Volume 7.
Issue 8.

The article presents a comprehensive analysis of the influence of surface coatings and microtextures on the frictional characteristics and durability of clutch components in professional motorsport applications. The study is based on an interdisciplinary approach that integrates engineering tribology, materials science, and applied mechanics of high-load transmission systems. Particular attention is given to content and comparative analysis of both domestic and international sources describing the behavior of DLC coatings, PTFE-based composites, and iron-based laser claddings under various friction modes, thermal loads, and cyclic stresses. Critical differences between coatings are identified in terms of friction coefficient, wear volume, thermal stability, and adhesion strength to the substrate. Based on empirical data, a typology of coating applicability is proposed for different motorsport disciplines, ranging from circuit racing to rally and drag racing. Summary tables are presented to reflect the operational properties of coatings at temperatures up to 250 °C and under boundary lubrication conditions. The necessity of context-specific coating selection is substantiated, taking into account track configuration, weight constraints, and cooling requirements. Special emphasis is placed on the role of microtextures in heat distribution and contact stress regulation within the clutch. This article will be of interest to design engineers, motorsport specialists, friction system developers, and surface engineering researchers involved in the design of transmission components for extreme operating conditions.

The study presents a systematic review and analysis of existing methodological approaches to preventing and neutralizing conflict situations in gambling and entertainment venues. The article aims to identify the specific challenges that arise in the process of ensuring security in gaming and entertainment establishments, where the risk of conflict incidents is elevated. The methodological framework comprises a comprehensive overview of specialized scholarly publications from 2021 to 2025, an analysis of best-practice experience from leading industry operators, and empirical data drawn from official statistical reports. The investigation identifies the principal conflictogenic factors: substantial financial losses, increased aggression under the influence of alcohol, and psychological instability among patrons. The limited effectiveness of traditional reactive security systems—primarily focused on responding to incidents after they occur—is demonstrated. To address the uncovered deficiencies, a three-tier model of proactive security is proposed. The practical significance of the findings is clear for security service directors, managers of gaming and entertainment complexes, and professionals in criminology and corporate security.

This article presents an analysis of the integrated methodological foundations for the development of video materials aimed at representatives of Generation Z whose media consumption is characterized by fragmentation and a high rate of change in the format of consumed content. The relevance of the study is dictated by a highly competitive environment that requires media projects to continuously renew their narrative and maintain a stable level of viewer engagement through optimization of creative and technical processes. The aim of the study is to identify and systematize the main existing principles for building a scalable production ecosystem using the example of the YouTube channel Blaza Plays. Special attention is paid to three clusters of success factors: firstly, precise calibration of the product concept based on psychographic profiling of the target audience; secondly, implementation of technological templates and automated editing pipelines that ensure a balance between standardization and creative flexibility; thirdly, development of an adaptive management model for the team of editors and camera operators that provides for regular feedback sessions, training in storytelling methodologies and humorous intonation. The practical significance of the work lies in the creation of a replicable scheme capable of effectively responding to rapidly changing platform trends and maintaining the competitiveness of media projects in the long term

Organizational culture has long been recognized as a foundational determinant of performance, innovation, and strategic adaptability. In parallel, leadership practices and business consulting have emerged as critical mechanisms through which cultural values are articulated, reinforced, and transformed, particularly under conditions of digital disruption and increasing environmental complexity. This research article develops a comprehensive, theory-driven examination of the interrelationships among organizational culture, leadership, consulting interventions, and organizational performance, with a particular focus on innovation, knowledge conversion, and digital transformation. Drawing exclusively on established literature in organizational culture, management, consulting research, and information systems, the study synthesizes insights from seminal and contemporary works to construct an integrative analytical framework. The article adopts a qualitative, conceptual research design grounded in systematic literature analysis and interpretive synthesis, following established methodological principles in business and information systems research. The findings reveal that organizational culture operates not merely as a contextual variable but as an active, dynamic system that shapes leadership behavior, mediates consulting effectiveness, and conditions the success of digital and business model innovation. Leadership is shown to function as a cultural carrier, while consultants increasingly act as change agents who bridge internal cultural constraints with external knowledge and technological opportunities. The discussion elaborates on theoretical implications, identifies persistent tensions and counter-arguments within the literature, and highlights limitations related to context dependency and measurement challenges. The article concludes by outlining future research directions and practical implications for leaders, consultants, and scholars seeking to understand and leverage culture as a strategic resource in contemporary organizations.

