Статьи

Представлено исследование произведений позднесоветского писателя Венедикта Васильевича Ерофеева (1938-1990) с целью определить на основе типов, количества и гибридных характеристик музыкальных отсылок, присутствующих в его творчестве, можно ли говорить о последовательном «музыкальном подтексте» как одной из ключевых его тем. Действительно, аналогично тому, что исследовали ученые в области религиозной и литературной тематики, страницы этого уникального автора насыщены скрытыми отсылками к нескольким популярным произведениям и фигурам российской, советской и международной музыкальной сцены. Методологически автор опирается на концепцию теории семиосферы Ю. Лотмана и намеревается воссоздать специфическую семиотическую атмосферу, в которой родились произведения Ерофеева, принимая во внимание также мемуары современников, критические материалы и биографию писателя. Междисциплинарный подход исследования связан с принципом диалога между литературными и художественными, музыкальными и семиотическими дискурсами. Среди многочисленных аллюзий в текстах автора можно в первую очередь выделить известные арии из опер и различные произведения классической музыки XIX и XX вв., которыми, несмотря на скромные средства и жизнь на обочине общества, Ерофеев был увлечен и тонким знатоком которых он являлся. Это было возможно в значительной степени благодаря советским радиопрограммам, в которых постоянно транслировалась подобная музыка, эти музыкальные мотивы интенсивно присутствовали в повседневной жизни людей брежневской эпохи. По многим свидетельствам, наряду с алкоголем, они были среди немногих составляющих жизни, способных скрасить серость тех лет. Основные объекты исследовательского интереса автора статьи - музыкальные образы, присутствующие в знаменитой поэме в прозе «Москва - Петушки» (1970) и в трагедии «Вальпургиева ночь, или “Шаги Командора”» (1985), а также в «Записных книжках» из сборника «Бесполезное ископаемое» (2001), в юношеском дневнике писателя «Записки психопата» (1956-1957) и в незавершенной ритмической прозе «Благая весть» (1962).

This paper studies the works of the late-Soviet writer Venedikt Vasilyevich Erofeev (1938-1990) with the aim of determining, based on the types, quantity, and hybrid characteristics of the musical references present in them, if it is possible to speak of a consistent “musical subtext” as one of the fils rouges in his creative writing. In fact, similarly to what has been investigated by scholars about the religious and literary domains, the pages of this author sui generis are scattered with hidden references to several popular works and protagonists of the Russian, Soviet, and international music scene. Drawing upon the methodological point of view on the conceptualization of Lotman’s semiosphere theory, the article intends to recreate the peculiar semiotic atmosphere in which Erofeev’s works were born, considering also memoirs of contemporaries, critical materials and a recent biography of the writer. The interdisciplinary approach of the research relates to the principle of dialogue between the literary and the artistic, the musical and the semiotic discourses. Among the manifold allusions in the author’s texts one can find famous arias from operas and various pieces of classical music from the nineteenth and twentieth centuries, of which, despite his modest means and his life on the margins of society, Erofeev was a passionate and fine connoisseur. This was mainly possible thanks to Soviet radio programmes, which between the 1950s and the late 1970s constantly broadcast classical music and operatic arias: with their universal themes, celebrated heroes and vocal virtuosity these musical motifs were intensely present in the daily life of the Brezhnev era. According to a lot of testimonies, along with alcohol, they were among the few elements able to “shake out” the greyness and immobilism of those years, indelibly marking even the imagination of ordinary people. After a biographical contextualization of the author, the main areas of interest will be the musical elements present in the famous prose-poem Moskva - Petushki (1970) and in the tragedy Val’purgieva Noch’, ili “Shagi Komandora” (Walpurgis Night, or “The Steps of the Commander”, 1985). Secondly, some passages of the Notebooks from the collection Bespoleznoe iskopaemoe (Useless Fossil, 2001), of the writer’s youth diary Zapiski psichopata (Memoirs of a Psychopath, 1956-1957) and of the unfinished rhythmic prose Blagaja Vest’ (The Gospel, 1962) will be also taken into consideration.

