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Increasing the profitability of sales agents has been and continues to be given great attention. The article discusses various approaches to solving this problem, one of which is reinforcement learning, which is actively used to solve algorithmic trading problems. Increasing the efficiency (profitability) of algorithmic trading is possible in two ways, on the one hand, improving the algorithms, on the other hand, enriching the data that is transmitted to the input to the algorithms. The study confirmed the feasibility of using derived financial indicators for the tasks of applying trading algorithms based on reinforcement learning algorithms. The main idea of ​​the research implementation is aimed at obtaining the results of the sales agent's work based on Q-learning on technical indicators and on derived technical indicators (the agent is implemented in Python). The substantiation of the choice of the Q-learning method for solving the problem is carried out, the basics of decision-making, policy, strategy, and reinforcement learning are considered. The paper considers the issues of increasing the efficiency (profitability) of a sales agent based on the Q-learning algorithm by transferring derivative technical indicators to him, determined and substantiated derived technical indicators, verified the results of a sales agent's work on technical indicators and derived technical indicators. In the study presented in the article, an empirical test of the possibility of creating synthetic financial features to improve the efficiency of learning algorithms was carried out, in addition, the verification of obtaining the necessary results when using reinforcement learning algorithms was carried out. Empirical confirmation has been carried out that the use of derived financial indicators to increase the efficiency (profitability) of sales agents based on the Q-learning method with the use of reinforcement learning algorithms is expedient.

Abstract Background With the high prevalence of COVID-19 infections worldwide, the multisystem inflammatory syndrome in adults (MIS-A) is becoming an increasingly recognized entity. This syndrome presents in patients several weeks after infection with COVID-19 and is associated with thrombosis, elevated inflammatory markers, hemodynamic compromise and cardiac dysfunction. Treatment is often with steroids and intravenous immunoglobulin (IVIg). The pathologic basis of myocardial injury in MIS-A, however, is not well characterized. In our case report, we obtained endomyocardial biopsy that revealed a pattern of myocardial injury similar to that found in COVID-19 cardiac specimens. Case presentation A 26-year-old male presented with fevers, chills, headache, nausea, vomiting, and diarrhea 5 weeks after his COVID-19 infection. His SARS-CoV-2 PCR was negative and IgG was positive, consistent with prior infection. He was found to be in cardiogenic shock with biventricular failure, requiring inotropes and diuretics. Given concern for acute fulminant myocarditis, an endomyocardial biopsy (EMB) was performed, showing an inflammatory infiltrate consisting predominantly of interstitial macrophages with scant T lymphocytes. The histologic pattern was similar to that of cardiac specimens from COVID-19 patients, helping rule out myocarditis as the prevailing diagnosis. His case was complicated by persistent hypoxemia, and a computed tomography scan revealed pulmonary emboli. He received IVIg, steroids, and anticoagulation with rapid recovery of biventricular function. Conclusions MIS-A should be considered as the diagnosis in patients presenting several weeks after COVID-19 infection with severe inflammation and multi-organ involvement. In our case, EMB facilitated identification of MIS-A and guided therapy. The patient’s biventricular function recovered with IVIg and steroids.

The time-domain (TD) induced polarization (IP) method is used as an extension of direct current (DC) resistivity measurements to capture information on the ability of the subsurface to develop electrical polarization. In the TD, the transient voltage decay is measured after the termination of the current injection. To invert tomographic TD IP data sets into frequency-domain (FD) models of complex electrical resistivity, a suitable approach for converting TD IP transients and their corresponding uncertainties into the FD is essential. To apply existing FD inversion algorithms to TD IP measurements, a conversion scheme must transform the measured decay curves into FD impedances and also propagate the corresponding measurement uncertainty from the TD to the FD. Here, we present such an approach based on a Debye decomposition (DD) of the decay curve into a relaxation-time distribution and the calculation of the equivalent spectrum. The corresponding FD data error can be obtained by applying error propagation through all of these steps. To accomplish the DD we implement a non-linear Gauss–Newton inversion scheme. We test the conversion scheme in a synthetic study and demonstrate its application to field data on a tomographic TD IP data set measured on the Maletoyvaemskoie ore field (Kamchatka, Russia). The proposed conversion scheme yields accurate impedance data for relaxation processes, which are resolved by the TD measurements. The error propagation scheme provides a reasonable FD uncertainty estimate, as confirmed by a Monte Carlo analysis of the underlying parameter distributions.

