Neural Simulation of Digital Twin of Top Management Motivation Mechanism in Regional Government Agencies

The aim of the research was the problem of neural simulation of the digital twin of non-financial and financial motivation of top management in government agencies, as well as the strategic potential of regions. Bayesian regularization is used as the network training algorithm because the quasi-time series developed for 83 regions in Russia for the period from 2010 to 2021 is highly noisy. The inner layer of the network has 15 neurons since in this case, the network is trained most optimally. In the verification stage of the trained network, the comparison of actual and forecast data showed that in 2021, the error of the trained network was to average the fluctuations of the quasi-time series. In other words, the network does not account for the overall downward trend in the data. This problem requires a separate in-depth study. For instance, in the case of the Nizhny Novgorod Region, it has been observed that in 2020 and 2021, top managers performed better than those in the leading region (Moscow) based on the parameter of the total area of residential premises per capita. Therefore, they should be financially rewarded for their performance. In terms of non-financial motivation, the top managers should be rewarded more in 2021 than in 2020. The strategic potential of the Nizhny Novgorod Region as a whole is more developed in 2021 than in 2020, which allows us to assess the region's development prospects positively

Development of State Digital Platforms: A Methodological Toolkit for Analysing the Attainment of Regional Health Care Systems’ Target Indicators

The introduction of digital healthcare platforms has had a positive impact on the accessibility of the healthcare system among the population and increased the efficiency of state control over the healthcare of society. But like any evolution, this digital progress has a number of imperfections. In particular, digital methods for automated monitoring of the achievement of regional healthcare systems target indicators for the purpose of operational supervision and taking timely measures in the public health maintenance of certain territories are practically absent. The aim of the work is to develop a methodological toolkit for automated analysis of the achievement of regional health systems target indicators across state digital platforms. The proposed methodology is based on the author's system of indicators, the automated calculation of which will allow monitoring the effectiveness of health care systems in selected regions in real-time, as well as to take timely measures to maintain and protect public health, to form strategies in the development of regional health care systems. The object of the study is the regional health care system of the Russian Federation. The application of the proposed methodological tools makes it possible to rank the territories by the level of values of complex standardized indicators, taking into account financial conditions, resources, and markers for achieving target indicators. Automated monitoring of these indicators allows us to determine the types of strategies for the development of the healthcare system in selected regions. The proposed approach to monitoring the performance of regional healthcare systems will facilitate the development and enhancement of strategies for their progress, aiming to ensure high standards of quality of life among the population

Digital Techniques Share Price Modeling based on a Time-varying Walrasian Equilibrium under Exchange Processes in the Financial Market

This paper aims to develop an analytical theory of share pricing in a financial market environment. The proposed approach corresponds to an actual auction mechanism in which an electronic stock exchange terminal processes real-time data. The theoretical framework is based on the microeconomic model of an individual investor’s net demand. Equity resources and resources of “free” capital (exchanged for shares) owned by traders and the investors’ perception of the structure of the target portfolio are considered the initial variables of the model. The model differs from the classical theory of asset pricing in its notion of fundamental variables. The relations derived for the aggregated net demand in the stock market describe share pricing as a market exchange that results in the Walrasian equilibrium approximation. The authors offered an appropriate econometric technique for estimating the parameters of instantaneous aggregated net demand. The developed approach was tested using the Walrasian equilibrium concept, which demonstrated that the modeled share price corresponded with the observed share price for the Russian financial market. As an example, the authors presented the results of the investment strategy based on the developed approach for the Russian financial market during the 2008–2009 crash. The authors based their approach on identifying the expectations of the stock market participants through an analysis of high-frequency trading platform information. The microeconomic model describes the motives of traders for placing limit orders in the stock market and associates the price and volume of a particular limit order within the parameters of the capital capacity of the net demand of the trader. The application of the algorithm allows for the monitoring of the financial market situation and reveals the market expectations of traders based on the analysis of information transmitted by an order book of a trading platform

