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The implementation of new automation technologies together with the development of artificial intelligence can free up a significant amount of labor. This sharply increases the risks of digital transformation. At the same time, certain regions and cities differ greatly in their ability to adapt to future changes. In this article, we seek to determine the capabilities of Russian regions to reduce risks and adapt to digital transformation. The literature stipulates that there are several factors able to reduce these risks. First of all, they are associated with retraining, ICT and STEAM-technologies’ development, the promotion of economic activities that are less subject to automation. As a result of econometric calculations, we identified several factors that contribute to the new industries’ development (in our case, ICT development), and, accordingly, increase regional adaptivity. These factors  include diversification, the concentration of human capital, favorable entrepreneurship conditions, the creative potential of residents, and the development of ICT infrastructure. We identified several regions with high social risks and low adaptivity, which are mainly the poorly developed regions of southern Russia, where entrepreneurial risks are high, STEAM specialists are not trained, shadow economy is large. This work contributes policy tools for adaptation to digital transformation.

Finding the position of the polar boundary of the outer electron radiation belt, relative to the position of the auroral oval, is a long-standing problem. Here we analyze it using the data of the METEOR-M1 auroral satellite for the period from 11 November 2009 to 27 March 2010. The geomagnetic conditions during the analyzed period were comparatively quiet. METEOR-M1 has a polar solar-synchronous circular orbit with an altitude of ≈832 km, a period of 101.3 min, and an inclination of 98∘. We analyze flux observations of auroral electrons with energies between 0.03 and 16 keV, and electrons with energies >100 keV, measured simultaneously by the GGAK-M set of instruments, composed of semiconductors, scintillator detectors, and electrostatic analyzers. We assume that in the absence of geomagnetic storms the polar boundary of the outer radiation belt can be identified as a decrease in the count rate of precipitating energetic electrons to the background level. It was found that this boundary can be located both inside the auroral oval or equatorward of the equatorial boundary of the auroral precipitation. It was also found that for slightly disturbed geomagnetic conditions the polar boundary of the outer radiation belt is almost always located inside the auroral oval. We observe that the difference between the position of the polar boundary of the outer radiation belt and the position of the equatorial boundary of the auroral precipitation depend on the AE and PC indices of geomagnetic activity. The implications of these results in the analysis of the formation of the outer radiation belt are discussed.

The aim of this paper is to evaluate which university's characteristics have the greatest impact on the competitiveness of universities in their ability to attract better students in Russia. We examined the impact of three groups of factors,related to teaching, research and entrepreneurial activities of universities. The quantile regression model was applied for the subsample of public and private higher education institutions localized in Russia. The results prove that not only traditional, teaching-related factors affect the attractiveness of the universities. We found that the research quality and entrepreneurial experience both increase the ability to accumulate the best applicants by Russian universities. However, the synergy between training, research and business activities is not always achieved. The importance of science and business-oriented activities varies between public and private institutions. According to the results from the quantile regression the importance of the certain factors differs between the quantiles of the dependent variable distribution. Our findings might be useful for the governmental authorities during the universities' assessment as well as for the higher education institutions themselves - in order to define their strategic development and attract better students.

The study aims at identifying the role of traditional and new factors that contribute to attracting highly educated workers. We summarized the key literature facts and performed econometric analyses on previously unused data on both internal and external migration with higher education in the Russian regions from 2008 to 2019. Our methodology differs from traditional models based on migration flows between destinations and focuses on characteristics of receiving regions. We showed that densely populated metropolitan areas with broader labour markets opportunities stimulate highly skilled mobility; higher income, new vacancies and housing availability are among significant traditional factors. However, migrants with higher education also chose educated, healthy communities and favourable business environment as such regions provided wider career and other opportunities. It is shown for the first time for Russia that improving the business climate helps to attract highly skilled human capital. Mild climate and comfortable environment turned out to be preferable, although the richest centres of oil and gas production in the north are actively attracting migrants. Improved access to the Internet and further digitalization can reduce migration, which may be related to the prospects of remote work. High scientific and educational potential is significant, but only attracting students is not enough, as they will leave a region after graduation. In conclusion, we offered some non-trivial policy recommendations based on the identified factors and considering the new pandemic reality: high-tech cluster development, proactive scientific and entrepreneurial policy, and measures to improve urban environment in the largest agglomerations and southern regions.

Spending on innovation increased annually in the 2000s in Russia’s regions, but innovation productivity varies greatly between regions. In the current climate of sanctions between Russia and Western countries and limitations on international technology transfer, there is a growing need to analyse the factors influencing regional innovation. Previous empirical studies using a knowledge production function approach have found that the main factor of the growth of regional innovation is increasing spending on research and development (R&D). Our econometric analyses show that the quality of human capital, a product of the number of economically active urban citizens with a higher education (the so-called creative class) has the greatest influence on the number of potentially commercializable patents. Other significant factors were buying equipment, which indicates a high rate of wear and tear of Russian machinery, and spending on basic research. The ‘centre-periphery’ structure of Russia’s innovation system favours the migration of highly qualified researchers to leading regions, which weakens the potential of the ‘donor regions’. However, at the same time, we see significantly fewer limitations on knowledge spillovers in the form of patents and - in this case - proximity to the ‘centres’ is a positive factor.