The article examines existing methods of digital technologies and online platforms as tools for promoting and selling wedding dresses. The relevance of the study is determined by the rapid, nearly exponential, increase in the influence of information and communication technologies and Internet platforms on consumer behavior patterns and the formation of business strategies in the bridal wear industry. The aim of the work is to conduct an in-depth analysis and systematization of contemporary approaches to the application of digital tools and Internet resources in order to enhance the effectiveness of marketing promotion strategies and processes and the commercial realization of wedding attire. The research is based on a methodology that includes analysis of recent scholarly publications and empirical market research data. Within the framework of the study, a detailed examination is carried out of the most significant digital means, among which are social media and influencer marketing, specialized e-commerce platforms, as well as innovative solutions in the field of augmented (AR) and virtual (VR) reality. This article is intended for a wide range of specialists: researchers in the fields of digital marketing and e-commerce, professionals in the wedding industry, as well as entrepreneurs seeking to optimize business models and increase competitiveness in the market of exclusive bridal wear. As a result of the systematic analysis, fundamental conclusions are formulated regarding the necessity of applying a comprehensive, multichannel approach when establishing a presence in the digital space, and it is also confirmed that deep personalization of commercial offers and interactive engagement with the target audience—particularly prospective brides—are key factors for success under contemporary market conditions. [References maintained in square brackets].

This paper examines the persistent tension between abstract moral thought experiments—most notably the trolley problem—and the concrete engineering, legal, and social realities of autonomous vehicle decision-making. We synthesize philosophical analyses, empirical studies, technical descriptions of perception and control systems, and recent regulatory and dataset-auditing work to produce a coherent account of ethically bounded architectures for autonomous driving systems. The central argument is that a purely philosophical framing (e.g., sacrificial dilemmas) is insufficient for designing viable autonomous driving ethics; instead, ethically bounded AI must integrate formal ethical constraints, decision-theoretic planning, robust perception, human-centered accountability mechanisms, dataset auditing, and meaningful human control. We propose a layered framework that links (1) low-level safety and collision mitigation algorithms, (2) intermediate decision-theoretic planning incorporating probabilistic risk assessment and distributive ethical constraints, and (3) high-level governance mechanisms for transparency, auditing, and legal alignment. We analyze normative trade-offs between utilitarian, deontological, and contractualist approaches and show how these philosophical families map onto technical choices in architecture, datasets, and evaluation. The paper also explores responsibility attribution, the role of simulated and real-world datasets in shaping moral behavior, and the procedural mechanisms needed to operationalize “meaningful human control.” Finally, we identify research priorities and policy recommendations to move from rhetorical trolley-problem debates to implementable, justifiable systems that can be audited and regulated. The conclusions emphasize layered safeguards, multidisciplinary governance, dataset quality assurance, and a move away from binary sacrificial framing toward continuous harm-minimization under uncertainty. (max 400 words)

The purpose of this article is to define methodological approaches and the practical application of the rustic style as an example of practical eco-design in the modern world.

The research methods used in the article include: abstract- logical method; system analysis; observation and generalization; analysis and synthesis; expert evaluation methods; and graphical method.

