189 research outputs found

    Specific Absorption Rate of Assembly of Magnetite Nanoparticles with Cubic Magnetic Anisotropy

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    The presence of strong magnetic dipole interaction in assemblies of fractal clusters of nearly spherical magnetite nanoparticles, which arise in a biological media loaded with magnetic nanoparticles, leads to a significant decrease of the specific absorption rate of these assemblies in alternating magnetic field. However, the specific absorption rate of the assembly can be increased if the nanoparticles are covered by non magnetic shells of sufficiently large thickness comparable with the nanoparticle diameter. Keywords: Magnetite nanoparticles, Magneto- dipole interaction, Specific absorption rate, Numerical simulatio

    Dissipative Chaos in Semiconductor Superlattices

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    We consider the motion of ballistic electrons in a miniband of a semiconductor superlattice (SSL) under the influence of an external, time-periodic electric field. We use the semi-classical balance-equation approach which incorporates elastic and inelastic scattering (as dissipation) and the self-consistent field generated by the electron motion. The coupling of electrons in the miniband to the self-consistent field produces a cooperative nonlinear oscillatory mode which, when interacting with the oscillatory external field and the intrinsic Bloch-type oscillatory mode, can lead to complicated dynamics, including dissipative chaos. For a range of values of the dissipation parameters we determine the regions in the amplitude-frequency plane of the external field in which chaos can occur. Our results suggest that for terahertz external fields of the amplitudes achieved by present-day free electron lasers, chaos may be observable in SSLs. We clarify the nature of this novel nonlinear dynamics in the superlattice-external field system by exploring analogies to the Dicke model of an ensemble of two-level atoms coupled with a resonant cavity field and to Josephson junctions.Comment: 33 pages, 8 figure

    Mechanical, Structural and Scaling Properties of Coals: Depth-sensing Indentation Studies

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    This paper discusses special features of mechanical behaviour of coals discovered using depth-sensing indentation (DSI) techniques along with other traditional methods of material testing. Many of the special features are caused by the presence of multiscale complex heterogeneous internal structures within the samples and brittleness of some coal components. Experimental methodology for studying mechanical properties of coals and other natural extreme materials like bones is discussed. It is argued that values of microhardness of bituminous coals correlate strongly with the maximum load; therefore, the use of this parameter in application to coals may be meaningless. For analysis of the force-displacement curves obtained by DSI, both Oliver–Pharr and Galanov–Dub approaches are employed. It is argued that during nanoindentation, the integrity of the internal structure of a coal sample within a small area of high stress field near the tip of indenter may be destroyed. Hence, the standard approaches to mechanical testing of coals should be re-examined. Β© 2019, Springer-Verlag GmbH Germany, part of Springer Nature.Acknowledgements Research was supported by the Russian Science Foundation (Grant β„– 16-17-10217)

    Π˜Π½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Π΅ возмоТности свСдСний административного ΡƒΡ‡Ρ‘Ρ‚Π° ΠΎ сдСлках с ΠΆΠΈΠ»ΠΎΠΉ Π½Π΅Π΄Π²ΠΈΠΆΠΈΠΌΠΎΡΡ‚ΡŒΡŽ для расчёта Ρ†Π΅Π½ Π½Π° российском Ρ€Ρ‹Π½ΠΊΠ΅ Тилья

