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Tsar Mikhail Romanov: His Entry into Power

Andrej Pavlov
2019 Vestnik Volgogradskogo Gosudarstvennogo Universiteta. Seriâ 4. Istoriâ, Regionovedenie, Meždunarodnye Otnošeniâ  
As historical literature shows, the election of Tsar Mikhail Romanov at the Zemsky Sobor of 1613 occurred without broad support of boyars and nobles.  ...  The article is based on the use and comprehensive analysis of the sources, which show the process of approval of Tsar Mikhail Romanov in power.  ... 
doi:10.15688/jvolsu4.2019.2.13 fatcat:3hpk3ngu2ngqplhhlgkxgllrqe

To See the Sovereign's Eyes: The Admission of Members of Court at Easter in the Reign of Mikhail Romanov

Andrei Pavlov
2020 Quaestio Rossica  
A set of documents has survived from the reign of Mikhail Fyodorovich about the admission of different groups of Moscow nobles and clerks to "see the sovereign's eyes" at Easter either in the komnata (  ... 
doi:10.15826/qr.2020.4.522 fatcat:rp65eghfrvbwfmx7czgn2mwgmq

Modern national historiography on the historical importance of crowning Mikhail Fyodorovich Romanov as tzar
Современная отечественная историография об историческом значении избрания на царство Михаила Фёдоровича Романова

P. Uvarov, S. Dmitrina
2018 Bulletin of the South Ural State University Series «Social Sciences and the Humanities»  
doi:10.14529/ssh180206 fatcat:f5fdamlxunbobbexceyl4hu4a4


D. D. Kopaneva
2020 Proceedings of Petrozavodsk State University  
Romanov.  ...  The article deals with a notable episode in the Russian-Persian relations in the XVII century regarding the history of a money loan given by the Persian Shah Abbas I to the Russian Tsar Mikhail Fyodorovich  ... 
doi:10.15393/ fatcat:chu74isfd5fw7e6lsrf5yqyrke

Zero misorientation interfaces in graphene

Mikhail Rozhkov, Nikita Abramenko, Anna Kolesnikova, Alexey Romanov
2020 Letters on Materials  
This article presents the results on the modeling of straight-line interfaces that induce no misorientation of adjacent regions in graphene: zero misorientation interfaces (ZMIs). The interfaces in the hexagonal graphene lattice are represented as ensembles of disclinated carbon rings with broken rotational symmetry of the sixth order. The basic elements of such ensembles are structural units -complexes of disclinated rings with zero disclination charge. Using molecular dynamics simulation, the
more » ... energies and atomic densities for ZMIs are found. Calculations demonstrate that atomic densities in ZMIs are lower than the atomic density in defect-free graphene. No direct correlation has been revealed between the atomic density and the interface energy. It is assumed, that the elastic field caused by ZMI defect structure contributes significantly to the energy of interface. Low-energy ZMIs possess linear energies not exceeding ~0.6 -0.8 eV / Å, that is comparable to the energies of the grain boundaries, i. e. boundaries with misorientation, in graphene. Based on a mesoscopic approach operating with disclination schemes, in which defective carbon rings are replaced by disclinations, strain maps are plotted, and energies are found for two selected low-energy ZMIs. It is demonstrated that, at the distance of ZMI half-period from interface line, strains decrease to values of ~0.05. The energies of low-energy ZMIs calculated within the framework of two approaches: atomistic and mesoscopic, although differ numerically, coincide by the order of magnitude.
doi:10.22226/2410-3535-2020-4-551-557 fatcat:qpveizcc4fgurnfrrq36s2v7ye

Decoder Modulation for Indoor Depth Completion [article]

Dmitry Senushkin, Mikhail Romanov, Ilia Belikov, Anton Konushin, Nikolay Patakin
2021 arXiv   pre-print
Depth completion recovers a dense depth map from sensor measurements. Current methods are mostly tailored for very sparse depth measurements from LiDARs in outdoor settings, while for indoor scenes Time-of-Flight (ToF) or structured light sensors are mostly used. These sensors provide semi-dense maps, with dense measurements in some regions and almost empty in others. We propose a new model that takes into account the statistical difference between such regions. Our main contribution is a new
more » ... coder modulation branch added to the encoder-decoder architecture. The encoder extracts features from the concatenated RGB image and raw depth. Given the mask of missing values as input, the proposed modulation branch controls the decoding of a dense depth map from these features differently for different regions. This is implemented by modifying the spatial distribution of output signals inside the decoder via Spatially-Adaptive Denormalization (SPADE) blocks. Our second contribution is a novel training strategy that allows us to train on a semi-dense sensor data when the ground truth depth map is not available. Our model achieves the state of the art results on indoor Matterport3D dataset. Being designed for semi-dense input depth, our model is still competitive with LiDAR-oriented approaches on the KITTI dataset. Our training strategy significantly improves prediction quality with no dense ground truth available, as validated on the NYUv2 dataset.
arXiv:2005.08607v2 fatcat:wzzsqrbh5rfftfzhkfoh2fb43u

Learning High-Resolution Domain-Specific Representations with a GAN Generator [article]

Danil Galeev, Konstantin Sofiiuk, Danila Rukhovich, Mikhail Romanov, Olga Barinova, Anton Konushin
2020 arXiv   pre-print
In recent years generative models of visual data have made a great progress, and now they are able to produce images of high quality and diversity. In this work we study representations learnt by a GAN generator. First, we show that these representations can be easily projected onto semantic segmentation map using a lightweight decoder. We find that such semantic projection can be learnt from just a few annotated images. Based on this finding, we propose LayerMatch scheme for approximating the
more » ... epresentation of a GAN generator that can be used for unsupervised domain-specific pretraining. We consider the semi-supervised learning scenario when a small amount of labeled data is available along with a large unlabeled dataset from the same domain. We find that the use of LayerMatch-pretrained backbone leads to superior accuracy compared to standard supervised pretraining on ImageNet. Moreover, this simple approach also outperforms recent semi-supervised semantic segmentation methods that use both labeled and unlabeled data during training. Source code for reproducing our experiments will be available at the time of publication.
arXiv:2006.10451v1 fatcat:bzbzgpcqhfgexbwkudnpnistie

