Competition of research works of scientific and pedagogical collectives summed up the results
Project “Improving the performance of internal combustion engines by improving diagnostics and maintenance of mechanisms and systems” (application from the Academy of Engineering, head — Igor Kevorkovich Danilov). The project aims to develop effective solutions to improve the performance of internal combustion engines. The researchers plan to obtain an analytical relationship between the fuel injection pressure indicator and the movement of the bypass valve stem of the high-pressure line of fuel equipment. Based on the obtained dependence, the project team is going to develop a method and device for diagnosing the fuel equipment of modern engines.
Project “Experimental study of a highly efficient multi-stage heat pump installation” (application from the Academy of Engineering, head — Yuri Antipov). The key goal of the project is to create a three-stage installation. The researchers plan to find out how the temperature difference between low-potential and high-potential heat sources (1), the number of stages of the installation itself (2) and the composition of the refrigerant (3) affect its efficiency.
Project “Development of a software package for predicting self-ignition (detonation) of fuels used in spark-ignition engines” (application from the Academy of Engineering, head — Ivan Zaev). The goal of the project is to develop a mathematical model for calculating the thermodynamic parameters of the working process of an engine with forced spark ignition. The project team develops methods for calculating the moment of self-ignition of a fuel-air mixture. This is necessary to determine the operating conditions of the engine without detonation for a given design.
Project “Development of innovative clusters within the BRICS: transition from national projects to network interaction” (application from the Faculty of Economics, head — Vladimir Davydov). The project is aimed at developing recommendations for optimal organizational, legal and marketing support for the development of network interaction between BRICS innovation clusters.
Project “Application of medicinal plants and their extracts to improve growth, immunity and disease resistance in fish” (application from the Agrarian and Technological Institute, head- Yousefi Morteza). The aim of the project is to provide scientific justification for the identification and use of inexpensive and environmentally friendly feed additives (medicinal plants and their extracts) to improve the immunity and growth indicators of various fish species.
Imagine a world where everyone has enough food, clean water, access to education, and decent work. A world where nature is protected and the future of our planet is cared for. These are the Sustainable Development Goals—to achieve a sustainable future for all! To this end, in 2015, the United Nations (UN) defined 17 Sustainable Development Goals (SDGs). The SDGs are a global plan that helps countries and people work together towards a better future. All 193 UN member states have joined the plan.
Researchers from the Faculty of Artificial Intelligence at RUDN University conducted a large-scale study that revealed systemic errors in large language models (LLMs) when diagnosing depression based on text. This work, carried out in collaboration with colleagues from AIRI, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow Institute of Physics and Technology, and MBZUAI, not only identifies the problem but also lays the foundation for the creation of more reliable and secure tools for detecting depression and anxiety.
Alexandra Sentyabreva, a junior researcher at the Laboratory of Cell Technologies and Tissue Engineering at RUDN Research Institute of Molecular and Cellular Medicine at the Russian University of People's Friendship, won the competition for young scientists at the All-Russian Scientific Conference “Topical Issues of Morphogenesis in Norm and Pathology.” She was awarded the Academician A.P. Avtsyn Prize.
Imagine a world where everyone has enough food, clean water, access to education, and decent work. A world where nature is protected and the future of our planet is cared for. These are the Sustainable Development Goals—to achieve a sustainable future for all! To this end, in 2015, the United Nations (UN) defined 17 Sustainable Development Goals (SDGs). The SDGs are a global plan that helps countries and people work together towards a better future. All 193 UN member states have joined the plan.
Researchers from the Faculty of Artificial Intelligence at RUDN University conducted a large-scale study that revealed systemic errors in large language models (LLMs) when diagnosing depression based on text. This work, carried out in collaboration with colleagues from AIRI, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow Institute of Physics and Technology, and MBZUAI, not only identifies the problem but also lays the foundation for the creation of more reliable and secure tools for detecting depression and anxiety.
Alexandra Sentyabreva, a junior researcher at the Laboratory of Cell Technologies and Tissue Engineering at RUDN Research Institute of Molecular and Cellular Medicine at the Russian University of People's Friendship, won the competition for young scientists at the All-Russian Scientific Conference “Topical Issues of Morphogenesis in Norm and Pathology.” She was awarded the Academician A.P. Avtsyn Prize.