Background. It is proposed to develop agent-based network metacomputer systems and applications based on logical methods and related conceptual graphical models, which allows combining imperative and declarative methods when designing the functional architecture and software of a metacomputer. Formalized specifications for creating agent-based network applications based on conceptual and logical models of artificial intelligence are proposed. The term “metacomputer” is chosen to denote the network environment in which the action script is deployed. Another name is a cloudnetwork application, in principle it means the same thing, but it differs in the additional consideration of terminology from the field of modern network technologies in an explicit form. In connection with the growing importance of global computer networks in science and education, the problem of creating large-scale applications is relevant. A functional organization of metacomputer agent-based network distributed computing is proposed, which implements the main structures of distributed programming, where the network is actually considered as a computer with distributed program control based on the messagedriven computing paradigm, and not as a means of implementing the simple client-server or master-slave applications. The aim of the work is to increase the level of parallelism in data processing in metacomputer systems by organizing the pipeline movement of messages over the network. Materials and methods. Conceptual models, logical-algebraic operating models, logical Petri nets are used as the main methods. Results. Conceptual graphs of distributed algorithms and logical-algebraic operational expressions suitable for use as directly executable specifications are proposed, a method is developed for moving from conceptual graphs to executable specifications that define the functional architecture of a metacomputer. Simulation models for distributed algorithms have been developed. Conclusions. The practical implementation of the above concepts and models will increase the level of parallelism in the operation of agent-based virtual metacomputer systems due to the pipeline organization of message passing.

The main scientific and practical results of the study and assessment of ventilation control in coal mines using the decomposition method based on data from the analysis of aerodynamic parameters of air distribution are presented. This will lead to increased safety and reduced accident rates in mining operations at coal mines. Methods of decomposition, statistical dynamics, set theory, fundamental laws of mining aerodynamics, and discrete mathematics are described. The studies were carried out based on the experimental data of the authors using various mathematical and statistical methods. A universal technique is proposed that can be used in mine workings for analysis, assessment of ventilation processes and associated aerodynamic factors, as well as optimization of the air distribution control system under various operating modes. A methodology and application software developed on its basis have been compiled. Automated geographic information systems such as GIS K-MINE® (Krivoy Rog, Ukraine) and VENTSIM are recommended. This system has been approved by regulatory authorities in Ukraine and is utilized by specialists from industry institutes, State Mining Supervision authorities, mines, and others. They are adapted for coal mines, ensuring increased safety and efficiency of work. This will ensure increased safety, labor protection, and reduced accident rates in coal mining operations. [ABSTRACT FROM AUTHOR]

Introduction. Ligaments play a critical role in the body, linking bones together. Ligament ruptures are the most common manifestations of serious musculoskeletal injuries. This is especially true for the anterior cruciate ligament of the knee joint. In trauma surgery, orthopedics, the ligament functional recovery can be achieved by using tissue autografting, synthetic and biological prostheses. Of great interest to surgeons is the use of prostheses made of biological tissues of animal origin, since they are easily available and, when high-quality processing is achieved, they are safe, retaining their natural structure and strength. Purpose of the study. To decellularize the bovine tendon according to our originally developed technique and to investigate its efficacy in terms of the presence of cellular elements and physical and mechanical parameters of the material. Material and methods. To manufacture the prototype of the ligament prosthesis product, we developed the technique for processing the bovine tendon, as the most similar material by structure, including its mechanical processing, chemical and physical processing methods and a special treatment with supercritical carbon dioxide fluid containing nonionic surfactant Tween-80 for decellularization and extraction of organic components in addition to collagen framework, while maintaining strength properties. Histological studies were performed to check for the residues of cellular elements, and the measurements of the physical and mechanical properties of the material were made. Results. Histological examination of the material showed that after processing, 0–2 cells in the field of view were found in the material. The strength properties of the material were 503 kgf/mm2 before processing and 605 kgf/mm2 after processing. Conclusion. The data obtained in the study confirmed that the processing performed qualitatively affected the elimination of cells, did not worsen but even increased the mechanical strength of the material. Further study of the biocompatible properties of the material is required.

