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Institution

Moscow State University

EducationMoscow, Russia
About: Moscow State University is a education organization based out in Moscow, Russia. It is known for research contribution in the topics: Laser & Population. The organization has 66747 authors who have published 123358 publications receiving 1753995 citations. The organization is also known as: MSU & Lomonosov Moscow State University.


Papers
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Journal ArticleDOI
TL;DR: ExoCAT provided significant neuroprotective effects in in vitro and in vivo models of PD and has a potential to be a versatile strategy to treat inflammatory and neurodegenerative disorders.

1,197 citations

Journal ArticleDOI
B. P. Abbott1, R. Abbott1, T. D. Abbott2, Sheelu Abraham3  +1271 moreInstitutions (145)
TL;DR: In 2019, the LIGO Livingston detector observed a compact binary coalescence with signal-to-noise ratio 12.9 and the Virgo detector was also taking data that did not contribute to detection due to a low SINR but were used for subsequent parameter estimation as discussed by the authors.
Abstract: On 2019 April 25, the LIGO Livingston detector observed a compact binary coalescence with signal-to-noise ratio 12.9. The Virgo detector was also taking data that did not contribute to detection due to a low signal-to-noise ratio, but were used for subsequent parameter estimation. The 90% credible intervals for the component masses range from to if we restrict the dimensionless component spin magnitudes to be smaller than 0.05). These mass parameters are consistent with the individual binary components being neutron stars. However, both the source-frame chirp mass and the total mass of this system are significantly larger than those of any other known binary neutron star (BNS) system. The possibility that one or both binary components of the system are black holes cannot be ruled out from gravitational-wave data. We discuss possible origins of the system based on its inconsistency with the known Galactic BNS population. Under the assumption that the signal was produced by a BNS coalescence, the local rate of neutron star mergers is updated to 250-2810.

1,189 citations

Journal ArticleDOI
B. P. Abbott1, Richard J. Abbott1, T. D. Abbott2, Matthew Abernathy3  +978 moreInstitutions (112)
TL;DR: The first observational run of the Advanced LIGO detectors, from September 12, 2015 to January 19, 2016, saw the first detections of gravitational waves from binary black hole mergers as discussed by the authors.
Abstract: The first observational run of the Advanced LIGO detectors, from September 12, 2015 to January 19, 2016, saw the first detections of gravitational waves from binary black hole mergers. In this paper we present full results from a search for binary black hole merger signals with total masses up to 100M⊙ and detailed implications from our observations of these systems. Our search, based on general-relativistic models of gravitational wave signals from binary black hole systems, unambiguously identified two signals, GW150914 and GW151226, with a significance of greater than 5σ over the observing period. It also identified a third possible signal, LVT151012, with substantially lower significance, which has a 87% probability of being of astrophysical origin. We provide detailed estimates of the parameters of the observed systems. Both GW150914 and GW151226 provide an unprecedented opportunity to study the two-body motion of a compact-object binary in the large velocity, highly nonlinear regime. We do not observe any deviations from general relativity, and place improved empirical bounds on several high-order post-Newtonian coefficients. From our observations we infer stellar-mass binary black hole merger rates lying in the range 9−240Gpc−3yr−1. These observations are beginning to inform astrophysical predictions of binary black hole formation rates, and indicate that future observing runs of the Advanced detector network will yield many more gravitational wave detections.

1,172 citations

Journal ArticleDOI
TL;DR: A high-capacity and high-rate sodium-ion anode based on ultrathin layered tin(II) sulfide nanostructures, in which a maximized extrinsic pseudocapacitance contribution is identified and verified by kinetics analysis.
Abstract: Sodium-ion batteries are a potentially low-cost and safe alternative to the prevailing lithium-ion battery technology. However, it is a great challenge to achieve fast charging and high power density for most sodium-ion electrodes because of the sluggish sodiation kinetics. Here we demonstrate a high-capacity and high-rate sodium-ion anode based on ultrathin layered tin(II) sulfide nanostructures, in which a maximized extrinsic pseudocapacitance contribution is identified and verified by kinetics analysis. The graphene foam supported tin(II) sulfide nanoarray anode delivers a high reversible capacity of ∼1,100 mAh g(-1) at 30 mA g(-1) and ∼420 mAh g(-1) at 30 A g(-1), which even outperforms its lithium-ion storage performance. The surface-dominated redox reaction rendered by our tailored ultrathin tin(II) sulfide nanostructures may also work in other layered materials for high-performance sodium-ion storage.

1,162 citations

01 Jan 2003
TL;DR: Most widely used methods and techniques for skin color modelling and recognition are reviewed and their numerical evaluation results are collected.
Abstract: Skin color has proven to be a useful and robust cue for face detection, localization and tracking. Image content filtering, content-aware video compression and image color balancing applications can also benefit from automatic detection of skin in images. Numerous techniques for skin color modelling and recognition have been proposed during several past years. A few papers comparing different approaches have been published [Zarit et al. 1999], [Terrillon et al. 2000], [Brand and Mason 2000]. However, a comprehensive survey on the topic is still missing. We try to fill this vacuum by reviewing most widely used methods and techniques and collecting their numerical evaluation results.

1,155 citations


Authors

Showing all 68238 results

NameH-indexPapersCitations
Krzysztof Matyjaszewski1691431128585
A. Gomes1501862113951
Robert J. Sternberg149106689193
James M. Tour14385991364
Alexander Belyaev1421895100796
Rainer Wallny1411661105387
I. V. Gorelov1391916103133
António Amorim136147796519
Halina Abramowicz134119289294
Grigory Safronov133135894610
Elizaveta Shabalina133142192273
Alexander Zhokin132132386842
Eric Conte132120684593
Igor V. Moskalenko13254258182
M. Davier1321449107642
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023541
20221,582
20217,040
20208,673
20198,296
20187,187