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    Purpose of the study. Development, justification and testing of a methodology for improving statistical monitoring of average prices in the Russian housing market, based on the use of registration information of the Unified State Register of Real Estate (USRN) on transactions for the purchase of residential real estate, in accordance with international statistical standards for Residential Property Price statistics.Materials and methods. The theoretical basis of the study was the United Nations system of national accounts (version of 2008), including the European system of accounts as amended in 2010. The research methodological base was made up of official statistical sources: metadata and international statistics guidelines in the field of national accounting, Handbook on Residential Property Price Indices and related housing indicators, as well as methodological provisions and an album of Rosstat forms, and methodological materials of the administrative statistics of the Federal Service for State Registration, Cadastre and Cartography of the Russian Federation (Rosreestr). The depersonalized registration data on households’ market transactions of the Unified State Register of Property Rights and Transactions maintaining by Rosreestr were used as an information database of the research.Results. The main result of the study is the design and substantiation of a system of indicators for the construction of an integrated information source for Residential Property Price statistics, on the base on interdepartmental information interaction.Conclusion. The proposed system of indicators will provide a highquality database that could be used in order to construct constant quality House Prices for various types of homogeneous residential property in the housing market, complying with the concepts of international statistical standards.ЦСль исслСдования. Π Π°Π·Ρ€Π°Π±ΠΎΡ‚ΠΊΠ°, обоснованиС ΠΈ апробация ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠΈ ΡΠΎΠ²Π΅Ρ€ΡˆΠ΅Π½ΡΡ‚Π²ΠΎΠ²Π°Π½ΠΈΡ статистичСского наблюдСния Π·Π° срСдними Ρ†Π΅Π½Π°ΠΌΠΈ Π½Π° российском Ρ€Ρ‹Π½ΠΊΠ΅ Тилья, Π½Π° основС использования рСгистрационной ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ ΠΎ сдСлках ΠΏΠΎ ΠΊΡƒΠΏΠ»Π΅-ΠΏΡ€ΠΎΠ΄Π°ΠΆΠ΅ ΠΆΠΈΠ»ΠΎΠΉ нСдвиТимости Π² Π•Π΄ΠΈΠ½ΠΎΠΌ государствСнном рССстрС нСдвиТимости (ЕГРН), Π² соотвСтствии с ΠΌΠ΅ΠΆΠ΄ΡƒΠ½Π°Ρ€ΠΎΠ΄Π½Ρ‹ΠΌΠΈ ΡƒΡ‡Ρ‘Ρ‚Π½Ρ‹ΠΌΠΈ стандартами статистики Ρ†Π΅Π½ Π½Π° Ρ€Ρ‹Π½ΠΊΠ΅ ΠΆΠΈΠ»ΠΎΠΉ нСдвиТимости.ΠœΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π»Ρ‹ ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹. ВСорСтичСской основой исслСдования стала систСма Π½Π°Ρ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… счСтов ООН Π² Ρ€Π΅Π΄Π°ΠΊΡ†ΠΈΠΈ 2008 Π³ΠΎΠ΄Π°, Π² Ρ‚ΠΎΠΌ числС СвропСйской систСмы счСтов Π² Ρ€Π΅Π΄Π°ΠΊΡ†ΠΈΠΈ 2010 Π³ΠΎΠ΄Π°. ΠœΠ΅Ρ‚ΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡ‡Π΅ΡΠΊΡƒΡŽ Π±Π°Π·Ρƒ исслСдования составили ΠΎΡ„ΠΈΡ†ΠΈΠ°Π»ΡŒΠ½Ρ‹Π΅ статистичСскиС источники: ΠΌΠ΅Ρ‚Π°Π΄Π°Π½Π½Ρ‹Π΅ ΠΈ руководства ΠΌΠ΅ΠΆΠ΄ΡƒΠ½Π°Ρ€ΠΎΠ΄Π½ΠΎΠΉ статистики Π² области ΡƒΡ‡Ρ‘Ρ‚Π° ΠΈ Π°Π½Π°Π»ΠΈΠ·Π° Ρ†Π΅Π½ Π½Π° Ρ€Ρ‹Π½ΠΊΠ΅ ΠΆΠΈΠ»ΠΎΠΉ нСдвиТимости, мСтодологичСскиС полоТСния ΠΈ альбом Ρ„ΠΎΡ€ΠΌ Росстата, Π° Ρ‚Π°ΠΊΠΆΠ΅ ΠΌΠ΅Ρ‚Π°Π΄Π°Π½Π½Ρ‹Π΅ административной статистики Π€Π΅Π΄Π΅Ρ€Π°Π»ΡŒΠ½ΠΎΠΉ слуТбы государствСнной рСгистрации, кадастра ΠΈ ΠΊΠ°Ρ€Ρ‚ΠΎΠ³Ρ€Π°Ρ„ΠΈΠΈ (РосрССстра). Π’ качСствС ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½ΠΎΠΉ Π±Π°Π·Ρ‹ для провСдСния ΡΠΊΡΠΏΠ΅Ρ€ΠΈΠΌΠ΅Π½Ρ‚Π°Π»ΡŒΠ½Ρ‹Ρ… расчётов Π±Ρ‹Π»ΠΈ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Π½Ρ‹ дСпСрсонифицированныС свСдСния Π•Π΄ΠΈΠ½ΠΎΠ³ΠΎ государствСнного рССстра нСдвиТимости ΠΈ мСтодологичСскиС ΠΌΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π»Ρ‹ ΠΏΠΎ Π΅Π³ΠΎ вСдСнию.Π Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹. Π“Π»Π°Π²Π½Ρ‹ΠΌ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠΌ Π²Ρ‹ΠΏΠΎΠ»Π½Π΅Π½Π½ΠΎΠ³ΠΎ исслСдования прСдставляСтся конструированиС ΠΈ обоснованиС систСмы ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»Π΅ΠΉ для формирования ΠΈΠ½Ρ‚Π΅Π³Ρ€Π°Π»ΡŒΠ½ΠΎΠ³ΠΎ ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ Ρ„ΠΎΠ½Π΄Π° статистики Ρ†Π΅Π½ Π½Π° Ρ€Ρ‹Π½ΠΊΠ΅ Тилья, основанного Π½Π° мСТвСдомствСнном ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½ΠΎΠΌ взаимодСйствии.Π—Π°ΠΊΠ»ΡŽΡ‡Π΅Π½ΠΈΠ΅. ΠŸΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½Π½Π°Ρ систСма ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»Π΅ΠΉ обСспСчит качСствСнный, ΡΠΎΠΎΡ‚Π²Π΅Ρ‚ΡΡ‚Π²ΡƒΡŽΡ‰ΠΈΠΉ трСбованиям ΠΌΠ΅ΠΆΠ΄ΡƒΠ½Π°Ρ€ΠΎΠ΄Π½Ρ‹Ρ… стандартов расчёт срСдних Ρ†Π΅Π½ ΠΊΠ²Π°Π΄Ρ€Π°Ρ‚Π½ΠΎΠ³ΠΎ ΠΌΠ΅Ρ‚Ρ€Π° ΠΎΠ±Ρ‰Π΅ΠΉ ΠΏΠ»ΠΎΡ‰Π°Π΄ΠΈ ΠΊΠ²Π°Ρ€Ρ‚ΠΈΡ€ Π½Π° Ρ€Ρ‹Π½ΠΊΠ΅ ΠΆΠΈΠ»ΠΎΠΉ нСдвиТимости, Π² Ρ€Π°Π·Ρ€Π΅Π·Π΅ Π³Ρ€ΡƒΠΏΠΏ ΠΊΠ²Π°Ρ€Ρ‚ΠΈΡ€, ΠΎΠ΄Π½ΠΎΡ€ΠΎΠ΄Π½Ρ‹Ρ… ΠΏΠΎ Π½Π°Π±ΠΎΡ€Ρƒ основных установлСнных для Ρ„Π΅Π΄Π΅Ρ€Π°Π»ΡŒΠ½ΠΎΠ³ΠΎ статистичСского наблюдСния ΠΏΡ€ΠΈΠ·Π½Π°ΠΊΠΎΠ², Π½Π° ΠΊΠ²Π°Ρ€Ρ‚Π°Π»ΡŒΠ½ΠΎΠΉ ΠΈ Π³ΠΎΠ΄ΠΎΠ²ΠΎΠΉ основС

