Prospects for the implementation of the "digital government" project of the Russian Federation

The theoretical foundations for the development of the digital economy and e-government are considered in this article. The main objectives of Russia's transition to the digital economy are listed. The relevance of the development of the digital government concept is considered. The indicators of the current level of state development in the framework of digitalization and the formation of e-government are analyzed. The main problems, the solution of which makes the implementation of the digital government project of the Russian Federation possible, are singled out. Digital economy development is associated not only with the progress of the information technology and innovation industry, but also with the improvement of the labor market, where new jobs, professions and personnel are created. In this regard, there is a rapid process of the foundation of society, where one job becomes low-paid, and new professions allow one to receive a personal income at the level of top managers of small and medium-sized enterprises.peer-reviewe

Supernova Ia: a Converging Delayed Detonation Wave

A model of a carbon-oxygen (C--O) presupernova core with an initial mass 1.33 M_\odot, an initial carbon mass fraction 0.27, and with an average mass growth-rate 5 x 10^{-7} M_\odot/yr due to accretion in a binary system was evolved from initial central density 10^9 g/cm^3, and temperature 2.05 x 10^8 K through convective core formation and its subsequent expansion to the carbon runaway at the center. The only thermonuclear reaction contained in the equations of evolution and runaway was the carbon burning reaction 12C + 12C with an energy release corresponding to the full transition of carbon and oxygen (with the same rate as carbon) into 56Ni. As a parameter we take \alpha_c - a ratio of a mixing length to the size of the convective zone. In spite of the crude assumptions, we obtained a pattern of the runaway acceptable for the supernova theory with the strong dependence of its duration on \alpha_c. In the variants with large enough values of \alpha_c=4.0 x 10^{-3} and 3.0 x 10^{-3} the fuel combustion occurred from the very beginning as a prompt detonation. In the range of 2.0 x 10^{-3} >= \alpha_c >= 3.0 x 10^{-4} the burning started as a deflagration with excitation of stellar pulsations with growing amplitude. Eventually, the detonation set in, which was activated near the surface layers of the presupernova (with m about 1.33 M_\odot) and penetrated into the star down to the deflagration front. Excitation of model pulsations and formation of a detonation front are described in detail for the variant with \alpha_c=1.0 x 10^{-3}.Comment: 13 pages, 11 figures, to appear in Astronomy Letter

EVALUATING THE EFFECT OF VARIOUS SULFHYDRIL GROUP ACTIVATORS ON EXPERIMENTALLY INDUCED CATARACT IN TEST ANIMALS

No abstrac

Intermediate Fusion Approach for Pneumonia Classification on Imbalanced Multimodal Data

In medical practice, the primary diagnosis of diseases should be carried out quickly and, if possible, automatically. The processing of multimodal data in medicine has become a ubiquitous technique in the classification, prediction and detection of diseases. Pneumonia is one of the most common lung diseases. In our study, we used chest X-ray images as the first modality and the results of laboratory studies on a patient as the second modality to detect pneumonia. The architecture of the multimodal deep learning model was based on intermediate fusion. The model was trained on balanced and imbalanced data when the presence of pneumonia was determined in 50% and 9% of the total number of cases, respectively. For a more objective evaluation of the results, we compared our model performance with several other open-source models on our data. The experiments demonstrate the high performance of the proposed model for pneumonia detection based on two modalities even in cases of imbalanced classes (up to 96.6%) compared to single-modality models’ results (up to 93.5%). We made several integral estimates of the performance of the proposed model to cover and investigate all aspects of multimodal data and architecture features. There were accuracy, ROC AUC, PR AUC, F1 score, and the Matthews correlation coefficient metrics. Using various metrics, we proved the possibility and meaningfulness of the usage of the proposed model, aiming to properly classify the disease. Experiments showed that the performance of the model trained on imbalanced data was even slightly higher than other models considered.In medical practice, the primary diagnosis of diseases should be carried out quickly and, if possible, automatically. The processing of multimodal data in medicine has become a ubiquitous technique in the classification, prediction and detection of diseases. Pneumonia is one of the most common lung diseases. In our study, we used chest X-ray images as the first modality and the results of laboratory studies on a patient as the second modality to detect pneumonia. The architecture of the multimodal deep learning model was based on intermediate fusion. The model was trained on balanced and imbalanced data when the presence of pneumonia was determined in 50% and 9% of the total number of cases, respectively. For a more objective evaluation of the results, we compared our model performance with several other open-source models on our data. The experiments demonstrate the high performance of the proposed model for pneumonia detection based on two modalities even in cases of imbalanced classes (up to 96.6%) compared to single-modality models’ results (up to 93.5%). We made several integral estimates of the performance of the proposed model to cover and investigate all aspects of multimodal data and architecture features. There were accuracy, ROC AUC, PR AUC, F1 score, and the Matthews correlation coefficient metrics. Using various metrics, we proved the possibility and meaningfulness of the usage of the proposed model, aiming to properly classify the disease. Experiments showed that the performance of the model trained on imbalanced data was even slightly higher than other models considered