This study identifies the fundamental concepts and structure of the rustic style. It examines how, in floristic art, the rustic decoration direction is expressed in compositions that use wildflowers (according to season), dried flowers and cereal grasses, tree branches, moss, bark, fabrics of natural fibers such as burlap, linen, ropes, and wooden elements. Key ecological principles embodied in the rustic style are defined, including the use of local resources; recycling and reuse;

simplicity and conscious consumption. The main principles and characteristics of decorating with natural materials are determined—use of seasonal and locally grown plants; emphasis on recycling and reusing items (e.g., glass jars, wooden boxes, bottles); rejection of synthetic plastic, floral foam, and glitter; décor that influences emotions by calming, inspiring, and shaping style. Furthermore, the study finds that one of the key features of rustic interiors is the widespread use of untreated wood, which must not be painted or varnished but only treated with special agents for pest protection. The use of rustic style in decorating modern offices, cafés, and other spaces is characterized, and its negative aspects and limitations are identified: risk of appearing careless or overly simplistic; stylistic constraints; seasonal dependence; durability issues; difficulties in cleaning and transporting décor; limited color palette; and lack of technological compatibility.

Against the backdrop of the rapid expansion of the global nail care segment and the parallel tightening of client expectations regarding safety and quality, hardware-based manicure methods (e-file) are coming to the fore. At the same time, their use remains surrounded by mythologized perceptions and caution, mainly due to the presumed risk of mechanical injury. This study aims at an evidence-based verification of the safety profile and effectiveness of e-file manicure using the authors’ combined technique E-File Dry Manicure as a case in point. The adopted methodology includes a systematic analysis of dermatology and cosmetology literature, a comparative technical examination of the geometry of manicure bits with extrapolation of principles from podology, and a qualitative case study based on the practical implementation of the technique in the US market. The findings indicate that the decisive parameter determining the safety of the intervention is the geometry of the working part of the bit. The study demonstrates that the use of an attachment with a rounded apex (rounded cone) in combination with subsequent manual cuticle removal using nippers forms a methodically balanced protocol that minimizes the likelihood of damage to the nail matrix and periungual folds, in contrast to approaches relying on bits with a sharp tip (e.g., flame). It is concluded that the specified combined technique is a safe, universal, and clinically effective alternative capable of raising industry safety standards. The material is intended for practicing technicians, educators, salon owners, and representatives of beauty industry regulators.

Businesses increasingly encounter inefficiencies in employee expense management and corporate credit card reconciliations. Manual expense management processes take time, are error-prone, and are low in transparency, especially when a great many credit card transactions are involved. This research paper explains how the integration of JPMorgan Chase (JPMC) corporate credit cards with Oracle Cloud Enterprise Resource Planning (ERP) changes expense reporting, approval procedures, and payment reconciliation. With formalized architecture using Oracle Expenses, Payables, and middleware integration, companies can automate expense capture, enforce policy adherence, and speed payment cycles. This article includes a U.S.-based manufacturing firm case study that automated its expense processes, which reduced processing time by 45% and strengthened expense policy compliance by 70%. With the help of data, visualizations, and cited best practices, the research illustrates the way these integrations are critical for operational nimbleness and financial mastery.

The electric vehicle (EV) revolution demands new materials that address performance, safety, and sustainability imperatives. High-performance polymers are emerging as essential replacements for heavy metals and brittle glass in electric vehicle battery systems, where they offer weight reduction, insulation, thermal management, and fire hazard solutions. This paper explores how high-performance polymers can help enhance EV performance by offering lightweight, high-durability, thermally and electrically feasible alternatives to traditional metals and glass. By the analysis of some of the most significant polymer families, such as polyurethanes, epoxies, and glass-filled nylons. A comprehensive analysis of over 40 peer-reviewed papers, industry reports, and technical standards was conducted to analyze and detail their specific applications in thermal management, electrical insulation, and mechanical protection in high-voltage battery systems. The findings emphasize the key role of polymers in the development of faster, safer, and more efficient electric vehicles.

