Purpose: This article explores the adoption of Artificial Intelligence (AI) in Human Resource Management (HRM) in the UAE, focusing on the critical challenges of fairness, bias, and privacy in recruitment processes. The study aims to understand how AI is transforming HR practices in the UAE, highlighting the issues of bias and privacy while examining real-world applications of AI in recruitment, employee engagement, talent management, and learning and development. Methodology: Through case study methodology, detailed insights are gathered from these companies to understand real-world applications of AI in HRM. A comparative analysis is conducted, comparing AI-driven HRM practices in UAE-based organizations with international examples to highlight global trends and best practices. Findings: The research reveals that while AI holds significant potential to streamline HR functions such as recruitment, onboarding, performance monitoring, and talent management, it also discusses challenges and strategies companies face and develop in integrating AI into their HRM processes, reflecting the broader context of AI adoption in the UAE’s HR landscape. Originality: This paper contributes to the growing body of literature on AI in HRM by focusing on the unique context of the UAE, a rapidly developing market with a highly diverse workforce. It highlights the specific challenges and opportunities faced by organizations in the UAE when implementing AI in HRM, particularly regarding fairness, bias, and data privacy.

According to official data, modern Russia has the lowest unemployment rate. However, there is still a huge contingent of hidden unemployment, many times higher than the official level. This situation is paradoxically combined with an acute and continuously growing shortage of qualified production personnel. Using a lot of factual material, the author reveals the causes of this phenomenon. The main one is the depopulation of the indigenous population, which is being replaced by people of other ethnic groups with the lowest qualification level. At the same time, due to the destruction (“optimization”) of the education system, the intellectual and qualification level of the indigenous population is continuously decreasing. The other is the various types and waves of growing emigration of “brains” and “golden hands.” As a result, for more than thirty years, the contingent of old engineering and technical personnel has exhausted itself, while new ones have not been trained in the required volume and quality. A huge personnel “hole” has formed. The author proposes to close this “hole” on the basis of a radical reorientation of the entire Russian education system, starting with kindergarten, school, etc. It is also necessary to reformat the public consciousness accordingly, especially the mass consciousness of young people.

Purpose: This research paper aims to justify the need for the Quality of Hire (QOH) construct as a value-adding focus for strategic human resource management (SHRM). The traditional focus on efficiency and cost-oriented recruitment metrics overlooks the importance of QOH in providing a competitive advantage and delivering long-term value. The study expands the economic theory of human resource development and develops a profit-building concept relevant to SHRM by exploring the practices that enable QOH in organizations. Design: The study utilizes a case-study method to examine a target firm’s mechanisms to build QOH in its recruitment process. It applies a structuration theory lens to analyze the behavior of various actors, their agencies, and the continuous interplay between structure and action in enabling QOH. Findings: The findings suggest that assessing and building measures for getting QOH is a complex task for organizations due to the inherent reliance on lag measures such as performance and tenure. The study highlights that QOH can be enabled through changes in the firm’s recruitment practices. Originality: This paper contributes to recruitment research in two significant ways. First, it expands on the under-researched construct of QOH, providing clarity on its definition and importance. Second, it identifies lead practices that organizations can incorporate into their recruitment and selection processes to enable QOH. By using a structuration theory lens, the study explores how actors in the recruitment process adapt and align with new structural rules to enable QOH. Research implications: The research builds on the structuration theory in recruitment and selection and exhorts practitioners in organizations to move beyond efficiency-oriented recruitment practices and focus on practices that contribute to QOH. By considering post-hire outcomes, such as job performance and long-term retention, organizations can improve their talent acquisition and retention strategies, creating long-term value for the organizations.

Two-dimensional hexagonal boron nitride nanosheets (h-BNNS) were synthesized on silver (Ag) substrates via a scalable, room-temperature atmospheric pressure plasma (APP) technique, employing borazine as a precursor. This approach overcomes the limitations of conventional chemical vapor deposition (CVD), which requires high temperatures (>800 °C) and low pressures (10−2 Pa). The h-BNNS were characterized using FT-IR spectroscopy, confirming the presence of BN functional groups (805 cm−1 and 1632 cm−1), while FESEM/EDS revealed uniform nanosheet morphology with reduced particle size (80.66 nm at 20 min plasma exposure) and pore size (28.6 nm). XRD analysis demonstrated high crystallinity, with prominent h-BN (002) and h-BN (100) peaks, and Scherrer calculations indicated a crystallite size of ~15 nm. The coatings exhibited minimal disruption to UV-VIS reflectivity, maintaining Ag's optical properties. Crucially, Vickers hardness tests showed a 39% improvement (38.3 HV vs. 27.6 HV for pristine Ag) due to plasma-induced cross-linking and interfacial adhesion. This work establishes APP as a cost-effective, eco-friendly alternative for growing h-BNNS on temperature-sensitive substrates, with applications in optical mirrors, corrosion-resistant coatings, energy devices and gas sensing.

Simulation training in dental medical eduaction is a modern high-tech approach in providing quality higher education. Simulation training immerses students in realistic scenarios, allowing them to develop both technical and non-technical skills essential for effective patient care. This study highlights key contemporary issues in high-tech simulation training for dental education and consolidates its rationale and benefits. We searched the databases PubMed, Scopus, Web of Science, and ResearchGate. This review includes 36 articles published in English, Russian, and Ukrainian from 2020 to 2024. Non-peer-reviewed papers or those not published in indexed journals were not considered. Simulation training was found to impact integration of theory and practice, training a wide range of psychomotor skills, development of complex clinical competences, cultivating confidence, empathy and patient-oriented care, neuroplasticity of the brain and the cognitive load. Pedagogical benefits and the place of simulation training in the curriculum were also discussed.