Vol. 5 No. 07 (2025): Volume 05 Issue 07

This article deeply covers the role of soft skills, i.e. effective methodology for developing soft skills in future computer science teachers, modern pedagogical technologies, interactive educational methods and project-practical tasks. The study emphasizes the importance of soft skills such as communication, creative and critical thinking, cooperation and leadership in increasing the professional and personal potential of computer science teachers. Also, the consistent and stable formation of soft skills in students as a result of the gradual introduction of interactive methods, project tasks and digital technologies in the modern educational process is substantiated using practical examples and graphic materials. The methodological recommendations presented in the article are of significant theoretical and practical importance in the professional development of computer science teachers.

The development of manufacturing technologies is fundamentally transforming industrial activities, with digital twin technologies emerging as a revolutionary solution. A digital twin is a virtual model of a real-world object, enabling real-time monitoring, analysis, and optimization of processes. This article explores the essence of digital twin technology, its applications, and its significance in enhancing efficiency, reducing costs, and fostering innovation in modern manufacturing. Furthermore, the study analyzes the challenges of implementing this technology and outlines future prospects.

The article presents the current relevance of trilingual electronic translation and a brief description of electronic translation. The principles, tasks, and bases of work multilingual translator’s functional modul are clearly presented. In addition, a description of the functional module of the software package for trilingual electronic translation is presented by scheme. The main features of the functional module, the advantages of using functional modules in the program, and the functional module scheme of the software package created specifically for trilingual electronic translation are presented. The blocks of this functional module and the tasks of its implementation are described on the basis of a full life cycle.

Glycated albumin demonstrates a convincing correlation with glycated hemoglobin levels in patients with type 2 diabetes mellitus. This indicator allows one to evaluate the state of carbohydrate metabolism, reflecting the average glucose level over a shorter period of time compared to glycated hemoglobin. Such ratio makes glycated albumin an important marker for monitoring the course of the disease, especially in cases where it is necessary to quickly respond to changes in blood glucose levels.

This study investigates the effect of sodium-based modifiers on the catalytic synthesis of high-molecular-weight liquid hydrocarbons from syngas (CO + H₂). Catalysts with the composition 20%Co–20%Fe–5%B–1.5%Zr–(0–2)%Na supported on Al₂O₃ and SiO₂ were synthesised using the incipient wetness impregnation method. Various sodium compounds (NaNO₃, NaCl, Na₂CO₃, and NaOH) were applied as modifiers. The catalysts were characterised using chromatographic, X-ray diffraction, and technological analysis methods to determine their phase composition, distribution of active sites, and reaction efficiency.

The study highlights the influence of support material nature and sodium loading on CO conversion, hydrocarbon productivity, and product selectivity. According to the analysis, Na modification significantly enhanced the activation of active centres and chain growth probability in Al₂O₃-based catalysts, while this effect was less pronounced for catalysts supported on SiO₂. Additionally, both the sodium source and the sequence of metal deposition on the carrier surface were found to play a critical role in determining overall catalyst performance and product distribution.

These findings confirm the potential of sodium-modified cobalt–iron–boron–zirconium catalysts in achieving high productivity and selectivity in Fischer–Tropsch-type hydrocarbon synthesis. The results provide practical insights for the design of advanced catalytic systems for efficient syngas conversion.

This article investigates the oil-degrading potential of indigenous bacterial strains isolated from various oil-contaminated soils and products in the Jarkurgan and Kumkurgan districts of Surkhandarya region. Based on the analysis of the quantity and quality of microorganisms present in collected samples of soil, oil sludge, crude oil, and water, 24 pure bacterial isolates—predominantly occurring species—were isolated. These strains were comparatively characterized in terms of their growth and oil-degrading activity in a minimal medium supplemented with crude oil as the sole carbon source. Additionally, nine bacterial isolates exhibiting high oil-degrading potential were studied under conditions of Raimondo synthetic medium containing 1.0–2.0% crude oil, focusing on their morphological characteristics and hydrocarbon utilization efficiency.