The study analyzes how pedagogical approaches in makeup schools are being transformed under the influence of artificial intelligence (AI), augmented reality (AR), and virtual reality (VR) tools, and determines their role in the formation of cognitive and psychomotor skills. The methodological basis relies on a systematized review of publications from Scopus and IEEE and a qualitative comparative analysis in a case study format of leading technological solutions (Modiface, PerfectCorp, Pivot Point LAB). The interpretation of materials was carried out through the theoretical lens of TPAACK (Technological Pedagogical Aesthetic and Content Knowledge), which makes it possible to consider the technological component in conjunction not only with pedagogical and content knowledge, but also with the aesthetic component that is critical for the makeup artist profession. The results obtained indicate that AI tools are most effective at the cognitive stage of learning: algorithmic processing of appearance parameters and facial morphology contributes to the automation of analytical operations and reduces the share of routine procedures, reallocating the educational emphasis toward semantic interpretation of data and the adoption of artistically justified decisions. AR simulators, in turn, provide a safe format for psychomotor practice, making it possible to train movement accuracy and application technique without material losses and without risk to the model. At the same time, the didactic return of these tools decreases due to systematic distortions in learners self-assessment of mastered skills, as well as due to a pedagogical gap manifested in a mismatch between the pace of updating teaching methods and the speed of implementing technological tools. A comparative review of the cases shows that the greatest degree of maturity is characteristic of pedagogical ecosystems in which digital solutions are integrated with their own educational model and mechanisms for objective monitoring of progress; Pivot Point LAB is highlighted as an example, demonstrating a more coherent architecture of learning and control of the dynamics of competency formation. The set of conclusions confirms that the TPAACK framework serves as a necessary foundation for designing effective and inclusive digital learning environments in professional makeup education, as it ensures consideration of technological, pedagogical, content, and aesthetic components within a single logic. The conducted study has practice-oriented value for the EdTech research community, developers of educational software, and management teams of vocational education organizations in the beauty industry.

Financial risk assessment is a critical function within the financial industry, encompassing the identification, measure- ment, and mitigation of various risks such as credit risk, market risk, operational risk, and liquidity risk. Traditional methods often rely on quantitative models built upon struc- tured numerical data, which, while effective, frequently over- look the vast amount of unstructured information available in financial documents. This paper explores the integration of Natural Language Processing (NLP) and Machine Learn- ing (ML) techniques to automate and enhance financial risk assessment. We propose a comprehensive framework that leverages NLP to extract meaningful insights from diverse unstructured textual data sources, including financial news, company reports, social media, and regulatory filings. These extracted features, combined with traditional quantitative data, are then fed into advanced machine learning models to provide more accurate, timely, and holistic risk evalua- tions. Our approach aims to overcome the limitations of existing models by providing a more accurate, timely, and in- terpretable solution for financial market analysis, ultimately leading to more robust decision-making and improved fi- nancial stability. We demonstrate how NLP can identify early warning signals, detect emerging risks, and provide a nuanced understanding of market sentiment and corporate health, which are often missed by purely numerical analyses. The integration of ML models further allows for the identi- fication of complex patterns and predictive capabilities that enhance the overall risk assessment process.

This article develops a comprehensive, publication-ready theoretical and practical framework that synthesizes agility, value-added logistics services, and digital intelligence within contemporary logistics and warehouse operations. Drawing on established and emergent literatures in logistics flexibility, third-party logistics (3PL) strategies, warehouse operational responses to e-commerce and pandemic shocks, big data analytics, digital technologies, RFID contextualization, machine learning forecasting, and environmental logistics, the paper constructs a multi-layered model for evaluating, designing, and improving logistics performance. The structured abstract outlines the problem, methods, principal findings, and implications. First, the problem context is identified: contemporary logistics providers face intensifying demand volatility, service differentiation requirements, and rapid technological change that together strain traditional warehouse and distribution paradigms (Ho & Chang, 2015; Lee et al., 1997). Second, the method synthesizes theoretical constructs and empirical insights from the provided references into a conceptual model that links innovation and service capabilities, logistics flexibility, value-added services, digital technologies, and sustainability outcomes (Gunasekaran et al., 2017; Ivanov et al., 2019). Third, the key findings show that the interplay of organizational capabilities (innovation and service orientation), operational strategies (value-added services and outsourcing), and digital intelligence (big data analytics, IoT, RFID, and machine learning) produces superior logistics performance, resilience to shocks such as pandemics, and opportunities for sustainable improvements when managed coherently (Ho & Chang, 2015; Michel, 2020; Gunasekaran et al., 2017). Finally, implications for practitioners highlight a staged implementation pathway that emphasizes capability assessment, modular service design, data architecture development, workforce upskilling, and sustainability alignment. The article contributes an integrative, citation-grounded roadmap for research and practice while identifying specific avenues for empirical validation.