Relevance. The interconnectedness of global financial markets implies that shocks in one region can have widespread implications. The recent geopolitical tensions in the Middle East and Western Europe, have significantly heightened Geopolitical Risk (GPR) and Economic Policy Uncertainty (EPU). Country-specific financial stability can experience ripple effects from these external sources of risk, indicating a direct link between geopolitical events and economic policy uncertainties that contribute to financial stress. Research Objective. This study examines the risk spillovers from Global Geopolitical Risk (GLGPR) and Economic Policy Uncertainty (GLEPU) to the country-wise Financial Stress Index (FSI) of the USA, China, and Russia. Our goal is to determine which of these giants demonstrates superior resilience in terms of financial stability against these external sources of risks. Data and Methods. Using Cross-Quantilogram (CQ), Partial-CQ and Recursive-CQ (R-CQ), we evaluate a weekly high-frequency data from 2000 to 2023 to identify patterns of these spillover effects. Results. Our findings indicate that GLGPR has mixed spillover effects on the USA’s FSI under varying market conditions, while the FSI shows long-term resilience to GLEPU. For China, GLGPR only boosts the FSI during long-term bullish markets, and GLEPU demonstrates pronounced adverse impact at the bullish market. In contrast, the Russian FSI reacts unevenly to both GLGPR and GLEPU, experiencing greater severity. Overall, the USA’s financial market exhibits the highest resilience to GLEPU, while the Chinese market demonstrates the greatest resilience to GLGPR. In contrast, the Russian financial market shows the highest exposure to these global risks. Conclusions. No previous empirical study has examined the financial stress response of these three globally powerful economies to external sources of risk such as GLGPR and GLEPU. Most of the previous research focuses solely on stock market returns or their volatility in relation to these risks, whereas we focus on a composite measure of stability that encompasses all four sectors of a financial market. Our research fills this gap, particularly in the context of current geopolitical tensions among these global players, making it highly relevant for both academics and policymakers.

Relevance. Similar to other countries, Indonesia’s economy was significantly impacted by the COVID-19 pandemic, especially at the district and city levels. As the second-largest contributor to Indonesia’s GDP, East Java faced noticeable economic downturns. Industry, the region’s main economic sector, played a key role in these challenges, making it essential to evaluate all sectors from a regional economic perspective to navigate this turbulence effectively. Research objective. This study investigates the regional economy’s sectoral competitiveness in East Java, with a particular focus on the 17 sectors categorized by Statistic Indonesia (Badan Pusat Statistik-BPS) before and after COVID-19. Data and methods. The study relies on data from Badan Pusat Statistik (BPS)). The dataset includes GDP information for 11 regions, namely 7 districts and 4 cities, in East Java from 2018 to 2022, covering the pre- and post-pandemic periods. Methodologically, the study employed Location Quotient (LQ) analysis and Mix and Share Analysis. LQ analysis was used to assess the concentration and comparative advantage of East Java’s regions. Mix and Share and Shift-Share analyses were applied to identify the competitive industries in specific regions and their advantages. Results. The findings show positive economic growth in most regions of East Java before and after the pandemic, except for two regencies that saw a decline. The study emphasizes the need to strengthen regional resilience at the village level using the Village Fund from the national budget. Conclusions. Regional stakeholders, central government interventions, and continued development of leading sectors are essential for mitigating the effects of COVID-19. According to regional economic theory, collaboration between the government and businesses is crucial for enhancing competitive advantage and increasing the number of leading sectors.

A graph G is splittable if its set of vertices can be represented as the union of a clique and a coclique. We will call a graph H a {splittable ancestor} of a graph G if the graph G is reducible to the graph H using some sequential lifting rotations of edges and H is a splittable graph. A splittable r-ancestor of G we will call its splittable ancestor whose Durfey rank is r. Let us set s=(1/2)(sumtl(λ)−sumhd(λ)), where hd(λ) and tl(λ) are the head and the tail of a partition λ. The main goal of this work is to prove that any graph G of Durfey rank r is reducible by s successive lifting rotations of edges to a splittable r-ancestor H and s is the smallest non-negative integer with this property. Note that the degree partition dpt(G) of the graph G can be obtained from the degree partition dpt(H) of the splittable r-ancestor H using a sequence of s elementary transformations of the first type. The obtained results provide new opportunities for investigating the set of all realizations of a given graphical partition using splittable graphs.

The paper considers the problem of finding the reachable set for a linear system with determinate and stochastic Liu’s uncertainties. As Liu’s uncertainties, we use uniformly distributed ordinary uncertain values defined in some uncertain space and independent of one another. This fact means that the state vector of the system becomes infinite-dimensional. As determinate uncertainties, we consider feedback controls and unknown initial states. Besides, there is a constraint in the form of a sum of uncertain expectations. The initial estimation problem reduces to a determinate multi-step problem for matrices with a fixed constraint at the right end of the trajectory. This reduction requires some information on Liu’s theory. We give necessary and sufficient conditions for the finiteness of a target functional in the obtained determinate problem. We provide a numerical example of a two-dimensional two-step system.