This study explores the effect of low-temperature treatment (LTT) on the graphitization behavior of malleable cast iron during annealing. The results show that a properly selected LTT regime significantly promotes the formation of graphite inclusions, thereby accelerating cementite decomposition. The efficiency of LTT is determined by several key factors, including treatment temperature, duration, number of cycles, and the pre-treatment cooling conditions. Single-stage LTT is most effective at 300–400°C, while double and multi-stage treatments demonstrate enhanced performance, especially when the first cycle is conducted within 100–400°C. Longer exposure times further improve graphite inclusion formation, and the resulting structural changes remain stable even after prolonged storage at room temperature. Additionally, slow heating from 20°C to 700°C is identified as a viable alternative to traditional LTT, offering similar structural benefits. The most effective annealing approach involves holding the material at 300–400°C followed by a gradual rise to the pearlite transformation range, a method well-suited to the capabilities of standard industrial equipment. These findings provide valuable guidance for optimizing heat treatment practices in malleable cast iron manufacturing.

Suspended Cable-Driven Parallel Robots (CDPRs) are increasingly utilized in various applications due to their large workspace and high payload capacity. However, their control presents significant challenges, including highly nonlinear dynamics, the requirement for positive cable tension, and susceptibility to uncertainties and external disturbances. Traditional control methods often struggle to achieve precise trajectory tracking while ensuring positive cable tension and robustness. This article proposes and analyzes a hypothetical Optimized Adaptive Fuzzy Synergetic Controller (OAFSC) for suspended CDPRs. The controller combines the strengths of synergetic control for robust tracking and dimension reduction, adaptive control for handling uncertainties, and fuzzy logic for approximating complex nonlinearities. Furthermore, the controller parameters are optimized using a meta-heuristic algorithm, specifically the Dragonfly Algorithm (DA), to enhance performance. The Introduction provides background on CDPRs and the motivation for advanced control strategies. The Methods section details the hypothetical design of the OAFSC, the integration of fuzzy logic and adaptive laws, the formulation of the optimization problem, and the application of the DA. Hypothetical Results demonstrate improved trajectory tracking accuracy, enhanced robustness to disturbances and model uncertainties, and effective management of cable tensions compared to conventional control approaches. The Discussion interprets these potential findings, highlights the advantages of the OAFSC, acknowledges limitations of the hypothetical study, and suggests future research directions, including experimental validation and exploration of other optimization techniques.

Background: Type 2 diabetes mellitus (DM) is associated with various complications, including potential effects on bone health. Although elderly patients with Type 2 diabetes mellitus may exhibit normal bone mineral density, they are paradoxically at a higher risk of fractures. The underlying mechanisms remain multifactorial and involve glycemic control, hormonal regulation, and nutrient deficiencies.

Objective: To evaluate bone mineral density (BMD) in elderly patients with type 2 diabetes mellitus and investigate its relationship with glycemic control, vitamin D levels, and calcium status.

Patients and Methods: A prospective, cross-sectional study was conducted on 46 patients aged > 65 years at Merjan Teaching Hospital Babil, Iraq, between May 2024 and May 2025. Data collected included demographics, HbA1c levels, serum vitamin D and calcium levels, and bone mineral density measured via DEXA scans at the spine and hips.

Results: Osteoporosis was present in 54.3% of the patients, and 34.8% of the patients were classified as osteopenic. The majority of the patients were females. A positive correlation was found between HbA1c and DEXA T-scores (r = 0.313, p = 0.034), and patients with poor glycemic control (mean HbA1c = 9.2%) had a higher prevalence of osteoporosis. No significant correlations were found between bone mineral density (Dexa T-scores) and serum vitamin D (r = -0.057, p = 0.705) or calcium levels (r = -0.080, p = 0.597). The right hip had the highest site-specific prevalence of osteoporosis (41.3%).

