Modeling Methods Research Articles

Criteria and tools for improving trust relations between dairy cluster stakeholders

The article shows the necessity and timeliness of building trusting relationships between stakeholders in projects to create a dairy cluster - an association of institutionally independent enterprises integrated into an inter-industry complex, in order to obtain a synergetic result from balanced cooperative relations between them. The cluster should take into account the interests of all its participants, so maintaining trust between them is necessary for the formation of the food chain in the dairy business, which in turn serves as a catalyst for the effective development of the dairy industry, increasing the volume of production and quality of dairy products. The aim is to study the influence of factors on the common interest, partnership between stakeholders in the project environment, as well as the development of methodological and practical recommendations for the application of tools of effective interaction between them, which contributes to the success of the project and the achievement of common goals. Methods - abstract-logical to identify problems and causes, online survey of respondents using Google-form, Cronbach's Alpha modeling methods are used to assess the reliability and internal consistency of questions in the model created in the Smart PLS program when analyzing complex relationships between latent variables (constructs) that cannot be measured directly. In the course of the study 76 respondents from all regions of Kazakhstan, which are potential stakeholders in the activities of the dairy subcomplex, were interviewed. Results - reliability and validity of the chosen conceptual model were established, the necessity of deepening the hypotheses put forward during the life cycle of the project on the functioning of the dairy cluster was proved. Conclusions - innovative entrepreneurship cannot be successful without managing the process of forming an atmosphere of trusting relations along the entire chain of the production process - from investors to consumers.

UTILIZING GAUSSIAN PROCESS REGRESSION FOR NONLINEAR MAGNETIC SEPARATION PROCESS IDENTIFICATION

This paper presents a novel approach utilizing Gaussian Process Regression (GPR) to identify dynamic models with nonlinear parameters in magnetic separation processes. It aims to address the complex and dynamic nature of these processes by employing advanced modeling methods. The effectiveness of GPR is demonstrated through its application to simulated signals representing real iron ore separation processes, highlighting its potential to enhance existing models and optimize processes. Conducted within the MATLAB, this research lays the groundwork for further advancement and practical implementation. The utilization of GPR in magnetic separation offers innovative modeling of nonlinear dynamic processes, promising improved efficiency and precision in industrial applications.

Balance Sparse Decomposition Method with Nonconvex Regularization for Gearbox Fault Diagnosis

As an important part of rotating machinery, gearboxes often fail due to their complex working conditions and harsh working environment. Therefore, it is very necessary to effectively extract the fault features of the gearboxes. Gearbox fault signals usually contain multiple characteristic components and are accompanied by strong noise interference. Traditional sparse modeling methods are based on synthesis models, and there are few studies on analysis and balance models. In this paper, a balance nonconvex regularized sparse decomposition method is proposed, which based on a balance model and an arctangent nonconvex penalty function. The sparse dictionary is constructed by using Tunable Q-Factor Wavelet Transform (TQWT) that satisfies the tight frame condition, which can achieve efficient and fast solution. It is optimized and solved by alternating direction method of multipliers (ADMM) algorithm, and the non-convex regularized sparse decomposition algorithm of synthetic and analytical models are given. Through simulation experiments, the determination methods of regularization parameters and balance parameters are given, and compared with the L1 norm regularization sparse decomposition method under the three models. Simulation analysis and engineering experimental signal analysis verify the effectiveness and superiority of the proposed method.

Analysis of culvert design methods as methods of ensuring reliability at the design stage

This analysis focuses on the factors and methods for ensuring the reliability of metal culverts, which are essential for the trouble-free operation of motorways. Special attention is paid to the calculation methods for structures with annular cross-sections. The results of the work are conclusions about the necessity of their annular cross-section. They also conclude the importance of developing these structures to enhance culverts’ durability and failure-free operation. This involves considering the stochastic nature of load parameters, structural materials, and operating conditions. Addressing this issue is possible through the assessment of reliability indicators for culverts using simulation modeling methods.

