Improved velocity law parameterization for hot star winds

The velocity law of hot star winds is usually parameterized via the so-called beta velocity law. Although this parameterization stems from theoretical considerations, it is not the most accurate description of the wind velocity law that follows from hydrodynamical calculations. We show that the velocity profile of our hydrodynamical wind models is described much better by polynomial approximation. This approximation provides a better fit than the beta velocity law already for the same number of free parameters.Comment: 3 pages, 2 figures, accepted for publication in Astronomy & Astrophysic

Developing Intelligent Assistants to Search for Content on Websites of a Certain Genre

This paper discusses an approach to automatic generation of intelligent assistants, which provide information search on the content of a website. A feature of the approach is to use genre models, developed for a given type of resource (educational, informational, etc.), on the basis of which the genre structuring and subsequent thematic clustering of the content of the target website is performed. The resulting genre structures allow us to define more precisely the boundaries of thematic clusters related to the topic of the user’s search query. The search quality evaluation for the Russian-language websites showed an F-score of 87.8% and originality of 80.9%, which exceeds the Yandex search engine results by 1.1% and 9.1%, respectively. In order to predict user information needs, a method for refining the resulting sample is proposed. It allows a user to get information implicitly, based on current and previous queries, about what the user was not satisfied with in the previous search results. A model of user’s search intentions has been developed and its computational component includes a method for evaluating query closeness based on the FRiS function. Based on the proposed methods, a chatbot was created on the Telegram messenger platform to search the websites of educational institutions. The experiments showed that the user needs the average of 1.75 qualifying questions to find the necessary information.This paper discusses an approach to automatic generation of intelligent assistants, which provide information search on the content of a website. A feature of the approach is to use genre models, developed for a given type of resource (educational, informational, etc.), on the basis of which the genre structuring and subsequent thematic clustering of the content of the target website is performed. The resulting genre structures allow us to define more precisely the boundaries of thematic clusters related to the topic of the user’s search query. The search quality evaluation for the Russian-language websites showed an F-score of 87.8% and originality of 80.9%, which exceeds the Yandex search engine results by 1.1% and 9.1%, respectively. In order to predict user information needs, a method for refining the resulting sample is proposed. It allows a user to get information implicitly, based on current and previous queries, about what the user was not satisfied with in the previous search results. A model of user’s search intentions has been developed and its computational component includes a method for evaluating query closeness based on the FRiS function. Based on the proposed methods, a chatbot was created on the Telegram messenger platform to search the websites of educational institutions. The experiments showed that the user needs the average of 1.75 qualifying questions to find the necessary information

Superalkali Coated Rydberg Molecules.

A series of complexes of Na, K, NH4, and H3O with [bpy.bpy.bpy]cryptand, [2.2.2]cryptand, and spherical cryptand were investigated via DFT and ab initio methods. We found that by coating Rydberg molecules with the organic skin one could further decrease their ionization potential energy, reaching the values of ∼1.5 eV and a new low record of 1.3 eV. The neutral cryptand complexes in this sense possess a weakly bounded electron and may be considered as very strong reducing agents. Moreover, the presence of an organic cage increases the thermodynamic stability of Rydberg molecules making them stable toward the proton detachment

Автоматизированная обучающая система «Множества» (исследования организации 1-й части проекта)

The issues of building an automated learning system “Sets” which will allow students to master one of the important topics of the discipline “Discrete Mathematics” and to develop logical and mathematical thinking in this direction are studied. The corresponding topic of the 1st part of the project includes materials related to the concept of a set, operations on sets, algebra of sets, proofs of statements for sets, and the derivation of formulas for the number of set elements. The system is based on a construction of the statements proof editor for a set and of the formulas derivation editor for the number of set elements, both editors are to be used for teaching. The first of these allows students to split the original statement into a number of simpler statements, taken together equivalent to the original statement, to choose a method of proving each simple statement and to conduct their step-by-step proof. The second editor allows (using the inclusion-exclusion principle and the formula of the number of complement elements) to derive a step-by-step formula for the number of set elements through the specified numbers of elements for sets from which the resulting set is constructed. An important part of the system is to monitor the correctness of all actions of students, and on this basis the entire learning system is developed. The logical supervision over the correctness of the selected action in the first editor is performed by a Boolean function created by the system and corresponding to this action and by checking it for identical truth. In the second editor, invariants such as characteristic strings of the set and of its number of elements are used for verification. The rest of the system is related to learning of set algebra and to preparation to editors usage. The main focus here is on the learning strategy in which testing the understanding of the learned material is rather rigorous and eliminating the random choice of answers. The division of the material into sections with verification of the success of teaching not only by tests, but also by exercises and tasks, allows students to master the complex logical and mathematical techniques of proving statements for sets and derivation of formulas for the number of set elements.Исследуются вопросы построения автоматизированной обучающей системы «Множества», которая позволит учащемуся освоить одну из важных тем дисциплины «Дискретная математика» и развить логико-математическое мышление в этом направлении. Соответствующая тема 1-й части проекта включает материал, связанный с понятием множества, операциями над множествами, алгеброй множеств, доказательствами утверждений для множеств, выводом формул для количества элементов множества. В основе системы лежит построение с целью использования для обучения редактора доказательства утверждений для множества и редактора вывода формул для количества элементов множества. Первый из них позволяет студенту разбить исходное утверждение на ряд более простых утверждений, в совокупности эквивалентных исходному утверждению, выбрать метод доказательства каждого простого утверждения и провести их пошаговое доказательство. Второй редактор позволяет, используя формулу включения и исключения и формулу количества элементов дополнения, вывести пошагово формулу для количества элементов множества через заданные количества элементов, связанных с ним множеств. Важной частью системы является контроль правильности всех действий студента, и на этой основе разработана вся система обучения. Логический контроль правильности выбранного действия в первом редакторе осуществляется созданием системой булевой функции, соответствующей этому действию, и проверкой ее на тождественную истинность. Во втором редакторе для контроля используются такие инварианты, как характеристическая строка множества и характеристическая строка количества элементов множества. Остальная часть системы связана с обучением алгебре множеств и подготовке к использованию редакторов. При этом основное внимание уделяется стратегии обучения, при которой проверка понимания усвоенного материала является довольно строгой, исключающей случайный выбор ответов. Разбиение материала на секции с контролем успешности обучения не только тестами, но и упражнениями и задачами, позволяет студенту овладеть сложным логико-математическим аппаратом доказательства утверждений для множеств и вывода формулы для количества элементов множества

