As a result of experimental research, this article presents test-experimental data on the occurrence of stress-deformation states of flexural concrete beams with basalt reinforcement under the influence of force.

The study aims to establish the correlation between international trade, the tourist sector, foreign direct investments, GDP growth, and climatic changes in China. The study has conducted an analysis of the data spanning from 1995 to 2023, utilizing FMOLS and DOLS models to investigate the enduring correlation between international trade, foreign direct investment, and climate change. The co-integration analysis indicates a favorable association between international trade, foreign direct investment (FDI), and GDP growth. Nevertheless, the rise in global trade and the expansion of GDP has adverse effects on climate change. The study investigated the significant impact of the tourist sector on climate change, particularly in China, where it has a predominantly negative effect. The Chinese government is under pressure to promote the use of renewable energy sources in order to mitigate the climatic impacts of international trade and foreign direct investment. Additionally, they should enhance their tourist industry regulations to minimize pollution generated by the transportation sector.

In today's world of online cinemas and streaming platforms such as Netflix and YouTube, data quality plays a key role in ensuring high user satisfaction. A scalable AI/ML anomaly detection tool is used to improve data quality and enhance the reliability of video streams. This paper examines various approaches to anomaly detection, including supervised and unsupervised learning, as well as deep learning methods such as autoencoders and recurrent neural networks. In addition, the application of AI/ML for predicting user behavior and optimizing the resources of video streaming services is analyzed. The introduction of such technologies allows not only to improve the quality of video streams but also to reduce the cost of content moderation and network resource management. The prospects for the development of these technologies and their impact on the video-streaming industry are discussed.

In the context of the rapid development of financial technologies, automation of financial processes is becoming a key aspect of the management of modern companies. This work is devoted to the development and implementation of an integrated financial process automation system in the holding. The main focus is on improving the efficiency of the company, reducing staff costs and strengthening control over financial flows. The study analyzes various aspects of automation, such as the use of the 1C system for initial and complex automation of financial accounting, integration with other systems and the development of unique solutions adapted to the specifics of the enterprise. The practical part of the work demonstrates the successful application of the developed solutions in a real holding company, which confirms their effectiveness and importance for optimizing financial management. The work also highlights the experience of using these solutions in various projects, emphasizing their role in improving the financial stability and competitiveness of the company.

Keratin-based polyester composites represent a promising class of materials combining the sustainability of natural fibers with the versatility of synthetic polymers. This study evaluates the abrasion resistance and mechanical properties of composites made from keratin and polyester to assess their potential for various applications, including durable textiles and structural components. Keratin fibers were extracted and incorporated into a polyester matrix to form composite samples. These samples underwent a series of tests to determine their mechanical properties, including tensile strength, elongation at break, and modulus. Additionally, abrasion resistance was assessed using standard wear tests to evaluate the composites' durability under conditions of friction and wear. The results indicate that the incorporation of keratin fibers significantly enhances the mechanical properties of polyester composites. Notably, the tensile strength and modulus of the composites increased with the keratin content, demonstrating improved load-bearing capacity. However, the elongation at break exhibited a trade-off, with higher keratin content leading to reduced flexibility. The abrasion resistance tests revealed that keratin-based composites exhibit superior resistance to wear compared to pure polyester, highlighting their potential for applications requiring enhanced durability.

Pollution caused by burning the post-harvest agriculture waste and plastic waste in is a very serious problem that needs a solution. The amount of agricultural waste in Egypt ranges from 30 to 35 million tons a year. Out of this amount, only 11 million tons are used as animal feed and organic manure and the rest is burned. Egypt also produces 5.4 million tons of plastics yearly, only 20% of which is recycled. The rest is either burned resulting in highly toxic dioxins or dumped in water sources causing endanger to aquatic life. Egypt does not produce wood and imports more than three billion dollars’ worth of wood yearly, including wood plastic composites (WPC). WPC is a composite material widely used in decking, fencing, garden furniture, cladding, and kitchen cabinets and made of wood fiber, thermoplastics, and additives. This work investigates the sustainable sources to produce WPC from different types of agriculture and plastic wastes. To produce WPC of high quality, the processing, physical, and mechanical testing were carried out on the produced WPC. Three types of post-harvest waste were experimented, orange tree trimmings, cotton stems, and casuarina tree trimmings. Both virgin and recycled High Density Polyethylene (vHDPE & rHDPE respectively) plastic were experimented. Both Maleic Anhydride grafted polyethylene (MAPE) and silane coupling agents were also experimented. Results show that, the compound that had the best WPC properties had the following recipe: orange wood at 50% by weight with 0.11 mesh size, rHDPE at 50%, MAPE coupling agent at 5%.

This study examines the integration of AI and GenAI in B2C companies' growth strategies, addressing the transformative impact on business processes and customer interactions. Utilizing a comprehensive analysis of McKinsey reports and current research, the paper develops a strategic framework for AI integration in B2C sectors. The research reveals a significant increase in AI adoption, with 72% of organizations implementing AI technologies. The study outlines key areas of transformation, including hyper-personalization of customer experiences, operational efficiency optimization, and acceleration of innovation cycles. A novel strategic framework is proposed, encompassing readiness assessment, roadmap development, and risk management strategies. The findings highlight the critical importance of ethical considerations and organizational culture transformation in successful AI integration. This research contributes to the understanding of AI-driven strategies in B2C, offering insights into long-term economic effects, consumer behavior changes, and regulatory implications of AI adoption in the digital economy era.

The paper considers methods of effective training of trainee pilots to work as co-pilots, with an emphasis on improving flight safety. Special attention is paid to theoretical training, which provides fundamental knowledge, and practical training on simulators, which helps to consolidate skills. Various approaches are considered, including problem-based and heuristic learning, as well as game methods that develop cognitive abilities and stress tolerance of pilots. An important aspect is distance learning, which includes online schools, webinars and individual coaching. Special attention is paid to the methodology aimed at working with highly automated aircraft and the importance of meteorological training. The use of innovative methods and technologies, such as the 4D system, helps to optimize teamwork and improve the professional training of pilots. In conclusion, the need to integrate competence-based and contextual approaches to improve the quality of education is emphasized.

In modern software engineering, unit testing plays a central role in maintaining the reliability and quality of the code. In light of this, the article "Methods for Improving Unit Tests to Improve Code Reliability" highlights various strategies and practices aimed at optimizing the unit testing process. Based on extensive research and many years of experience, methods such as improving the independence of tests, increasing their determinism and readability, as well as the introduction of test automation techniques are presented. Important aspects are discussed, including test-driven development (TDD), test coverage analysis, and component isolation. The purpose of the article is to provide readers with a comprehensive set of recommendations for creating faster, clearer and more reliable tests, which ultimately contributes to the development of better software.

Understanding the dynamic tensile deformation characteristics of deep coal rock is essential for improving the safety and efficiency of underground mining operations. This study investigates the behavior of deep coal rock under dynamic tensile loading conditions using advanced testing techniques and numerical simulations. Samples of deep coal rock were subjected to high strain rate tensile tests to observe their deformation and failure patterns. The results reveal significant insights into the tensile strength, strain rate sensitivity, and fracture mechanisms of deep coal rock. Numerical models were developed to simulate the experimental conditions, and the outcomes were validated against the experimental data. The findings demonstrate that dynamic tensile loading significantly affects the mechanical properties of deep coal rock, leading to a better understanding of its response under real-world mining conditions. This research contributes to the development of more accurate predictive models for assessing the stability and safety of deep underground coal mines.