QSAR Modeling, Molecular Docking and ADMET Study of Aryl Fluorosulfate Derivatives as Potential Anti-TB Agents

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb) infection, stands as a global infectious disease presenting substantial public health challenges due to its high incidence and mortality rates. The prolonged use of conventional anti-TB therapies has led to the emergence of severe drug resistance in Mtb, resulting in extended treatment durations, increased costs, poor patient compliance, and reduced cure rates. This phenomenon has posed a significant burden on global TB prevention and control efforts, necessitating a shift in research focus toward the exploration of novel anti-TB drugs. In this context, utilizing QSAR modeling methods, our study systematically investigated the relationship between the chemical structures of 36 aryl fluorosulfate derivatives and their inhibitory activity against Mtb. Robust and predictive Topomer CoMFA and HQSAR models were developed, featuring Topomer CoMFA model parameters: q 2 = 0.659, r 2 = 0.969, F = 102.877, N = 6, SEE = 0.138; HQSAR model parameters: q 2 = 0.705, r 2 = 0.873, SEE = 0.264, HL = 199, N = 4. Leveraging these models, structural modifications were applied to the compounds using the ZINC15 database, leading to the successful design and screening of three novel compounds with desirable inhibitory activity. Molecular docking and ADMET performance prediction results indicated that these three new compounds exhibit strong binding capabilities and promising pharmaceutical potential. This study provides valuable insights and research directions for the development of aryl fluorosulfate derivatives as potential agents for tuberculosis treatment and as novel drugs.

Optimized Dropping and Rolling and Virtual Surface Method for High Packing Fraction of Dispersed Fuel Particles in Annular Container

Because of their favorable thermal conductivity and commendable fuel performance, dispersed fuel elements have been widely adopted in research reactors. However, the geometric complexity resulting from the high packing density of dispersed fuel poses challenges to current geometric modeling methods. Various implicit and explicit modeling techniques have been implemented in Monte Carlo codes. Implicit methods struggle to achieve the correct packing fraction and, therefore, lack accuracy. In this paper, we introduce the Optimized Dropping and Rolling and Virtual Surface method for precise and efficient geometric modeling of such structures. Simultaneously, we apply this novel method to the packing process of an annular container. Test results across various packing fraction cases demonstrate that our modified Optimized Dropping and Rolling method significantly enhances packing efficiency, surpassing the Distinct Element Method hundreds of times.

О некоторых аспектах выявления и расследования преступлений, совершенных в отношении половой свободы и неприкосновенности несовершеннолетних

Introduction. The article is devoted to some problematic issues that arise in the practice of investigating crimes committed against sexual freedom and inviolability of minors (rape, sexual violence, lewd acts, sexual intercourse and other acts of sexual nature with a person under the age of sixteen). The criminalistic characteristics of crimes are given, special attention is paid to the characteristics of the offender and the victim, the methods of committing crimes, the mechanism of trace formation. Typical investigative situations that develop at the initial stage are revealed, the specifics of initiating a criminal case and organising an investigation are revealed, criminal and criminal procedure legislation is analysed. Methods. The methodological basis was the system of scientific research methods used, based on the universal dialectical method, the use of which determines the choice of systemic, activity-based, functional and interdisciplinary approaches in the study of the personality of the offender and the victim in cases of crimes against sexual freedom and inviolability of minors and the totality of its properties and qualities as an integral object. In addition, when studying the mechanism of crime and the investigator’s search and cognitive activity, historical, formal-logical, statistical, sociological, comparativelegal, and modeling methods were used. Results. The most problematic aspects of obtaining significant criminalistic information as a result of verbal investigative actions have been identified, recommendations have been developed to overcome possible opposition from suspected defendants, as well as legal representatives of the victim; the legal positions of judicial authorities and law enforcement practice have been analysed; algorithms for the investigator’s actions in identified problematic situations have been formed. The provisions are substantiated that a minor as a subject of criminal proceedings has a number of characteristics of a demographic, socio-role and moral-psychological nature, which determine the peculiarities of perception, memorisation, analysis and reproduction of significant criminalistic information about the act committed against them. The conclusion is reasoned that special attention should be paid to the tactics of interrogation of victims, which is limited by the current criminal procedural requirements and is characterised by short-termism, one-time nature, and the list of participants. The importance of the results of this investigative action is justified by the prevalence of the results of interrogations in the evidence base for this category of crimes, because due to the postponement of the crime from the beginning of the investigation, the search for other traces, as well as the production of experimental and search investigative actions is significantly complicated.

