Abstract: The results about the plagiarism problem are presented. The reasons for its distribution in publishing and educational activities and ways of eradication are considered. Such root causes of this phenomenon as: loss of trust tradition in publishing activity with updating authors; insensitivity to publishing ethics of the modern authors grown up in the period of loyalty to plagiarism; commercialization of anti-plagiarism campaigns; weak motivation of authors to publishing activity. The concept about fairness as honest by J. Rawls is proposed to substantiate the methodological approach to solving the problem of dishonesty in publishing, including plagiarism. With its help, the idea about forming of relationships system "publishing-authors" on the basis of the justice principles as honesty is substantiated. The approach to the formation of the ethical framework for relations in the chain "publishing – authors – students – IT-managers – employers" on the basis of the justice principles, such as: equality rights of the requirements about their own benefits, mutual honesty; ethical restrictions on actions, that harm those in the worst position, which are students-readers. The procedure of development and coordination of justice principles in publishing activity with the help of the website of publishing house is offered. These principles should be reflected in the ethical code of publishing.

Abstract: The sequential nested mixed methods study focused on comparative analysis of middle school mathematics teachers’ content knowledge in two countries. The study consisted of two stages: (1) quantitative study of teacher content knowledge; (2) qualitative study of teacher topic-specific content knowledge. The initial sample for the first stage included lower secondary mathematics teachers from the U.S. (grades 6–9, N=102) and Russia (grades 5–9, N=97). The Teacher Content Knowledge Survey (TCKS) was applied to assess teacher content knowledge based on the cognitive domains of Knowing, Applying, and Reasoning, as well as addressing the lower secondary mathematics topics of Number, Algebra, Geometry, Data and Chance. The second stage – an interpretive cross-case study – aimed at the examination of the U.S. and Russian teachers’ topic-specific knowledge on the division of fractions. For the second stage, N=16 teachers (8 – from the U.S., and 8 – from Russia) were selected for the study using non-probability purposive sampling technique based on teachers’ scores on the TCKS. Teachers were interviewed on the topic of fraction division using questions addressing their content and pedagogical content knowledge. The study revealed that there are explicit similarities and differences in teachers’ content knowledge as well as its cognitive types. The study results may inform the field on priorities placed on lower secondary mathematics teachers’ knowledge in the USA and Russia. It also suggests close comparison and learning about issues related to teacher knowledge in both countries with a potential focus on re-examining practices in teacher preparation and professional development.

Abstract: We propose to re-implement basic emotions described by Silvian Tomkins via "Cube of emotions" of Hugo Lövheim, and spiking NNs. We use the basic mechanism of noradrenaline neuromodulation and map it to the influence over computational processes in modern computers. We implement noradrenaline pathways via neuro-biological simulator NEST.

Abstract: The system for automated parallelization SAPFOR (System FOR Automated Parallelization) includes tools for program analysis and transformation. The main goal of the system is to reduce the complexity of program parallelization. SAPFOR system is focused on the investigation of multilingual applications in Fortran and C programming languages. The low-level LLVM IR representation is used in SAPFOR for program analysis. This representation allows us to perform various IR-level optimizations to improve the quality of program analysis. At the same time, it loses some features of the program, which are available in its higher level representation. One of these features is the multi-dimensional structure of the arrays. Data dependence analysis is one of the main problems which should be solved to automate program parallelization. Moreover, such an analysis belongs to the class of NP-hard problems. Knowledge of the multidimensional structure of arrays allows in many cases to take into account the structure of index expressions in calls to arrays and reduce the complexity of the analysis. In addition, the use of multi-dimensional arrays allows us to use multi-dimensional processor matrix and to parallelize a whole loop nests, rather than a single loop in the nest. So, parallelism of a program is going to be increased. These opportunities are natively supported in the DVM system. This paper discusses the approach used in the SAPFOR system to recover the form of multi-dimensional arrays by their linearized representation in LLVM IR. The proposed approach has been successfully evaluated on various applications including performance tests from the NAS Parallel Benchmarks suite.

Abstract: The noradrenaline pathways plays important role in the emotional appraisal and feedback, as well as decision-making. We present the software system capable of automatic generation of PyNEST code based on high-level description of neuronal pathways.

Abstract:

The Virtual Reality Trainer for the Prenatal Detection of Congenital Heart Disease and Associated Malformations project addresses the need to improve specialized training in prenatal diagnosis through immersive technologies. Its theoretical module, “My Friend the Lung”, gamifies learning about fetal cardiovascular anatomy through 3D puzzles, timed challenges, and badges, achieving good results in its pilot test, is noteworthy. The practical module simulates ultrasounds with haptic devices, reducing diagnostic errors and enabling the generation of personalized ultrasounds. A database with 1,200 labeled studies was consolidated as a fundamental source of information. The implementation aims to initially reduce clinical errors, with the potential to decrease perinatal mortality. This project fuses technological innovation, medical rigor, and interactive pedagogy, positioning gamification as an essential tool in medical education and laying the groundwork for its expansion to other specialties.

Abstract: The group of motions of the Lobachevskii plane, as well as that of the Euclidean plane, is generated by reflections in straight lines.This allows ones to develop an approach to constructing the Poincaré model of Lobachevskii plane based on the properties of inversions and pencils of circles in the Euclidean plane.

Abstract:

The work is a development of research conducted by the authors in the field of creating a Common Digital Space for Scientific Knowledge (CDSSK). Previous research has proposed a unified structure for representing the ontology of CDSSK elements (subspaces, classes and attributes of objects, relationships between objects or attributes). In the process of modeling the ontology using the example of the universal and a number of thematic subspaces of the CDSSK, the need for some adjustments to the structure of the ontology regarding CDSSK directories was revealed to ensure the possibility of describing nested data attributes. In addition, the concept of “data attribute value dictionary type” was introduced into the ontology; two types of dictionaries were defined – “static” and “dynamic”. This information makes it possible to simplify formal-logical control algorithms when generating CDSSK content. An indication of the dictionary type has been introduced into the structure of object attribute directories. The presented work describes the modified structure of the ontology using the example of 11 auxiliaries and 10 subject classes of the CDSSK universal subspace (USS). Examples of directories of each class, built in accordance with the ontology structure model, a list of object attributes and examples of static dictionaries are given.

Abstract:

A novel approach to supervised face generation using open-source generative models including StyleGAN2 and Ridge Regression is presented. A methodology that extends StyleGAN2 to control facial characteristics such as age, race, gender, facial expression, and hair attributes is developed, and an extensive dataset of human faces with attribute annotations is utilized. The faces were encoded in 256-dimensional latent space using the StyleGAN2 encoder, resulting in a set of characteristic latent codes. We applied the t-SNE algorithm to cluster these feature-based codes, demonstrated the ability to control face generation, and subsequently trained Ridge regression models for each dimension of the latent codes using the labeled features. When decoded using StyleGAN2, the resulting codes successfully reconstructed face images while maintaining the association with the input features. The developed approach provides an easy and efficient way to supervised face generation using existing generative models such as StyleGAN2, and opens up new possibilities for different application areas.