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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.’
August 21, 2026
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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How the adoption of Industry 4.0 technologies is related to participation in global and domestic value chains: Evidence from Russia

International Journal of Innovation Studies. 2024. Vol. 8. No. 2. P. 93–108.
Fedyunina A., Gorodnyi N., Simachev Y. V.

This study explores the relationships among Industry 4.0 technologies, their application areas, and the involvement of Russian manufacturing firms in global and domestic value chains (GVCs and DVCs). Using an original survey dataset of approximately 1,700 Russian manufacturing firms, we apply logit and multinomial logit regressions. We make a novel contribution to the literature by uncovering an asymmetry in the adoption of Industry 4.0 technologies among Russian industrial firms in Domestic Value Chains (DVCs) and Global Value Chains (GVCs). This asymmetry has the potential to impede GVC localization and DVC internationalization. Based on our results, software automation solutions are the only ones demonstrating statistical significance for firms participating in GVCs, DVCs, and both GVCs and DVCs simultaneously. Companies in DVCs demonstrate a broader utilization of Industry 4.0 technologies across various application areas. We also identify evidence of reshoring in DVCs, indicating that Industry 4.0 adoption encourages firms to establish enduring relationships with domestic suppliers. Highlighting that differences in technology adoption are influenced by external factors, including adherence to international standards and regulatory principles, we propose policy implications for developing countries. Recommendations encompass reducing entry barriers to DVCs, improving procurement transparency, and promoting competition in the digital solutions market to empower firms for seamless GVC integration.

Research target: Economics and Management
Language: English
DOI
Keywords: Industry 4.0Global value chainsdomestic value chainsforward linkagesbackward linkages
Publication based on the results of:
Strategies and factors of adaptation of companies during economic shocks and disruptions in value chains in post-communist economies (2023)
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