Inflation is one of the most important macroeconomic indicators that have a great impact on the population of any country and region. Inflation is influenced by a range of factors, including inflation expectations. Many central banks take this factor into consideration while implementing monetary policy within the inflation targeting regime. Nowadays, a lot of people are active users of the Internet, especially social networks. It is hypothesised that people search, read, and discuss mainly only those issues that are of particular interest to them. It is logical to assume that the dynamics of prices may also be in the focus of users’ discussions. So, such discussions could be regarded as an alternative source of more rapid information about inflation expectations. This study is based on unstructured data from VKontakte social network used to analyse upward and downward inflationary trends (on the example of the Omsk region). The sample of more than 8.5 million posts was collected between January 2010 and May 2022. The authors used BERT neural networks to solve the problem. These models demonstrated better results than the benchmarks (e. g., logistic regression, decision tree classifier, etc.). It makes possible to define pro-inflationary and disinflationary types of keywords in different contexts and get their visualisation with SHAP method. This analysis provides additional operational information about inflationary processes at the regional level The proposed approach can be scaled for other regions. At the same time, the limitation of the work is the time and power costs for the initial training of similar models for all regions of Russia.

Despite the growing popularity of online shopping, there is a lack of research on regional differences in consumer behaviour and preferences, particularly among women. The study aims to investigate the regional differences in women’s online shopping behaviour in Kazakhstan by conducting an in-depth analysis of the factors influencing female consumers. Using data from a survey of 400 women across different regions of Kazakhstan, logistic regression analysis was utilised to examine the relationship between online shopping frequency and several independent variables. The analysis found that the pandemic significantly affected online shopping behaviour in Kazakhstan, leading to decreased shopping frequency across all regions. Additionally, we found that women living in urban areas were significantly more likely to shop online frequently than those in rural areas, with an odds ratio of 0.504 (p = 0.014). The research also revealed notable differences in Internet penetration rates, with Karaganda, Pavlodar regions and Astana city having the highest rates among women (93.1 %, 93.0 %, and 94.5 %, respectively), while Atyrau and Kyzylorda regions had the lowest (80.7 % and 80.0 %). Therefore, it is recommended that policymakers should focus on expanding Internet infrastructure in remote regions by developing customised online marketplaces that meet the needs of urban areas like Almaty city. The findings of this study underscore the importance of considering regional differences in understanding the factors that drive online shopping behaviour in Kazakhstan. By investing in initiatives that promote e-commerce adoption and cater to consumers’ unique needs and preferences in different regions, policymakers can help foster a more inclusive and dynamic e-commerce ecosystem in Kazakhstan.

Export development is a priority for the Russian economy, as it plays a crucial role in ensuring sustainable economic growth. In this context, understanding the determinants of regional export development is essential. In their export activities, Russian companies face a range of limiting factors, many of which have been thoroughly examined, with corresponding mitigation strategies incorporated into export plans. However, the role of the global climate agenda and the energy transition in shaping export development remains largely unexplored for Russian regions. The shift of focus to fulfilling environmental goals creates a new type of economic risk for exporters - transitional climate risks, which intensified after February 2022. This study investigates the comprehensive impact of the global energy transition on export flows in Russian regions and identifies region-specific factors that influence how the energy shift affects export levels. The hypothesis is that the global energy transition creates both risks and opportunities for Russian regions, with varying effects depending on the specific components of the energy shift and the socio-economic and environmental characteristics of each region. Using the gravity equation with the Poisson Pseudo-Maximum Likelihood (PPML) technique, the study finds that the impact of the global energy transition on Russian regional exports is multidirectional. First, environmental regulations in partner countries reduce exports from many Russian regions by 0.3 %, though regions with favorable socio-economic conditions for innovation and active regional environmental policies see an increase in exports-by 0.3 % and 0.7 %, respectively. Second, the production of alternative energy in partner countries decreases Russian exports by 0.2 %. Finally, exports from mineral-abundant Russian regions benefit from the global energy transition. These findings contribute to the literature on Russian export promotion and offer valuable policy insights for addressing the challenges and opportunities posed by the global energy transition.