    ΠŸΡ€ΠΎΠ±Π»Π΅ΠΌΡ‹ Ρ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠΉ ΠΈΠ΄Π΅Π½Ρ‚ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΠΈ ΠΏΠΎΡ‚Π΅Ρ€ΡŒ производства ΠΎΡ‚ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ COVID-19 ΠΈ ΠΏΡƒΡ‚ΠΈ ΠΈΡ… Ρ€Π΅ΡˆΠ΅Π½ΠΈΡ Π² систСмС ΠΌΠ΅ΠΆΠ΄ΡƒΠ½Π°Ρ€ΠΎΠ΄Π½Ρ‹Ρ… статистичСских стандартов

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    Purpose of research. Analysis of the information capabilities of the methodology of the UN national accounts system as amended in 2008 to solve the problems of regional identification of production losses from the COVID-19 pandemic. The coronavirus infection pandemic caused a decline in production in almost all types of economic activity. The Russian government has identified a strategy to counter the extraordinary economic crisis triggered by the pandemic. The range of addressees of anti-crisis measures of the executive branch in the sectors of producers is determined, at the federal and regional levels, according to the main type of activity declared during registration, in accordance with the approved list of codes of the Russian National Classifier of Types of Economic Activity for the types of activities that are most affected by the pandemic and self-isolation regime. The approved list of such types of activities over the past 2 months has been repeatedly adjusted by the Government of the Russian Federation, taking into account the recommendations of experts and proposals of business-structures, in order to ensure the highest efficiency and targeted state support for manufacturers. Ensuring targeted state support during optimization of the federal resources distribution between regions - is an urgent task that requires accurate regional identification of production losses from the COVID-19 pandemic. However, the solution of this problem is significantly difficult in relation to the activities of multi-regional producers - enterprises that carry out production simultaneously in several territories of the Russian Federation. This is due to the characteristics of the organization system of statistical accounting of resources and production results in the enterprise sector. The paper considers the possibility of assessing the gross value added at the regional level for the aggregate of local producing units, grouped by the type of economic activity, based on methodological principles harmonized with international standards and guidelines of the current version of the national and regional accounts system and provided with resources of official (state and administrative) statistics of the Russian Federation.Materials and methods. The research information base was made up of official statistical sources: metadata and international statistics guidelines in the field of subnational accounting, methodological provisions and an album of ROSSTAT forms, as well as methodological materials of administrative statistics of the Federal Tax Service (FTS) and the Social Insurance Fund. The methodological basis of the study was the United Nations system of national accounts as amended in 2008, including the European system of regional accounts as amended in 2010.Results. The paper analyzes the principles of the European system of regional accounts, which are useful to use in Russian statistics for