352 research outputs found
Π£ΠΊΠ»ΠΎΠ½Π΅Π½ΠΈΠ΅ ΠΎΡ ΡΠΏΠ»Π°ΡΡ Π½Π°Π»ΠΎΠ³ΠΎΠ²: Π±ΠΈΠ±Π»ΠΈΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΠΉ Π°Π½Π°Π»ΠΈΠ· ΡΠΎΡΠ΅ΠΊ Π·ΡΠ΅Π½ΠΈΡ Π²Π»Π°ΡΡΠΈ, Π±ΠΈΠ·Π½Π΅ΡΠ° ΠΈ Π½Π°ΡΠΊΠΈ
Π‘ΡΠ°ΡΡΡ ΠΏΠΎΡΠ²ΡΡΠ΅Π½Π° Π°Π½Π°Π»ΠΈΠ·Ρ ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΠΉ, ΠΊΠ°ΡΠ°ΡΡΠΈΡ
ΡΡ ΠΏΡΠΎΠ±Π»Π΅ΠΌΡ ΡΠΊΠ»ΠΎΠ½Π΅Π½ΠΈΡ ΠΎΡ ΡΠΏΠ»Π°ΡΡ Π½Π°Π»ΠΎΠ³ΠΎΠ². ΠΡΠ° ΡΠ΅ΠΌΠ° ΠΏΡΠΈΠ²Π»Π΅ΠΊΠ°Π΅Ρ ΠΏΡΠΈΡΡΠ°Π»ΡΠ½ΠΎΠ΅ Π²Π½ΠΈΠΌΠ°Π½ΠΈΠ΅ Π½Π΅ ΡΠΎΠ»ΡΠΊΠΎ Π½Π°ΡΡΠ½ΠΎΠ³ΠΎ ΡΠΎΠΎΠ±ΡΠ΅ΡΡΠ²Π°. Π ΡΡΠ°ΡΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΡΠ΅ΡΡΡ ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΈΠ΅ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ°ΡΠΈΠΊΠΈ Π½Π°ΡΡΠ½ΡΡ
ΡΠ°Π±ΠΎΡ ΠΏΠΎ ΡΠΊΠ»ΠΎΠ½Π΅Π½ΠΈΡ ΠΎΡ ΡΠΏΠ»Π°ΡΡ Π½Π°Π»ΠΎΠ³ΠΎΠ² ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈΠΌ Π²ΠΎΠΏΡΠΎΡΠ°ΠΌ, ΠΎΠ±ΡΡΠΆΠ΄Π°Π΅ΠΌΡΠΌ Π·Π°ΠΈΠ½ΡΠ΅ΡΠ΅ΡΠΎΠ²Π°Π½Π½ΡΠΌΠΈ Π»ΠΈΡΠ°ΠΌΠΈ. Π ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠ° Π½Π°ΡΡΠ½ΡΡ
ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΠΉ ΠΏΠΎ Π΄Π°Π½Π½ΠΎΠΉ ΡΠ΅ΠΌΠ°ΡΠΈΠΊΠ΅ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π»Π°ΡΡ ΡΠ»Π΅ΠΊΡΡΠΎΠ½Π½Π°Ρ Π±Π°Π·Π° e-Library. Π ΠΊΡΡΠ³ Π·Π°ΠΈΠ½ΡΠ΅ΡΠ΅ΡΠΎΠ²Π°Π½Π½ΡΡ
Π»ΠΈΡ, Π½Π°ΠΏΡΡΠΌΡΡ Π·Π°Π²ΠΈΡΡΡΠΈΡ
ΠΎΡ ΠΏΡΠ°Π²ΠΈΠ» Π½Π°Π»ΠΎΠ³ΠΎΠΎΠ±Π»ΠΎΠΆΠ΅Π½ΠΈΡ, Π²Ρ
ΠΎΠ΄ΡΡ Π±ΠΈΠ·Π½Π΅ΡΡΠΎΠΎΠ±ΡΠ΅ΡΡΠ²ΠΎ ΠΈ Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π΅Π½Π½ΡΠ΅ ΠΎΡΠ³Π°Π½Ρ. ΠΠ»Ρ Π½ΠΈΡ
ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠ°ΠΌΠΈ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΏΠΎ ΠΈΡΡΠ»Π΅Π΄ΡΠ΅ΠΌΠΎΠΉ ΡΠ΅ΠΌΠ΅ ΡΠ²Π»ΡΡΡΡΡ ΡΠ»Π΅ΠΊΡΡΠΎΠ½Π½Π°Ρ Π±Π°Π·Π° ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΠΉ ΠΈΠ·Π΄Π°ΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ Π΄ΠΎΠΌΠ° Β«ΠΠΎΠΌΠΌΠ΅ΡΡΠ°Π½ΡΡΒ» ΠΈ Β«Π ΠΎΡΡΠΈΠΉΡΠΊΠ°Ρ Π³Π°Π·Π΅ΡΠ°Β». ΠΠ»Ρ Π°Π½Π°Π»ΠΈΠ·Π° ΠΎΡΠΎΠ±ΡΠ°Π½Π° 301 ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΡ Π·Π° 2013-2015 Π³Π³. ΠΠ·ΡΡΠ΅Π½ΠΈΠ΅ ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΈΡ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ°ΡΠΈΠΊΠΈ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΎΡΡ ΠΏΡΡΠ΅ΠΌ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ Π² ΡΠ°Π·ΡΠ΅Π·Π΅ Π²ΠΈΠ΄ΠΎΠ² ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΠΉ. ΠΠ° ΠΏΠ΅ΡΠ²ΠΎΠΌ ΡΡΠ°ΠΏΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π±ΡΠ» Π²ΡΠΏΠΎΠ»Π½Π΅Π½ ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΉ ΠΊΠΎΠ½ΡΠ΅Π½Ρ-Π°Π½Π°Π»ΠΈΠ· ΠΏΠΎΡΡΠ΅Π΄ΡΡΠ²ΠΎΠΌ Π²ΡΡΠ²Π»Π΅Π½ΠΈΡ ΠΎΠ±ΡΠΈΡ
ΡΠ΅ΠΌ, ΠΎΠ±ΡΡΠΆΠ΄Π°Π΅ΠΌΡΡ
Π² ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΡΡ
. ΠΠ°ΡΠ΅ΠΌ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΡΡ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· ΡΠ΅ΡΠ΅Π· ΡΡΠ°Π²Π½Π΅Π½ΠΈΠ΅ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΠΉ ΠΏΠΎ ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΠΎΠΉ ΡΠ΅ΠΌΠ΅ ΠΈΠ· ΠΊΠ°ΠΆΠ΄ΠΎΠ³ΠΎ ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠ°. ΠΠ»Ρ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΠΈ Π²ΠΈΠ·ΡΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π»ΠΈΡΡ ΠΌΠ΅ΡΠΎΠ΄Ρ Π±ΠΈΠ±Π»ΠΈΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΠΈ ΠΊΠ°ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ. Π Π°ΡΡΠ΅ΡΡ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΠ»ΠΈΡΡ Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΠ΄ΡΠΊΡΠ° QDA Miner v.5.0 ΠΌΠΎΠ΄ΡΠ»Ρ WordStat v.7.1.7. Π ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π±ΡΠ»ΠΈ ΡΠ΄Π΅Π»Π°Π½Ρ Π²ΡΠ²ΠΎΠ΄Ρ, ΡΡΠΎ ΡΠ°ΠΌΡΠΌΠΈ ΠΏΠΎΠΏΡΠ»ΡΡΠ½ΡΠΌΠΈ ΡΠ΅ΠΌΠ°ΠΌΠΈ, ΠΈΠ½ΡΠ΅ΡΠ΅Ρ ΠΊ ΠΊΠΎΡΠΎΡΡΠΌ Π½Π΅ ΠΌΠ΅Π½ΡΠ΅ΡΡΡ, ΡΠ²Π»ΡΡΡΡΡ: ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ Π·Π°ΠΊΠΎΠ½ΠΎΠ΄Π°ΡΠ΅Π»ΡΡΡΠ²Π°, Π·Π°ΠΊΠΎΠ½ΠΎΡΠ²ΠΎΡΡΠ΅ΡΡΠ²ΠΎ ΠΈ ΡΡΠΈΠ»Π΅Π½ΠΈΠ΅ ΠΏΡΠΈΠ½ΡΠΆΠ΄Π΅Π½ΠΈΡ. Π’Π΅ΠΌΡ, ΠΊ ΠΊΠΎΡΠΎΡΡΠΌ Π·Π° ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΠΌΡΠΉ ΠΏΠ΅ΡΠΈΠΎΠ΄ ΡΠ½ΠΈΠ·ΠΈΠ»ΡΡ ΠΈΠ½ΡΠ΅ΡΠ΅Ρ, ΠΊΠ°ΡΠ°ΡΡΡΡ ΠΌΠ΅ΠΆΠ΄ΡΠ½Π°ΡΠΎΠ΄Π½ΡΡ
Π°ΡΠΏΠ΅ΠΊΡΠΎΠ² Π½Π°Π»ΠΎΠ³ΠΎΠΎΠ±Π»ΠΎΠΆΠ΅Π½ΠΈΡ, ΡΠ΅Π½Π΅Π²ΠΎΠΉ Π΄Π΅ΡΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ, ΡΠΎΠ±ΡΡΠ²Π΅Π½Π½ΠΎΡΡΠΈ ΠΈ ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΈΠΉ. ΠΡΠΌΠ΅ΡΠ΅Π½ΠΎ Π²ΡΡΠ°ΠΆΠ΅Π½Π½ΠΎΠ΅ Π²ΠΎΠ·ΡΠ°ΡΡΠ°Π½ΠΈΠ΅ ΠΈΠ½ΡΠ΅ΡΠ΅ΡΠ° ΡΠΎΠΎΠ±ΡΠ΅ΡΡΠ²Π° ΠΊ ΡΠΈΡΠΌΠ°ΠΌ-ΠΎΠ΄Π½ΠΎΠ΄Π½Π΅Π²ΠΊΠ°ΠΌ, ΡΡΠΊΠΎΠ²ΠΎΠ΄ΡΡΠ²Ρ ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΠΉ, Π° ΡΠ°ΠΊΠΆΠ΅ ΠΊ Π²ΠΎΠΏΡΠΎΡΠ°ΠΌ ΡΡΡΠ°ΡΠΎΠ² ΠΈ ΠΏΠ΅Π½ΠΈ. ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΎ Π²ΡΡΠ²ΠΈΡΡ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΠΎΠ΅ Π½Π΅ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΈΠ΅ ΡΠ΅ΠΌ, ΠΎΠ±ΡΡΠΆΠ΄Π°Π΅ΠΌΡΡ
Π±ΠΈΠ·Π½Π΅ΡΠΎΠΌ ΠΈ Π²Π»Π°ΡΡΡΡ, ΠΏΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ Ρ ΡΠ΅ΠΌΠ°ΠΌΠΈ Π½Π°ΡΡΠ½ΡΡ
ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΠΉ. Π Π°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½Π½ΡΠ΅ Π² Π½Π°ΡΡΠ½ΡΡ
ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΡΡ
ΡΠ΅ΠΌΡ (ΡΠ΅Π½Π΅Π²Π°Ρ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠ°, ΠΊΠΎΡΡΡΠΏΡΠΈΡ, ΡΠΈΡΠΌΡ-ΠΎΠ΄Π½ΠΎΠ΄Π½Π΅Π²ΠΊΠΈ, Π²Π·Π½ΠΎΡΡ Π½Π° ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎΠ΅ ΡΡΡΠ°Ρ
ΠΎΠ²Π°Π½ΠΈΠ΅), Π³ΠΎΡΠ°Π·Π΄ΠΎ ΡΠ΅ΠΆΠ΅ Π²ΡΡΡΠ΅ΡΠ°ΡΡΡΡ Π½Π° ΡΠ΅ΡΡΡΡΠ°Ρ
ΠΈΠ·Π΄Π°ΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ Π΄ΠΎΠΌΠ° Β«ΠΠΎΠΌΠΌΠ΅ΡΡΠ°Π½ΡΡΒ» ΠΈ Π² Β«Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π³Π°Π·Π΅ΡΠ΅Β», ΡΠΎΡΡΠ΅Π΄ΠΎΡΠ°ΡΠΈΠ²Π°ΡΡΠΈΡ
ΠΎΡΠ½ΠΎΠ²Π½ΠΎΠ΅ Π²Π½ΠΈΠΌΠ°Π½ΠΈΠ΅ Π½Π° Π²ΠΎΠΏΡΠΎΡΠ°Ρ
Π·Π°ΠΊΠΎΠ½ΠΎΡΠ²ΠΎΡΡΠ΅ΡΡΠ²Π° ΠΈ ΠΎΠ±ΡΡΠΆΠ΄Π΅Π½ΠΈΡ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ Π² Π·Π°ΠΊΠΎΠ½ΠΎΠ΄Π°ΡΠ΅Π»ΡΡΡΠ²Π΅. ΠΠ½Π°Π»ΠΈΠ· Π²Π·Π°ΠΈΠΌΠΎΡΠ²ΡΠ·Π΅ΠΉ Π² ΡΠ΅ΠΊΡΡΠ°Ρ
