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July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.
July 20, 2026
Scientists Propose Method for More Efficient Resource Use in Machine Learning
An international group of researchers, including mathematicians from the AI and Digital Science Institute at the HSE Faculty of Computer Science, has provided a theoretical justification for a simple and computationally efficient method of estimating uncertainty in Stochastic Gradient Descent (SGD). The paper has been published on the scientific preprint server arXiv.org and presented at AISTATS 2026.

 

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Training poverty in India: Reassessing the effect of social ascription

International Journal of Training and Development. 2021. Vol. 25. No. 3. P. 277–300.
Anikin V. A.

This paper set out to reassess the effects of economic and social determinants of the probability of formal vocational training in India. Applying the four-level cross-classified logistic model to the 2011–2012 National Sample Survey data, the paper identified the association between formal training and ‘good jobs’ in large urban electrified firms that offer permanent employment and regular monthly salary to their skilled occupation workers. Nevertheless, India remains a country of severe training poverty. This study confirms that the traditional mindset of the society does contribute to the training poverty; however, this impact is much limited to the household level and religious groups, such as Christians, which are systematically excluded from formal training as compared to Hindus, Sikhs and Buddhists. In contrast, the lower castes and deprived social backgrounds do not affect, as predicted by previous studies. Moreover, it is shown that unskilled males from the rural area of India were less likely to receive formal training as compared to educated single women

Research target: Education Economics and Management Other social sciences Social and Economic Geography (including Urban and Transportation Studies) Sociology (including Demography and Anthropology Social Sciences
Priority areas: economics sociology management state and public administration humanitarian
Language: English
Full text
DOI
Keywords: modernisationIndiaskills developmentmultilevel modellingascriptiontraining povertygood jobscastes
Publication based on the results of:
Analysis of adaptation of various socio-economic and demographic groups to the pandemic consequences in the context of new social policy measures (2021)
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