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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.’
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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?

International Conference of COFE-FETEC 2023: “Forest Operations: A Tool for Forest Management”

Northern Arizona University, 2023.
Podolskaia E., Akay A. E.

Paper covers the use and features of roads seasonality parameter in the presently publicly available Open datasets. Roads seasonality was considered as a factor of transport accessibility for the forest transport modeling at the regional level of large Siberian federal district, Russia. As analysis of papers shows, roads seasonality is mainly related to the winter conditions and low temperatures, researchers are focused on the winter roads. North big countries like Russia and Canada are the most interested data users in the domain of GIS transport projects. We state a lack of seasonality data, declared in the world databases, but not actually included. Forestry and forest industry need a combination of infrastructural data, and roads seasonality has a role of parameter to be included in the transport accessibility scenarios to reach forest fires and forest resources by ground means. Data on the roads seasonality for the regions of Russian could be found in the form of map view and text description. We have analyzed roads seasonality attributes of four Open datasets available online (Open Street Map, gRoads1, Natural Earth of 1:10 000 000, and Global roads inventory project or GRIP); for Siberian federal district only two of them have an indicator of seasonality (OSM and GRIP). Seasonal use of roads in the forest management depends on the features like relief and rivers, swamps and soils, they would be investigated in the future research. Roads conditions depending on season could be included in the transport scenarios for the regions. Artificial Intelligence and remote sensing materials in combination could lead to the continuation of such research.

Research target: Earth Sciences Agriculture, Forestry, and Fisheries
Language: English
Full text
Text on another site
Keywords: seasonalityforestryGISapplications based on open dataroads
International Conference of COFE-FETEC 2023: “Forest Operations: A Tool for Forest Management”
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