adequate accounting of the activities’ results of multiregional enterprises at the place of actual production and methodological approaches to assessing the number of such enterprises and the results of their production at the subnational level are proposed. The results obtained will allow us to estimate the loss of multiregional enterprises of different types of activity from the decline in production as a result of the ban on interregional relations during the COVID-19 pandemic, in order to determine the recipients of state support for enterprises in the regions. In particular, the proposed indicator for reducing the regional GVA for the most affected by the quarantine measures activities can be used as a condition for the allocation of funds as part of overcoming the consequences of the pandemic. The application of the proposed methodology in calculating the gross value added at the place of actual production for the aggregate of geographically separate divisions of multiregional enterprises will increase the targeting and effectiveness of state support for enterprises and entrepreneurs affected by the consequences of the spread of coronavirus infection, and will optimize the distribution of federal resources between regions, which is a prerequisite for successful overcoming β€œcoronacrisis”.ЦСль исслСдования. Анализ ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… возмоТностСй ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ систСма Π½Π°Ρ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… счСтов ООН Π² Ρ€Π΅Π΄Π°ΠΊΡ†ΠΈΠΈ 2008 Π³ΠΎΠ΄Π° для Ρ€Π΅ΡˆΠ΅Π½ΠΈΡ ΠΏΡ€ΠΎΠ±Π»Π΅ΠΌ Ρ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠΉ ΠΈΠ΄Π΅Π½Ρ‚ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΠΈ ΠΏΠΎΡ‚Π΅Ρ€ΡŒ производства ΠΎΡ‚ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ COVID-19. ПандСмия коронавирусной ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΈ Π²Ρ‹Π·Π²Π°Π»Π° спад производства практичСски Π²ΠΎ всСх Π²ΠΈΠ΄Π°Ρ… экономичСской Π΄Π΅ΡΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ. ΠŸΡ€Π°Π²ΠΈΡ‚Π΅Π»ΡŒΡΡ‚Π²ΠΎ Π Π€ ΠΎΠΏΡ€Π΅Π΄Π΅Π»ΠΈΠ»ΠΎ ΡΡ‚Ρ€Π°Ρ‚Π΅Π³ΠΈΡŽ противодСйствия Ρ‚Π΅ΠΊΡƒΡ‰Π΅ΠΌΡƒ экономичСскому кризису, спровоцированному ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠ΅ΠΉ. ΠšΡ€ΡƒΠ³ адрСсатов антикризисных мСроприятий ΠΈΡΠΏΠΎΠ»Π½ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΠΉ власти Π² сСкторах ΠΏΡ€ΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡ‚Π΅Π»Π΅ΠΉ опрСдСляСтся ΠΈ Π½Π° Ρ„Π΅Π΄Π΅Ρ€Π°Π»ΡŒΠ½ΠΎΠΌ, ΠΈ Π½Π° Ρ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠΌ ΡƒΡ€ΠΎΠ²Π½Π΅ ΠΏΠΎ заявлСнному ΠΏΡ€ΠΈ рСгистрации основному Π²ΠΈΠ΄Ρƒ Π΄Π΅ΡΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ, Π² соотвСтствии с ΡƒΡ‚Π²Π΅Ρ€ΠΆΠ΄Π΅Π½Π½Ρ‹ΠΌ ΠΏΠ΅Ρ€Π΅Ρ‡Π½Π΅ΠΌ ΠΊΠΎΠ΄ΠΎΠ² ΠžΠšΠ’Π­Π” Π²ΠΈΠ΄ΠΎΠ² Π΄Π΅ΡΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ, Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΠΏΠΎΡΡ‚Ρ€Π°Π΄Π°Π²ΡˆΠΈΡ… ΠΎΡ‚ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ ΠΈ Ρ€Π΅ΠΆΠΈΠΌΠ° самоизоляции. Π£Ρ‚Π²Π΅Ρ€ΠΆΠ΄Ρ‘Π½Π½Ρ‹ΠΉ ΠΏΠ΅Ρ€Π΅Ρ‡Π΅Π½ΡŒ Ρ‚Π°ΠΊΠΈΡ… Π²ΠΈΠ΄ΠΎΠ² Π΄Π΅ΡΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ Π·Π° послСдниС 2 мСсяца Π½Π΅ΠΎΠ΄Π½ΠΎΠΊΡ€Π°Ρ‚Π½ΠΎ коррСктировался ΠŸΡ€Π°Π²ΠΈΡ‚Π΅Π»ΡŒΡΡ‚Π²ΠΎΠΌ Π Π€, с ΡƒΡ‡Ρ‘Ρ‚ΠΎΠΌ Ρ€Π΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°Ρ†ΠΈΠΉ экспСртов ΠΈ ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΈΠΉ бизнСс – структур, Ρ‡Ρ‚ΠΎΠ±Ρ‹ ΠΎΠ±Π΅ΡΠΏΠ΅Ρ‡ΠΈΡ‚ΡŒ Π½Π°ΠΈΠ±ΠΎΠ»ΡŒΡˆΡƒΡŽ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΈΠ²Π½ΠΎΡΡ‚ΡŒ ΠΈ Π°Π΄Ρ€Π΅ΡΠ½ΠΎΡΡ‚ΡŒ государствСнной ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΊΠΈ ΠΏΡ€ΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡ‚Π΅Π»Π΅ΠΉ. ΠžΠ±Π΅ΡΠΏΠ΅Ρ‡Π΅Π½ΠΈΠ΅ адрСсности государствСнной ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΊΠΈ ΠΏΡ€ΠΈ ΠΎΠΏΡ‚ΠΈΠΌΠΈΠ·Π°Ρ†ΠΈΠΈ распрСдСлСния ΠΌΠ΅ΠΆΠ΄Ρƒ Ρ€Π΅Π³ΠΈΠΎΠ½Π°ΠΌΠΈ Ρ„Π΅Π΄Π΅Ρ€Π°Π»ΡŒΠ½Ρ‹Ρ… рСсурсов – это Π°ΠΊΡ‚ΡƒΠ°Π»ΡŒΠ½Π°Ρ Π·Π°Π΄Π°Ρ‡Π°, которая Ρ‚Ρ€Π΅Π±ΡƒΠ΅Ρ‚ Ρ‚ΠΎΡ‡Π½ΠΎΠΉ Ρ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠΉ ΠΈΠ΄Π΅Π½Ρ‚ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΠΈ ΠΏΠΎΡ‚Π΅Ρ€ΡŒ производства ΠΎΡ‚ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ COVID-19. Однако Ρ€Π΅ΡˆΠ΅Π½ΠΈΠ΅ этой Π·Π°Π΄Π°Ρ‡ΠΈ сущСствСнно Π·Π°Ρ‚Ρ€ΡƒΠ΄Π½Π΅Π½ΠΎ Π² ΠΎΡ‚Π½ΠΎΡˆΠ΅Π½ΠΈΠΈ Π΄Π΅ΡΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ ΠΌΡƒΠ»ΡŒΡ‚ΠΈΡ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… ΠΏΡ€ΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡ‚Π΅Π»Π΅ΠΉ – прСдприятий, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ ΠΎΡΡƒΡ‰Π΅ΡΡ‚Π²Π»ΡΡŽΡ‚ производство ΠΎΠ΄Π½ΠΎΠ²Ρ€Π΅ΠΌΠ΅Π½Π½ΠΎ Π½Π° Π½Π΅ΡΠΊΠΎΠ»ΡŒΠΊΠΈΡ… тСрриториях Π Π€. Π­Ρ‚ΠΎ обусловлСно особСнностями ΠΎΡ€Π³Π°Π½ΠΈΠ·Π°Ρ†ΠΈΠΈ систСма статистичСского ΡƒΡ‡Ρ‘Ρ‚Π° рСсурсов ΠΈ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² производства Π² сСкторС прСдприятий. Π’ Ρ€Π°Π±ΠΎΡ‚Π΅ Ρ€Π°ΡΡΠΌΠ°Ρ‚Ρ€ΠΈΠ²Π°ΡŽΡ‚ΡΡ возмоТности ΠΎΡ†Π΅Π½ΠΊΠΈ Π²Π°Π»ΠΎΠ²ΠΎΠΉ Π΄ΠΎΠ±Π°Π²Π»Π΅Π½Π½ΠΎΠΉ стоимости Π½Π° Ρ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠΌ ΡƒΡ€ΠΎΠ²Π½Π΅ для совокупности мСстных производящих Π΅Π΄ΠΈΠ½ΠΈΡ†, сгруппированных ΠΏΠΎ Π²ΠΈΠ΄Π°ΠΌ экономичСской Π΄Π΅ΡΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ, Π½Π° основС мСтодологичСских ΠΏΡ€ΠΈΠ½Ρ†ΠΈΠΏΠΎΠ², Π³Π°Ρ€ΠΌΠΎΠ½ΠΈΠ·ΠΈΡ€ΠΎΠ²Π°Π½Π½Ρ‹Ρ… с ΠΌΠ΅ΠΆΠ΄ΡƒΠ½Π°Ρ€ΠΎΠ΄Π½Ρ‹ΠΌΠΈ стандартами ΠΈ руководствами Π°ΠΊΡ‚ΡƒΠ°Π»ΡŒΠ½ΠΎΠΉ вСрсии систСмы Π½Π°Ρ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… ΠΈ Ρ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… счСтов ΠΈ обСспСчСнных рСсурсами ΠΎΡ„ΠΈΡ†ΠΈΠ°Π»ΡŒΠ½ΠΎΠΉ (государствСнной ΠΈ административной) статистики Π Π€.ΠœΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π»Ρ‹ ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹. Π˜Π½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½ΡƒΡŽ Π±Π°Π·Ρƒ исслСдования составили ΠΎΡ„ΠΈΡ†ΠΈΠ°Π»ΡŒΠ½Ρ‹Π΅ статистичСскиС источники: ΠΌΠ΅Ρ‚Π°- Π΄Π°Π½Π½Ρ‹Π΅ ΠΈ руководства ΠΌΠ΅ΠΆΠ΄ΡƒΠ½Π°Ρ€ΠΎΠ΄Π½ΠΎΠΉ статистики Π² области ΡΡƒΠ±Π½Π°Ρ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠ³ΠΎ ΡƒΡ‡Ρ‘Ρ‚Π°, мСтодологичСскиС полоТСния ΠΈ альбом Ρ„ΠΎΡ€ΠΌ Росстата, Π° Ρ‚Π°ΠΊΠΆΠ΅ мСтодологичСскиС ΠΌΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π»Ρ‹ административной статистики Π€Π΅Π΄Π΅Ρ€Π°Π»ΡŒΠ½ΠΎΠΉ Π½Π°Π»ΠΎΠ³ΠΎΠ²ΠΎΠΉ слуТбы (ЀНБ) ΠΈ Π€ΠΎΠ½Π΄Π° ΡΠΎΡ†ΠΈΠ°Π»ΡŒΠ½ΠΎΠ³ΠΎ страхования (Π€Π‘Π‘). ΠœΠ΅Ρ‚ΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡ‡Π΅ΡΠΊΠΎΠΉ основой исслСдования стала систСма Π½Π°Ρ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… счСтов ООН Π² Ρ€Π΅Π΄Π°ΠΊΡ†ΠΈΠΈ 2008 Π³ΠΎΠ΄Π°, Π² Ρ‚ΠΎΠΌ числС СвропСйской систСмы Ρ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… счСтов Π² Ρ€Π΅Π΄Π°ΠΊΡ†ΠΈΠΈ 2010 Π³ΠΎΠ΄Π°.