WIKI-TECHNOLOGIES IN THE ACADEMIC MASTER LEVEL PROGRAMMS OF MODERN RUSSIAN INNOVATIVE UNIVERSITY

The article describes a mechanism for the application of wiki-technology in academic master level programs for the formation of general, cultural and professional competencies of graduates from modern Russian innovative University. Using as an example the competency matrix of basic and optional parts of the Master level educational program in the field of «Finance and Credit» authors consider what forms of work with the wiki-technology (writing and placing own articles, reviewing and editing existing articles, the translation of the article on the course subject from a foreign language into Russian, addition of self-created graphic and video content into existing articles) can also generate the competence of master level students. That gives the students the opportunity, along with gaining contemporary knowledge, to develop creativity, entrepreneurial skills, to get an experience of scientific work in groups. And it also helps Russian universities to improve their positions in the world university rankings

Phytochemical Analysis, Antibacterial and Antibiofilm Activities of <i>Aloe vera</i> Aqueous Extract against Selected Resistant Gram-Negative Bacteria Involved in Urinary Tract Infections

In bacterial infections, including urinary tract infections (UTIs), the gap between the development of new antimicrobials and antimicrobial resistance is dramatically increasing, especially in Gram-negative (Gram–) bacteria. All healthy products that can be used per se or that may be sources of antibacterial compounds should be considered in the fight against this major public health threat. In the present study, the phytochemical composition of Aloe vera extract was investigated by HPLC–MS/MS, and we further evaluated its antibacterial and antibiofilm formation activity against selected resistant Gram– bacteria involved in UTIs, namely, Achromobacter xylosoxidans 4892, Citrobacter freundii 426, Escherichia coli 1449, Klebsiella oxytoca 3003, Moraxella catarrhalis 4222, Morganella morganii 1543, Pseudomonas aeruginosa 3057, and a reference strain E. coli ATCC 25922. Inhibition zones (IZs) of the extract were determined using the well diffusion method, minimum inhibitory (MIC), and bactericidal (MBC) concentration by the two-fold serial microdilution assay, and antibiofilm formation activity by the crystal violet attachment assay. Aloe-emodin and its derivatives were the major constituent (75.74%) of A. vera extract, the most important of them being aloesin (30.22%), aloe-emodin-diglucoside (12.58%), and 2′-p-methoxycoumaroylaloeresin B (9.64%). The minerals found in the extract were sulfur (S), silicon (Si), chlorine (Cl), potassium (K), and bromine (Br). Except for the clinical strain E. coli 1449, which was totally non-susceptible, A. vera demonstrated noteworthy antibacterial activity with MIC and MBC values ranging from 0.625 to 5 mg/mL and 5 to 10 mg/mL, respectively. A. vera also demonstrated dose-dependent antibacterial effects, and the reference strain E. coli ATCC 25922 was the most susceptible with MIC = 0.625 and IZ = 19 mm at 20 mg/mL. The antibiofilm formation potential of A. vera extract was strong at 2MIC and MIC (93–100% of biofilm formation inhibition), moderate at MIC/2 (32–41%), weak at MIC/4 (14–21%), and nil at MIC/8

Experimental and Computational Insight into the Chemical Bonding and Electronic Structure of Clathrate Compounds in the Sn–In–As–I System

Inorganic clathrate materials are of great fundamental interest and potential practical use for application as thermoelectric materials in freon-free refrigerators, waste-heat converters, direct solar thermal energy converters, and many others. Experimental studies of their electronic structure and bonding have been, however, strongly restricted by (i) the crystal size and (ii) essential difficulties linked with the clean surface preparation. Overcoming these handicaps, we present for the first time a comprehensive picture of the electronic band structure and the chemical bonding for the Sn_{24–<i>x</i>–δ}In_<i>x</i>As_{22–<i>y</i>}I₈ clathrates obtained by means of photoelectron spectroscopy and complementary quantum modeling