SOCIAL AND ENVIRONMENTAL FACTORS DETERMINING THE HEALTH STATE OF YOUTH STUDENTS IN UKRAINE

One of the bases of sustainable development of mankind is the health of the young generation. The priority of this issue is especially important in the perspective of European integration processes in Ukraine. Youth is an important component of the human resource that every state should take care of. Preserving, restoring and improving the psycho-physiological condition of young people is the key to the survival and further progress of mankind. The purpose of our research is to analyze the importance of individual factors and their combinations that can affect the health of students. Analysis, synthesis and modeling methods were used to study the state of research. The results of our research were carried out with the help of empirical methods: pedagogical observation, questionnaires, interviews, testing, the method of experimental evaluations. Mathematical statistics methods were used to process the research results. This study explores the social and environmental factors affecting the health of university students in Ukraine, emphasizing the importance of promoting a healthy lifestyle among youth. The research highlights the role of education in shaping health culture, noting gaps in the current system's approach to instilling necessary attitudes toward health. The study draws on data from student health assessments and reveals a high prevalence of chronic diseases, especially among students from radiation-contaminated areas. The investigation further examines the genetic and immunological markers influencing students' health, finding that prolonged stress, radiation exposure, and physical inactivity significantly impact immune responses. Additionally, the research explores the link between thyroid and lipid metabolism issues and students' exposure to ionizing radiation. The findings suggest that moderate physical activity and immunomodulators may help mitigate stress-induced immunosuppression. The study concludes that addressing these social and environmental health determinants is critical for improving the well-being of Ukrainian youth and calls for tailored physical education programs and preventive health measures.

THEORETICAL PRINCIPLES OF THE FORMATION OF SPIRITUAL CULTURE IN FUTURE TEACHERS OF ARTISTS

The problem of spirituality, spiritual culture and their role in the formation of the creative personality of student youth is quite relevant. The process of forming spirituality is an important aspect of the modern humane educational paradigm. According to the scientific community, it is spirituality that expresses the degree of "humanization" of the pedagogical process. Questions of spirituality have interested humanity at all times and have been studied by many sciences: philosophy, pedagogy, psychology, sociology, ethics, aesthetics, etc. In the New Ukrainian School Program in the Progress to Values, it is stated that now it is important to intensify efforts to raise the spiritual level of Ukrainian youth, to form a stable system of deep moral and spiritual values in them. The purpose of the article is to describe the concept of spiritual culture and the formation of artistic ideas in future teachers during the study of Ukrainian folk art. Analysis, synthesis and modeling methods were used to study the state of research. The results of our research was carried out with the help of empirical methods: pedagogical observation, questionnaires, interviews, testing, the method of experimental evaluations. Mathematical statistics methods were used to process the research results. In the research, we used a complex of general scientific and pedagogical methods. To ensure an objective and comprehensive study of the researched phenomenon, an analysis of scientific, scientific-methodical, and art sources was carried out; the state of development of the problem and prospects for further research were determined; generalization of pedagogical experience in teaching art in a higher education institution. The formation of a spiritual personality takes place in the interconnected process of education and training. An important role in the formation of the spiritual sphere of the individual belongs to education. Its tasks are classified according to the following directions: formation of a scientific outlook; education of a conscious attitude to learning, development of cognitive activity and culture of mental work; education of political consciousness and development of civic activity; education of a creative attitude to work, preparation for a conscious choice of profession; education of morality and culture of behavior; formation of legal awareness and education of civil responsibility; education of aesthetic culture and development of artistic abilities, etc.

Investigation on the Coalescence of Filaments in Fused Filament Fabrication Process for Amorphous Polyether Ketone Ketone for Varying Nozzle Diameters and Chamber Temperatures.

The use of Fused Filament Fabrication (FFF) of high-performance polymers is becoming increasingly prevalent, leading to the exploration of new applications. The use of such materials in critical cases for aerospace applications necessitates the verification of industry standards, particularly with regard to the requirements for part porosity. The authors investigate the effect of nozzle diameter and cooling temperature printing parameters on the porosity of the part by using existing modelling methods based on the sintering of cylinders and spheres and comparing the results to microscope snapshots of sections of parts. The models are able to be used as limits for predicting the longitudinal neck growth of the part. The authors show through experiments that the value of the cooling temperature of the deposited filament has a minimal effect on the outcome, while nozzle diameter has a strong impact on the resulting porosity. The modelling results show that there is a significant impact of both the nozzle diameter and cooling temperature on the porosity of the part. This implies that further refinement of the models is needed for the resulting parts to be applied in critical structures.

