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April 30, 2026
HSE Researchers Compile Scientific Database for Studying Childrens Eating Habits
The database created at HSE University can serve as a foundation for studying children’s eating habits. This is outlined in the study ‘The Influence of Age, Gender, and Social-Role Factors on Children’s Compliance with Age-Based Nutritional Norms: An Experimental Study Using the Dish-I-Wish Web Application.’ The work has been carried out as part of the HSE Basic Research Programme and was presented at the XXVI April International Academic Conference named after Evgeny Yasin.
April 30, 2026
New Foresight Centre Study Identifies the Most Destructive Global Trends for Humankind
A team of researchers from the HSE International Research and Educational Foresight Centre has examined how global trends affect the quality of human life—from life expectancy to professional fulfilment. The findings of the study titled ‘Human Capital Transformation under the Influence of Global Trends’ were published in Foresight.
April 28, 2026
Scientists Develop Algorithm for Accurate Financial Time Series Forecasting
Researchers at the HSE Faculty of Computer Science benchmarked more than 200,000 model configurations for predicting financial asset prices and realised volatility, showing that performance can be improved by filtering out noise at specific frequencies in advance. This technique increased accuracy in 65% of cases. The authors also developed their own algorithm, which achieves accuracy comparable to that of the best models while requiring less computational power. The study has been published in Applied Soft Computing.

 

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Направления поддержки малых предприятий промышленного сектора экономики: региональный аспект

Друкеровский вестник. 2022. № 2. С. 86–109.
Arkhipova M., Cherviakova A. A.

Innovation activity of small industrial enterprises substantially varies across Russian regions that makes relevant the search of distinctive features of innovative entrepreneurship in Russian regions in order to develop targeted support for small innovative enterprises and to create new job places in digital economy. Multidimensional clustering of Russian regions by the indicators of small industrial enterprises’ innovation activity and its comparison with EU-27 are presented in the paper. The data of the form of the federal statistical survey N 2-MP innovation for 2017 and 2019 as well as the data of Community Innovation Survey (CIS) for 2018 are used in the analysis. Rather high indicators of small industrial enterprises’ innovation activity and the most favorable conditions for this are typical for a small number of Russian regions. In the majority of Russian regions small industrial enterprises’ innovation activity is lower than on average in Russia as well as in European countries. In these regions the expansion of small enterprises’ access to external financial sources for innovation activity seems to be relevant. Besides, in the cluster with the lowest indicators of small industrial enterprises’ innovation activity support measures promoting R&D among small enterprises are needed

Research target: Economics and Management
Language: Russian
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Keywords: малый бизнескластеризациямалое предпринимательствоклассификациярегионы Россииsmall businessсубъекты Российской Федерацииclusteringclassificationмалые промышленные предприятияregional heterogeneityрегиональная неоднородность Russian regions small entrepreneurshipsmall industrial enterprisestargeted supportадресная поддержка
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