SCI Библиотека

Relevance. The paper explores interregional cooperation, examining the challenges of aligning spatial and innovation development in macro-regions, with a focus on two federal districts of Russia. The study assesses the potential of interregional cooperation among neighboring regions within a single federal district, as well as among more distant regions across different federal districts. Research Objective. The study aims to test two hypotheses: the first deals with the viability of imitation innovation strategies in peripheral regions of both intra and inter-federal districts. The second hypothesis concerns the presence of innovation interdependence (autocorrelation) among regions from different federal districts, influenced by the level and industrial compatibility of innovation outputs. Data and methods. The study employs the DEA method to identify central and peripheral regions (imitator regions) by calculating technical efficiency indicators. It also uses coupling interregional complementarity indexes to assess the potential for interregional cooperation in innovation and technological import substitution, considering the industrial profiles of the regions. Spatial autocorrelation is evaluated by using Moran’s Index to estimate the level of regional interdependence, factoring in the level and industry conformity of innovation output. The novelty of the proposed methodological approach lies in the application of interregional indexes of innovation complementarity as weighting coefficients in Moran’s Index calculation. Results. The study reveals a rise in spatial inequality, competition among regions, and constrained interregional innovation cooperation across federal districts. Geographical proximity currently plays a pivotal role in cooperation, with initial indications of a macro-regional space evolving through knowledge exchange. However, both hypotheses concerning imitation strategies and autocorrelation are only confirmed for regions within a single federal district. Conclusions. The findings of this study regarding spatial autocorrelation offer valuable insights for policymakers in the sphere of regional innovation.

Внедрение лантаноидсодержащих металломезогенов с уникальными структурными, жидкокристаллическими (ЖК), оптическими и магнитными свойствами в полифункциональные материалы ограничивается сложностью предсказания характеристик получаемых образцов. Неоднозначно установленное влияние строения мезогенных комплексов на оптические свойства, их зависимость от различных факторов и малоизученные фотофизические механизмы усложняют применение данных соединений. Данная работа направлена на расширение теоретических подходов к созданию оптических материалов на основе мезогенных биядерных комплексов европия(III) (Eu(III)) с замещенными β-дикетонами и основаниями Льюиса. На основе проведенных квантово-химических расчетов были изучены взаимосвязи между строением комплексов, их геометрическими параметрами, энергиями возбужденных состояний, параметрами интенсивности люминесценции, скоростями внутримолекулярного переноса энергии и значениями теоретического квантового выхода. Было показано, что в отличие от ЖК-поведения, зависящего в основном от лигандного окружения комплексов Eu(III), их оптические свойства определяются строением лигандов и координационных полиэдров.

Relevance. As permanent settlements in the Russian Far North suffer increasing depopulation, a “shadow” settlement framework is emerging through rotational labor migration. Despite nearly half a century of history, rotational shift work in the North remains largely spontaneous, posing risks to sustainable development. Research Objective. This study examines rotational shift settlements as elements of the population settlement system in the Russian Far North and analyzes their role in transforming the region’s settlement patterns. Data and Methods. Data on rotational shift camps were gathered from various open web sources and the Ministry for the Development of the Far East and the Arctic. Information on permanent settlements was obtained from Rosstat (Federal State Statistics Service). The study employed systemic and comparative analysis methods. Results. Unlike other Russian regions, rotational shift settlements in the Far North were initially integrated into the local settlement system. However, socio-economic changes in the 1990s disrupted the established Soviet model of integration, leading to the spontaneous development of these settlements. This unregulated growth poses increasing risks in such areas as ecology and social well-being. Conclusions. To regulate the status of rotational settlements, legislative initiatives should be supported by updated conceptual and terminological frameworks. The urbanization process in this geostrategically important and environmentally vulnerable region must be controlled or at least predictable to ensure timely responses to emergencies.

Relevance. Intergovernmental budgetary regulation is pivotal for promoting territorial equalization and bridging socio-economic gaps among regions. It ensures equitable access to public goods for all citizens, irrespective of their location. The effective distribution of federal financial assistance, guided by the principles of budget federalism, is essential for maintaining macroeconomic stability and fostering sustainable socio-economic development on the national and regional levels. Research Objective. The study aims to assess the competitive positions of Russian regions within the distribution system of federal intergovernmental transfers. Method and Data. To investigate Russia’s system of intergovernmental transfers, the research employs statistical methods, including structural-dynamic, grouping, and graphical analysis, along with novel analytical tools like the dependence coefficient and income coefficient. The study encompasses data from 2015 to 2022, sourced from the Federal Treasury and Federal State Statistics Service (Rosstat). Results. The study analyzes the dynamics of transfers from the federal budget to regional budgets and shows significant transformations in the transfer structure, revealing a decrease in non-targeted transfers and an increase in targeted ones. The study also examines the differences between regions in the distribution of these transfers. Russian regions were grouped depending on the share of federal transfers in their total budget income and the average per capita income in their consolidated budget. The study introduces a novel methodological approach through the use of newly developed tools - the dependence coefficient and income coefficient - to evaluate regional competitiveness. Conclusion. Despite an overall increase in federal transfers, persistent regional disparities intensify competition for financial assistance. These findings can be of interest to policymakers at federal and regional levels, researchers, and educators in relevant fields.