The article investigates a low-temperature plasma of the magnetron discharge of a device used for the synthesis of dielectric films by reactive cathode sputtering. The aim of the study is to determine the temperature characteristics of plasma particles and a sputtered substance, as well as the mechanism for the formation of a chemical bond between sputtered atoms and active gas molecules. A study of the composition and energy parameters of the plasma, as well as the chemical composition of the particles obtained by sputtering, was carried out by a spectroscopic method. The quantitative composition was determined by a mass spectrometer to determine the composition of the sputtered particles.

In recent decades, the amount of information that humankind has accumulated has increased tremendously. People cannot analyze it effectively using simple algorithms, and data structures due to these approaches do not understand the se¬mantics of the data. Thus, there is a need for such a data structure that would store a massive number of entities that would be accessible and easy to understand for machines, and moreover, saves the semantics. One efficient kind of structure is a knowledge graph, which quite recently ap¬peared and became the subject of research for the last few years due to its interesting and sophisticated architecture. The peak of knowledge graph interest came at the time when Google introduced their Knowledge Graph technology in 2012, and since then, it has become apparent what this concept of a knowledge graph is. However, it is still unclear how to use this technology in practice due to the small number of existing infor¬mation on this theme. In this paper, we introduce and review all steps of knowledge graph implementation. In addition to that, this article in¬cludes information about problems that need to be solved for having its instance of the knowledge graph; also, we consider machine learning em¬bedding methods to analyze knowledge graph structure, practical steps for KG usage, and so on.

The study included 31 oncological patients who underwent surgical treatment for head and neck tumors. Airway patency was assured by fibrooptic intubation of the trachea while preserving the patient's spontaneous breathing. 15-20 min before the fibrooptic tracheal intubation, dexmedetomidine was administered intravenously at the dose of 3 μg/kg per 1 h until the loading dose of 1 μg/kg was reached. Fibrooptic intubation of the trachea had been applied till the patient's sedation exceeded 3 scores on the Ramsay sedation scale. In all observations, patients maintained spontaneous breathing. Immediately prior to the introduction of the fibrobronchoscope, lidocaine in the dose of 1.5 mg/kg and ketamine (0.5 mg/kg) were administered intravenously. Further, fibrooptic tracheal intubation was carried out, the quality of which was evaluated by the anesthesiologist directly while it was performed and by the patient in the postoperative period.

MXenes are of great practical interest. While the physical properties of such a well-known MAX phase as Ti3AlC2 and the Ti3C2 MXene that is based on it have been widely studied, it is extremely important to study the properties of new four-component MAX-phases and the MXenes based on them. To do this, first, it is necessary to characterize the obtained materials. In this work, the Ti3−xNbxC2 MXene was characterized. Since the material is fairly new, there are no crystallographic data for such systems in the international databases. We proposed a method for the determination of the main unit cell parameters of the new Ti3−xNbxC2 MXene, which was based on a combination of the DFT method, TEM studies, and an X-ray diffraction analysis.

This paper presents results from a study which tested the validity of a conceptual model which proposes six dimensions of integrative knowledge and learning that result from students engaging in the core activities associated with the Integrative Knowledge Portfolio Process and Generative Knowledge Interviewing. These methods facilitate learning experiences that help students to identify, connect, synthesize and demonstrate knowledge and skills they are gaining from all areas of life. Six hundred and twenty students (both traditional and non-traditional) from 14 different learning environments across two campuses responded to pre/post surveys before and after they engaged with these methods. Results showed that students made significant gains on all six dimensions of integrative knowledge and learning which resulted in their increased capacity to: 1. identify, demonstrate and adapt knowledge gained within/across different contexts; 2. adapt to differences (i.e. in people and situations) in order to create solutions; 3. understand and direct oneself as a learner; 4. become a reflexive, accountable, and relational learner; 5. identify and discern one's own and others' perspectives; and 6. develop a professional digital identity. Students' gains on these dimensions were significant regardless of their academic discipline, race/ethnicity, gender, year in school or the type of learning environment in which they engaged with the Integrative Knowledge Portfolio Process.