Π Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹. Π’ Ρ€Π°Π±ΠΎΡ‚Π΅ ΠΏΡ€ΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡ€ΠΎΠ²Π°Π½Ρ‹ ΠΏΡ€ΠΈΠ½Ρ†ΠΈΠΏΡ‹ СвропСйской систСмы Ρ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… счСтов, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ ΠΏΠΎΠ»Π΅Π·Π½ΠΎ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Ρ‚ΡŒ Π² российской статистикС для Π°Π΄Π΅ΠΊΠ²Π°Ρ‚Π½ΠΎΠ³ΠΎ ΡƒΡ‡Ρ‘Ρ‚Π° Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² Π΄Π΅ΡΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ ΠΌΡƒΠ»ΡŒΡ‚ΠΈΡ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… прСдприятий ΠΏΠΎ мСсту фактичСского производства ΠΈ ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½Ρ‹ мСтодологичСскиС ΠΏΠΎΠ΄Ρ…ΠΎΠ΄Ρ‹ ΠΊ ΠΎΡ†Π΅Π½ΠΊΠ΅ количСства Ρ‚Π°ΠΊΠΈΡ… прСдприятий ΠΈ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² ΠΈΡ… производства Π½Π° ΡΡƒΠ±Π½Π°Ρ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠΌ ΡƒΡ€ΠΎΠ²Π½Π΅. ΠŸΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹Π΅ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ позволят Π°Π΄Π΅ΠΊΠ²Π°Ρ‚Π½ΠΎ ΠΎΡ†Π΅Π½ΠΈΡ‚ΡŒ ΠΏΠΎΡ‚Π΅Ρ€ΠΈ ΠΌΡƒΠ»ΡŒΡ‚ΠΈΡ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… прСдприятий Ρ€Π°Π·Π½Ρ‹Ρ… Π²ΠΈΠ΄ΠΎΠ² Π΄Π΅ΡΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ ΠΎΡ‚ спада производства Π² Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Π΅ Π·Π°ΠΏΡ€Π΅Ρ‚Π° Π½Π° ΠΌΠ΅ΠΆΡ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Π΅ связи Π² ΠΏΠ΅Ρ€ΠΈΠΎΠ΄ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ COVID-19, с Ρ†Π΅Π»ΡŒΡŽ опрСдСлСния ΠΏΠΎΠ»ΡƒΡ‡Π°Ρ‚Π΅Π»Π΅ΠΉ государствСнной ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΊΠΈ прСдприятий Π² Ρ€Π΅Π³ΠΈΠΎΠ½Π°Ρ…. Π’ частности, ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½Π½Ρ‹ΠΉ ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»ΡŒ сниТСния Ρ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠΉ Π’Π”Π‘ ΠΏΠΎ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΠΏΠΎΡΡ‚Ρ€Π°Π΄Π°Π²ΡˆΠΈΠΌ ΠΎΡ‚ ΠΊΠ°Ρ€Π°Π½Ρ‚ΠΈΠ½Π½Ρ‹Ρ… ΠΌΠ΅Ρ€ Π²ΠΈΠ΄Π°ΠΌ Π΄Π΅ΡΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ ΠΌΠΎΠΆΠ΅Ρ‚ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Ρ‚ΡŒΡΡ Π² качСствС условия ΠΏΡ€ΠΈ Π²Ρ‹Π΄Π΅Π»Π΅Π½ΠΈΠΈ Ρ„ΠΎΠ½Π΄ΠΎΠ² Π² Ρ€Π°ΠΌΠΊΠ°Ρ… прСодолСния послСдствий ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ. ΠŸΡ€ΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΠΎΠΉ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ Π² расчётах Π²Π°Π»ΠΎΠ²ΠΎΠΉ Π΄ΠΎΠ±Π°Π²Π»Π΅Π½Π½ΠΎΠΉ стоимости ΠΏΠΎ мСсту фактичСского производства для совокупности Ρ‚Π΅Ρ€Ρ€ΠΈΡ‚ΠΎΡ€ΠΈΠ°Π»ΡŒΠ½ΠΎ обособлСнных ΠΏΠΎΠ΄Ρ€Π°Π·Π΄Π΅Π»Π΅Π½ΠΈΠΉ ΠΌΡƒΠ»ΡŒΡ‚ΠΈΡ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… прСдприятий повысит Π°Π΄Ρ€Π΅ΡΠ½ΠΎΡΡ‚ΡŒ ΠΈ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΈΠ²Π½ΠΎΡΡ‚ΡŒ государствСнной ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΊΠΈ прСдприятий ΠΈ ΠΏΡ€Π΅Π΄ΠΏΡ€ΠΈΠ½ΠΈΠΌΠ°Ρ‚Π΅Π»Π΅ΠΉ, ΠΏΠΎΡΡ‚Ρ€Π°Π΄Π°Π²ΡˆΠΈΡ… ΠΎΡ‚ послСдствий распространСния коронавирусной ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΈ, ΠΈ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΡ‚ ΠΎΠΏΡ‚ΠΈΠΌΠΈΠ·ΠΈΡ€ΠΎΠ²Π°Ρ‚ΡŒ распрС- Π΄Π΅Π»Π΅Π½ΠΈΠ΅ Ρ„Π΅Π΄Π΅Ρ€Π°Π»ΡŒΠ½Ρ‹Ρ… рСсурсов ΠΌΠ΅ΠΆΠ΄Ρƒ Ρ€Π΅Π³ΠΈΠΎΠ½Π°ΠΌΠΈ, Ρ‡Ρ‚ΠΎ являСтся Π½Π΅ΠΎΠ±Ρ…ΠΎΠ΄ΠΈΠΌΡ‹ΠΌ условиСм ΡƒΡΠΏΠ΅ΡˆΠ½ΠΎΠ³ΠΎ прСодолСния «коронакризиса»