Simulation modelling demonstrates differential performance of connectivity methods in their ability to predict genetic diversity in complex landscapes

ContextThere have been few evaluations of how well different connectivity modelling methods are able to predict the spatial genetic structure and genetic diversity of populations residing in complex landscapes. Given the wide application of connectivity modelling tools in applied conservation planning, it is crucial to broadly evaluate how these models perform across resistance, movement, and population structure conditions in predicting genetic diversity patterns. Such evaluations are critical to provide rigorous, biologically based guidance for conservation and management applications. ObjectivesOur goal was to investigate how the predictions of three connectivity models were related to spatial patterns of genetic diversity complex landscapes, considering factors such as population structure, resistance, genetic drift, genetic disequilibrium, and organism movement abilities. MethodsWe evaluated the performance of several connectivity methods across seven a priori landscape resistance surfaces to provide a broad assessment of their performance. We used CDPOP, an individual-based, spatially explicit population and genetic simulation model, to simulate genetic diversity across these resistance surfaces. This provided a pool of genetic diversity patterns that were the response factor in our simulation experiment. We then simulated landscape connectivity with several popular connectivity methods, including resistant kernels, Circuitscape, and Pathwalker, and evaluated how well they were able to predict spatial patterns of genetic diversity. ResultsResistant kernel outperformed other connectivity methods in predicting landscape patterns of genetic diversity. The strongest relationships occurred when the population process has created spatial structure but has not yet led to significant genetic diversity loss due to drift. The time lag disequilibrium was relatively short. Long simulation times resulted in severe reduction in prediction ability due to drift. ConclusionsResistant kernel predictions were much more strongly related to spatial patterns of genetic diversity than were predictions produced by Circuitscape and Pathwalker, across a large combination of population structures. Strong relationships exist between functional connectivity and genetic diversity, with clearer and stronger associations seen in spatial patterns of allelic richness compared to heterozygosity or spatial effective population size. Our results confirm the strong relationship between genetic diversity and population connectivity, and suggest that computationally efficient incidence function algorithms, such as resistant kernel methods, are well suited to predicting functional connectivity.

Action enhancement of antimicrobial peptides by their combination with enzymes hydrolyzing fungal quorum molecules

Recently, the lactonase activity of several enzymes (lactonase AiiA, organophosphate hydrolase (His6-OPH) and New Delhi metallo-β-lactamase (NDM-1)) was revealed in the hydrolysis of lactone-containing fungal Quorum Sensing molecules (FQSM). This study was aimed at the investigation of possible use of these enzymes as components of antifungal combinations with antimicrobial peptides (AMPs) to increase their action efficiency against various fungi. For this, the interaction of various AMPs with AiiA, NDM-1 or His6-OPH, as well as the effect of AMPs on the catalytic characteristics of these enzymes in the hydrolysis of FQSM in enzyme/AMP combinations, were studied using in silico computer modeling methods. Enzymes combinations with 3 AMPs Bacitracin, Colistin and Polymyxin B were selected as the most rational in terms of maintaining the effectiveness of AMP and the catalytic activity of enzymes. The antifungal action of the selected combinations against cells of mycelial fungi and yeast was studied in vitro. It was found that combinations of the enzymes AiiA, His6-OPH and NDM-1 with Bacitracin, Colistin and Polymyxin B provide a significant increase in the action efficiency (up to 5000 times) of both AMPs and enzymes against fungi. The most effective variants were obtained for Polymyxin B in multicomponent combinations with enzymes.

Impedance modeling and quantitative stability analysis of grid-connected voltage source converters under complex unbalanced conditions

The stability issues caused by voltage source converters (VSCs), which are commonly used in renewable energy systems, are investigated in this paper. Much literature has investigated the impedance models and quantitative stability analysis for converters under the weak and unbalanced grid. However, on the one hand, harmonic-transfer-function (HTF)-based modeling methods are complex, and the established infinite-order models may suffer from unreasonable truncation. On the other hand, these existing impedance models without considering all unbalance factors are inaccurate. Both of these may bring wrong stability analysis results. Therefore, this paper proposes a simple impedance extension method and considers all unbalance factors to derive the impedance model of the converter. However, due to the established higher-order impedance model, the traditional impedance-ratio based stability analysis method is not applicable to multi-input multi-output (MIMO) systems. The commonly used eigenvalue-based GNC and diagonalization-based methods applicable to MIMO systems are cumbersome and not suitable for quantitative analysis. Therefore, in this paper, a quantitative analysis tool of system stability based on the phase-frequency characteristics of determinants is developed. Then, stability regions in the multi-parameter space are obtained. Finally, the established impedance model and the quantitative analysis results are validated via both simulations and hardware experiments.© 2017 Elsevier Inc. All rights reserved.

