Value Orientations of Russian Youth in Interaction Models between the State and Civil Society

In the context of the formation of civil society in modern Russia with the traditionally significant role of the state, the problem of studying the inclusion of young people in a particular model of the relationship between these two institutions is of particular relevance. This choice will determine a certain type of political system in Russia in the future. The purpose of the study is to identify empirically groups of young people who are determined by the direction of value orientations in public life and their involvement in various models of interaction between the state and civil society. The empirical basis of the study was a project conducted in 2019 by Saint Petersburg State University and Altai State University to study the political consciousness of Russian youth. As a result of using multidimensional methods of analysis, the connection between the involvement of the citizen-state models and the types of value orientations of Russian youth is revealed. Four groups of young people were obtained, stratified by value orientations, the specifics of relations between the state and citizens of our country, and the choice of the preferred type of state to live in.

The Application of Spatial Autoregressive Models for Analyzing the Influence of Spatial Factors on Real Estate Prices and Values

The spatial distribution of real estate in specific geographic locations, real estate transactions, and the prices and values of properties are a highly complex spatial phenomena that should be analyzed with the use of multidimensional methods. Spatial factors are taken into account in the modeling process to increase the reliability of real estate market analyses, and spatial autoregressive models are applied to determine the effect of spatial factors on real estate prices and values. The present study relies on a review of the literature and the results of an experiment. The concept and principles of market analysis were designed with the use of spatial autoregressive models, and the influence of selected spatial factors on real estate prices was presented on maps. Analyses involving autoregressive models enable reliable modeling and support correct interpretation of the observed processes.

Cloud Service for Multidimensional Processing of Quantitative Data for Solving Geological

The study describes the developed cloud web service for multidimensional processing of quantitative data for solving a wide class of scientific geological tasks. The computing node “Multidimensional methods of data analysis” provides processing of tabular data using various methods of modern data analysis and allows to set their parameters and visualize the results. The node includes wide range of methods such as data preprocessing, descriptive statistics, cluster analysis, factor analysis, correlation analysis, regression analysis. Computing node “Multidimensional methods of data analysis” is a part of Computational analytical geological environment of State Geological Museum of RAS and is integrated with its services. At the same time, the computing node is an independent cloud web service which implements REST API for interaction with it. This allows a wide range of users to access multidimensional data analysis methods located on a computing node and provides capabilities of its integration into information systems as a thirdparty application for processing tabular data.

Application of Canonical Variate Analysis to Compare Different Groups of Food Industry Companies in Terms of Financial Liquidity and Profitability

Financial liquidity and profitability are two critical phenomena present in the financial economy of a company, whose relations depend on each other and may course in different directions. At the same time, they are an example of the complexity of the problem, which demands a proper approach, allowing one to reconcile two opposing objectives of any enterprise, i.e., maximizing the benefits for the owners and minimizing the risk of losing financial liquidity. Until now, the relationship between liquidity and profitability has not been examined explicitly, using multidimensional methods in particular. Nevertheless, the links between profitability and financial liquidity maintenance ensure the sustainable development of enterprises in different branches. This paper formulates two aims: scientific and practical. The scientific one concerns adopting the canonical variate analysis method to visualize the differences and relationships between food industry companies regarding financial liquidity and profitability. The practical one relates to indicating the relationship between financial liquidity and profitability in different groups of food industry companies. To study the relationships between the selected groups of enterprises and describe them, the liquidity and profitability ratios were utilized, involving canonical variate analysis based on transformation by linear combination and singular value decomposition. The analysis found that the most important feature highlighting the group of the examined entities regarding financial liquidity was the cash conversion cycle. The research results showed the existence of multidirectional relationships between liquidity and profitability. The research indicates that they depend on indicators describing financial dependencies and the industries in which they operate. This led to a much deeper and broader interpretation of the assessment of the financial situation of companies to support their sustainable development.