    Oligomerization of the E. coli Core RNA Polymerase: Formation of (Ξ±2Ξ²Ξ²'Ο‰)2–DNA Complexes and Regulation of the Oligomerization by Auxiliary Subunits

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    In this work, using multiple, dissimilar physico-chemical techniques, we demonstrate that the Escherichia coli RNA polymerase core enzyme obtained through a classic purification procedure forms stable (Ξ±2Ξ²Ξ²'Ο‰)2 complexes in the presence or absence of short DNA probes. Multiple control experiments indicate that this self-association is unlikely to be mediated by RNA polymerase-associated non-protein molecules. We show that the formation of (Ξ±2Ξ²Ξ²'Ο‰)2 complexes is subject to regulation by known RNA polymerase interactors, such as the auxiliary SWI/SNF subunit of RNA polymerase RapA, as well as NusA and Οƒ70. We also demonstrate that the separation of the core RNA polymerase and RNA polymerase holoenzyme species during Mono Q chromatography is likely due to oligomerization of the core enzyme. We have analyzed the oligomeric state of the polymerase in the presence or absence of DNA, an aspect that was missing from previous studies. Importantly, our work demonstrates that RNA polymerase oligomerization is compatible with DNA binding. Through in vitro transcription and in vivo experiments (utilizing a RapAR599/Q602 mutant lacking transcription-stimulatory function), we demonstrate that the formation of tandem (Ξ±2Ξ²Ξ²'Ο‰)2–DNA complexes is likely functionally significant and beneficial for the transcriptional activity of the polymerase. Taken together, our findings suggest a novel structural aspect of the E. coli elongation complex. We hypothesize that transcription by tandem RNA polymerase complexes initiated at hypothetical bidirectional β€œorigins of transcription” may explain recurring switches of the direction of transcription in bacterial genomes

