60 research outputs found
Π’ΠΠΠΠΠΠΠΠ― Π‘Π ΠΠΠΠΠΠΠΠΠΠ«Π₯ Π’ΠΠΠΠ ΠΠ C Π‘ΠΠΠΠ Π ΠΠΠΠΠΠΠΠ Π‘ΠΠΠΠ Π
The paper presents the results of the research on the Middle Ages iron axes found in different years in the north of Western Siberia and the Urals, excluding pole-axe (berdysh Rus.) that appear in large numbers in the study area with the growing of the Russian population. The relevance of such study has matured, since there are enough sources that need to be generalized and critically compiled. Taking into account the morphological features of the archaeological evidence, the authors propose to classify all currently known axes by 2 groups and 13 types. The first group including 3 types of minting axes were made exclusively for combat use. The second group includes 10 types of axes, classified as universal, which served both for the military and for economic purposes. The text with the description of the sites contains also table with the data on the basic parameters of axes (item length, blade width) and the time of their use (existence). For the first time, a new type of battle axe (type 13), accidentally found in the Khanty-Mansi Autonomous Okrug - Ugra, is published. We present analogues of this subject among the products of Russian blacksmiths of the 13th-14th centuries and explain the position on the dating and on origin of the axe. The paper discusses the evolution of certain types of objects, describes plots concerning the origin of certain items (imports from Volga Bulgaria, Russian lands, etc.) and the special attitude of the local population to this type of weapon, which could be stored for centuries in the holy places of the Ob Ugrians. The authors come to the conclusion that imported axes of the second group were used as a standard for Siberian blacksmiths. But local products, characterized by primitive technology (a multilayer package), low quality welding of iron strips and an abundance of slag inclusions, can be finally identified only after metallographic microstructural analysis. This research should be prolonged, because annual archaeological investigations replenish the source base, and, with no doubt, the typology of axes proposed in the article will be supplemented and adjusted. Β© 2020 Tyumen Scientific Centre of Siberian Branch of the Russian Academy of Sciences. All rights reserved.Π Π°Π±ΠΎΡΠ° Π²ΡΠΏΠΎΠ»Π½Π΅Π½Π° ΠΏΠΎ ΠΡΠΎΠ³ΡΠ°ΠΌΠΌΠ΅ Π£ΡΠ Π ΠΠ β 18-6-6-15 Β«ΠΡΡ
Π΅ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΏΠ°ΠΌΡΡΠ½ΠΈΠΊΠΈ ΠΊΠ°ΠΊ ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠΈ ΠΏΠΎ ΡΠ΅ΠΊΠΎΠ½ΡΡΡΡΠΊΡΠΈΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΡ Π΄ΡΠ΅Π²Π½ΠΈΡ
