263 research outputs found
Practical Computing with Pattern Structures in FCART Environment
International audienceA new general and efficient architecture for working with pattern structures, an extension of FCA for dealing with "complex" descriptions, is introduced and implemented in a subsystem of Formal Concept Analysis Research Toolbox (FCART). The architecture is universal in terms of possible dataset structures and formats, techniques of pattern structure manipulation
Concept Relation Discovery and Innovation Enabling Technology (CORDIET)
Concept Relation Discovery and Innovation Enabling Technology (CORDIET), is a
toolbox for gaining new knowledge from unstructured text data. At the core of
CORDIET is the C-K theory which captures the essential elements of innovation.
The tool uses Formal Concept Analysis (FCA), Emergent Self Organizing Maps
(ESOM) and Hidden Markov Models (HMM) as main artifacts in the analysis
process. The user can define temporal, text mining and compound attributes. The
text mining attributes are used to analyze the unstructured text in documents,
the temporal attributes use these document's timestamps for analysis. The
compound attributes are XML rules based on text mining and temporal attributes.
The user can cluster objects with object-cluster rules and can chop the data in
pieces with segmentation rules. The artifacts are optimized for efficient data
analysis; object labels in the FCA lattice and ESOM map contain an URL on which
the user can click to open the selected document
Collaborative Technologies in Education: How to Build an Effective System for Blended Learning?
Π‘ΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠ΅ ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎ ΠΈΠ·ΠΌΠ΅Π½ΠΈΠ»ΠΎΡΡ ΠΏΠΎΠ΄ Π²Π»ΠΈΡΠ½ΠΈΠ΅ΠΌ ΠΏΠΎΠ²ΡΠ΅ΠΌΠ΅ΡΡΠ½ΠΎ ΠΏΡΠΎΠ½ΠΈΠΊΠ°ΡΡΠΈΡ
Π² Π½Π΅Π³ΠΎ ΡΠΈΡΡΠΎΠ²ΡΡ
ΡΠ΅ΡΠ΅Π½ΠΈΠΉ, ΡΡΠ°Π½ΠΎΠ²ΡΡΡΡ ΠΏΠΎΠΏΡΠ»ΡΡΠ½ΡΠΌΠΈ ΡΠ°Π½Π΅Π΅ Π½Π΅Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΡΠ΅ ΡΠΎΡΠΌΡ ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΠΈ ΡΡΠ΅Π±Π½ΠΎΠ³ΠΎ ΠΏΡΠΎΡΠ΅ΡΡΠ°. ΠΠ΄Π½ΠΎΠΉ ΠΈΠ· ΡΠ°ΠΊΠΈΡ
ΡΠΎΡΠΌ ΡΠ²Π»ΡΠ΅ΡΡΡ Π³ΠΈΠ±ΡΠΈΠ΄Π½ΠΎΠ΅ ΠΎΠ±ΡΡΠ΅Π½ΠΈΠ΅, ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠ° ΠΊΠΎΡΠΎΡΠΎΠ³ΠΎ ΡΡΠ°Π»Π° Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΠΉ ΠΏΠΎΠ²ΡΠ΅ΠΌΠ΅ΡΡΠ½ΠΎ Π±Π»Π°Π³ΠΎΠ΄Π°ΡΡ Π³Π»ΠΎΠ±Π°Π»ΡΠ½ΠΎΠΌΡ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΡ ΠΈ ΠΊΠΎΠ½Π²Π΅ΡΠ³Π΅Π½ΡΠΈΠΈ ΡΠ΅Π»Π΅ΠΊΠΎΠΌΠΌΡΠ½ΠΈΠΊΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΠΎΠ·Π΄Π°Π½ΠΈΡ ΠΎΠ±Π»Π°ΡΠ½ΡΡ
ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠΈΡΡΠ΅ΠΌ ΡΡΠ΅Π±Π½ΠΎΠ³ΠΎ Π½Π°Π·Π½Π°ΡΠ΅Π½ΠΈΡ. Π¦ΠΈΡΡΠΎΠ²ΡΠ΅ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΏΡΠΈΠ½ΠΎΡΡΡ Π½Π΅ ΡΠΎΠ»ΡΠΊΠΎ Π²ΠΈΠ΄ΠΈΠΌΡΠ΅ ΠΏΡΠ΅Π»Π΅ΡΡΠΈ Π°Π²ΡΠΎΠΌΠ°ΡΠΈΠ·Π°ΡΠΈΠΈ ΡΡΡΠΈΠ½Π½ΡΡ
ΠΎΠΏΠ΅ΡΠ°ΡΠΈΠΉ, Π½ΠΎ ΠΈ ΡΡΠ°Π½ΠΎΠ²ΡΡΡΡ ΠΏΡΠΈΡΠΈΠ½ΠΎΠΉ ΠΏΠ΅ΡΠ΅ΠΎΡΠΌΡΡΠ»Π΅Π½ΠΈΡ ΠΈ ΡΡΠ°Π½ΡΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΡΡΠ°Π²ΡΠΈΡ
ΠΏΡΠΈΠ²ΡΡΠ½ΡΠΌΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² Π½Π΅ ΡΠΎΠ»ΡΠΊΠΎ Π² ΠΏΡΠ΅ΠΏΠΎΠ΄Π°Π²Π°Π½ΠΈΠΈ, Π½ΠΎ ΠΈ Π² ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΠΈ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠΌ ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ. ΠΠ°Π½Π½Π°Ρ ΡΠ°Π±ΠΎΡΠ° ΡΡΠΎΠΊΡΡΠΈΡΠΎΠ²Π°Π½Π° Π½Π° Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡΡ
, ΠΏΡΠ΅Π΄ΠΎΡΡΠ°Π²Π»ΡΠ΅ΠΌΡΡ
ΠΊΠΎΠ»Π»Π°Π±ΠΎΡΠ°ΡΠΈΠ²Π½ΡΠΌΠΈ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΠΌΠΈ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠΌΠΈ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠΈ ΡΡΠ΅Π±Π½ΠΎΠ³ΠΎ ΠΏΡΠΎΡΠ΅ΡΡΠ°, ΠΈ ΠΎΡΠ²Π΅ΡΠ°Π΅Ρ Π½Π° Π½Π΅ΠΊΠΎΡΠΎΡΡΠ΅ Π²Π°ΠΆΠ½ΡΠ΅ Π²ΠΎΠΏΡΠΎΡΡ, ΡΠ²ΡΠ·Π°Π½Π½ΡΠ΅ Ρ ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΠ΅ΠΉ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠΉ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠΈ Π³ΠΈΠ±ΡΠΈΠ΄Π½ΠΎΠ³ΠΎ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ, Π² ΡΠΎΠΌ ΡΠΈΡΠ»Π΅ Π½Π° ΡΡΠΎΠ²Π½Π΅ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ.Nowadays education has been significantly transformed by the widespread use of digital solutions. This has made it popular to carry out the new approaches to educational processes, which cannot be easily implemented before. Πne of such forms is blended learning, and it becomes possible everywhere thanks to the global distribution and convergence of telecommunication technologies and to the appearance of cloud-based educational software. At the same time digital technologies have brought the apparent profit for the routines automatization and have become the reason of rethinking as in casual teaching and learning processes as in the modern educational management. This paper focuses on how to support educational processes with technologies. It is also answers several significant questions about effective blended learning support, especially at the administration level.Π‘ΡΠ°ΡΡΡ ΠΏΠΎΠ΄Π³ΠΎΡΠΎΠ²Π»Π΅Π½Π° Π² Ρ
ΠΎΠ΄Π΅ ΡΠ°Π±ΠΎΡ Π² ΡΠ°ΠΌΠΊΠ°Ρ
ΠΡΠΎΠ³ΡΠ°ΠΌΠΌΡ ΡΡΠ½Π΄Π°ΠΌΠ΅Π½ΡΠ°Π»ΡΠ½ΡΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ ΠΠ°ΡΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ ΡΠ½ΠΈΠ²Π΅ΡΡΠΈΡΠ΅ΡΠ° Β«ΠΡΡΡΠ°Ρ ΡΠΊΠΎΠ»Π° ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈΒ» (ΠΠΠ£ ΠΠ¨Π) ΠΈ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΡΡΠ΅Π΄ΡΡΠ² ΡΡΠ±ΡΠΈΠ΄ΠΈΠΈ Π² ΡΠ°ΠΌΠΊΠ°Ρ
Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠΈ Π²Π΅Π΄ΡΡΠΈΡ
ΡΠ½ΠΈΠ²Π΅ΡΡΠΈΡΠ΅ΡΠΎΠ² Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ 5β100
Analysis of User Activity in Wireless Local Area Network of Petrozavodsk State University
Wireless networks are widely used for Internet access in public places, trading centers and educational institutions. The study of users' activity in these places can help solve problems of marketing, security, location, and monitoring of public transport. The article describes an experiment to measure the activity of users in wireless networks of Petrozavodsk State University because some educational and administrative processes are slowed because of a strict speed limit for all users. The authors developed a method to determine users' activity without the access to the service equipment and personal data, as well as a software complex to implement this method. Then they collected and analyzed data on the hours of the highest and lowliest activity, class schedule effect, and the dynamics of users' returns to the network. The information obtained was used to determine the allowed constraints of the Internet access speed for network users. A number of equations take into account the typical behavior of wireless network users, their activity and the capacity of external network channels. Computed rates for speed limits significantly exceed the established indicators in the network of Petrozavodsk University during hours of average and minimum network load. The results obtained can be used in corporate networks to dynamically calculate the permissible speed limit and to improve the quality of user service
Exonic enhancers: proceed with caution in exome and genome sequencing studies
Exonic enhancers (eExons) are coding exons that also function as enhancers of the gene in which they reside or (a) nearby gene(s). Mutations that affect the enhancer activity of these eExons have been associated with human disease. Therefore, eExon mutations should be taken into account in exome and genome sequencing projects, not only because of the ability of these mutations to modify the encoded proteins but also because of their effects on enhancer activity
Different Effect of Proteasome Inhibition on Vesicular Stomatitis Virus and Poliovirus Replication