О самосопряженном подпространстве односкоростного оператора переноса

Роман Владимирович Романов, Roman Vladimirovich Romanov, Михаил А Тихомиров, Mikhail A Tikhomirov
2011 Математические заметки  
doi:10.4213/mzm8599 fatcat:sfv2sdjccveenenhflhfx363jq

A new subspecies ofMagnolia virginiana (Magnoliaceae)from western Cuba

Alejandro Palmarola-Bejerano, Mikhail S. Romanov, Alexey V. F. C. Bobrov
2008 Willdenowia  
., Romanov, M. S. & Bobrov, A. V. F. C.: A new subspecies of Magnolia virginiana (Magnoliaceae) from western Cuba [Novitiae florae cubensis 29]. -Willdenowia 38: 545-549.  ...  Romanov & A. V. Bobrov, subsp. nov. Holotype: Cuba, Prov. Matanzas, Municipio Martí, Ciénaga de Majaguillar, camino de la Alameda a la Ciénaga de Gonzalito, 8.10.2006.  ...  ibid., 22°59'45"N, 80°58'45"W, bosque secundario de ciénaga, flores color crema, 27.2.2007, Greuter, Palmarola & Rankin 26651 (B, HAJB, JE, PAL-Gr); ibid., Ciénaga de Gonzalito, 21.3.2007, Palmarola, Romanov  ... 
doi:10.3372/wi.38.38214 fatcat:qdqembrzc5fmnaoifrpvm4oxnm

Current vegetation data from the Prioksko-Terrasnyi Biosphere Reserve

Mikhail Shovkun, Natalya Ivanova, Larisa Khanina, Michael Romanov, Vasily Demidov
2021 Biodiversity Data Journal  
Photo by Mikhail Shovkun.  ...  Quality control: Species were identified using the key (Gubanov et al. 1995) by Mikhail Shovkun.  ... 
doi:10.3897/bdj.9.e71266 pmid:34539205 pmcid:PMC8410754 fatcat:dbxdkx7a5jdpxk47lnkb7nlaae

Application of exergy analysis for estimation of geotechnical systems stability

Mikhail V Romanov, Andrey V Shamshin, Oleg G. Vorobyev
2019 Linnaeus Eco-Tech  
ECOLOGICAL TECHNOLOGY AND MANAGEMENT KALMAR, SWEDEN, September 22-24, 1999 Mikhail Romanov, Russia  ... 
doi:10.15626/eco-tech.1999.019 fatcat:hbbsrs7hlzbepbphjbsifwzap4


Pavel A. Smelov, Mikhail V. Karmanov, Andrey A. Romanov
2015 Statistika i Èkonomika  
doi:10.21686/2500-3925-2015-4-164-169 fatcat:dqlaq4aj4jeinpxk3xwgqcadju

Genetic markers of meat productivity of the Romanov sheep breed: IGFBP-3, GHo и CAST

Mikhail N. Kostylev, Marina V. Abramova, Anna V. Ilyina, Maria S. Barysheva, Yulia I. Malina, Evgeny G. Evdokimov, Yusupzhan A. Yuldashbaev, Salbak O. Chylbak-ool, Abdulmuslim M. Abdulmuslimov
2021 Agrarian science  
For molecular genetic analysis, samples taken from Romanov sheep in micro-populations of the Yaroslavl region from the ear by pluck were isolated.  ...  Evaluation of gene polymorphism in the population GHo Romanov sheep showed the presence of three genotypes AA, AB and BB with frequency of allele A and b — 63% and 37%, respectively.  ...  ., Scientific town, Makhachkala, 367014, Republic of Dagestan dagniisx@yandex.ruKey words: Romanov sheep breed, meat productivity genes, IGFBP-3, GHo. CAST, adult weight For citation: Mikhail N.  ... 
doi:10.32634/0869-8155-2020-343-11-36-40 fatcat:gmskd52horeh7pctq4sepblbcy

Double Refinement Network for Efficient Indoor Monocular Depth Estimation [article]

Nikita Durasov, Mikhail Romanov, Valeriya Bubnova, Pavel Bogomolov, Anton Konushin
2019 arXiv   pre-print
Monocular depth estimation is the task of obtaining a measure of distance for each pixel using a single image. It is an important problem in computer vision and is usually solved using neural networks. Though recent works in this area have shown significant improvement in accuracy, the state-of-the-art methods tend to require massive amounts of memory and time to process an image. The main purpose of this work is to improve the performance of the latest solutions with no decrease in accuracy.
more » ... this end, we introduce the Double Refinement Network architecture. The proposed method achieves state-of-the-art results on the standard benchmark RGB-D dataset NYU Depth v2, while its frames per second rate is significantly higher (up to 18 times speedup per image at batch size 1) and the RAM usage per image is lower.
arXiv:1811.08466v2 fatcat:rv5dcdvjfjgxxgciquf4p3wfuq

Stability of Intelligent Automatic Control Systems

Nina Kazachek, Valery Lokhin, Sergey Manko, Mikhail Romanov
2017 International Journal of Innovative Computing, Information and Control  
doi:10.24507/ijicic.13.02.547 fatcat:zmxoqrjgijerfm376bwb6d7cpq
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