Conclusions: Osteoporosis is highly prevalent among elderly patients, particularly women. Poor glycemic control (high HbA1c level) and increased age were significantly associated with lower bone density.

Recommendation: DEXA scans of multiple sites, particularly the spine and hips, are essential for detecting osteoporosis in this population.

Word count: 2,654 words, excluding references.

Funding Statement: The study was supported by grant NN from the Foundation of Basic Research. This work was carried out under research program NNN of NN University. Author NN was supported by grant NN from the Ministry of NN.

Ethical Compliance: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Data Access Statement: Research data supporting this publication are available from the NN repository at located at www.NNN.org/download/.

Conflict of Interest declaration: The authors declare that they have no affiliations with or involvement in any organization or entity with any financial interest in the subject matter or materials discussed in this manuscript.

Author Contributions: AB and MJ contributed to the design and implementation of the research, JK to the analysis of the results and to the writing of the manuscript. VK conceived the original and supervised the project.

In this article, the bond strength between GFRP rebar and concrete is investigated, and the differences compared to the bond between steel rebar and concrete are analyzed.

This article systematically analyzes the need to organize independent learning of students based on artificial intelligence (AI) technologies, organizational and technical conditions, existing platforms, problems and solutions. First of all, the need to introduce AI tools is justified based on the limitations of traditional education, the need to increase student activity and the need for personalized education. Harmonizing curricula with AI technologies, increasing teachers' digital literacy, developing methodological manuals and forming monitoring systems are identified as the main organizational conditions. Also, provision of technically modern ICT, access to AI platforms, electronic libraries and the presence of stable Internet are considered as important infrastructures for effective independent learning. The article briefly analyzes learning platforms based on local and foreign practical experience and shows their functional capabilities. At the same time, problems such as technological inequality, low level of training, financial and legal restrictions and specific solutions to eliminate them are proposed. Finally, methodological, technical, and strategic recommendations are presented to increase the effectiveness of independent learning using AI. This article serves as a scientific, theoretical, and practical basis for the formation of a digital learning environment based on artificial intelligence in the education system of Uzbekistan.

This article provides theoretical and practical information as well as proofs about the antyle and mantissa, and highlights the main points of it. It also suggests methods for solving several complex and Olympic-type problems with the help of the antyle and mantissa.

This article is dedicated to the development, technological foundations, and practical applications of modern Sign Language Recognition (SLR) systems. Advanced vision-based systems—particularly architectures such as MediaPipe Holistic, OpenPose, SignAll, Sign Language Transformer, and RWTH-PHOENIX—are analyzed in terms of their algorithmic principles, advantages, and limitations. These systems, based on artificial intelligence and deep learning architectures, enable the spatial-temporal, multimodal, and contextual recognition of sign language glosses.

The MediaPipe system provides real-time detection of facial, body, and hand movements, while OpenPose excels at modeling the user’s body pose in 2D and 3D formats. The SignAll system integrates NLP components for translating sign language glosses. SLR systems based on the PHOENIX14T corpus, developed by RWTH Aachen University, are considered a benchmark for sign segmentation. In particular, the Transformer-based Sign Language Transformer model allows for seamless translation of sign language glosses into English text.

The article thoroughly addresses issues such as multimodal signal analysis (gesture, pose, facial expression) for more accurate interpretation of sign movements, the creation of a contextual semantic representation model, real-time processing, and platform integration. Additionally, the practical significance of modern SLR systems in education, communication, and human-computer interaction (HCI) is analyzed.

The current work demonstrates morphologic characteristics of close and red-listed species of the sect. Kolpakowskianae based fresh plant specimens. Similar and distinct characters were listed and sixty-nine new characters will be recommended for the forthcoming issue of “Flora of Uzbekistan”. Also, results of molecular investigations related to the species was discussed.