Proteasome activity is an important part of viral replication. In this study, we examined the effect of proteasome inhibitors on the replication of vesicular stomatitis virus (VSV) and poliovirus. We found that the proteasome inhibitors significantly suppressed VSV protein synthesis, virus accumulation, and protected infected cells from toxic effect of VSV replication. In contrast, poliovirus replication was delayed, but not diminished in the presence of the proteasome inhibitors MG132 and Bortezomib. We also found that inhibition of proteasomes stimulated stress-related processes, such as accumulation of chaperone hsp70, phosphorylation of eIF2Ξ±, and overall inhibition of translation. VSV replication was sensitive to this stress with significant decline in replication process. Poliovirus growth was less sensitive with only delay in replication. Inhibition of proteasome activity suppressed cellular and VSV protein synthesis, but did not reduce poliovirus protein synthesis. Protein kinase GCN2 supported the ability of proteasome inhibitors to attenuate general translation and to suppress VSV replication. We propose that different mechanisms of translational initiation by VSV and poliovirus determine their sensitivity to stress induced by the inhibition of proteasomes. To our knowledge, this is the first study that connects the effect of stress induced by proteasome inhibition with the efficiency of viral infection
A Transcriptional Enhancer from the Coding Region of ADAMTS5
The revelation that the human genome encodes only approximately 25,000 genes and thus cannot account for phenotypic complexity has been one of the biggest surprises in the post-genomic era. However, accumulating evidence suggests that transcriptional regulation may be in large part responsible for this observed mammalian complexity. Consequently, there has been a strong drive to locate cis-regulatory regions in mammalian genomes in order to understand the unifying principles governing these regions, including their genomic distribution. Although a number of systematic approaches have been developed, these all discount coding sequence.Using the computational tool PRI (Pattern-defined Regulatory Islands), which does not mask coding sequence, we identified a regulatory region associated with the gene ADAMTS5 that encompasses the entirety of the essential coding exon 2. We demonstrate through a combination of chromatin immunoprecipitation and reporter gene studies that this region can not only bind the myogenic transcription factors MYOD and myogenin and the E-protein HEB but can also function as a very strong myogenic transcriptional enhancer.Thus, we report the identification and detailed characterization of an exonic enhancer. Ultimately, this leads to the interesting question of why evolution would be so parsimonious in the functional assignment of sequence