Π² ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΈΠΈ Ρ ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠ°ΠΌΠΈ ΠΈ Π³ΠΎΠ΄ΠΎΠΌ ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΠΈ ΠΏΠΎΠΊΠ°Π·Π°Π», ΡΡΠΎ ΡΠ΅ΠΌΡ Π½Π°ΡΡΠ½ΡΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ ΡΠ±Π»ΠΈΠΆΠ°ΡΡΡΡ Ρ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ°ΠΌΠΈ, ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΠΌΡΠΌΠΈ Π²Π»Π°ΡΡΡΡ, Π° Π±ΠΈΠ·Π½Π΅Ρ-ΡΠΎΠΎΠ±ΡΠ΅ΡΡΠ²ΠΎ Π² Π±ΠΎΠ»ΡΡΠ΅ΠΉ ΡΡΠ΅ΠΏΠ΅Π½ΠΈ Π²ΠΎΠ²Π»Π΅ΠΊΠ°Π΅ΡΡΡ ΠΎΠ±ΡΡΠΆΠ΄Π΅Π½ΠΈΠ΅ ΠΏΡΠ°Π²ΠΎΠ²ΠΎΠΉ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ°ΡΠΈΠΊΠΈ, Ρ. Π΅. ΡΠΎΡΠΊΠ° Π·ΡΠ΅Π½ΠΈΡ Π²Π»Π°ΡΡΠΈ Π²ΠΎ ΠΌΠ½ΠΎΠ³ΠΎΠΌ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ΅Ρ ΠΎΠ±ΡΡΠΆΠ΄Π΅Π½ΠΈΠ΅ ΡΠ΅ΠΌΡ ΡΠΊΠ»ΠΎΠ½Π΅Π½ΠΈΡ ΠΎΡ Π½Π°Π»ΠΎΠ³ΠΎΠ² Π±ΠΈΠ·Π½Π΅Ρ-ΡΠΎΠΎΠ±ΡΠ΅ΡΡΠ²ΠΎΠΌ, ΠΈ Π½Π°ΡΡΠ½ΡΠΌΠΈ ΠΊΡΡΠ³Π°ΠΌΠΈ. Π’Π°ΠΊΠΈΠΌ ΠΎΠ±ΡΠ°Π·ΠΎΠΌ, Π±ΠΈΠ±Π»ΠΈΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΌΠ΅ΡΠΎΠ΄Ρ Π°Π½Π°Π»ΠΈΠ·Π° ΡΠ΅ΠΊΡΡΠΎΠ² ΠΌΠΎΠ³ΡΡ ΠΏΡΠΈΠΌΠ΅Π½ΡΡΡΡΡ Π΄Π»Ρ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ Π½Π°ΡΡΠ½ΡΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ, ΡΠΎΡΡΠ°Π²Π»Π΅Π½ΠΈΡ ΠΎΠ±Π·ΠΎΡΠΎΠ² Π»ΠΈΡΠ΅ΡΠ°ΡΡΡΡ ΠΈ ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΏΠΎΠΈΡΠΊΠ° ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ.This article analyzes the publications relating to the problem of tax evasion. This topic is attractive not only for the academic community, but also for public at whole. The article explores to what extent the scientific publications on tax evasion correspond to practical issues discussed among the stakeholders. We used the electronic database of e-Library as a source of scientific publications on the subject. The principal stakeholders directly dependent on the taxation are the taxpayers and public authorities. We used the electronic database of publications Β«KommersantΒ» publishing house and the Β«Rossiyskaya GazetaΒ» to reflect issues discussed among the stakeholders. We selected for analyze 301 publications for the period of 2013-2015. The study was conducted by comparing the publication activity by types and period of publications. In the first stage of the study we have done the qualitative content analysis by identification the common themes discussed in hole sample of publications. Then, a quantitative analysis was conducted by comparing the distribution of publications on a particular topic from each source. We used bibliometric analysis method for the quantitative and bibliographic mapping method to visualize the results of research. Calculations were performed using the software QDA Miner v.5.0 module WordStat v.7.1.7. As a result, studies have concluded that the most popular topics of interest for which no changes are: changes in legislation, legislation and increased enforcement. Using the results of the conducted study, we can identify the main similarities and differences between the monitored sources. We can see the special attention to the: Legislation changes, Law enforcement, Entrepreneurship. Marked reduction of interest can be noted regarding to the following topics: International aspects of taxation, Shadow economy, Ownership, property, investment. The growth of interest can be noted in relation to the following topics: Directorship, Article of the Tax Code, Short-lived companies, Arrears and