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September 7, 2026
Biologists Discover 'Molecular Fingerprint' of Preeclampsia
Researchers at HSE University employed a new method to model hypoxia in placental cells during pregnancies complicated by preeclampsia and identified molecular markers of tissue hypoxia. Since hypoxia is one of the key mechanisms underlying preeclampsia, these findings are important for a more accurate and timely diagnosis of the disease and for the development of effective treatment methods. The paper has been published in Placenta.
September 7, 2026
‘Speech, Facial Expressions, and Gestures Cannot Lie
Would you like to know whether a speaker’s trembling voice or an accidental gesture can give them away? At HSE University in Nizhny Novgorod, researchers are developing an algorithm that analyses speech, facial expressions, and gestures, and determines whether information is truthful with 92% accuracy. The project has applications ranging from forensic examination and bank recruitment to fundamental research. Anna Khomenko, head of the research group and Senior Research Fellow at the Centre for Language and Brain at the HSE Faculty of Humanities in Nizhny Novgorod, explains how students and researchers are working together to create a corpus of video recordings, train a classifier, and prepare to introduce computer vision technology.
September 4, 2026
Time to Showcase Your Research: Applications Are Now Open for Student Research Paper Competition 2026
Taking part in the Student Research Paper Competition (SRPC) gives you an opportunity to present your research to experts, receive an independent assessment, and determine the future direction of your work. The competition is open to students graduating in 2026 not only from HSE University but from universities in Russia and abroad. Papers may be submitted in Russian and English, and in some fields also in French, German, and Spanish.

 

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Взаимосвязь сетевых характеристик и субъектности сетевых сообществ в социальной сети Твиттер

Вопросы кибербезопасности. 2020. Т. 37. № 3. С. 40–57.
Chepovskiy A., Воронин А. Н., Ковалева Ю. В.

The purpose of the study: analysis of the graph of interacting objects of social networks based on the selection of implicit communities, assessment of the subjectivity of the selected communities and comparison of the network characteristics of communities and various indicators of their subjectivity.

Method: communities detection on the constructed weighted graph of a social network, psycholinguistic analysis of community content using a list of discourse markers of subjectivity, statistical methods for identifying the relationship between network characteristics and the frequency of discourse markers.

Results: algorithms to construct a graph and to import user attributes were developed, an algorithm for dividing a weighted graph into implicit user communities was implemented, the subjectivity of the content of the selected network communities in the social network Twitter has was assessed, the relationship and directional shift in the connectivity of the graph and various indicators of the subjectivity of the network community were identified.

Research target: Computer Science Psychology
Priority areas: IT and mathematics
Language: Russian
Full text
DOI
Keywords: social subjectivitysocial network analysisnetwork communityвыделение сообществанализ социальной сетиdiscourse markersдискурсивные маркерысоциальный графgraph community detection
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