R&D&I является важным направлением инновационного роста отечественных субъектов экономики. Замкнутость на внутренней системе управления инновациями может не привести к результатам, запланированным в рамках ключевых стратегических документов государственного уровня. Расширение ее границ и вовлечение внешних участников в решение проблем инновационной деятельности станет опорой для создания мощной интегрированной структуры, обеспечивающей инновационный лифт и научно-технологическое обновление предприятий. Научно обоснованный подход к формированию сбалансированной системы коллаборативного управления инновациям - залог устойчивого функционирования инновационно-активных предприятий. Цель настоящего исследования состоит в формировании научно-практических рекомендаций по созданию R&D&I системы поддержки инновационно-активных предприятий для обеспечения эффективности их функционирования в условиях глобальных экономических вызовов. В процессе достижения поставленной цели использовались следующие методы научного познания: структурный анализ и синтез, системный анализ, обобщение и описание, моделирование. По результатам проведенного исследования разработана структурно-функциональная модель R&D&I системы поддержки инновационно-активных предприятий, в отличие от существующих, создающая платформу для сбалансированного инновационного развития и роста конкурентоспособности посредством когерентной организации интегрированных инновационных цепочек и результативного управления инновациями в единой синергетической среде. Научные выводы и предложения имеют высокую значимость для развития теоретико-методологических положений теории инноватики, управления инновационной деятельностью и решения проблем инновационно-активных предприятий РФ. Исследование опирается на современные труды ведущих отечественных и зарубежных экономистов. R&D&I система поддержки инновационно-активных предприятий создает основу для их устойчивого функционирования в условиях санкционных ограничений и экономических потрясений. Автором определен вектор развития отечественных предприятий для обеспечения эффективной реализации миссии и достижения стратегических целей.

In the context of sanctions pressure on Russia the issues of import substitution in the field of digital technologies are getting even more urgent. Highly qualified specialists with respective competencies are in short demand in the country. The government take some measures to that end, but they can solve all the problems. Engagement of required specialists from abroad - those working on a remote basis - could improve the situation. However, there are certain unresolved issues in the labor legislation of the Russian Federation and some other countries, including members of international economic integration organizations such as the Eurasian Economic Union that hinder this process. Identification of hindrances and restrictions preventing free movement of human resources in EAEU member states and efficient use of remote work in the field of IT is what this paper is dedicated to. To that end the actual situation unfolding in the labor market of the field of IT on the territory of EAEU member states has been analyzed, and so has been labor and other legislation of member states regulating the labor of remote workers and the academic literature and papers published in the periodicals. The system analysis and comprehensive review of sources and comparative legal studies have become the main methods of research. As a result, legal and organizational restrictions preventing efficient application of remote work of IT specialists typical for some or even all EAEU member states have been identified. Also, there have been suggested some ways to overcome the identified restrictions that can be implemented by adopting new legal provisions or by amending the existing ones.

Usage of neural network technologies, namely various learning and self-learning programs that gather, analyze a great volume of information on an employee and manufacturing process, have an access to a worldwide network, are integrated with video-, audio-, and other fixation systems by employers generates new economic and technological and social and legal risks. Inconsistence of labor and information legislation in the field of protection of personal data of employees determines novel conditions for potential violations of rights of employees and growth of the quantity of labor conflicts. Separate problems are caused by gathering and treating personal data with artificial intelligence and far from all of them are technical in nature, even if determined by specific features of neural network technologies. This article discusses main risks for personal data of employees under conditions of usage of specific neural network technologies for staff recruitment and supervision over employees, including monitoring in order to ensure the safety of work performance. With this object in view, labor codes, laws, and bylaws on labor protection, laws on protection of personal data of the countries of the EAEU. Systemic and complex analysis of sources of legal regulation and comparative legal studies were primary investigative techniques. In consequence of this, legal and social risks of usage of neural network technologies for staff recruitment and organization of supervision over compliance with labor discipline by employees, especially in regard to the provision of safe labor conditions, as well as discrepancies between labor and information legislations were revealed. Several methods for overcoming revealed discrepancies, which allow to ensure a proper protection of employees’ rights in the field of protection of personal data before long, were proposed.

Introduction. Coronavirus infection has received much attention over the past three years. In addition to its enormous social significance, the COVID-19 pandemic has highlighted a number of conceptually new clinical aspects of human immunopathology. Due to a higher susceptibility to infectious complications, this problem is particularly relevant for patients suffering from autoimmune inflammatory rheumatic diseases (AIRDs). In the presence of AIRDs, the possibility of developing a wide range of delayed COVID-19 effects becomes most likely. According to the COVID-19 Global Rheumatology Alliance registries, of 600 cases of new coronavirus infection in patients with AIRDs, about 46% required hospitalization.