fines. The study revealed a certain disparity between the topics discussed among academic community and stakeholders. The topics discussed in the majority of scientific texts (shadow economy, corruption, the firm one-day, social security contributions), a much rarer can be found in the publication of Β«KommersantΒ» and Β«Rossiyskaya GazetaΒ» which focuses mainly on matters of legislation. Analysis of the relationships in the texts according to the source and year of publication showed that research topics converge with issues considered by the public authorities. The business community more involved in discussion the legal issues, because the government notion works upon the impression about tax evasion of the business community and academia. Thus, bibliometric text analysis techniques can be used for research, preparation of literature reviews and thematic information retrieval
Antihyperlipidemic effects of Pleurotus ostreatus (oyster mushrooms) in HIV-infected individuals taking antiretroviral therapy
<p>Abstract</p> <p>Background</p> <p>Antiretroviral treatment (ART) regimens in HIV patients commonly cause significant lipid elevations, including increases in both triglycerides and cholesterol. Standard treatments for hypercholesterolemia include the HMG CoA reductase inhibitors, or "statins." Because many ART agents and statins share a common metabolic pathway that uses the cytochrome P450 enzyme system, coadministration of ART with statins could increase statin plasma levels significantly. The oyster mushroom, <it>Pleurotus ostreatus</it>, has been shown in animal models to decrease lipid levels - a finding that has been supported by preliminary data in a small human trial.</p> <p>Methods</p> <p>To assess the safety and efficacy of <it>P. ostreatus </it>in patients with HIV and ART-induced hyperlipidemia, a single-arm, open-label, proof-of-concept study of 8 weeks' duration with a target enrollment of 20 subjects was conducted. Study patients with ART-induced elevated non-HDL cholesterol levels (> 160 mg/dL) were enrolled. Participants received packets of freeze-dried <it>P. ostreatus </it>(15 gm/day) to be administered orally for the 8 week trial period. Lipid levels were drawn every two weeks to assess efficacy. Safety assessments included self-reported incidence of muscle aches and measurement of liver and muscle enzymes. Mean within-person change in lipid levels were estimated using generalized estimating equations to account for repeated observations on individuals. A 30 mg/dL decrease in non-HDL cholesterol was deemed clinically significant.</p> <p>Results</p> <p>126 patients were screened to enroll 25, of which 20 completed the 8-week study. The mean age was 46.4 years (36-60). Patients had a mean 13.7 yrs of HIV infection. Mean non-HDL cholesterol was 204.5 mg/dL at day 0 and 200.2 mg/dL at day 56 (mean within-person change = -1.70; 95% confidence interval (CI) = -17.4, 14.0). HDL cholesterol levels increased from 37.8 mg/dL at day 0 to 40.4 mg/dL on day 56 (mean within-person change = 2.6; 95% CI = -0.1, 5.2). Triglycerides dropped from 336.4 mg/dL on day 0 to 273.4 mg/dL on day 56 (mean within-person change = -63.0; 95% CI = -120.9, -5.1). Only 3 individuals achieved a sustained clinically significant (30 mg/dL) decline in non-HDL cholesterol after 8 weeks of therapy. There were no adverse experiences reported other than patients' distaste for the preparation. Liver function tests and muscle enzymes were not affected by the 8 weeks of treatment.</p> <p>Conclusions</p> <p><it>Pleurotus ostreatus </it>as administered in this experiment did not lower non-HDL cholesterol in HIV patients with ART-induced hypercholesterolemia. Small changes in HDL and triglycerides were not of a clinical magnitude to warrant further study.</p> <p>Trial Registration</p> <p>clinicaltrials.gov Identifier: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00069524">NCT00069524</a></p
Uncertainty in context-aware systems: A case study for intelligent environments
Data used be context-aware systems is naturally incomplete and not always reflect real situations. The dynamic nature of intelligent environments leads to the need of analysing and handling uncertain information. Users can change their acting patterns within a short space of time. This paper presents a case study for a better understanding of concepts related to context awareness and the problem of dealing with inaccurate data. Through the analysis of identification of elements that results in the construction of unreliable contexts, it is aimed to identify patterns to minimize incompleteness. Thus, it will be possible to deal with flaws caused by undesired execution of applications.Programa Operacional TemΓ‘tico Factores de Competitividade (POCI-01-0145-
INSULIN AND ANALOGS: NARRATIVE LITERATURE REVIEW
As insulinas e seus anΓ‘logos sΓ£o divididos em trΓͺs tipos principais: os de ação curta, distribuΓdas nas categorias de ação curta e ultracurta ou rΓ‘pida; ação intermediΓ‘ria e ação longa. A insulina aspart e lispro possuem ação ultracurta e rΓ‘pida, a insulina glulisina sofre absorção duas vezes mais rΓ‘pida que a insulina regular e atinge um pico plasmΓ‘tico duas vezes maior. A insulina regular Γ© uma insulina zinco cristalina, de ação curta, empregada em casos emergenciais hiperglicΓͺmicos. As de ação intermediΓ‘ria sΓ£o: protamina neutra de Hagedorn (NPH) ou isΓ³fana e a lente. A insulina glargina Γ© um anΓ‘logo de insulina modificada, a qual foi desenvolvida para proporcionar uma concentração constante de insulina. A insulina detemir Γ© um anΓ‘logo solΓΊvel, com ação prolongada, caracteriza por nΓ£o possuir pico de ação. Este trabalho Γ© uma revisΓ£o narrativa, descritiva e exploratΓ³ria sobre a insulina e seus anΓ‘logos, voltados para o estudo da insulina no Diabetes mellitus (DM), pois, Γ© a melhor escolha para o tratamento do DM tipo 1.
