution of the valley to hydrocarbon transit from deep formations is estimated. The Subkhankulovsky swell is specified as possible hydrocarbon deposit within the basement. Β© 2009
Bottom topography, length, chamber structure of timergazin canyon-like valley and problems of oil and gas exploration in basement
In this article there are specified: a sub-latitudinal valley bottom topography of South Tatar arch, valley length and a position of directive pallial-crustal first order fracture. The valley bottom chamber was considered as continental rift structure with fracture-block tectonics in plan. The possible contribution of the valley to hydrocarbon transit from deep formations is estimated. The Subkhankulovsky swell is specified as possible hydrocarbon deposit within the basement. Β© 2009
Bottom topography, length, chamber structure of timergazin canyon-like valley and problems of oil and gas exploration in basement
In this article there are specified: a sub-latitudinal valley bottom topography of South Tatar arch, valley length and a position of directive pallial-crustal first order fracture. The valley bottom chamber was considered as continental rift structure with fracture-block tectonics in plan. The possible contribution of the valley to hydrocarbon transit from deep formations is estimated. The Subkhankulovsky swell is specified as possible hydrocarbon deposit within the basement. Β© 2009
Sound localization and quantification analysis of an automotive engine cooling module
Sound emissions of an automotive engine cooling system are studied using both single-microphone directivity measurements and a rotating beamforming technique. These measurements provide reference acoustic data on such a system and some new understanding of the effect that the radiator induces on the distribution of sound sources. Indeed, the beamforming results indicate that, above the frequency limit allowed by the Rayleigh criterion, it is possible to localize and quantify the noise sources even through the heat-exchanger core. Moreover, for the investigated operating points along the fan performance curve, the sources are always distributed at the tip of the blades and, in particular, at the leading edge. The present evidence, confirmed by the similar trends of the frequency spectra with and without the heat exchanger, leads to the conclusion that the dominant sound mechanism is the turbulence-interaction noise. Nevertheless, this turbulence is produced within the gap between the fan ring and its casing rather than generated by the radiator core. The latter appears to induce negligible acoustic transmission losses but, more significantly, is found to have a minimal influence on the aerodynamic modification of sound sources for all the analyzed operating conditions.Green Open Access added to TU Delft Institutional Repository βYou share, we take care!β β Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Wind Energ