ΠΠ°ΡΠΎΡΠΈΠ·ΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΌΠ΅Ρ Π°Π½ΠΈΠ·ΠΌΡ, Π»Π΅ΠΆΠ°ΡΠΈΠ΅ Π² ΠΎΡΠ½ΠΎΠ²Π΅ Π°Π½ΡΠΈΠΏΡΠΈΡ ΠΎΡΠΈΠΊ-ΠΈΠ½Π΄ΡΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ ΡΠ°ΡΠ΄ΠΈΠ²Π½ΠΎΠΉ Π΄ΠΈΡΠΊΠΈΠ½Π΅Π·ΠΈΠΈ
Purpose. To analyze the results of classical and modern studies reflecting the pathophysiological mechanisms of antipsychotic-induced tardive dyskinesia.Materials and methods. We searched for full-text publications in Russian and English in the databases of E-Library, PubMed, Web of Science and Springer published over the past decade, using keywords (tardive dyskinesia (TD), drug-induced tardive dyskinesia, antipsychotics (AP), neuroleptics, typical antipsychotics, atypical antipsychotics, pathophysiology, etiology and combinations of these words). In addition, the review included earlier publications of historical interest.Results. The lecture proposed theories of development of AP-induced TD, examining its effect on dopaminergic receptors, dopaminergic neurons, neurons of the basal ganglia, and other theories: activation of estrogen receptors, disorders of melatonin metabolism, disorders of the endogenous opioid system, oxidative stress with predominant oxidation processes, blockade of 5-HT2-receptors, a decrease in the pyridoxine level, genetic predisposition, interaction of AP with the brain trace element β iron, carbonyl stress and immune inflammation and the role of the neurotrophic factor.Conclusion. The disclosure of the mechanisms of AP-induced TD will allow the development of a strategy for personalized prevention and therapy of the considered neurological complication of the AP-therapy for schizophrenia in real clinical practice.Β Π¦Π΅Π»Ρ β Π°Π½Π°Π»ΠΈΠ· ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² ΠΊΠ»Π°ΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ, ΠΎΡΡΠ°ΠΆΠ°ΡΡΠΈΡ
ΠΏΠ°ΡΠΎΡΠΈΠ·ΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΡ Π°Π½ΡΠΈΠΏΡΠΈΡ
ΠΎΡΠΈΠΊ-ΠΈΠ½Π΄ΡΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ ΡΠ°ΡΠ΄ΠΈΠ²Π½ΠΎΠΉ Π΄ΠΈΡΠΊΠΈΠ½Π΅Π·ΠΈΠΈ.ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. ΠΡΠΎΠ²Π΅Π΄Π΅Π½ ΠΏΠΎΠΈΡΠΊ ΠΏΠΎΠ»Π½ΠΎΡΠ΅ΠΊΡΡΠΎΠ²ΡΡ
ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΠΉ Π½Π° ΡΡΡΡΠΊΠΎΠΌ ΠΈ Π°Π½Π³Π»ΠΈΠΉΡΠΊΠΎΠΌ ΡΠ·ΡΠΊΠ°Ρ
Β Π·Π° ΠΏΠΎΡΠ»Π΅Π΄Π½Π΅Π΅ Π΄Π΅ΡΡΡΠΈΠ»Π΅ΡΠΈΠ΅ Π² Π±Π°Π·Π°Ρ
Π΄Π°Π½Π½ΡΡ
Π΅Library, PubMed, Web of Science, Springer, ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡ ΠΊΠ»ΡΡΠ΅Π²ΡΠ΅ ΡΠ»ΠΎΠ²Π° Β«ΡΠ°ΡΠ΄ΠΈΠ²Π½Π°Ρ Π΄ΠΈΡΠΊΠΈΠ½Π΅Π·ΠΈΡΒ» (Π’Π), Β«Π»Π΅ΠΊΠ°ΡΡΡΠ²Π΅Π½Π½ΠΎ-ΠΈΠ½Π΄ΡΡΠΈΡΠΎΠ²Π°Π½Π½Π°Ρ ΡΠ°ΡΠ΄ΠΈΠ²Π½Π°Ρ Π΄ΠΈΡΠΊΠΈΠ½Π΅Π·ΠΈΡΒ»,Β Β«Π°Π½ΡΠΈΠΏΡΠΈΡ
