Zobrazeno 1 - 10
of 624
pro vyhledávání: '"A. P. Babichev"'
We study domain walls (DWs) arising in field theories where $Z_2$-symmetry is spontaneously broken by a scalar expectation value decreasing proportionally to the Universe temperature. The energy density of such melting DWs redshifts sufficiently fast
Externí odkaz:
http://arxiv.org/abs/2410.21971
Publikováno v:
JCAP09(2024)047
Employing the publicly available CosmoLattice code, we conduct numerical simulations of a domain wall network and the resulting gravitational waves (GWs) in a radiation-dominated Universe in the $Z_2$-symmetric scalar field model. In particular, the
Externí odkaz:
http://arxiv.org/abs/2406.17053
Autor:
Pavel E. Kopytov, Vladislav V. Andryushkin, Evgeniy V. Pirogov, Maxim S. Sobolev, Andrey V. Babichev, Yuri M. Shernyakov, Mikhail V. Maximov, Andrey V. Lyutetskiy, Nikita A. Pikhtin, Leonid Ya. Karachinsky, Innokenty I. Novikov, Sicong Tian, Anton Yu. Egorov
Publikováno v:
Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki, Vol 24, Iss 5, Pp 709-716 (2024)
The results of investigation of the gain properties of 1300 nm vertical-cavity surface-emitting lasers active regions based on In0.60Ga0.40As/In0.53Al0.20Ga0.27As superlattices and threshold characteristics comparison of superlattices and highly la
Externí odkaz:
https://doaj.org/article/32f389a449994c8fb8ab2680d4c25c36
Publikováno v:
Business Systems Research, Vol 15, Iss 1, Pp 67-90 (2024)
In managing business processes of complex hierarchical systems, primary attention is given to analysing, accelerating, and optimising the basic processes typical for any company.
Externí odkaz:
https://doaj.org/article/3252ed0953cb432e8f5e4794ec29f162
Publikováno v:
Мелиорация и гидротехника, Vol 14, Iss 3, Pp 134-154 (2024)
Purpose: selection of ways for grape bush forming for the conditions of the Crimean Peninsula based on the analysis of their use in similar natural and climatic conditions. Discussion. Obtaining high yields of table grape varieties of appropriate qua
Externí odkaz:
https://doaj.org/article/f8f65b05889a49f8926df84b0dcc2e2c
Publikováno v:
Технічна інженерія, Vol 1, Iss 93, Pp 255-261 (2024)
The article considers the problem of measuring the torque of electric motors using machine vision technology. It is shown that traditional methods based on the installation of force-measuring sensors on the shaft of an electric motor require complex
Externí odkaz:
https://doaj.org/article/926b8698985e430994883b2ad6890cdc
Publikováno v:
Journal of Aerospace Technology and Management, Vol 16 (2024)
The article provides a brief analytical review of mathematical models of the working process used to study the parameters and characteristics of a gas turbine engine at all stages of its creation and operation. It is shown that the first-level mathem
Externí odkaz:
https://doaj.org/article/cb1b721468474303984142039e71d1ee
Autor:
K. M. Ingley, M. Zatzman, A. M. Fontebasso, W. Lo, V. Subasri, A. Goldenberg, Y. Li, S. Davidson, N. Kanwar, L. Waldman, L. Brunga, Y. Babichev, E. G. Demicco, A. Gupta, M. Szybowska, S. Thipphavong, D. Malkin, A. Villani, A. Shlien, R. A. Gladdy, R. H. Kim
Publikováno v:
npj Genomic Medicine, Vol 9, Iss 1, Pp 1-8 (2024)
Abstract Familial gastrointestinal stromal tumors (GIST) are rare. We present a kindred with multiple family members affected with multifocal GIST who underwent whole genome sequencing of the germline and tumor. Affected individuals with GIST harbore
Externí odkaz:
https://doaj.org/article/7edfc5a77ead4ecca1d15f59767646b0
Autor:
Quach, Patrick, Jollivet, Arnaud, Babichev, Andrey, Isac, Nathalie, Morassi, Martina, Lemaitre, Aristide, Yunin, Pavel, Frayssinet, Eric, de Mierry, Philippe, Jeannin, Mathieu, Bousseksou, Adel, Colombelli, Raffaele, Tchernycheva, Maria, Cordier, Yvon, Julien, François
We report on a GaN/AlGaN quantum cascade detector operating in the terahertz spectral range. The device was grown by metal organic chemical vapor deposition on a c-sapphire substrate and relies on polar GaN/AlGaN step quantum wells. The active region
Externí odkaz:
http://arxiv.org/abs/2204.07117
Publikováno v:
IEEE Access, Vol 12, Pp 28437-28448 (2024)
This manuscript explores the application of deep learning (DL) techniques for classifying gene expression data. A key aspect of our research is the comparative analysis of various DL neural network architectures, including Convolution Neural Networks
Externí odkaz:
https://doaj.org/article/9df7f1efa24149c398a5838aa0798882