    The 3-Base Periodicity and Codon Usage of Coding Sequences Are Correlated with Gene Expression at the Level of Transcription Elongation

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    Background: Gene transcription is regulated by DNA transcriptional regulatory elements, promoters and enhancers that are located outside the coding regions. Here, we examine the characteristic 3-base periodicity of the coding sequences and analyse its correlation with the genome-wide transcriptional profile of yeast. Principal Findings: The analysis of coding sequences by a new class of indices proposed here identified two different sources of 3-base periodicity: the codon frequency and the codon sequence. In exponentially growing yeast cells, the codon-frequency component of periodicity accounts for 71.9 % of the variability of the cellular mRNA by a strong association with the density of elongating mRNA polymerase II complexes. The mRNA abundance explains most of the correlation between the codon-frequency component of periodicity and protein levels. Furthermore, pyrimidine-ending codons of the four-fold degenerate small amino acids alanine, glycine and valine are associated with genes with double the transcription rate of those associated with purine-ending codons. Conclusions: We demonstrate that the 3-base periodicity of coding sequences is higher than expected by the codon usage frequency (CUF) and that its components, associated with codon bias and amino acid composition, are correlated with gene expression, principally at the level of transcription elongation. This indicates a role of codon sequences in maximising the transcription efficiency in exponentially growing yeast cells. Moreover, the results contrast with the common Darwinia

    The Generation of Promoter-Mediated Transcriptional Noise in Bacteria

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    Noise in the expression of a gene produces fluctuations in the concentration of the gene product. These fluctuations can interfere with optimal function or can be exploited to generate beneficial diversity between cells; gene expression noise is therefore expected to be subject to evolutionary pressure. Shifts between modes of high and low rates of transcription initiation at a promoter appear to contribute to this noise both in eukaryotes and prokaryotes. However, models invoked for eukaryotic promoter noise such as stable activation scaffolds or persistent nucleosome alterations seem unlikely to apply to prokaryotic promoters. We consider the relative importance of the steps required for transcription initiation. The 3-step transcription initiation model of McClure is extended into a mathematical model that can be used to predict consequences of additional promoter properties. We show in principle that the transcriptional bursting observed at an E. coli promoter by Golding et al. (2005) can be explained by stimulation of initiation by the negative supercoiling behind a transcribing RNA polymerase (RNAP) or by the formation of moribund or dead-end RNAP-promoter complexes. Both mechanisms are tunable by the alteration of promoter kinetics and therefore allow the optimization of promoter mediated noise.Comment: 4 figures, 1 table. Supplemental materials are also include
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