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News
October 19, 2026
'Cultural Studies Seeks to Understand What Lies Beneath the Surface of Everyday Things'
Maxim Zhiganov has been exploring different aspects of sound for many years—first in relation to his native Perm and then on a broader, global scale. In this interview for the HSE Young Scientists project, he talks about sound maps, the special issue of the journal Logos, and why it is important to make the familiar less clear and obvious.
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At HSE University–St Petersburg, Experts Discuss How AI Changes Tourist Routes and Cultural Heritage
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Networks under deep uncertainty concerning food security

The Journal of the New Economic Association. 2024. No. 3(64). P. 12–29.
Aleskerov F. T., Dutta S., Egorov D., Tkachev D.

We propose new models to find the vulnerable countries in terms of food security. These models are based on network analysis under deep uncertainty. The conditions of deep uncertainty affect the supply and demand of food, namely, carbohydrates of the countries. Under such conditions networks of the carbohydrate supply between countries are constructed. The countries vulnerability in terms of food security were studied by new centrality indices taking into account carbohydrate consumptions of countries and the possibility of group influence of countries to a country. Also, our models show direct and indirect dependence on import of carbohydrates from other countries. The scenario of one of such situations was constructed, and our models for studying this situation were tested. The vulnerable countries are identified in terms of carbohydrate consumption from main crops in different scenarios based on real data using our new models. The developed models can make the food policy of countries more efficient.

Research target: Economics and Management Mathematics
Language: English
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Keywords: продовольственная безопасностьсетевой анализсценарный анализnetwork analysisscenario analysisfood insecurityглубокая неопределенностьdeep uncertainty
Publication based on the results of:
Study of the models and methods of decision-making under conditions of deep uncertainty. Extension and testing of developed methods (2024)
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