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  • ДИСКРЕТНО-ДИНАМИЧЕСКОЕ МОДЕЛИРОВАНИЕ ГОСУДАРСТВЕННОГО РЕГУЛИРОВАНИЯ ЧЕЛОВЕЧЕСКОГО КАПИТАЛА
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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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ДИСКРЕТНО-ДИНАМИЧЕСКОЕ МОДЕЛИРОВАНИЕ ГОСУДАРСТВЕННОГО РЕГУЛИРОВАНИЯ ЧЕЛОВЕЧЕСКОГО КАПИТАЛА

Математическое моделирование. 2020. Т. 32. № 6. С. 81–96.
Каменев Г. К., Kamenev I.

The article considers the problem of multi-criteria optimization of the state regulation of the quality of human capital in the information society. It describes human capital's dynamic by discrete model, taking into account the age dynamics of awareness and cognitive abilities of the individual as a carrier of information. Lifelong indices of human capital are constructed on the trajectories of human’s productivity and creativity, taking into account the increase in the quality of human capital in youth, and further, its decline in older age. The problem of state regulation is described as a bicriteria maximization of two population’s mathematical expectations of indices for the generation, taking into account not only the natural distribution of indices by starting values, but also the possibilities of socialization in the state-controlled education system. The identification of the model is based on the known population constraints on the phase tube of trajectories. The model is identified and researched by methods using approximation by Shannon’s metric nets. It is shown that the optimal choice of educational priorities by the state depends on the parameters of society: age mortality rates and the budget of time available for socialization of non-adults. There are combinations of parameters that lead to conflict of control criteria, so the solution is a set of Pareto-optimal strategies. For Russia, there is a dominant solution that prioritizes the development of cognitive abilities rather than awareness.

Research target: Mathematics Economics and Management Education
Priority areas: economics state and public administration IT and mathematics
Language: Russian
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Text on another site
Keywords: информационное обществочеловеческий капиталinformation societyмногокритериальная оптимизацияmulticriteria optimizationдинамическая модельdiscrete modelcognitive abilitiesкогнитивные способностидискретная модельоптимальность по Паретоdynamical modeleducation governanceгосударственное регулирование образованияhuman capitalPareto-optimalitymetric data analysisметрический анализ данных
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