Constitutional right of a child to a family: implementation issues

В статье рассматривается Конвенция о правах ребенка в контексте обеспечения права ребенка на семью. Анализируется семья как социальный институт, исходя из своих целей, в том числе в качестве множественной единицы, а не простым собранием единиц, отдельных или обособленных индивидуумов, ради чего мы должны защищать ее, заботясь о наилучших интересах ребенка. Исследуется вопросы ограничения компетенции Комиссии по делам несовершеннолетних и защите их прав.The article deals with the Convention on the Rights of the Child in the context of ensuring the child's right to a family. The family is analyzed as a social institution, based on its goals, including as a multiple unit, and not a simple collection of units, separate or isolated individuals, for which we must protect it, taking care of the best interests of the child. The issues of limiting the competence of the Commission on juvenile affairs and the protection of their rights are being investigated

Machine learning in predicting immediate and long-term outcomes of myocardial revascularization: a systematic review

Machine learning (ML) is among the main tools of artificial intelligence and are increasingly used in population and clinical cardiology to stratify cardiovascular risk. The systematic review presents an analysis of literature on using various ML methods (artificial neural networks, random forest, stochastic gradient boosting, support vector machines, etc.) to develop predictive models determining the immediate and long-term risk of adverse events after coronary artery bypass grafting and percutaneous coronary intervention. Most of the research on this issue is focused on creation of novel forecast models with a higher predictive value. It is emphasized that the improvement of modeling technologies and the development of clinical decision support systems is one of the most promising areas of digitalizing healthcare that are in demand in everyday professional activities

The Methodology of a Locomotive Simulation Model Development within the Model-Oriented Approach

The use of mathematical modelling at the early stages of product design makes it possible to substantiate fundamental technical solutions, taking into account all possible (large number) requirements for the product by consumers and operation. At this (early) stage, it is important to use well-tested and convenient tools for designers to create virtual stands and digital twins (DC), confirming compliance, as well as forming the structure of systems and products as a whole. The article discusses a comprehensive methodology for the process of constructing a numerical model of a locomotive for analysing dynamics under various operating conditions. It is based on the top-level structural model (LBM), which is presented in the form of a block diagram and is used at all stages of product design. The required detailing of such a model depends on the actual tasks. The detailed models of the systems that have been developed within the framework of the work are presented. © 2021 Institute of Physics Publishing. All rights reserved

Algorithm for selecting predictors and prognosis of atrial fibrillation in patients with coronary artery disease after coronary artery bypass grafting

Aim. To develop an algorithm for selecting predictors and prognosis of atrial fibrillation (AF) in patients with coronary artery disease (CAD) after coronary artery bypass grafting (CABG).Material and methods. This retrospective study included 886 case histories of patients with CAD aged 35 to 81 years (median age, 63 years; 95% confidence interval [63; 64]), who underwent isolated CABG under cardiopulmonary bypass. Eighty-five patients with prior AF were excluded from the study. Two groups of persons were identified, the first of which consisted of 153 (19,1%) patients with newly recorded AF episodes, the second — 648 (80,9%) patients without cardiac arrhythmias. Preoperative clinical and functional status was assessed using 100 factors. Chi-squared, Fisher, and Mann-Whitney tests, as well as univariate logistic regression (LR) were used for data processing and analysis. Multivariate LR and artificial neural networks (ANN) were used to develop predictive models. The boundaries of significant ranges of potential predictors were determined by stepwise assessment of the odds ratio and p-value. The model accuracy was assessed using 4 metrics: area under the ROC-curve (AUC), sensitivity, specificity, and accuracy.Results. A comprehensive analysis of preoperative status of patients made it possible to identify 11 factors with the highest predictive potential, linearly and nonlinearly associated with postoperative AF (PAF). These included age (55-74 years for men and 60-78 years for women), anteroposterior and superior-inferior left atrial dimensions, transverse and longitudinal right atrial dimensions, tricuspid valve regurgitation, left ventricular end systolic dimension >49 mm, RR length of 1000-1100 ms, PQ length of 170-210 ms, QRS length of 50-80 ms, QT >420 ms for men and >440 ms for women, and heart failure with ejection fraction of 4560%. The metrics of the best predictive ANN model were as follows: AUC — 0,75, specificity — 0,73, sensitivity — 0,74, and accuracy — 0,73. These values in best model based on multivariate LR were lower (0,75; 0,7; 0,68 and 0,7, respectively).Conclusion. The developed algorithm for selecting predictors made it possible to verify significant predictive ranges and weight coefficients characterizing their influence on PAF development. The predictive model based on ANN has a higher accuracy than multivariate HR