ΠΎΠ±ΡΠ΅ΡΡΠ² Π£ΡΠ°Π»Π° ΠΈ ΡΠ΅Π²Π΅ΡΠ° ΠΠ°ΠΏΠ°Π΄Π½ΠΎΠΉ Π‘ΠΈΠ±ΠΈΡΠΈΒ» (ΡΡΠΊ. Π΄.ΠΈ.Π½. Π.Π€. Π¨ΠΎΡΠΈΠ½)
Applying Financial Information to Manage Corporate Risks from the COVIDβ19 Pandemic
The COVID-19 pandemic has had a significant impact on the economy at all levels, from global markets to micro-enterprises. At the same time, the pandemic and its consequences have left a wide digital footprint. Its study seems to be extremely relevant, since approaches to the analysis of the digital footprint of a pandemic and the use of its results for risk management can be successfully applied in the event of similar threats. The relevance of the problem is also recognized by economists who note the significant impact of the pandemic on the economy and economic theory in general. The aim of the study is to develop approaches to the rapid quantitative assessment of the impact of the pandemic on the university based on the data of accounting financial systems, their testing and generation of proposals for minimizing the risks of financial and economic activities. The scientific hypothesis of the study is that based on the analysis of data transmitted to the social insurance fund on the disability of employees, the effectiveness of risk management of financial and economic activities in a pandemic at the university level can be improved. Growth in efficiency is ensured by adjusting plans to minimize risks, taking into account the heterogeneity of the impact of the pandemic on employees depending on age, gender, and belonging to the category of personnel. For data integration and analysis, the authors used Data Science approaches. Using the data of Ural Federal University as an example, the information content of the analyzed data is shown and what management decisions to minimize risks can be made on their basis. An approach to the quantitative analysis of the impact of the pandemic on employees of a legal entity is proposed. The effectiveness of using distance learning to counter the pandemic, the vulnerability to the pandemic of certain categories of employees, the gender structure of disability are demonstrated. The theoretical significance of the work lies in the development of approaches to the use of financial information to improve risk management. The information obtained can be applied in practice, in particular, to clarify the calculation of reserves, improve technical specifications in the development of information systems.ΠΠ°Π½Π΄Π΅ΠΌΠΈΡ COVID-19 ΠΎΠΊΠ°Π·Π°Π»Π° ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ΅ Π²Π»ΠΈΡΠ½ΠΈΠ΅ Π½Π° ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΡ Π½Π° Π²ΡΠ΅Ρ