The global power sector is pivotal to achieving climate targets, yet its decarbonization presents complex challenges, including the risk of stranded assets. This article proposes an Electricity Climate Alignment Metric (ECAM) to comprehensively assess and track global progress towards a low-carbon electricity future. The ECAM integrates key components such as carbon intensity, share of low-carbon electricity, fossil fuel plant profiles, committed emissions, stranded asset risk, and investment flows. Anticipated results highlight a multi-speed transition and pinpoint regions vulnerable to stranded assets due to existing fossil fuel infrastructure. The discussion emphasizes the profound policy and investment implications, advocating for accelerated renewable deployment, managed fossil fuel phase-out, robust carbon pricing, and international cooperation. The ECAM aims to provide quantifiable insights for policymakers and investors to navigate the transition, manage financial risks, and accelerate the shift to a climate-compatible electricity system.

The accelerating adoption of cloud computing for business transformation presents organizations with a complex array of security challenges. As enterprises migrate critical workloads to cloud environments, they confront not only traditional threats such as Distributed Denial‑of‑Service (DDoS) attacks and data storage vulnerabilities, but also increased attack surfaces brought by microservices architectures, scalable load balancing, and dynamic identity and access management (IAM). This paper presents an integrative, theoretically grounded synthesis of existing research on cloud security, weaving together three often‑disparate domains: zero‑trust architectures (ZTA), IAM, and adaptive load‑balancing as a resilience mechanism against availability and performance threats. Drawing on seminal and recent contributions—including studies on DDoS defense in cloud contexts (Agrawal & Tapaswi, 2019), the security implications of cloud migration (Shitta‑Bey & Adewole, 2023), nature‑inspired load balancing strategies (Milan et al., 2019), and burgeoning literature on zero‑trust deployment in microservices (Kesarpu, 2025; Hosney et al., 2022; Che & Sheng, 2023; Hong et al., 2023)—the paper delivers a multi-layered conceptual framework aimed at securing cloud‑enabled business operations. The results highlight that pure cloud migration without systematically integrating ZTA and IAM leaves enterprises exposed to data breaches and service disruptions. Similarly, conventional load‑balancing algorithms, when not aligned with dynamic identity and access control policies, may inadvertently magnify security vulnerabilities. The discussion outlines challenges, potential trade‑offs among performance, flexibility, and security, and proposes a unified security architecture that balances resilience, access control, and scalability. Finally, the paper identifies gaps in empirical evaluation, advocating for future research on real‑world deployments and automated orchestration of security controls.

Multinational companies that manage data across jurisdictional boundaries are having trouble integrating artificial intelligence systems with multi-cloud architectures. This is especially true since over 90% of businesses use multiple cloud providers and deal with complicated AI governance frameworks. This paper examines how well AI governance frameworks in India and the US deal with multi-cloud data residency compliance issues through a systematic literature evaluation based on PRISMA standards and thematic analysis of 26 publications, including academic articles, government policy papers, and industry reports published between 2020 and 2025. The study points out significant cross-border regulatory coordination problems and examines whether existing bilateral strategies need more ways to work together. The thematic analysis identified trends in regulatory frameworks and compliance problems, revealing "regulatory incommensurability" as a central theme—meaning that following one jurisdiction's rules goes against the basic ideas behind another's procedures. The Digital Personal Data Protection Act in India has a permission-by-default approach, which is very different from the USA's restriction-by-default approach. This leads to impossible compliance situations instead of coordination problems. Organizations face systemic inefficiencies because of duplicate infrastructure and multiple governance systems that do not provide the same level of AI safety or data security. For example, 35% of data breaches include "shadow data" not covered by existing frameworks. The results show that traditional working methods cannot settle significant disagreements between AI governance frameworks. This means that new theoretical approaches are needed that acknowledge valid regulatory differences while making it easier for multinational companies to use AI systems in both jurisdictions.