Explainable Predictive Maintenance
Explainable Artificial Intelligence (XAI) fills the role of a critical
interface fostering interactions between sophisticated intelligent systems and
diverse individuals, including data scientists, domain experts, end-users, and
more. It aids in deciphering the intricate internal mechanisms of ``black box''
Machine Learning (ML), rendering the reasons behind their decisions more
understandable. However, current research in XAI primarily focuses on two
aspects; ways to facilitate user trust, or to debug and refine the ML model.
The majority of it falls short of recognising the diverse types of explanations
needed in broader contexts, as different users and varied application areas
necessitate solutions tailored to their specific needs.
One such domain is Predictive Maintenance (PdM), an exploding area of
research under the Industry 4.0 \& 5.0 umbrella. This position paper highlights
the gap between existing XAI methodologies and the specific requirements for
explanations within industrial applications, particularly the Predictive
Maintenance field. Despite explainability's crucial role, this subject remains
a relatively under-explored area, making this paper a pioneering attempt to
bring relevant challenges to the research community's attention. We provide an
overview of predictive maintenance tasks and accentuate the need and varying
purposes for corresponding explanations. We then list and describe XAI
techniques commonly employed in the literature, discussing their suitability
for PdM tasks. Finally, to make the ideas and claims more concrete, we
demonstrate XAI applied in four specific industrial use cases: commercial
vehicles, metro trains, steel plants, and wind farms, spotlighting areas
requiring further research.Comment: 51 pages, 9 figure
ΠΠ°Π»ΠΎΠ³ΠΎΠ²ΠΎΠ΅ ΡΡΠΈΠΌΡΠ»ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΈΠΉ ΡΠ°ΡΡΠ½ΡΡ ΠΈΠ½Π²Π΅ΡΡΠΎΡΠΎΠ² Π² ΠΎΠ±Π»ΠΈΠ³Π°ΡΠΈΠΈ Π² Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ
Π‘ΡΠ°ΡΡΡ ΠΏΠΎΡΠ²ΡΡΠ΅Π½Π° Π°Π½Π°Π»ΠΈΠ·Ρ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠ΅ΠΉ Π½Π°Π»ΠΎΠ³ΠΎΠ²ΠΎΠ³ΠΎ ΡΡΠΈΠΌΡΠ»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΈΠΉ ΡΠ°ΡΡΠ½ΡΡ
ΠΈΠ½Π²Π΅ΡΡΠΎΡΠΎΠ² Π² ΠΎΠ±Π»ΠΈΠ³Π°ΡΠΈΠΈ Π² Π Π€. ΠΠ΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΡΡΡ Π½Π°Π»ΠΎΠ³ΠΎΠ²ΠΎΠ³ΠΎ ΡΡΠΈΠΌΡΠ»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΡΠΈΠΎΠ±ΡΠ΅ΡΠ΅Π½ΠΈΡ ΠΎΠ±Π»ΠΈΠ³Π°ΡΠΈΠΉ ΡΠ°ΡΡΠ½ΡΠΌΠΈ ΠΈΠ½Π²Π΅ΡΡΠΎΡΠ°ΠΌΠΈ ΠΎΡΠΌΠ΅ΡΠ΅Π½Π° ΠΊΠ°ΠΊ ΡΠΎΡΡΠ°Π²Π½Π°Ρ ΡΠ°ΡΡΡ ΡΡΡΠ°ΡΠ΅Π³ΠΈΠΈ Π±ΠΎΠ½Π΄ΠΈΠ·Π°ΡΠΈΠΈ, Π·Π°ΡΠ²Π»Π΅Π½Π½ΠΎΠΉ ΠΠ°Π½ΠΊΠΎΠΌ Π ΠΎΡΡΠΈΠΈ. Π¦Π΅Π»ΡΡ Π½Π°ΡΡΠΎΡΡΠ΅ΠΉ ΡΡΠ°ΡΡΠΈ ΡΠ²Π»ΡΠ΅ΡΡΡ Π°Π½Π°Π»ΠΈΠ· ΡΠΏΠ΅ΡΠΈΡΠΈΠΊΠΈ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΈΠΎΠ½Π½ΡΡ
