The current stage of the tools development for processing Russian-language texts is associated with a weak elaboration of algorithms for identifying entities and dividing sentences into semantic, logically justified parts. In particular, how to determine an actor, actions performed by him/her, and the object(s) over which these actions are performed in a sentence. It is important to understand that the NLP algorithm should be designed in such a way that would identify the listed elements of the sentence not by the principle of a pre-compiled dictionary and the coincidence of parts of the sentence with it, but on the basis of highlighting universal dependencies. To this end, the team of authors have developed and tested algorithms based on the design of patterns universally describing various parts of a sentence: an actor, his/her actions and objects that these actions are directed to. To solve this problem, authors used the tools for parsing sentences into parts of speech and their dependencies (StanfordNLP); processing dependencies and identifying the tree structure of the sentence.

We consider the nonparametric estimation of the multivariate probability density function and its partial derivative with a support on nonnegative axis by dependent data. We use the class of kernel estimators with asymmetric gamma kernel functions. The gamma kernels are nonnegative; they may change their shape depending on the position on the semi-axis and possess good boundary properties for a wide class of densities. Asymptotic estimates of the multivariate density and of its partial derivatives such as biases, variances, and covariances are derived. The optimal bandwidth of both estimates is obtained as a minimum of the mean integrated squared error (MISE) by dependent data with a strong mixing. Optimal convergence rates of the MISE both for the density and its derivative are found.

The article aims to identify the size, prospects and purpose of the digital economy. Based on the methodology of analysis and synthesis, structuring of scientific positions using a systematic approach, abstract and logical types of analysis and analysis of statistical data, the author reveals the problem of the need to form a system of special knowledge about the essence and principles of digital economy functioning, which should be formulated by specialists in the basic and applied economic sciences and allow to create a basis for a systematic scientific-based multi-parameter study of the digital economy continuum. However, the study shows that the digital economy, including its digital segment, shows a slower growth than previously expected and predicted. There is also a lag in the rate of development of the biotechnology industry. Yet, this does not call into question that the digital economy will develop at a faster pace in the near future. The result is an empirically based conclusion that, while the actual size of the digital economy is small relative to the size of all world production, the growth rate of digital technologies is exponentially increasing, expanding the space of the digital economy. For quality transformation, the underlying digital technology needs socialization, which implies the development of the technology itself, its size and acceptance by society. As a result of socialization, the most important general purpose of the digital economy—to meet the needs of consumers, and its special purpose—to contribute to the development of human capital, improve the quality of life of individuals, countries and the entire population of the planet, as well as reduce the uneven development of regions of the planet and economic sectors, should be fulfilled.

Usually, DEA methods are used for the assessment of a region’s disaster vulnerability. However, most of these methods work with precise values of all the characteristics of the regions. At the same time, in real life, quite often most of the data consists of expert estimates or approximate values. In this regard, we propose to use modified DEA methods, which will take into account inaccuracy of the data. We apply these methods to the evaluation of wildfire preventive measures in the Russian Federation regions.

In modern conditions, requirements for the level of training of analysts, the need for training experts for modern decision support centers for managing business systems (situational centers) requires the use of modern educational technologies that can use the information accumulated in the systems, experience analysis and problem-solving, external sources for the formation of skills and abilities to analyze in new or complex crisis situations and the preparation of appropriate management decisions.