Towards lightweight convolutional neural networks for object detection

We propose model with larger spatial size of feature maps and evaluate it on object detection task. With the goal to choose the best feature extraction network for our model we compare several popular lightweight networks. After that we conduct a set of experiments with channels reduction algorithms in order to accelerate execution. Our vehicle detection models are accurate, fast and therefore suit for embedded visual applications. With only 1.5 GFLOPs our best model gives 93.39 AP on validation subset of challenging DETRAC dataset. The smallest of our models is the first to achieve real-time inference speed on CPU with reasonable accuracy drop to 91.43 AP.Comment: Submitted to the International Workshop on Traffic and Street Surveillance for Safety and Security (IWT4S) in conjunction with the 14th IEEE International Conference on Advanced Video and Signal based Surveillance (AVSS 2017

A New Legal Concept for Understanding the Essence of Production and Consumption Waste: A View from Russia

Abstract Recently, production and consumption waste has been recognized as a distinct legal category in the environmental law of the Russian Federation. This regulatory category has been changed several times within a short period. The study evidences that these changes were ontological, resulting from a change in approach to the distinction of waste from other results of economic activity. In practice, these changes introduced new characteristics into the concept of waste, each of which is related to one of the approaches to understanding the essence of waste identified by the authors of the article. The article reveals handicaps of earlier and contemporary approaches to understanding the legal essence of waste in Russia. Based on the results of the study, a new subjective approach is proposed. This approach can serve as a starting point for shaping a new conceptual understanding of waste able to improve environmental law and promote quality enforcement

Development of a Novel Mathematical Model That Explains SARS-CoV-2 Infection Dynamics in Caco-2 Cells

Mathematical modeling is widely used to study within-host viral dynamics. However, to the best of our knowledge, for the case of SARS-CoV-2 such analyses were mainly conducted with the use of viral load data and for the wild type (WT) variant of the virus. In addition, only few studies analyzed models for in vitro data, which are less noisy and more reproducible. In this work we collected multiple data types for SARS-CoV-2-infected Caco-2 cell lines, including infectious virus titers, measurements of intracellular viral RNA, cell viability data and percentage of infected cells for the WT and Delta variants. We showed that standard models cannot explain some key observations given the absence of cytopathic effect in human cell lines. We propose a novel mathematical model for in vitro SARS-CoV-2 dynamics, which included explicit modeling of intracellular events such as exhaustion of cellular resources required for virus production. The model also explicitly considers innate immune response. The proposed model accurately explained experimental data. Attenuated replication of the Delta variant in Caco-2 cells could be explained by our model on the basis of just two parameters: decreased cell entry rate and increased cytokine production rate

New findings of spinturnicid mites (Mesostigmata: Gamasina: Spinturnicidae) from the Caucasus

The Caucasus is a large region in Eurasia consisting of four countries: Russia, Georgia, Azerbaijan, and Armenia. Although it is one of the biodiversity hotspots in the world, the bat ectoparasite fauna has been poorly studied. To promotionally fill in the gaps regarding bat ectoparasites, we conducted five field surveys on bats and their ectoparasites at nine localities within the region between April 2016 and March 2021. Eight species and subspecies of spinturnicid mites were recorded over the surveys: Eyndhovenia euryalis oudemansi, Spinturnix acuminata acuminata, S. emarginata, S. myoti, S. nobleti, S. plecotina, S. psi, and S. punctata. Among them, three species, Spinturnix emarginata, S. nobleti and S. punctate, are newly recorded from the Caucasus region, and one each of subspecies and species, Eyndhovenia euryalis oudemansi and S. plecotina, are newly recorded from Georgia. In addition, Myotis tschuliensis was recorded as a new host species of S. myoti. © 2021 Elsevier B.V

EDUCATIONAL SYSTEM OF NNGASU: TRADITIONS AND INNOVATIONS

The article analyzes the stages of formation and development of the system of level and continuing education in Nizhny Novgorod State University of Architecture and Construction (NNGASU) in the context of the modernization of modern national higher school. The work shows the specifics of educational activities of NNGASU as one of the leading architectural and engineering universities in Russia. The publication summarizes the innovative experience of university education

Donor–acceptor (E)-2-[2-(2,2′-bithiophen-5-yl)vinyl]benzo[d]thiazole: synthesis, optical, electrochemical studies and charge transport characteristics

International audienc

A checklist of bat-associated macronyssid mites (Acari: Gamasina: Macronyssidae) of Russia, with new host and geographical records

The family Macronyssidae (Acari: Mesostigmata) comprises mostly obligate blood-sucking ectoparasites of bats (Mammalia: Chiroptera) and some other animals, such as small mammals, reptiles and birds. Here, we document and curate previously known data, and, based on our extensive survey, provide this article of bat-associated macronyssid mites of the Russian Federation. We record a total of 24 mite species belonging to 4 genera (Ichoronyssus, Macronyssus, Steatonyssus, and Cryptonyssus). Twenty-seven new host-parasite associations are reported. In addition, were provide data on five major Russian regions, for which bat-associated mite records were lacking