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September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.
September 7, 2026
Biologists Discover 'Molecular Fingerprint' of Preeclampsia
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September 7, 2026
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Would you like to know whether a speaker’s trembling voice or an accidental gesture can give them away? At HSE University in Nizhny Novgorod, researchers are developing an algorithm that analyses speech, facial expressions, and gestures, and determines whether information is truthful with 92% accuracy. The project has applications ranging from forensic examination and bank recruitment to fundamental research. Anna Khomenko, head of the research group and Senior Research Fellow at the Centre for Language and Brain at the HSE Faculty of Humanities in Nizhny Novgorod, explains how students and researchers are working together to create a corpus of video recordings, train a classifier, and prepare to introduce computer vision technology.

 

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The Tail Wagging the Dog? Top-down and Bottom-up Explanations for Bureaucratic Appointments in Authoritarian Regimes

Russian Politics. 2018. Vol. 3. No. 2. P. 239–259.
Burkhardt F., Libman A.

The paper investigates the link between the sub-national variation of political regimes in a (at the federal level) non-democratic country and the appointments of federal officials in the sub-national provinces. In particular, we look at the appointment of the chief federal inspectors to the regions in Putin’s Russia in 2000–2012. Our main research question is whether appointment patterns can be explained by top-down concerns of the central government willing to keep control over the most unruly regions or by bottom-up self-selection of bureaucrats belonging to influential groups into more attractive positions more suitable for rent-seeking. The advantage of our case is that data we have at hand allow us to distinguish these two logics. Our results indicate that for the Russian chief federal inspectors in 2000–2012 bottom-up self-selection appears to be the more plausible explanation of the link between sub-national political regimes and appointment patterns.

Research target: Political Science, International Relations, and Public Administration Economics and Management
Priority areas: state and public administration
Language: English
DOI
Text on another site
Keywords: bureaucracyauthoritarianismfederalismRussian politicsvertical of powerappointmentsregional bureaucracysub-national regimes Russian regionssiloviki
Publication based on the results of:
Political Economy of Development: Mechanisms of Path-Dependence and Change (2018)
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