Π½Π°Π»ΠΎΠ³ΠΎΠ²ΡΡ
Π»ΡΠ³ΠΎΡ Π² Π Π€, Π²ΡΡΠ²Π»Π΅Π½ΠΈΠ΅ ΡΠΏΠΎΡΠ½ΡΡ
ΠΈ ΡΡΠ΅Π±ΡΡΡΠΈΡ
ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠΈΠ·Π°ΡΠΈΠΈ Π²ΠΎΠΏΡΠΎΡΠΎΠ². ΠΡΠΌΠ΅ΡΠ΅Π½Ρ ΡΠΈΡΠΎΠΊΠΎΠ΅ ΠΎΡΠ²Π΅ΡΠ΅Π½ΠΈΠ΅ ΡΠ΅ΠΌΡ Π½Π°Π»ΠΎΠ³ΠΎΠ²ΠΎΠ³ΠΎ ΡΡΠΈΠΌΡΠ»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΈΠΉ Π² ΠΈΠ½ΠΎΡΡΡΠ°Π½Π½ΠΎΠΉ ΠΏΠ΅ΡΠΈΠΎΠ΄ΠΈΡΠ΅ΡΠΊΠΎΠΉ Π»ΠΈΡΠ΅ΡΠ°ΡΡΡΠ΅ ΠΈ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈ ΠΏΠΎΠ»Π½ΠΎΠ΅ ΠΈΠ³Π½ΠΎΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ Π΄Π°Π½Π½ΠΎΠΉ ΡΠ΅ΠΌΠ°ΡΠΈΠΊΠΈ ΠΎΡΠ΅ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΌΠΈ Π°Π²ΡΠΎΡΠ°ΠΌΠΈ. Π ΡΡΠ°ΡΡΠ΅ ΠΏΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Ρ Π½Π°Π»ΠΎΠ³ΠΎΠ²ΡΠ΅ Π½ΠΎΠ²Π°ΡΠΈΠΈ Π² ΠΎΠ±Π»Π°ΡΡΠΈ ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΈΠΉ ΡΠΎΡΡΠΈΠΉΡΠΊΠΈΡ
ΡΠ°ΡΡΠ½ΡΡ
ΠΈΠ½Π²Π΅ΡΡΠΎΡΠΎΠ²: Π»ΡΠ³ΠΎΡΠ° ΠΏΠΎ ΠΊΡΠΏΠΎΠ½Π½ΠΎΠΌΡ Π΄ΠΎΡ
ΠΎΠ΄Ρ ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½ΡΡ
ΠΎΠ±Π»ΠΈΠ³Π°ΡΠΈΠΉ, ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΈΠΎΠ½Π½ΡΠ΅ Π½Π°Π»ΠΎΠ³ΠΎΠ²ΡΠ΅ Π²ΡΡΠ΅ΡΡ (ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΡΠ°Π»ΡΠ½ΡΠ΅ ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΈΠΎΠ½Π½ΡΠ΅ ΡΡΠ΅ΡΠ° ΠΈ Π»ΡΠ³ΠΎΡΠ° ΠΏΠΎ Π΄ΠΎΠ»Π³ΠΎΡΡΠΎΡΠ½ΠΎΠΌΡ Π²Π»Π°Π΄Π΅Π½ΠΈΡ ΡΠ΅Π½Π½ΡΠΌΠΈ Π±ΡΠΌΠ°Π³Π°ΠΌΠΈ), Π»ΡΠ³ΠΎΡΠ° ΠΏΠΎ Π΄ΠΎΠ»Π³ΠΎΡΡΠΎΡΠ½ΠΎΠΌΡ Π²Π»Π°Π΄Π΅Π½ΠΈΡ ΡΠ΅Π½Π½ΡΠΌΠΈ Π±ΡΠΌΠ°Π³Π°ΠΌΠΈ Π²ΡΡΠΎΠΊΠΎΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠ½ΠΎΠ³ΠΎ (ΠΈΠ½Π½ΠΎΠ²Π°ΡΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ) ΡΠ΅ΠΊΡΠΎΡΠ° ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ. ΠΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Ρ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ ΡΠΎΠ²ΠΌΠ΅ΡΠ΅Π½ΠΈΡ Π²ΡΡΠ΅Π½Π°Π·Π²Π°Π½Π½ΡΡ
Π»ΡΠ³ΠΎΡ. ΠΡΠΌΠ΅ΡΠ΅Π½ Π½Π΅Π΄ΠΎΡΡΠ°ΡΠΎΠΊ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΡ
Π΄Π°Π½Π½ΡΡ
Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ Π½Π°Π»ΠΎΠ³ΠΎΠ²ΡΡ
Π»ΡΠ³ΠΎΡ Π΄Π»Ρ ΡΠ°ΡΡΠ½ΡΡ
ΠΈΠ½Π²Π΅ΡΡΠΎΡΠΎΠ² Π²ΡΠ»Π΅Π΄ΡΡΠ²ΠΈΠ΅ ΠΊΠΎΡΠΎΡΠΊΠΎΠ³ΠΎ ΠΏΠ΅ΡΠΈΠΎΠ΄Π° ΠΈΡ
Π΄Π΅ΠΉΡΡΠ²ΠΈΡ. ΠΠ²ΡΠΎΡΡ ΠΏΡΠΈΡΠ»ΠΈ ΠΊ Π²ΡΠ²ΠΎΠ΄Ρ ΠΎΡΠ½ΠΎΡΠΈΡΠ΅Π»ΡΠ½ΠΎ ΠΎΡΡΡΡΡΡΠ²ΠΈΡ Π΅Π΄ΠΈΠ½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ ΠΏΡΠ΅Π΄ΠΎΡΡΠ°Π²Π»Π΅Π½ΠΈΡ Π»ΡΠ³ΠΎΡ ΡΠ°ΡΡΠ½ΡΠΌ ΠΈΠ½Π²Π΅ΡΡΠΎΡΠ°ΠΌ ΠΈ Π±ΠΎΠ»Π΅Π΅ ΡΠΈΡΠΎΠΊΠΎΠΌ Π»ΡΠ³ΠΎΡΠΈΡΠΎΠ²Π°Π½ΠΈΠΈ ΠΎΠ±Π»ΠΈΠ³Π°ΡΠΈΠΉ Π² ΡΡΠ°Π²Π½Π΅Π½ΠΈΠΈ Ρ ΠΏΡΠΎΡΠΈΠΌΠΈ ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΠΌΠΈ. ΠΠΎΠ½ΠΊΡΠ΅ΡΠ½ΡΠΌ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ°ΠΌΠΈ ΡΠ°Π±ΠΎΡΡ ΠΌΠΎΠΆΠ½ΠΎ ΡΡΠΈΡΠ°ΡΡ ΠΊΠΎΠ½ΡΡΠ°ΡΠ°ΡΠΈΡ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΡΡΠΈ Π²Π½Π΅ΡΠ΅Π½ΠΈΠΉ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ Π² ΠΠ Π Π€ Ρ ΡΠ΅Π»ΡΡ Π²ΡΡΠ°Π²Π½ΠΈΠ²Π°Π½ΠΈΡ Π½Π°Π»ΠΎΠ³ΠΎΠΎΠ±Π»ΠΎΠΆΠ΅Π½ΠΈΡ ΠΏΠΎ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄Π½ΡΠΌ ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΠΌ, ΡΠΎΠ·Π΄Π°Π½Π½ΡΠΌ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΎΠ±Π»ΠΈΠ³Π°ΡΠΈΠΉ, ΠΏΠ°ΡΠΌ ΠΏΠ°Π΅Π²ΡΡ