On the estimate of the sigma^(I = 1)_(KN)(0)-term value from the energy level shift of kaonic hydrogen in the ground state

Using the experimental data on the energy level shift of kaonic hydrogen in the ground state (the DEAR Collaboration, Phys. Rev. Lett. 94, 212302 (2005)) and the theoretical value of the energy level shift, calculated within the phenomenological quantum field theoretic approach to the description of strong low-energy anti-K N and anti-K NN interactions developed at Stefan Meyer Institut fuer subatomare Physik in Vienna, we estimate the value of the sigma^(I = 1)_(KN)(0)-term of low-energy anti-K N scattering. We get sigma^(I = 1)_(KN)(0) = (433 +/- 85) MeV. This testifies the absence of strange quarks in the proton structure.Comment: 7 pages, no figure

Uncertainties in Arctic sea ice thickness and volume: new estimates and implications for trends

Sea ice volume has decreased in the last decades, evoked by changes in sea ice area and thickness. Estimates of sea ice area and thickness rely on a number of geophysical parameters which introduce large uncertainties. To quantify these uncertainties we use freeboard retrievals from ICESat and investigate different assumptions about snow depth, sea ice density and area. We find that uncertainties in ice area are of minor importance for the estimates of sea ice volume during the cold season in the Arctic basin. The choice of mean ice density used when converting sea ice freeboard into thickness mainly influences the resulting mean sea ice thickness, while snow depth on top of the ice is the main driver for the year-to-year variability, particularly in late winter. The absolute uncertainty in the mean sea ice thickness is 0.28 m in February/March and 0.21 m in October/November. The uncertainty in snow depth contributes up to 70% of the total uncertainty and the ice density 30–35%, with higher values in October/November. We find large uncertainties in the total sea ice volume and trend. The mean total sea ice volume is 10 120 ± 1280 km³ in October/November and 13 250 ± 1860 km³ in February/March for the time period 2005–2007. Based on these uncertainties we obtain trends in sea ice volume of −1450 ± 530 km³ a^−1 in October/November and −880 ± 260 km³ a^−1 in February/March over the ICESat period (2003–2008). Our results indicate that, taking into account the uncertainties, the decline in sea ice volume in the Arctic between the ICESat (2003–2008) and CryoSat-2 (2010–2012) periods may have been less dramatic than reported in previous studies. However, more work and validation is required to quantify these changes and analyse possible unresolved biases in the freeboard retrievals

Group analysis and exact solutions of a class of variable coefficient nonlinear telegraph equations

A complete group classification of a class of variable coefficient (1+1)-dimensional telegraph equations $f(x)u_{tt}=(H(u)u_x)_x+K(u)u_x$, is given, by using a compatibility method and additional equivalence transformations. A number of new interesting nonlinear invariant models which have non-trivial invariance algebras are obtained. Furthermore, the possible additional equivalence transformations between equations from the class under consideration are investigated. Exact solutions of special forms of these equations are also constructed via classical Lie method and generalized conditional transformations. Local conservation laws with characteristics of order 0 of the class under consideration are classified with respect to the group of equivalence transformations.Comment: 23 page

Getting over the Crisis of Identity for Stabilization of the Personality Professional Health

Статья посвящена становлению профессионального здоровья психолога как составляющей общего психологического здоровья личности. Профессиональное здоровье во многом обеспечивается успешным преодолением кризиса профессиональной идентичности в период студенчества. Профессиональная идентичность занимает особое место в структуре «Я», нестабильна в процессе обучения, представляет целостное образование, включающее в себя ценностно-мотивационные и когнитивные характеристики. У студентов выпускного курса отмечается более выраженное проявление кризиса идентичности. Помочь личности преодолеть кризис профессиональной идентичности могут умения: 1) рефлексировать изменение в социальном окружении, 2) совершенствовать систему ценностей, 3) анализировать собственную профессиональную идентичность. Статтю присвячено становленню професійного здоров’я психолога як складової частини загального психологічного здоров’я особистості. Професійне здоров’я у багатьох випадках забезпечується успішним подоланням кризи професійної ідентичності в період студентства. Професійна ідентичність займає особливе місце у структурі «Я», нестабільна у процесі навчання, є цілісним утворенням, що включає цінністно-мотиваційні та когнітивні характеристики. У студентів випускного курсу помічено більший прояв кризи ідентичності. Допомогти особистості подолати кризу професійної ідентичності можуть вміння: 1) рефлексувати зміни у соціальному оточенні, 2) удосконалювати особистісну систему цінностей, 3)аналізувати власну професійну ідентичність. This article is devoted to the development of the psychologist’s professional health. We consider professional health as an important part of the psychological health in general. Successful getting over the professional crisis of identity ensures professional health. Professional identity occupies especial place in the structure of personality. Professional identity is a whole formation consisting of cognitive, motivational and valuable characteristics. It is not stable in the process of education. Students-graduators have more implications of identity crisis. In order to get over the crisis a person should get skills: 1) to reflect the changes in the social environment, 2) to develop own value system, 3) to analyze own professional identity