HSE Researchers Demonstrate Effectiveness of Machine Learning in Forecasting Inflation
Inflation is a key indicator of economic stability, and being able to accurately forecast its levels across regions is crucial for governments, businesses, and households. Tatiana Bukina and Dmitry Kashin at HSE Campus in Perm have found that machine learning techniques outperform traditional econometric models in long-term inflation forecasting. The results of the study focused on several regions in the Privolzhskiy Federal District have been published in HSE Economic Journal.
Ruthenium Complexes Can Accelerate the Development of New Medicines
A group of scientists at INEOS RAS, HSE University, and MIPT have synthesised catalysts containing a ruthenium atom and an aromatic ring. The scientists have isolated the mirror forms of these catalysts and investigated their effectiveness in producing heterocycles, which are commonly found in the structures of drugs. The research findings have been published in Chemical Communications.
Connecting Space and Time: Bilinguals Associate Time with Space in Both Their First and Second Languages
An international team of researchers including scientists at HSE University investigated how bilingual individuals associate time with space. It turns out that in both their first and second languages, people associate the past with the left side of space and the future with the right. In fact, the higher the proficiency in a second language, the more pronounced this relationship becomes. The study findings have been published in Scientific Reports.
Submission deadline: May 17, 2024