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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
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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.
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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The potential of material productivity alongside energy productivity in climate mitigation: Evidence from convergence tests in the EU28

Resources, Conservation and Recycling. 2021. Vol. 167. Article 105322.
Sedat Alataş, Karakaya E., Sarı E.

This study argues that improvements in material productivity might pave the way for a substantial reduction in emissions when adopted alongside energy productivity policies. We, therefore, compare the convergence pattern of material productivity with that of energy productivity from the mitigation perspective. To this end, we apply (un)conditional β, stochastic and club convergence tests to energy and material productivity data for the EU28 countries. From the methodological perspective, (i) we employ both cross-section and panel data estimators to test (un)conditional β-convergence; (ii) to test stochastic convergence, we use the newly-developed transformed Lagrange Multiplier (LM) and Residual Augmented Least Squares LM (RALSLM) unit root tests allowing for structural breaks in data; (iii) for club convergence analysis, we use the log-t test and endogenous data-driven algorithm proposed by Phillips and Sul (PS) (2007). While the estimated parameters find conditional β-convergence in energy productivity, they do not produce convincing evidence for material productivity. The unit root test results show the existence of stochastic convergence in both variables. The club convergence results reveal that there are six and five clubs for energy and material productivity, respectively. This means that although multiple equilibria exist for both variables of interest, material productivity seems to display a more homogeneous structure compared to energy productivity. According to our findings, we conclude that material productivity seems to have a greater potential for further reductions in emissions once policies are directly targeted for efficient use of material, which can enable the EU to achieve to become carbon-neutral by 2050.

Research target: Economics and Management
Language: English
DOI
Keywords: European Unionconvergencematerials energy efficiency
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