An international group of scientists and medical specialists, including HSE researchers, examined the role played by microRNA (miRNA) and long non-coding RNAs on the progression of ovarian cancer. Having analysed more than a hundred tumour samples, they found that miRNA can prevent cell mutation while long non-coding RNAs have the opposite effect of enabling such mutations. These findings can help design new drugs which act by regulating miRNA concentrations. The study was published in the International Journal of Molecular Sciences.
Tag "publications"
Vaccination is generally considered an essential tool for curbing the COVID-19 pandemic. Although Russia was one of the first countries to develop a vaccine against COVID-19 and launched an immunisation campaign in 2021, its vaccination rates remained low for a long time. By October 2021, only 36% of Russian adults were vaccinated, many of whom were compelled by their employers to do so. Having examined the factors contributing to low trust in vaccination among Russians, HSE economists suggest measures to improve vaccination uptake. The paper is published in Vaccine.
HSE University researchers have found that complex phonological tests involving several cognitive processes predict dyslexia better than simple ones. This may happen due to the fact that Russian-speaking children with dyslexia generally do not have difficulties distinguishing speech sounds. However, it’s not enough to use only phonological tests to reliably diagnose the causes of reading disorders. The results of the study were published in the Journal of Speech, Language and Hearing Research.
Economists from HSE University and the Vienna University of Economics and Business have figured out why, all else equal, trading goods across borders can be more expensive than trading the same goods within state borders. They argue that one of the reasons is underdeveloped infrastructure in border regions. Their study was published in the Journal of Urban Economics.
Scholars from the HSE Institute for Cognitive Neuroscience have translated the Emotional Contagion Scale into Russian and validated it on Russian-speaking participants. It was the first study of how people unconsciously ‘catch’ other people’s emotions using a Russian sample. The results of the survey, which involved more than 500 respondents, demonstrate that women are more inclined to imitate emotions of others than men. The study was published inFrontiers in Psychology.
HSE researchers have proposed a new neural network method for recognising emotions and people's engagement. The algorithms are based on the analysis of video images of faces and significantly outperform existing single models. The developed models are suitable for low-performance equipment, including mobile devices. The results can be implemented into video conferencing tools and online learning systems to analyse the engagement and emotions of participants. The results of the study were published in IEEE Transactions on Affective Computing.
Researchers from HSE University and the Pushkin Institute have demonstrated that pairwise comparisons work better than rating scales for measuring motivation. The reason is that many people cannot rank their motives in a hierarchical fashion. The study findings are published in Frontiers in Psychology.
An international team of scientists from the UK, Spain, Denmark and Russia (including researchers from the HSE Institute for Cognitive Neuroscience) conducted an experiment demonstrating that people automatically integrate extralinguistic information into grammatical processing during verbal communication. The study findings were published in the Scientific Reports Journal.
Researchers from HSE University and Moscow Polytechnic University have discovered that AI models are unable to represent features of human vision due to a lack of tight coupling with the respective physiology, so they are worse at recognizing images. The results of the study were published in the Proceedings of the Seventh International Congress on Information and Communication Technology.
A team of researchers from HSE MIEM, LPI RAS, and the University of Southern California have applied machine learning to the analysis of internal defects in perovskite solar cells and proposed ways to improve their energy efficiency. The findings of the study performed on the Cs2AgBiBr6 double perovskite can be used to develop more efficient and durable perovskite-based materials. The paper has been published in the Journal of Physical Chemistry Letters.