ΡΡΠΎΠ²Π½ΡΡ
, ΠΎΡ Π³Π»ΠΎΠ±Π°Π»ΡΠ½ΡΡ
ΡΡΠ½ΠΊΠΎΠ² Π΄ΠΎ ΠΌΠΈΠΊΡΠΎΠΏΡΠ΅Π΄ΠΏΡΠΈΡΡΠΈΠΉ. ΠΡΠΈ ΡΡΠΎΠΌ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΡ ΠΈ Π΅Π΅ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΠ²ΠΈΡ ΠΎΡΡΠ°Π²ΠΈΠ»ΠΈ ΡΠΈΡΠΎΠΊΠΈΠΉ ΡΠΈΡΡΠΎΠ²ΠΎΠΉ ΡΠ»Π΅Π΄. ΠΠ³ΠΎ ΠΈΠ·ΡΡΠ΅Π½ΠΈΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»ΡΠ΅ΡΡΡ ΡΡΠ΅Π·Π²ΡΡΠ°ΠΉΠ½ΠΎ Π°ΠΊΡΡΠ°Π»ΡΠ½ΡΠΌ, ΡΠ°ΠΊ ΠΊΠ°ΠΊ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Ρ ΠΊ Π°Π½Π°Π»ΠΈΠ·Ρ ΡΠΈΡΡΠΎΠ²ΠΎΠ³ΠΎ ΡΠ»Π΅Π΄Π° ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ ΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ Π΅Π³ΠΎ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² Π΄Π»Ρ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΡΠΈΡΠΊΠ°ΠΌΠΈ ΠΌΠΎΠ³ΡΡ Π±ΡΡΡ ΡΡΠΏΠ΅ΡΠ½ΠΎ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½Ρ Π² ΡΠ»ΡΡΠ°Π΅ Π²ΠΎΠ·Π½ΠΈΠΊΠ½ΠΎΠ²Π΅Π½ΠΈΡ Π°Π½Π°Π»ΠΎΠ³ΠΈΡΠ½ΡΡ
ΡΠ³ΡΠΎΠ·. ΠΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ ΠΏΡΠΎΠ±Π»Π΅ΠΌΡ ΠΏΡΠΈΠ·Π½Π°Π΅ΡΡΡ ΠΈ ΡΡΠ΅Π½ΡΠΌΠΈ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΡΠ°ΠΌΠΈ, ΠΊΠΎΡΠΎΡΡΠ΅ ΠΎΡΠΌΠ΅ΡΠ°ΡΡ ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ΅ Π²Π»ΠΈΡΠ½ΠΈΠ΅ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ Π½Π° ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΡ ΠΈ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΡΡ ΡΠ΅ΠΎΡΠΈΡ Π² ΡΠ΅Π»ΠΎΠΌ. Π¦Π΅Π»ΡΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠ²Π»ΡΠ΅ΡΡΡ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ° ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ΠΎΠ² ΠΊ ΠΎΠΏΠ΅ΡΠ°ΡΠΈΠ²Π½ΠΎΠΉ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΠΎΡΠ΅Π½ΠΊΠ΅ Π²Π»ΠΈΡΠ½ΠΈΡ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ Π½Π° ΡΠ½ΠΈΠ²Π΅ΡΡΠΈΡΠ΅Ρ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π΄Π°Π½Π½ΡΡ
ΡΡΠ΅ΡΠ½ΡΡ
ΡΠΈΠ½Π°Π½ΡΠΎΠ²ΡΡ
ΡΠΈΡΡΠ΅ΠΌ, ΠΈΡ
Π°ΠΏΡΠΎΠ±Π°ΡΠΈΡ ΠΈ Π³Π΅Π½Π΅ΡΠ°ΡΠΈΡ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΈΠΉ ΠΏΠΎ ΠΌΠΈΠ½ΠΈΠΌΠΈΠ·Π°ΡΠΈΠΈ ΡΠΈΡΠΊΠΎΠ² ΡΠΈΠ½Π°Π½ΡΠΎΠ²ΠΎ-Ρ
ΠΎΠ·ΡΠΉΡΡΠ²Π΅Π½Π½ΠΎΠΉ Π΄Π΅ΡΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ. ΠΠ°ΡΡΠ½Π°Ρ Π³ΠΈΠΏΠΎΡΠ΅Π·Π° ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠΎΡΡΠΎΠΈΡ Π² ΡΠΎΠΌ, ΡΡΠΎ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π°Π½Π°Π»ΠΈΠ·Π° Π΄Π°Π½Π½ΡΡ
, ΠΏΠ΅ΡΠ΅Π΄Π°Π²Π°Π΅ΠΌΡΡ
ΡΠΎΠ½Π΄Ρ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΡΡΠ°Ρ
ΠΎΠ²Π°Π½ΠΈΡ, ΠΎ Π½Π΅ΡΡΡΠ΄ΠΎΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ ΡΠΎΡΡΡΠ΄Π½ΠΈΠΊΠΎΠ² ΠΌΠΎΠΆΠ΅Ρ Π±ΡΡΡ ΠΏΠΎΠ²ΡΡΠ΅Π½Π° ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΡΠΈΡΠΊΠ°ΠΌΠΈ ΡΠΈΠ½Π°Π½ΡΠΎΠ²ΠΎ-Ρ
ΠΎΠ·ΡΠΉΡΡΠ²Π΅Π½Π½ΠΎΠΉ Π΄Π΅ΡΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ Π² ΡΡΠ»ΠΎΠ²ΠΈΡΡ
ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ Π½Π° ΡΡΠΎΠ²Π½Π΅ ΡΠ½ΠΈΠ²Π΅ΡΡΠΈΡΠ΅ΡΠ°. Π ΠΎΡΡ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠΈΠ²Π°Π΅ΡΡΡ ΠΊΠΎΡΡΠ΅ΠΊΡΠΈΠ΅ΠΉ ΠΏΠ»Π°Π½ΠΎΠ² ΠΏΠΎ ΠΌΠΈΠ½ΠΈΠΌΠΈΠ·Π°ΡΠΈΠΈ ΡΠΈΡΠΊΠΎΠ² Ρ ΡΡΠ΅ΡΠΎΠΌ Π½Π΅ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΠΎΡΡΠΈ Π²Π»ΠΈΡΠ½ΠΈΡ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ Π½Π° ΡΠΎΡΡΡΠ΄Π½ΠΈΠΊΠΎΠ² Π² Π·Π°Π²ΠΈΡΠΈΠΌΠΎΡΡΠΈ ΠΎΡ Π²ΠΎΠ·ΡΠ°ΡΡΠ°, Π³Π΅Π½Π΄Π΅ΡΠ°, ΠΏΡΠΈΠ½Π°Π΄Π»Π΅ΠΆΠ½ΠΎΡΡΠΈ ΠΊ ΠΊΠ°ΡΠ΅Π³ΠΎΡΠΈΠΈ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»Π°. ΠΠ»Ρ ΠΈΠ½ΡΠ΅Π³ΡΠ°ΡΠΈΠΈ ΠΈ Π°Π½Π°Π»ΠΈΠ·Π° Π΄Π°Π½Π½ΡΡ
Π°Π²ΡΠΎΡΠ°ΠΌΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π»ΠΈΡΡ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Ρ Data Science. ΠΠ° ΠΏΡΠΈΠΌΠ΅ΡΠ΅ Π΄Π°Π½Π½ΡΡ
Π£ΡΠ°Π»ΡΡΠΊΠΎΠ³ΠΎ ΡΠ΅Π΄Π΅ΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠ½ΠΈΠ²Π΅ΡΡΠΈΡΠ΅ΡΠ° ΠΏΠΎΠΊΠ°Π·Π°Π½Π° ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠ²Π½ΠΎΡΡΡ Π°Π½Π°Π»ΠΈΠ·ΠΈΡΡΠ΅ΠΌΡΡ
Π΄Π°Π½Π½ΡΡ
ΠΈ ΠΊΠ°ΠΊΠΈΠ΅ ΡΠΏΡΠ°Π²Π»Π΅Π½ΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ΅ΡΠ΅Π½ΠΈΡ ΠΏΠΎ ΠΌΠΈΠ½ΠΈΠΌΠΈΠ·Π°ΡΠΈΠΈ ΡΠΈΡΠΊΠΎΠ² ΠΌΠΎΠ³ΡΡ Π±ΡΡΡ ΠΏΡΠΈΠ½ΡΡΡ Π½Π° ΠΈΡ
ΠΎΡΠ½ΠΎΠ²Π΅. ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ ΠΊ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΌΡ Π°Π½Π°Π»ΠΈΠ·Ρ Π²ΠΎΠ·Π΄Π΅ΠΉΡΡΠ²ΠΈΡ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ Π½Π° ΡΠΎΡΡΡΠ΄Π½ΠΈΠΊΠΎΠ² ΡΡΠΈΠ΄ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π»ΠΈΡΠ°. ΠΡΠΎΠ΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΠΎΠ²Π°Π½Π° ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ Π΄ΠΈΡΡΠ°Π½ΡΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ Π΄Π»Ρ ΠΏΡΠΎΡΠΈΠ²ΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ, ΡΡΠ·Π²ΠΈΠΌΠΎΡΡΡ Π΄Π»Ρ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΡ
ΠΊΠ°ΡΠ΅Π³ΠΎΡΠΈΠΉ ΡΠΎΡΡΡΠ΄Π½ΠΈΠΊΠΎΠ², Π³Π΅Π½Π΄Π΅ΡΠ½Π°Ρ ΡΡΡΡΠΊΡΡΡΠ° Π½Π΅ΡΡΡΠ΄ΠΎΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ. Π’Π΅ΠΎΡΠ΅ΡΠΈΡΠ΅ΡΠΊΠ°Ρ Π·Π½Π°ΡΠΈΠΌΠΎΡΡΡ ΡΠ°Π±ΠΎΡΡ ΡΠΎΡΡΠΎΠΈΡ Π² ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ΅ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ΠΎΠ² ΠΊ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ ΡΠΈΠ½Π°Π½ΡΠΎΠ²ΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ Π΄Π»Ρ ΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½ΠΈΡ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΡΠΈΡΠΊΠ°ΠΌΠΈ. ΠΠΎΠ»ΡΡΠ΅Π½Π½Π°Ρ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡ ΠΌΠΎΠΆΠ΅Ρ Π±ΡΡΡ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½Π° Π½Π° ΠΏΡΠ°ΠΊΡΠΈΠΊΠ΅, Π² ΡΠ°ΡΡΠ½ΠΎΡΡΠΈ, Π΄Π»Ρ ΡΡΠΎΡΠ½Π΅Π½ΠΈΡ ΡΠ°ΡΡΠ΅ΡΠ° ΡΠ΅Π·Π΅ΡΠ²ΠΎΠ², ΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈΡ
Π·Π°Π΄Π°Π½ΠΈΠΉ ΠΏΡΠΈ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ΅ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠΈΡΡΠ΅ΠΌ.ΠΠ°Π½Π΄Π΅ΠΌΠΈΡ COVID-19 ΠΎΠΊΠ°Π·Π°Π»Π° ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ΅ Π²Π»ΠΈΡΠ½ΠΈΠ΅ Π½Π° ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΡ Π½Π° Π²ΡΠ΅Ρ
ΡΡΠΎΠ²Π½ΡΡ
, ΠΎΡ Π³Π»ΠΎΠ±Π°Π»ΡΠ½ΡΡ
ΡΡΠ½ΠΊΠΎΠ² Π΄ΠΎ ΠΌΠΈΠΊΡΠΎΠΏΡΠ΅Π΄ΠΏΡΠΈΡΡΠΈΠΉ. ΠΡΠΈ ΡΡΠΎΠΌ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΡ ΠΈ Π΅Π΅ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΠ²ΠΈΡ ΠΎΡΡΠ°Π²ΠΈΠ»ΠΈ ΡΠΈΡΠΎΠΊΠΈΠΉ ΡΠΈΡΡΠΎΠ²ΠΎΠΉ ΡΠ»Π΅Π΄. ΠΠ³ΠΎ ΠΈΠ·ΡΡΠ΅Π½ΠΈΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»ΡΠ΅ΡΡΡ ΡΡΠ΅Π·Π²ΡΡΠ°ΠΉΠ½ΠΎ Π°ΠΊΡΡΠ°Π»ΡΠ½ΡΠΌ, ΡΠ°ΠΊ ΠΊΠ°ΠΊ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Ρ ΠΊ Π°Π½Π°Π»ΠΈΠ·Ρ ΡΠΈΡΡΠΎΠ²ΠΎΠ³ΠΎ ΡΠ»Π΅Π΄Π° ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ ΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ Π΅Π³ΠΎ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² Π΄Π»Ρ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΡΠΈΡΠΊΠ°ΠΌΠΈ ΠΌΠΎΠ³ΡΡ Π±ΡΡΡ ΡΡΠΏΠ΅ΡΠ½ΠΎ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½Ρ Π² ΡΠ»ΡΡΠ°Π΅ Π²ΠΎΠ·Π½ΠΈΠΊΠ½ΠΎΠ²Π΅Π½ΠΈΡ Π°Π½Π°Π»ΠΎΠ³ΠΈΡΠ½ΡΡ
ΡΠ³ΡΠΎΠ·. ΠΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ ΠΏΡΠΎΠ±Π»Π΅ΠΌΡ ΠΏΡΠΈΠ·Π½Π°Π΅ΡΡΡ ΠΈ ΡΡΠ΅Π½ΡΠΌΠΈ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΡΠ°ΠΌΠΈ, ΠΊΠΎΡΠΎΡΡΠ΅ ΠΎΡΠΌΠ΅ΡΠ°ΡΡ ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ΅ Π²Π»ΠΈΡΠ½ΠΈΠ΅ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ Π½Π° ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΡ ΠΈ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΡΡ ΡΠ΅ΠΎΡΠΈΡ Π² ΡΠ΅Π»ΠΎΠΌ. Π¦Π΅Π»ΡΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠ²Π»ΡΠ΅ΡΡΡ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ° ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ΠΎΠ² ΠΊ ΠΎΠΏΠ΅ΡΠ°ΡΠΈΠ²Π½ΠΎΠΉ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΠΎΡΠ΅Π½ΠΊΠ΅ Π²Π»ΠΈΡΠ½ΠΈΡ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ Π½Π° ΡΠ½ΠΈΠ²Π΅ΡΡΠΈΡΠ΅Ρ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π΄Π°Π½Π½ΡΡ
ΡΡΠ΅ΡΠ½ΡΡ
ΡΠΈΠ½Π°Π½ΡΠΎΠ²ΡΡ
ΡΠΈΡΡΠ΅ΠΌ, ΠΈΡ
Π°ΠΏΡΠΎΠ±Π°ΡΠΈΡ ΠΈ Π³Π΅Π½Π΅ΡΠ°ΡΠΈΡ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΈΠΉ ΠΏΠΎ ΠΌΠΈΠ½ΠΈΠΌΠΈΠ·Π°ΡΠΈΠΈ ΡΠΈΡΠΊΠΎΠ² ΡΠΈΠ½Π°Π½ΡΠΎΠ²ΠΎ-Ρ
ΠΎΠ·ΡΠΉΡΡΠ²Π΅Π½Π½ΠΎΠΉ Π΄Π΅ΡΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ. ΠΠ°ΡΡΠ½Π°Ρ Π³ΠΈΠΏΠΎΡΠ΅Π·Π° ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠΎΡΡΠΎΠΈΡ Π² ΡΠΎΠΌ, ΡΡΠΎ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π°Π½Π°Π»ΠΈΠ·Π° Π΄Π°Π½Π½ΡΡ
, ΠΏΠ΅ΡΠ΅Π΄Π°Π²Π°Π΅ΠΌΡΡ
