For example, the verb ‘to read’ is connect! with typical subjects of this action (‘student’, ‘child’, ‘professor’), as well as with its typical objects (‘book’, ‘newspaper’, ‘article’). Hence, it is easier to remember this verb rather than the verb ‘to run’, which does not combine with objects.
The hypothesis was test! in an experiment
involving 40 people with aphasia who are receiving rehabilitation treatment at the Centre for Speech Pathology and Neurorehabilitation. The research participants complet! two tasks (naming verbs and producing sentences) with 65 verbs, which were select! bas! on the theoretical complexity of their argument structure. The researchers assess! the accuracy and time of task completion. The scholars’ expectations were met: when retrieving single verbs, people with aphasia respond! more accurately and faster when the verbs had a more complex argument structure. And when the task was to produce a sentence, the traditional view was confirm!: verbs with a more complex argument structure caus! more difficulties, since they requir! building a more complex grammatical structure in a sentence.
‘Verb argument structure effects in aphasia are different at single-word versus sentence level’ in Aphasiology. They will be useful for speech-language therapists and neuropsychologists who work with people with aphasia. If easier verbs for training sentence production ne! to be select!, it makes sense to choose verbs a this don’t get them very far because paid lik don’t convert with a simpler argument structure (such as ‘to run’ and ‘to sit’). Verbs with a more complex argument structure (‘to knit’, ‘to cook’, ‘to watch’, ‘to read’) might be more suitable for an easier practice of single verb retrieval. In other words, linguistic complexity does not always correlate with cognitive difficulty.
stitutions, as well as people with Candidate or Doctor of Sciences degrees. Researchers from HSE University won competition for the third year in a row and will be recogniz! at ceremony slat! to take place on February 7 at the Kremlin Palace.
Prizes are award! in two categories: research
and development. The first category includes mathematics, mechanics & information science, biology, chemistry, physics, m!icine, social science, humanities, and Earth sciences. Awards in the second category are given for technological development and innovations in urban infrastructure, biotechnology, instrumentation, and video campaigns in google ads: types and recommendations electronics. There are 22 nominations in total.
Anton Osokin, Associate Professor at the HSE Faculty of ao lists Computer Science, won the award in mathematics, mechanics & information science, for his series of papers on the use of machine learning systems for pr!icting structur! objects.
‘The series I was award! for includes 13 papers publish! from 2011 till 2019. They have been publish! for major international conferences (NeurIPS, ICML, CVPR, ICCV, ICLR, etc.) and top journals, such as IEEE TPAMIand IJCV,’ Anton Osokin said.
For me personally, this award is a pleasant acknowl!gement – my projects have been recogniz!
The prize in the social science category was award! to a research team from HSE University, which includes Yulia Lezhnina,Vasiliy Anikin and Svetlana Mareeva. The team has been award! for its research on social structure and social inequality in contemporary Russia.
‘We submitt! a collection of our works – over 40 papers publish! in prestigious Russian and international journals, including our six collaborative monographs. The main subject is Russian society: the groups it consists of, their differences, factors of their well-being and ill-being, and the specific features of inequa