Relevance. In the current economic climate, maintaining the integrity of regional economic space is crucial. This involves ensuring uniform socio-economic development across regions and promoting a high rate of technology transfer from the center to the periphery. Therefore, it is essential to identify sustainable points of spatial development that represent centers of power concentration and guide spatial transformation. Research objective. The study aims to assess the connectivity of the region’s economic space by measuring population mobility. This approach will help identify the centers of social and labor communications that represent sustainable points of spatial development. The focus of the study is on the municipal districts of Sverdlovsk region, which are key elements of its economic space. Data and methods. The study employed geoinformation analysis of origin-destination matrix of population flows in Sverdlovsk region (Russian Federation), provided by Russian mobile operators. Results. The paper presents the analysis of intracity and intercity population flows based on the average daily data of mobile operators for 2022. The intensity and diversification of population flows in the region’s municipal districts, reflecting the connectivity of its economic space, were estimated using geographic information systems and the Python programming language. The study revealed that Sverdlovsk region has a bicentric system of spatial interconnections, with two distinct centers of attraction: Ekaterinburg and Nizhny Tagil, with Ekaterinburg being the dominant center. Conclusions. The proposed classification of municipal districts by the level of their inclusion into the economic space of Sverdlovsk region illustrates that only 5% are characterized by intensive and diversified inter-territorial interaction, while 34% are characterized by low indicators of intensity and diversification of mobile population flows. The spatial structure of the municipalities in Sverdlovsk region, which are located in the zone of attraction to the agglomeration centers, will be maintained and reinforced.

Направления расходов бюджетов регионов в рамках госпрограмм классифицированы в соответствии с критерием поддержки развития реального сектора экономики. Выявлено, что северные регионы России лидируют по доле отраслей реального сектора в структуре экономики, но доля бюджетных расходов на поддержку реального сектора относительно низкая. Установлено, что отраслевая структура экономики оказывает определённое влияние на выбор структуры расходов региональных бюджетов северных регионов.

В статье рассматривается реализация региональной составляющей федерального проекта «Создание единого цифрового контура в здравоохранении на основе единой государственной информационной системы в сфере здравоохранения (ЕГИСЗ)» в Республике Коми в 2023 г. как показатель уровня цифрового развития отрасли здравоохранения в регионе.

Relevance. Fostering well-being ranks high on regional social policy agendas. With the dynamic shifts in the international economic landscape, known as geo-economic fragmentation, there’s a pressing urgency for stakeholders to optimize resource allocation at the regional level, increasing interest in efficient strategies to adapt to sanctions while enhancing overall well-being. Research objective. This article aims to investigate the dimensions and determinants of the eco- and human capital efficiency in Russian regions in the context of geo-economic fragmentation and sanctions pressure. Data and methods. A proposed three-stage approach integrates factor analysis to identify subjective well-being indicators, data envelopment analysis (DEA) to evaluate socio-eco-efficiency, and panel tobit regression to examine the determinants of efficiency. Microdata from the Rossat Comprehensive Observation of Living Conditions database were utilized, covering the period from 2014 to 2022. To assess efficiency, a DEA model is employed. The output indicators from this model were the estimated measures of subjective well-being. These indicators were validated through factor analysis and included professional satisfaction, safety assessment, accessibility and quality of social and cultural infrastructure in the regions. Results. In the given period, people reported feeling increasingly satisfied with jobs and quality of life, though there was a noticeable slowdown in the growth of human capital development indicators, environmental investments, and real income by early 2023. Efficiency varied significantly among the regions. Industrially developed mining areas and republics in the North Caucasus consistently showed high socio-eco-efficiency, despite limited resources. The efficiency benefited both from digitalization and increased per capita gross regional product, but urbanization had a negative impact. Conclusions. Amid geo-economic fragmentation, regional communities and job markets face significant challenges in adaptation. With the looming risk of declining satisfaction and perceived quality of life, it is imperative for regional policies to bolster tangible well-being indicators and invest in social capital and infrastructure to address these issues effectively.

Панорамная визуализация потока или теплоотдачи на поверхностных моделях является эффективным и информативным методом исследования направления в пограничном слое. Вследствие развития цифровых и технических возможностей научные исследования все более основаны на анализе больших данных с помощью искусственного интеллекта (ИИ). Насколько оправдано применение тех или иных методов ИИ в каждой конкретной задаче, пока открытый вопрос. Цель работы - обзор результатов применения нейронных сетей (НС) и машинного обучения для решения задач диагностики течений с помощью ЖК. А именно, для измерения полей температуры, тепловых потоков и векторов касательного напряжения внешнего трения. Кроме этого, актуальными задачами являются измерение физической характеристики ЖК и получение новых ЖК-смесей. Обсуждаются возможности и ограничения, области применения и перспективы нейросетевого подключения. А также программные средства для его реализации. Анализ литературных данных показал, что применение НС и глубокого машинного обучения для аппроксимации калибровочных зависимостей температуры и касательного напряжения от многофакторного оптического отклика ЖК позволяет получить точность, сравнимую с пределом контрольной выборки.

В статье освещено положение фармацевтической службы в Республике Коми. Дана характеристика коммерческих и государственных аптечных организаций, состояния льготного лекарственного обеспечения, лекарственного обеспечения медицинских организаций. Показано кадровое обеспечение фармацевтической службы. Описана деятельность региональной общественной организации «Фармацевтическая ассоциация» Республики Коми. Авторами даны рекомендации по развитию фармацевтической службы в Республике Коми.