Intensive socio-economic interactions are a prerequisite for the innovative development of the economy, but at the same time, they may lead to increased epidemiological risks. Persistent migration ...patterns, the socio-demographic composition of the population, income level, and employment structure by type of economic activity determine the intensity of socio-economic interactions and, therefore, the spread of COVID-19.
We used the excess mortality (mortality from April 2020 to February 2021 compared to the five-year mean) as an indicator of deaths caused directly and indirectly by COVID-19. Similar to some other countries, due to irregularities and discrepancies in the reported infection rates, excess mortality is currently the only available and reliable indicator of the impact of the COVID-19 pandemic in Russia.
We used the regional level data and fit regression models to identify the socio-economic factors that determined the impact of the pandemic. We used ordinary least squares as a baseline model and a selection of spatial models to account for spatial autocorrelation of dependent and independent variables as well as the error terms.
Based on the comparison of AICc (corrected Akaike information criterion) and standard error values, it was found that SEM (spatial error model) is the best option with reliably significant coefficients. Our results show that the most critical factors that increase the excess mortality are the share of the elderly population and the employment structure represented by the share of employees in manufacturing (C economic activity according to European Skills, Competences, and Occupations (ESCO) v1 classification). High humidity as a proxy for temperature and a high number of retail locations per capita reduce the excess mortality. Except for the share of the elderly, most identified factors influence the opportunities and necessities of human interaction and the associated excess mortality.
Convolutional neural networks (CNNs) have been widely used in image recognition and processing tasks. Memristor-based CNNs accumulate the advantages of emerging memristive devices, such as nanometer ...critical dimensions, low power consumption, and functional similarity to biological synapses. Most studies on memristor-based CNNs use either software models of memristors for simulation analysis or full hardware CNN realization. Here, we propose a hybrid CNN, consisting of a hardware fixed pre-trained and explainable feature extractor and a trainable software classifier. The hardware part was realized on passive crossbar arrays of memristors based on nanocomposite (Co-Fe-B)x(LiNbO3)100−x structures. The constructed 2-kernel CNN was able to classify the binarized Fashion-MNIST dataset with ~ 84% accuracy. The performance of the hybrid CNN is comparable to the other reported memristor-based systems, while the number of trainable parameters for the hybrid CNN is substantially lower. Moreover, the hybrid CNN is robust to the variations in the memristive characteristics: dispersion of 20% leads to only a 3% accuracy decrease. The obtained results pave the way for the efficient and reliable realization of neural networks based on partially unreliable analog elements.
Highlights • For favorable immune parameters’ borders we used parameters of actually fertile women. • We display 12 unfavorable immune parameter's deviations. • Immune deviations in common increase ...information about multiplicity of deviations. • Multiple deviations increase significance of prognosis for reproductive failure.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Convolutional neural networks (CNNs) have been widely used in image recognition and processing tasks. Memristor-based CNNs accumulate the advantages of emerging memristive devices, such as nanometer ...critical dimensions, low power consumption, and functional similarity to biological synapses. Most studies on memristor-based CNNs use either software models of memristors for simulation analysis or full hardware CNN realization. Here, we propose a hybrid CNN, consisting of a hardware fixed pre-trained and explainable feature extractor and a trainable software classifier. The hardware part was realized on passive crossbar arrays of memristors based on nanocomposite (Co-Fe-B)sub.x(LiNbOsub.3)sub.100−x structures. The constructed 2-kernel CNN was able to classify the binarized Fashion-MNIST dataset with ~ 84% accuracy. The performance of the hybrid CNN is comparable to the other reported memristor-based systems, while the number of trainable parameters for the hybrid CNN is substantially lower. Moreover, the hybrid CNN is robust to the variations in the memristive characteristics: dispersion of 20% leads to only a 3% accuracy decrease. The obtained results pave the way for the efficient and reliable realization of neural networks based on partially unreliable analog elements.
