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Mikhail I. Bogachev

Researcher at Saint Petersburg State Electrotechnical University

Publications -  125
Citations -  1988

Mikhail I. Bogachev is an academic researcher from Saint Petersburg State Electrotechnical University. The author has contributed to research in topics: Biofilm & Staphylococcus aureus. The author has an hindex of 21, co-authored 106 publications receiving 1481 citations. Previous affiliations of Mikhail I. Bogachev include Saint Petersburg State University & Kazan Federal University.

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Very early warning of next El Niño

TL;DR: An approach based on network analysis, which allows projection of an El Niño event about 1 y ahead, is developed and it is shown that this method correctly predicted the absence of El Niño events in 2012 and 2013 and now it is announced that the approach indicated the return ofEl Niño in late 2014 with a 3-in-4 likelihood.
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Improved El Niño forecasting by cooperativity detection

TL;DR: This work introduces a unique avenue toward El Niño prediction based on network methods, inspecting emerging teleconnections and can develop an efficient 12-mo forecasting scheme, i.e., achieve some doubling of the early-warning period.
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Effect of nonlinear correlations on the statistics of return intervals in multifractal data sets.

TL;DR: It is shown explicitly that all the observed quantities depend both on the threshold value and system size, and hence there is no simple scaling observed.
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Targeting microbial biofilms using Ficin, a nonspecific plant protease.

TL;DR: Ficin is a potent tool for staphylococcal biofilm treatment and fabrication of novel antimicrobial therapeutics for medical and veterinary applications and is not cytotoxic towards human breast adenocarcinoma cells and dog adipose derived stem cells.
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On spurious and corrupted multifractality: The effects of additive noise, short-term memory and periodic trends

TL;DR: In this paper, the performance of multifractal detrended fluctuation analysis (MF-DFA) applied to long-term correlated and multifractal data records in the presence of additive white noise, short-term memory and periodicities was studied.