ΡΠΎΠ½Π΄Ρ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΡΡΠ°Ρ
ΠΎΠ²Π°Π½ΠΈΡ, ΠΎ Π½Π΅ΡΡΡΠ΄ΠΎΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ ΡΠΎΡΡΡΠ΄Π½ΠΈΠΊΠΎΠ² ΠΌΠΎΠΆΠ΅Ρ Π±ΡΡΡ ΠΏΠΎΠ²ΡΡΠ΅Π½Π° ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΡΠΈΡΠΊΠ°ΠΌΠΈ ΡΠΈΠ½Π°Π½ΡΠΎΠ²ΠΎ-Ρ
ΠΎΠ·ΡΠΉΡΡΠ²Π΅Π½Π½ΠΎΠΉ Π΄Π΅ΡΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ Π² ΡΡΠ»ΠΎΠ²ΠΈΡΡ
ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ Π½Π° ΡΡΠΎΠ²Π½Π΅ ΡΠ½ΠΈΠ²Π΅ΡΡΠΈΡΠ΅ΡΠ°. Π ΠΎΡΡ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠΈΠ²Π°Π΅ΡΡΡ ΠΊΠΎΡΡΠ΅ΠΊΡΠΈΠ΅ΠΉ ΠΏΠ»Π°Π½ΠΎΠ² ΠΏΠΎ ΠΌΠΈΠ½ΠΈΠΌΠΈΠ·Π°ΡΠΈΠΈ ΡΠΈΡΠΊΠΎΠ² Ρ ΡΡΠ΅ΡΠΎΠΌ Π½Π΅ΠΎΠ΄Π½ΠΎΡΠΎΠ΄Π½ΠΎΡΡΠΈ Π²Π»ΠΈΡΠ½ΠΈΡ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ Π½Π° ΡΠΎΡΡΡΠ΄Π½ΠΈΠΊΠΎΠ² Π² Π·Π°Π²ΠΈΡΠΈΠΌΠΎΡΡΠΈ ΠΎΡ Π²ΠΎΠ·ΡΠ°ΡΡΠ°, Π³Π΅Π½Π΄Π΅ΡΠ°, ΠΏΡΠΈΠ½Π°Π΄Π»Π΅ΠΆΠ½ΠΎΡΡΠΈ ΠΊ ΠΊΠ°ΡΠ΅Π³ΠΎΡΠΈΠΈ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»Π°. ΠΠ»Ρ ΠΈΠ½ΡΠ΅Π³ΡΠ°ΡΠΈΠΈ ΠΈ Π°Π½Π°Π»ΠΈΠ·Π° Π΄Π°Π½Π½ΡΡ
Π°Π²ΡΠΎΡΠ°ΠΌΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π»ΠΈΡΡ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Ρ Data Science. ΠΠ° ΠΏΡΠΈΠΌΠ΅ΡΠ΅ Π΄Π°Π½Π½ΡΡ
Π£ΡΠ°Π»ΡΡΠΊΠΎΠ³ΠΎ ΡΠ΅Π΄Π΅ΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠ½ΠΈΠ²Π΅ΡΡΠΈΡΠ΅ΡΠ° ΠΏΠΎΠΊΠ°Π·Π°Π½Π° ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠ²Π½ΠΎΡΡΡ Π°Π½Π°Π»ΠΈΠ·ΠΈΡΡΠ΅ΠΌΡΡ
Π΄Π°Π½Π½ΡΡ
ΠΈ ΠΊΠ°ΠΊΠΈΠ΅ ΡΠΏΡΠ°Π²Π»Π΅Π½ΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ΅ΡΠ΅Π½ΠΈΡ ΠΏΠΎ ΠΌΠΈΠ½ΠΈΠΌΠΈΠ·Π°ΡΠΈΠΈ ΡΠΈΡΠΊΠΎΠ² ΠΌΠΎΠ³ΡΡ Π±ΡΡΡ ΠΏΡΠΈΠ½ΡΡΡ Π½Π° ΠΈΡ
ΠΎΡΠ½ΠΎΠ²Π΅. ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ ΠΊ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΌΡ Π°Π½Π°Π»ΠΈΠ·Ρ Π²ΠΎΠ·Π΄Π΅ΠΉΡΡΠ²ΠΈΡ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ Π½Π° ΡΠΎΡΡΡΠ΄Π½ΠΈΠΊΠΎΠ² ΡΡΠΈΠ΄ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π»ΠΈΡΠ°. ΠΡΠΎΠ΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΠΎΠ²Π°Π½Π° ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ Π΄ΠΈΡΡΠ°Π½ΡΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ Π΄Π»Ρ ΠΏΡΠΎΡΠΈΠ²ΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ, ΡΡΠ·Π²ΠΈΠΌΠΎΡΡΡ Π΄Π»Ρ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΡ
ΠΊΠ°ΡΠ΅Π³ΠΎΡΠΈΠΉ ΡΠΎΡΡΡΠ΄Π½ΠΈΠΊΠΎΠ², Π³Π΅Π½Π΄Π΅ΡΠ½Π°Ρ ΡΡΡΡΠΊΡΡΡΠ° Π½Π΅ΡΡΡΠ΄ΠΎΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ. Π’Π΅ΠΎΡΠ΅ΡΠΈΡΠ΅ΡΠΊΠ°Ρ Π·Π½Π°ΡΠΈΠΌΠΎΡΡΡ ΡΠ°Π±ΠΎΡΡ ΡΠΎΡΡΠΎΠΈΡ Π² ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ΅ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ΠΎΠ² ΠΊ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ ΡΠΈΠ½Π°Π½ΡΠΎΠ²ΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ Π΄Π»Ρ ΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½ΠΈΡ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΡΠΈΡΠΊΠ°ΠΌΠΈ. ΠΠΎΠ»ΡΡΠ΅Π½Π½Π°Ρ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡ ΠΌΠΎΠΆΠ΅Ρ Π±ΡΡΡ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½Π° Π½Π° ΠΏΡΠ°ΠΊΡΠΈΠΊΠ΅, Π² ΡΠ°ΡΡΠ½ΠΎΡΡΠΈ, Π΄Π»Ρ ΡΡΠΎΡΠ½Π΅Π½ΠΈΡ ΡΠ°ΡΡΠ΅ΡΠ° ΡΠ΅Π·Π΅ΡΠ²ΠΎΠ², ΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈΡ
