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July 24, 2026
'Physics Is What the World Is Literally Built On'
Physicist Nina Dzhanayeva, recipient of a Vladimir Potanin Foundation scholarship, focuses her research on nanophotonics. In this interview for the HSE Young Scientists project, she discusses nanowells, scientific intuition, and how physics can help in making frangipane cream puffs.
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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.

 

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Cross-efficiency of International Sanctions: Application of Data Envelopment Analysis and Network Methodology

P. 72–82.
Zaytsev D., Kuskova V., Lushnikova P., Khvatsky Gregory

In this paper we provide the methodology for evaluating ef- fectiveness of international sanctions using Data Envelopment Analysis (DEA), which we use for generating the network matrix for further anal- ysis. DEA is a non-parametric technique used to compare performance of similar units, such as departments or organizations. DEA has wide applications in all industries, and has been successfully used to compare performance of hospitals, banks, universities, etc. The most important advantage of this technique is that it can handle multiple input and out- put variables, even those not generally comparable to each other. We use the ”Threat and Imposition of Sanctions (TIES)” Data 4.0 for analysis. This database contains the largest number of cases of international sanctions (1412 from the years 1945-2005) imposed by some countries on others, takes into account simultaneous sanction imposition, and also estimates the cost of all sanctions - both for those who receive and those who impose them. As input variables for DEA model we use the impact of sender commitment, anticipated target and sender economic costs, and actual target and sender economic costs. As the output variable, we use the outcome of sanctions for senders. We describe how to use DEA cross-efficiency outputs to build the network of sanction episodes. Our proposed combination of DEA and network methodology allows us to cluster sanction episodes depending on their outcomes, and provides explanations of higher efficiency of one group of sanction episodes over the others.

Language: English
Full text
DOI
Keywords: network analysisEffectiveness of sanctionsData envelopment analysis (DEA)
Publication based on the results of:
Network Sciences: fundamental network research and analytical decision support for government and business (2020)

In book

Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Kazan, Russia, July 17–19, 2019, Revised Selected Papers. Communications in Computer and Information Science
Vol. 1086. , Springer, 2020.
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