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News
October 1, 2026
HSE Researchers Show How Congenital Motor Disorders Affect Brain Development
Researchers from HSE University’s Institute for Cognitive Neuroscience have synthesised the findings of their previous studies on brain development in children with obstetric brachial plexus palsy and arthrogryposis. Their analysis shows that impaired motor function in early childhood not only limits children’s motor experience but also affects memory, categorical thinking, and information processing. The study has been published in Frontiers in Psychology.
October 1, 2026
Window into the Body: Scientists Develop Neural Network to Detect Risk of 15 Diseases from Retinal Images
Russian universities, with the participation of HSE University, Sber, and Z-union, have developed a neural network that can simultaneously assess the risk of 15 types of pathology from retinal photographs, including not only eye diseases but also cardiovascular conditions. The AI system can help clinicians detect potentially concerning changes at an early stage, identify signs reflecting the condition of retinal blood vessels, and determine whether a patient may need further examination. The paper has been published in Frontiers in Medicine.
September 30, 2026
'We Did Not Limit the Time for Questions'
The International Laboratory for Supercomputer Atomistic Modelling and Multi-Scale Analysis at HSE University held a major conference on molecular dynamics. Participants had the opportunity to attend all the presentations, while speakers were given as much time as they needed to answer questions. The HSE News Service interviewed Grigory Smirnov, Head of the Laboratory, and Genri Norman, Chief Research Fellow, about the conference preparations and the discussions it generated.

 

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A Searching Tool for Russian Error-Annotated Learner English Corpus

NRU HSE , 2016.
Fenogenova A., Kuzmenko E.
Learner corpora constitute an effective resource for specialists in fields of second language acquisition, foreign language teaching and corpus linguistics. They tend to get significant scholarly help from statistical tools of various kinds. However, for valuable usage of a corpus it should provide convenient and powerful tools for searching and manipulating data. In this paper we focus on searching tools, presented in \textit{Russian Error-Annotated Learner English Corpus (REALEC)}, report our attempts to improve the format of the searching tools in our corpora. We also provide evidences that database search is much more efficient than common text search and demonstrate that search functionality in corpora is of great importance for research efficiency and extensive facilities.
Research target: Philology and Linguistics
Priority areas: humanitarian IT and mathematics
Language: English
Full text
Keywords: информационный поискlearner corporaанглийский язык как иностранныйEnglish as a second languageучебные корпусыautomatic search in corporaпоиск в корпусах
Publication based on the results of:
Лексикологические исследования на базе учебного корпуса REALEC (Learner corpus REALEC: Lexicological observations) (2016)
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