Π·Π°Π΄Π°Π½ΠΈΠΉ ΠΏΡΠΈ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ΅ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠΈΡΡΠ΅ΠΌ
Surface morphology and optical and magnetic properties of polyelectrolyte/magnetite nanoparticles nanofilms
Biomodification of Flax Fibrous Materials for Increase of Sorption to Organic Compounds
This paper was focused on the method to increase of the sorption properties in the flax fibrous material. This method was based on the original approach which includes the application of enzymatic catalysis as a destruction regulator of the polycarbohydrate components in the bast. The formed reaction products were used as reagents for reductive destruction of lignin. The changes in the fiber sorption capacity to the molecular markers were controlled after changing both the polymer composition of the fiber and the size of its pore. It was determined that the flax sorbents increase the adsorption of phenol vapors to 9β12 times and organic dyes from aqueous solutions to 4 times
Research and development potential of the Russian higher education institutions
The authors designate three problems in frames of this paper. First, to analyze the level of research activity of the best Russian universities at the start of the most important stage of higher education system reform - basing on the results of 2009-2010 and to assess what kind of resource they have received at their disposal from the state. Second, to understand which areas of research potential and how should the leading universities try to influence. Third, to assess the gap in the area of research and development potential that exists between the classified leading universities and other ones, to formulate ways to bridge this gap on the example of the Ural region. The approach to the assessment of research and development activity of the universities is suggested to solve these problems of comparison of methodologies for evaluating research results of universities in global rankings of higher education institutions. Basing on the results and conclusions, four key directions for significant growth of international level of scientific productivity of Russian universities are formulated
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