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October 5, 2026
Africa, Youth, and Civic Dialogue: Public Diplomacy Discussed at HSE University
In late September, HSE University hosted a roundtable discussion titled Civil Society in African Countries and Youth Participation in Public Diplomacy. Representatives of non-governmental organisations from Ghana, Ethiopia, and Russia, along with students from HSE University’s Bachelor’s Programme in Public Administration, discussed how young people without official diplomatic status can influence relations between countries and how the nonprofit sector can remain sustainable amid declining grant funding.
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.
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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.

 

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How Much Could We Trust the Inferred Neanderthal Segments?

Lobachevskii Journal of Mathematics. 2025. No. 46. P. 3537–3544.
Ilina A., Planche L., Shchur V.

Many modern human populations contain archaic Neanderthal segments through the archaic introgression event, which occurred 45,000–55,000 years ago. There are a few computational methods that could infer such tracts. The results of their inference is used in the downstream analysis to better understand the impact of the archaic component on the genetic diversity of modern humans, its genetic costs (in particular in term of health), to refine our joint population history, etc. In this paper we present a methodology for numerically evaluating the sources of errors which might affect downstream data analysis. Using simulations, we compare the performance of our recently developed method DAIseg and the previous state-of-the-art method hmmix. We show that DAIseg accurately reconstructs archaic tracts even with relatively low quality archaic genomes. We also confirm that most of the errors come from the short tracts which are very noisy to infer. Overall, our results can be used both as a guideline, and as a methodology for validating the use of the methods for archaic tract inference for particular downstream tasks.

Research target: Mathematics Biology
Language: English
DOI
Text on another site
Keywords: Viterbi AlgorithmNeanderthalsHMM
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