ΠΈΠ½Π²Π΅ΡΡΠΈΡΠΈΠΎΠ½Π½ΡΡ
ΡΠΎΠ½Π΄ΠΎΠ² ΠΈ ΠΊΠΎΡΡΠ΅ΠΊΡΠΈΡΠΎΠ²ΠΊΠΈ ΡΡΠ΄Π° ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠΎΠΌΠ΅Π½ΡΠΎΠ² ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ Π»ΡΠ³ΠΎΡ, Π° ΡΠ°ΠΊΠΆΠ΅ ΠΎΡΠ΅Π½ΠΊΡ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΠΎΠΏΠΈΡΠ°Π½Π½ΡΡ
Π»ΡΠ³ΠΎΡ.The paper addresses the specificities of tax incentives in the form of tax reliefs designated for individual investors, who invest in bonds in the Russian Federation. The need for the use of tax incentives to encourage individual investors to purchase bonds is regarded as an integral aspect of the bondization, announced by the Bank of Russia. The objective of this paper is to analyze the specific features of the investment tax relief implementation in the Russian Federation and to reveal issues that remain controversial and require particularization. It was found that stimulation of investment through tax is widely studied by foreign scientists; however, it is almost completely disregarded in Russia. The following tax innovations related to investments of individual Russian investors were analyzed: tax relief for coupon income, derived from corporate bonds; investment tax deductions (individual investment account and long-term capital gains exemption); long-term capital gains exemption for securities of the high-tech (innovation) sector of economy. Reconciliation schemes for the above-mentioned reliefs were identified. Insufficiency of quantitative data for the effectiveness evaluation of tax relief for individual investors was revealed, which was explained by the short validity period of this relief. The authors proved the absence of a uniform system tax relief instruments for individual investors and found that bond holders have more tax relief options, compared to share holders of other investment instruments. In this context, it was proposed to make amendments to the Tax Code of the Russian Federation in order to ensure tax equalization with relation to derivative instruments, designed on the basis of bonds, mutual fund units). In addition, it was recommended to adjust a number of technical aspects, connected with tax relief application and to evaluate the effectiveness of the reliefs under study
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