В условиях экономических санкций, введенных в отношении России рядом зарубежных партнеров в 2014 г., особое значение приобретают высокотехнологичные отрасли хозяйства как важнейший источник замещения импортной продукции на внутреннем рынке. Одной из ключевых мер поддержки таких отраслей служит развитие специализированных кластеров за счет установления новых и укрепления существующих связей между субъектами малого и среднего бизнеса, крупными предприятиями и научными организациями. Отправной точной эффективной кластерной политики служит идентификация регионов с высоким потенциалом кластеризации указанных отраслей.В работе представлена оригинальная методика выявления потенциальных кластеров и приведены результаты ее апробации в регионах России. Авторы демонстрируют, что большинство поддерживаемых государством пилотных инновационных проектов реализуются в регионах и отраслях, обладающих высоким кластерным потенциалом. Произведена типологизация пилотных инновационных территориальных кластеров в зависимости от потенциала кластеризации регионов их расположения, выраженного в соответствующем индексе. Определены регионы со сходными или более благоприятными условиями для формирования кластеров в инновационных отраслях, отобранных в качестве пилотных.Примечание: Уважаемые читатели, обращаем Ваше внимание, что в печатной версии статьи на картосхемах (рис. 1-7) цвета в легенде ошибочно приведены в обратном порядке. Следует читать: красным показаны наибольшие значения индекса, синим - наименьшие.

Data on transient atmospheric events (TAEs) were obtained from the Vernov satellite and are presented in this paper. The data are considered in conjunction with previous data obtained by the Universitetsky-Tatiana-1 and Universitetsky-Tatiana-2 satellites. The larger volume of stored scientific data in the Vernov mission and its advanced ultraviolet (UV) and red–infrared (R–IR) radiation detector (DUV) measurements allowed improved TAE-distribution data to be obtained over a wide range of photon numbers. The difference between features of luminous transients and ‘‘dim’’ transients, measured by the Universitetsky-Tatiana-2 satellite, is confirmed by Vernov’s data. There are also interesting dim UV events with no R–IR radiation. Such events are expected to be deep in the atmosphere at the level of thunderstorm clouds. They might be radiated by electric discharges of less power than lightning; in fact, at the preliminary stage of lightning. The observation of repeating dim TAEs in various time intervals, starting from tens of milliseconds and up to minutes, indicates that thunderstorm electric activity is much more variable than pure lightning strikes.

Затраты на поддержку инновационной деятельности в российских регионах в 2000-е гг. планомерно росли одновременно с сильной дифференциацией ее результатов. Внешнеэкономические санкции и ограничения по технологическому импорту придали актуальность исследованию факторов региональной изобретательской активности. Эмпирические работы в этой области подтвердили основные положения теоретической модели производственной функции знаний, определив ключевым фактором развития инноваций увеличение затрат на научные исследования.Как показано в статье, количество потенциально коммерциализируемых патентов в наибольшей степени зависит от качества человеческого капитала, производного от численности экономически активных горожан с высшим образованием (так называемый креативный класс). Значимым фактором выступают также затраты на приобретение оборудования вследствие его высокого износа и на фундаментальные исследования, закладывающие основу для новых разработок. Центр-периферийная структура российской инновационной системы способствует миграции высококвалифицированных исследователей в регионы-лидеры, ослабляя потенциал регионов-доноров. Вместе с тем ограничения на переток знаний в форме патентов существенно меньше, а потому близость к «центру» в этом случае рассматривается как положительный фактор.

Data on transient atmospheric events (TAEs) were obtained from the Vernov satellite and are presented in this paper. The data are considered in conjunction with previous data obtained by the Universitetsky-Tatiana-1 and Universitetsky-Tatiana-2 satellites. The larger volume of stored scientific data in the Vernov mission and its advanced ultraviolet (UV) and red-infrared (R-IR) radiation detector (DUV) measurements allowed improved TAE-distribution data to be obtained over a wide range of photon numbers. The difference between features of luminous transients and “dim” transients, measured by the Universitetsky-Tatiana-2 satellite, is confirmed by Vernov’s data. There are also interesting dim UV events with no R-IR radiation. Such events are expected to be deep in the atmosphere at the level of thunderstorm clouds. They might be radiated by electric discharges of less power than lightning; in fact, at the preliminary stage of lightning. The observation of repeating dim TAEs in various time intervals, starting from tens of milliseconds and up to minutes, indicates that thunderstorm electric activity is much more variable than pure lightning strikes.

In the current climate of sanctions imposed against Russia by several countries in 2014, special attention should be given to high-tech sectors of the economy as a key source of import substitution on the domestic market. One of the important policy measures is to support the development of high-tech, specialized clusters by forming new linkages and strengthening existing ones between small and medium-sized businesses, large enterprises, and research organizations. The starting point for an effective cluster policy is to define areas with high potential for clustering of these industries. The paper presents an original method to identify potential clusters and tests the method on Russian regions. We show that most of the state-supported pilot innovative territorial clusters are being developed in regions and sectors that have a high level of cluster potential. A typology of existing clusters depends on the index of clustering potential. We identified regions that have similar or comparatively favourable conditions for creating clusters in the pilot sectors.