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News
August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
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Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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The impact of income inequality on environmental quality: a sectoral-level analysis

Journal of Environmental Planning and Management. 2022. Vol. 65. No. 10. P. 1949–1974.
Alatas S., Akın T.

Many studies in the literature examine the income inequality-environment nexus at the country level. In this paper, we argue that the impact of inequality on sectoral emissions might vary and should be examined by considering sectoral-level differences. We focus on 28 OECD economies and use DOLSMG, BA-OLS, and CUP-FM estimators. Our findings reveal that a cointegration relationship exists among the series in the long run, indicating that both income and income inequality are crucial factors in sectoral emissions. The estimates show that a 1% increase in the Gini index leads to an increase in emissions from the power and building sectors by about 1.4%. On the other hand, a 1% rise in the Gini index positively contributes to the environment in the transport, other industrial combustion, and other sectors by about 0.05%, 0.05%, and 0.02%, respectively. Policies aimed at reducing carbon emissions should be designed at the sectoral level.

Research target: Economics and Management
Language: English
DOI
Text on another site
Keywords: income inequalityDynamic Panel DataOECD countriesSectoral EmissionsEKC hypothesis
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