Some Information Geometric Aspects of Cyber Security by Face Recognition

Secure user access to devices and datasets is widely enabled by fingerprint or face recognition. Organization of the necessarily large secure digital object datasets, with objects having content that may consist of images, text, video or audio, involves efficient classification and feature retrieval processing. This usually will require multidimensional methods applicable to data that is represented through a family of probability distributions. Then information geometry is an appropriate context in which to provide for such analytic work, whether with maximum likelihood fitted distributions or empirical frequency distributions. The important provision is of a natural geometric measure structure on families of probability distributions by representing them as Riemannian manifolds. Then the distributions are points lying in this geometrical manifold, different features can be identified and dissimilarities computed, so that neighbourhoods of objects nearby a given example object can be constructed. This can reveal clustering and projections onto smaller eigen-subspaces which can make comparisons easier to interpret. Geodesic distances can be used as a natural dissimilarity metric applied over data described by probability distributions. Exploring this property, we propose a new face recognition method which scores dissimilarities between face images by multiplying geodesic distance approximations between 3-variate RGB Gaussians representative of colour face images, and also obtaining joint probabilities. The experimental results show that this new method is more successful in recognition rates than published comparative state-of-the-art methods.

МОДЕЛИ ОНЛАЙН-МОБИЛИЗАЦИИ ПОЛИТИЧЕСКОГО ПРОТЕСТА СОВРЕМЕННОЙ РОССИЙСКОЙ МОЛОДЕЖИ (РЕЗУЛЬТАТЫ ЭМПИРИЧЕСКОГО ИССЛЕДОВАНИЯ)

The paper considers the problem of empirical search for models of online mobilization of the youth protest movement in the modern Russian metropolis. In the political practice of many countries, young people have become one of the most important objects of influence of various political actors, both internal and external. Also, in Russian political protest, young people are traditionally the driving force. In the last decade, the online environment has become the most effective and operational communication field for the construction of the political process. The greatest political impact was achieved by the online organization of protest actions, the key element of the strategy of which was the mobilization of the masses. The objectives of the study are to use multidimensional methods of analysis to identify the features that influence the formation of online mobilization models, and to give a descriptive description of each of the models. To study the problem, an online survey of representatives of the younger generation in all megacities of the Russian Federation was conducted, during which latent factors of political action in the online environment, online mechanisms for attracting the attention of users of social networks to political problems that play the role of a protest trigger, and types of political participation were identified. With the help of classification methods, the obtained factors were obtained four models of online mobilization of the political prosthesis of the youth of modern Russia.

APPLICATION OF MULTIDIMENSIONAL TIME MODEL TO DYNAMICAL RELATION OF POISSON SPIKE TRAINS IN NEURAL ION CURRENT MODELS AND FORMATION OF NON-CANONICAL BASES, ISLANDS, AND G-QUADRUPLEXES IN DNA, MRNA, AND RNA AT OR NEAR THE TRANSCRIPTION

Ground breaking application of mathematics and biochemistry to explain formation of non-canonical bases, islands, G-quadruplex structures, and analog bases in DNA and mRNA at or near the transcription with connection to neural networks is implemented using statistical and stochastic methods apparatus with the addition of quantum principles. As a result the usual transience of Poisson spike trains (PST) becomes very instrumental tool for finding periodical type of solutions to Fokker-Plank (FP) stochastic differential equation (SDE). The present study develops new multidimensional methods of finding solutions to SDE. This is based on more rigorous approach to mathematical apparatus through Kolmogorov-Chentsov continuity theorem (KCCT) that allows the stochastic processes with jumps under certain conditions to have γ-Holder continuous modification, which is used as basis for finding analogous parallels in dynamics of formation of CpG and non-CpG islands (CpGI or non CpGI), repeats of G-quadruplexes, and non canonical bases during DNA (de)- methylation and neural networks.

Quantitative NMR as a Versatile Tool for the Reference Material Preparation

The assessment of primary calibrator purity is critical for establishing traceability to the International System of Units (SI). Recently, quantitative nuclear magnetic resonance (qNMR) has been used as a purity determination method for reference material development, and many related measurement techniques have been designed to acquire accurate and reliable results. This review introduces the recent advances in these techniques (including multidimensional methods), focusing on the application of qNMR to reference material preparation.