Mutation in triangulated categories and rigid Cohen-Macaulay modules

We introduce the notion of mutation of $n$-cluster tilting subcategories in a triangulated category with Auslander-Reiten-Serre duality. Using this idea, we are able to obtain the complete classifications of rigid Cohen-Macaulay modules over certain Veronese subrings.Comment: 52 pages. To appear in Invent. Mat

Solar Wind Turbulence and the Role of Ion Instabilities

International audienc

Ложный сустав диафиза лучевой кости в сочетании с застарелыми вывихами головок лучевой и локтевой костей (клинический случай)

The authors presented a rare clinical case - the injury of forearm complicated by the formation of the pseudarthrosis of the radial shaft in combination with old dislocation of heads the radius and ulna. The differentiated approach to the choice of surgical tactics was proposed, which consists of several consistent stages: taking free autotransplant from the crest of iliac bone, resection of pseudarthrosis of radius with replacement of the bone defect by the graft for restoration of anatomic length, conducting combined strained osteosynthesis and elimination of dislocation of a head of radial and ulnar bones by transosseous osteosynthesis. The chosen treatment strategy allowed to restore the anatomy and function of the upper extremity.Представлен редкий клинический случай - травма предплечья, осложнившаяся формированием ложного сустава диафиза лучевой кости в сочетании с застарелыми вывихами головок лучевой и локтевой костей. Предложен дифференцированный подход к выбору тактики оперативного лечения, состоящего из несколько последовательных этапов: забор свободного аутотрансплантата из гребня подвздошной кости, резекция ложного сустава диафиза лучевой кости с замещением дефекта лучевой кости выделенным трансплантатом, комбинированный напряженный остеосинтез и чрескостный остеосинтез, направленный на устранение вывихов головок лучевой и локтевой костей. Выбранная тактика лечения позволила восстановить анатомию и функцию поврежденного сегмента

Analysis of 19.9 million publications from the PubMed/MEDLINE database using artificial intelligence methods: Approaches to the generalizations of accumulated data and the phenomenon of “fake news” [Анализ 19,9 млн публикаций базы данных PubMed/MEDLINE методами искусственного интеллекта: подходы к обобщению накопленных данных и феномен “fake news”]

Introduction. The English-language databases PubMed/MEDLINE and Embase are valuable information resources for finding original publications in basic and clinical medicine. Currently, there are no artificial intelligence systems to evaluate the quality of these publications. Aim. Development and testing of a system for sentiment analysis (i.e. analysis of emotional modality) of biomedical publications. Materials and methods. The technique of analysis of the “Big data” of biomedical publications was formulated on the basis of the topological theory of sentiment analysis. Algorithms have been developed that allow for the classification of texts from 16 sentiment classes with 90% accuracy (manipulative speech, research without positive results, propaganda, falsification of results, negative personal attitude, aggressive text, negative emotional background, etc.). Based on the algorithms, a scale for assessing the sentiment quality of research (β-score) is proposed. Results. Abstracts of 19.9 million publications registered in PubMed/MEDLINE over the past 50 years (1970–2019) were analyzed. It was shown that publications with low sentiment quality (the value of the β-score of the text is less than zero, which corresponds to the prevalence of manipulative and negative sentiments in the text) comprise only 18.5% (3.68 out of 19.9 million). The greatest values of the β-score were characterized by publications on sports medicine, systems biology, nutrition, on the use of applied mathematics and data mining in medicine. The rubrication of the entire array of publications by 27,840 headings (MESH-system of PubMed/MEDLINE) indicated an increase in the β-score by years (i.e., the positive dynamics of sentiment quality of the texts of publications) for 27,090 of the studied headings. The most intense positive dynamics was found for research in genetics, physiology, pharmacology, and gerontology. 249 headings with sharply negative dynamics of sentiment quality and with a pronounced increase in the manipulative sentiments characteristic of the tabloid press were highlighted. Separate assessments of international experts are presented that confirm the patterns identified. Conclusion. The proposed artificial intelligence system allows a researcher to make an effective assessment of the sentiment quality of biomedical research papers, filtering out potentially inappropriate publications disguised as “evidence-based”. Copyright © 2020, Farmakoekonomika. All rights reserved