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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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Об устойчивости результатов для правил агрегирования

Журнал Новой экономической ассоциации. 2022. № 5(57). С. 24–37.
Karabekyan D.

Some distortions are possible in the process of preference aggregation. For example, one voter who is pivotal for some preference profi le may not read instructions properly and accidently submit wrong preference. We study how different voting rules react to these distortions for three, four and fi ve alternatives with computer modelling. One of the results is: contrary to the results for the degree of manipulability estimations the most stable rule is the rule that requires less information from preferences when calculating fi nal results — threshold rule. With more alternatives the difference between this rule and rules that require information about the whole ranking is more visible. So, for the rules that require less information the probability to infl uence the results goes down when the number of alternatives increases. Another result: the resoluteness (weighted average number of alternatives in the fi nal outcome) is positively correlated with the stability of aggregation procedures. Threshold rule is the best one for the most cases when we consider both stability and resoluteness.

Research target: Economics and Management Computer Science
Language: Russian
DOI
Text on another site
Keywords: устойчивостьstabilityманипулированиеmanipulabilitythreshold ruleпороговое правилоaggregation rulesправила агрегирования
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