COMPARATIVE ANALYSIS OF FORMING TECHNOLOGY MULTI-GROUP TRAINS ON DIFFERENT SORTING DEVICES

Purpose. The purpose of the work is a comparative analysis of the multi-group trains forming technology on various sorting devices for solve the task of choosing the best sorting device depending on the initial conditions (combination of train and sorting devices parameters) using both one-sided and two-sided methods of forming such trains. Method. The methods of combinatorics, mathematical statistics and simulation modeling were used for comparative analysis of the of forming multigroup trains methods. The formalization of both classical one-sided and adapted two-sided formation methods was taken from published scientific publications. Results. An illustration of the use of one-sided and two-sided forming methods for real trains allows a better understanding of the reason for the superiority of some methods over others for certain initial conditions. As a result, with the help of a simulation model, the time indicators of the formation of multi-group trains were obtained for various initial conditions, the comparison of which allows to establish the best option for the implementation of the technology of the formation of multi-group trains. Practical importance. The performed analysis allows to choose the best method for each specific case of the initial conditions which will speed up the formation process and reduce the idling time of local cars at the stations. For this purpose, it is advisable to include the specified forming algorithm in the station dispatching staff decision-making support system, which based on the data about the cars parameters and given classification tracks specialization that used to form such trains, will allow to obtain the time parameters of train forming in different ways and choose the best of them (for example, with the minimum duration of the train formation), for which a shunting work plan will be offered.

Managing and editing UML documents: structure, integration, automation

Unified Modeling Language (UML) plays an important role in the modern software development process by offering standardized methods for visual modeling, analysis, and design of complex systems. This paper discusses the main aspects of storing, editing, and integrating UML documents with integrated development environments (IDEs). The main focus is on comparing the two main formats for storing UML models – XML Metadata Interchange (XMI) and JavaScript Object Notation (JSON). XMI, being an official standard developed by Object Management Group, provides a high degree of detail and compatibility with various UML tools, making it preferable for large and complex projects that require support for the full UML specification. At the same time, JSON is simple and flexible, which makes it suitable for projects where speed of development and ease of integration are important, although it is inferior to XMI in describing complex aspects of UML models. The paper analyzes in detail the methods of editing UML documents, including manual editing and automated approaches, using APIs and scripts. Manual editing is useful when you need to make small changes to the structure of a UML document, but it can be time-consuming and error-prone when working with large projects. Automation, on the other hand, provides effective tools for mass editing and generating UML elements, which significantly speeds up development and minimizes the likelihood of errors, especially since modern tools such as StarUML offer the necessary tools for programmatically modifying UML documents by integrating them into development processes. Combining of UML documents with integrated development environments also plays a key role in increasing development efficiency, as this allows automating code generation based on UML models, maintaining synchronization between code and diagrams, and facilitating visualization and documentation of architectural solutions. Despite the significant advantages, there are challenges associated with limited support for all UML features and potential conflicts between models and code. This only emphasizes the need for further research in this area. Prospects for further research include the development of new methods and tools for working with UML documents, improving their integration with development environments, and using artificial intelligence to automate the analysis and design of UML models. Attention should also be paid to the using of UML with continuous integration processes, which can significantly increase the flexibility and adaptability of software development. Thus, the study of the structure of storing, editing, and integrating UML documents is an important area for optimizing the design and development of modern software systems.

ТЕХНОЛОГИЯ АНАЛИЗА, ОЦЕНКИ И ПРОГНОЗИРОВАНИЯ КАЧЕСТВА ЖИЗНИ В КОНЦЕПЦИИ ЭКОНОМИКИ КАЧЕСТВА В УСЛОВИЯХ ЦИФРОВИЗАЦИИ СОЦИАЛЬНО-ЭКОНОМИЧЕСКОГО РАЗВИТИЯ

The quality of life contains and reflects all levels of quality, is considered as a comprehensive, integral indicator of social well-being and is the most important result of socio-economic development. In the course of achieving the goal set in the work to study the conceptual foundations of the formation of the terminological and methodological apparatus of the concept of “quality of life”, it was revealed that a fairly wide range of methods are in demand, which have found application in both the quality sciences and the life sciences. The quality economics methodology has played a special role in the devel- opment of modern research on the quality of life and the strengthening of its applied importance. The results obtained in a compact form reflect the development of scientific research on the quality of life in connection with related concepts and indicate a rapid expansion of the range of areas of research on the quality of life. The article notes the influence of digitaliza- tion and information technology on the chosen subject of research. A new view is proposed on the application of the method- ology of quality economics in conditions of dominance of branches of the knowledge economy. The prospects of modeling the quality of life based on the joint application of the quality economics methodology and an extensive group of mathemat- ical modeling methods are considered.