The purpose of the study is to identify and characterize the most typical conditions and factors affecting the organization of medical care and medical evacuation of victims of terrorist attacks ...based on the study and analysis of the experience of eliminating the medical and sanitary consequences of terrorist acts committed on the territory of Russia with the use of explosive devices and conventional weapons. Materials and methods of research. The materials of the study were: normative and methodological documents regulating the organization of medical care and medical evacuation during terrorist acts; dispatches and reports of the territorial centres for disaster medicine on the elimination of medical and sanitary consequences of 162 terrorist acts, including 6 terrorist attacks with the capture and holding of hostages committed in 1998-2010; documents of official correspondence of the All-Russian centre for disaster medicine Zashchita on issues of medical support of the population during terrorist acts; scientific papers and publications on the research problem. When performing the research, the following methods were used: historical, content analysis, statistical, and analytical. Research results and their analysis. The following issues were considered during the research: - means of conducting terrorist activities and their application specifics; - high degree of vulnerability and damage to the population; - the nature of the object where the terrorist act was committed; - sanitary losses and their characteristics; - psychological situation, capture and holding of hostages, the presence of a threat to their lives; - terms of elimination of medical and sanitary consequences of terrorist attacks; - the needs and capabilities of medical organizations (LMO) of the regions in delivery of medical assistance to victims of terrorist attacks; - needs and capabilities of LMO of the regions in medical evacuation; - features of the organization and conduct of measures to eliminate the consequences of terrorist acts. Based on the results of the analysis of the experience in liquidation of medical-sanitary consequences of terrorist attacks, as well as analysis of basic conditions and factors influencing the organization of medical care and conduct of medical evacuation, the methodical approaches are suggested: to comprehensive assessment of conditions and factors typical for terrorist attacks with use of explosive devices and conventional weapons; to use of medical-and-evacuation characteristics of victims in the organization of medical care and conduct of medical evacuation; to increase the readiness of the regional health sector in facing the challenges of liquidation of medical and sanitary consequences of terrorist attacks.
The objective of the study based on the analysis and evaluation of key performance indicators of the all-Russian center for disaster medicine "Zaschita" FMBA Rossii (WCMC "Protection" in the Center) ...and disaster medical Service (QMS), Russian Ministry of health to develop proposals and to identify priority areas for further development and improvement of the system of medical support of the population in emergency situations (es). Materials and methods of research. Materials research: normative and methodical documents governing the organization and operation of the all-Russian service for disaster medicine (VSMK), medical aid to victims in emergency and medical evacuation; records of the regional centers of emergency medical care and disaster medicine (SMP RC and IC), the territorial centers of emergency medicine (TSMC) and WCMC "Protection" on the activity of the elimination of the health consequences of emergencies in 2020 etc. Research methods: analytical, statistical, direct observation method, logical and information modeling. The results of the study and their analysis. In 2020, 2108 emergencies with health consequences occurred in the Russian Federation, excluding the COVID-19 pandemic, which is almost 25% less than in 2019. This situation can be explained by a decrease in the intensity of transport operations and the activity of the population during the pandemic. In order to further develop the system of medical support for the population in emergencies, the main tasks for 2021 are formulated.
Continuous variables quantum key distribution (CV-QKD) systems are a promising direction for quantum communications. Coherent detection, which is the basis of CV-QKD, requires taking into ...consideration and compensating phase distortions. Phase compensation algorithms rely on using reference pulses for phase drift estimation and correcting signal quadratures. The ratio of the number of reference pulses to that of the signal ones, affects the accuracy of the phase compensation algorithm. On the other hand, it influences the secure key rate (SKR). The paper considers the effect of the reference to signal ratio on the SKR, and proposes a modification of the phase compensation algorithm, which allows using a smaller number of references at a pulse repetition frequency close to that of the system phase noise, which results in increasing SKR. We also propose a method for estimating the phase noise in the system for selection of the optimal signal to reference ratio.
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