ΠΎΡΠΈΠΊΠΈΒ» (ΠΠ), Β«Π½Π΅ΠΉΡΠΎΠ»Π΅ΠΏΡΠΈΠΊΠΈΒ», Β«ΡΠΈΠΏΠΈΡΠ½ΡΠ΅ Π°Π½ΡΠΈΠΏΡΠΈΡ
ΠΎΡΠΈΠΊΠΈΒ», Β«Π°ΡΠΈΠΏΠΈΡΠ½ΡΠ΅ Π°Π½ΡΠΈΠΏΡΠΈΡ
ΠΎΡΠΈΠΊΠΈΒ»,Β Β«ΠΏΠ°ΡΠΎΡΠΈΠ·ΠΈΠΎΠ»ΠΎΠ³ΠΈΡΒ», Β«ΡΡΠΈΠΎΠ»ΠΎΠ³ΠΈΡΒ» ΠΈ ΠΊΠΎΠΌΠ±ΠΈΠ½ΠΈΡΠΎΠ²Π°Π½Π½ΡΠ΅ ΠΏΠΎΠΈΡΠΊΠΈ ΡΠ»ΠΎΠ². ΠΡΠΎΠΌΠ΅ ΡΠΎΠ³ΠΎ, Π² Π»Π΅ΠΊΡΠΈΡ Π²ΠΊΠ»ΡΡΠ΅Π½ΡΒ Π±ΠΎΠ»Π΅Π΅ ΡΠ°Π½Π½ΠΈΠ΅ ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΠΈ, ΠΈΠΌΠ΅ΡΡΠΈΠ΅ ΠΈΡΡΠΎΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΈΠ½ΡΠ΅ΡΠ΅Ρ.Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. Π Π»Π΅ΠΊΡΠΈΠΈ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Ρ ΡΠ΅ΠΎΡΠΈΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΠ-ΠΈΠ½Π΄ΡΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ Π’Π, ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°ΡΡΠΈΠ΅Β Π²Π»ΠΈΡΠ½ΠΈΠ΅ Π½Π° Π΄ΠΎΡΠ°ΠΌΠΈΠ½Π΅ΡΠ³ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ΅ΡΠ΅ΠΏΡΠΎΡΡ, Π΄ΠΎΡΠ°ΠΌΠΈΠ½Π΅ΡΠ³ΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π½Π΅ΠΉΡΠΎΠ½Ρ, Π½Π° Π½Π΅ΠΉΡΠΎΠ½Ρ Π±Π°Π·Π°Π»ΡΠ½ΡΡ
Β Π³Π°Π½Π³Π»ΠΈΠΉ, ΠΈ ΠΏΡΠΎΡΠΈΠ΅ ΡΠ΅ΠΎΡΠΈΠΈ: Π°ΠΊΡΠΈΠ²Π°ΡΠΈΡ ΡΡΡΡΠΎΠ³Π΅Π½ΠΎΠ²ΡΡ
ΡΠ΅ΡΠ΅ΠΏΡΠΎΡΠΎΠ², Π½Π°ΡΡΡΠ΅Π½ΠΈΠ΅ ΠΎΠ±ΠΌΠ΅Π½Π° ΠΌΠ΅Π»Π°ΡΠΎΠ½ΠΈΠ½Π°,Β Π½Π°ΡΡΡΠ΅Π½ΠΈΠ΅ ΡΠ½Π΄ΠΎΠ³Π΅Π½Π½ΠΎΠΉ ΠΎΠΏΠΈΠΎΠΈΠ΄Π½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ, ΠΎΠΊΡΠΈΠ΄Π°ΡΠΈΠ²Π½ΡΠΉ ΡΡΡΠ΅ΡΡ Ρ ΠΏΡΠ΅ΠΎΠ±Π»Π°Π΄Π°Π½ΠΈΠ΅ΠΌ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ²Β ΠΎΠΊΠΈΡΠ»Π΅Π½ΠΈΡ, Π±Π»ΠΎΠΊΠ°Π΄Π° 5-ΠΠ’2Β -ΡΠ΅ΡΠ΅ΠΏΡΠΎΡΠΎΠ², ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΠ΅ ΡΡΠΎΠ²Π½Ρ ΠΏΠΈΡΠΈΠ΄ΠΎΠΊΡΠΈΠ½Π°, Π³Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠ°Ρ ΠΏΡΠ΅Π΄ΡΠ°ΡΠΏΠΎΠ»ΠΎΠΆΠ΅Π½Π½ΠΎΡΡΡ, Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΠ΅ ΠΠ Ρ ΡΠ΅ΡΠ΅Π±ΡΠ°Π»ΡΠ½ΡΠΌ ΠΌΠΈΠΊΡΠΎΡΠ»Π΅ΠΌΠ΅Π½ΡΠΎΠΌ β ΠΆΠ΅Π»Π΅Π·ΠΎΠΌ, ΠΊΠ°ΡΠ±ΠΎΠ½ΠΈΠ»ΠΎΠ²ΡΠΉ ΡΡΡΠ΅ΡΡ ΠΈΒ ΠΈΠΌΡΠ½Π½ΠΎΠ²ΠΎΡΠΏΠ°Π»Π΅Π½ΠΈΠ΅, ΡΠΎΠ»Ρ Π½Π΅ΠΉΡΠΎΡΡΠΎΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ°ΠΊΡΠΎΡΠ°.ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅. Π Π°ΡΠΊΡΡΡΠΈΠ΅ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΠΎΠ² ΠΠ-ΠΈΠ½Π΄ΡΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ Π’Π Π΄Π°ΡΡ ΠΊΠ»ΡΡ ΠΊ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ΅ ΡΡΡΠ°ΡΠ΅Π³ΠΈΠΈΒ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ ΠΏΡΠΎΡΠΈΠ»Π°ΠΊΡΠΈΠΊΠΈ ΠΈ ΡΠ΅ΡΠ°ΠΏΠΈΠΈ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΠΌΠΎΠ³ΠΎ Π½Π΅Π²ΡΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΎΡΠ»ΠΎΠΆΠ½Π΅Π½ΠΈΡΒ ΠΠ-ΡΠ΅ΡΠ°ΠΏΠΈΠΈ ΡΠΈΠ·ΠΎΡΡΠ΅Π½ΠΈΠΈ Π² ΡΠ΅Π°Π»ΡΠ½ΠΎΠΉ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΡΠ°ΠΊΡΠΈΠΊΠ΅
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