Challenges in predictive modelling of chronic kidney disease: A narrative review.

The exponential rise in the burden of chronic kidney disease (CKD) worldwide has put enormous pressure on the economy. Predictive modeling of CKD can ease this burden by predicting the future disease occurrence ahead of its onset. There are various regression methods for predictive modeling based on the distribution of the outcome variable. However, the accuracy of the predictive model depends on how well the model is developed by taking into account the goodness of fit, choice of covariates, handling of covariates measured on a continuous scale, handling of categorical covariates, and number of outcome events per predictor parameter or sample size. Optimal performance of a predictive model on an independent cohort is desired. However, there are several challenges in the predictive modeling of CKD. Disease-specific methodological challenges hinder the development of a predictive model that is cost-effective and universally applicable to predict CKD onset. In this review, we discuss the advantages and challenges of various regression models available for predictive modeling and highlight those best for future CKD prediction.

Reconstructing of the geometry of Atg13 and Atg101 molecules while assembling the complex

Aim. Associated subproteins which constitute the ATG1 multi-protein complex in plants and mammals, including ULK1 in humans, are orchestral protein kinase atg-units in resistance to stress stimuli across their different nature. The goals of this endeavour were to characterize the molecular nature of the interaction of ATG13 with ATG101, followed by in silico docking to catch the plausible ensuing integration into a multimeric complex ULK1/ATG1, which initiates the assembly of a PAS-preautophagosomal structure in the first step of autophagy initiation. Methods. Protein structures were modeled by homology using AlphaFold, and molecular dynamics (MD) was performed using GROMACS 5.0 with the Charmm36. Results. By implementing computer modeling methods, a complex of protein kinase atg-units for both ATG13 and ATG101 proteins, reflecting the interaction interface and conformational properties, was constructed for detailed interpretation while forming the forthcoming assembly of the ULK1/ATG1 multi-protein platform. Conclusions. This study provides a high-quality model platform for further sequential studies of protein-protein docking and protein-protein interactions with the possibility of reconstructing a model of the full ULK1/ATG1 complex to identify ATG8 binding sites.

SDYN-GANs: Adversarial learning methods for multistep generative models for general order stochastic dynamics

We introduce adversarial learning methods for data-driven generative modeling of dynamics of nth-order stochastic systems. Our approach builds on Generative Adversarial Networks (GANs) with generative model classes based on stable m-step stochastic numerical integrators. From observations of trajectory samples, we introduce methods for learning long-time predictors and stable representations of the dynamics. Our approaches use discriminators based on Maximum Mean Discrepancy (MMD), training protocols using both conditional and marginal distributions, and methods for learning dynamic responses over different time-scales. We show how our approaches can be used for modeling physical systems to learn force-laws, damping coefficients, and noise-related parameters. Our adversarial learning approaches provide methods for obtaining stable generative models for dynamic tasks including long-time prediction and developing simulations for stochastic systems.

Methodical system of training future english language teachers based on a complex of approaches

Introduction. The article describes a methodical system for developing professional competencies of future English language teachers based on communicative, cognitive and synergetic approaches. The relevance of the study is due to the need to ensure effective professional training of future teachers in the context of the increasing complexity of the educational environment and the diversity of student needs. The purpose of the study is to design a methodical system based on a complex of approaches that allows creating more adaptive and flexible conditions for the training and professional development of future English language teachers, taking into account modern requirements and challenges in the field of education. Materials and Methods. During the study, a theoretical analysis of scientific literature and legal documents on the issue under study was carried out, as well as a comparative analysis of existing concepts of methodical systems and models for the formation of professional competencies of future teachers. The methods of analysis, synthesis, comparison, generalization and modelling are used in the study. Results. As a result of theoretical and comparative analysis of scientific research, generalization of our own practical experience, a methodical system for developing professional competencies of future English language teachers based on a complex of approaches has been developed, its key components, which ensure the comprehensive and systematic nature of the educational process, have been described, as well as the mechanism of their interaction. All components of the system are presented in target, content, conceptual and methodical, effective blocks. Discussions and Conclusions. The development of a methodology for the formation of professional competencies of future English language teachers based on communicative, cognitive and synergetic approaches in the process of studying special disciplines with a focus on the integration of disciplinarydevelopment and the progressive formation of competencies is a prospect for further research.