This paper deals with the numerical analysis of functionally graded spherical bodies subjected to combined thermal and mechanical loads. A method is presented to train deep neural networks to approximate the important solutions. We outline two approaches for generating the training dataset for a deep neural network, followed by a method for creating the neural network itself. Then, through a numerical example, we investigate the axisymmetric problems of radially graded spherical bodies (e.g., ideal spherical pressure vessels). Based on the results obtained, we evaluate the accuracy of solving the outlined problem using the proposed neural network.

The rapid advancement of digital technologies has raised uncertainty about the adequacy of traditional maintenance models to meet Industry 4.0 requirements. This study develops and validates an asset management framework to support the South African petrochemical industry’s transition to Maintenance 4.0. The framework was validated through a quantitative survey conducted within a leading petrochemical company in South Africa, ensuring its practical applicability. Descriptive statistical analysis confirmed 15 of 17 framework characteristics and supported five of seven theoretical propositions. Key enablers of Maintenance 4.0 adoption include the integration of human intelligence, machine learning, and real-time data, as well as the role of organizational culture and asset resilience in shaping outcomes. The study offers both theoretical contributions and practical guidance for maintenance professionals seeking to align maintenance practices with Industry 4.0 principles, with relevance extending beyond the immediate case context.

This study examines Romania’s progress in emergency caller location technologies and accessibility between 2020 and 2024, within the broader European context. Applying a PRISMA-informed review methodology, it draws on official reports, academic sources, and EU regulatory data to evaluate the implementation of Advanced Mobile Location (AML), HTML5 geolocation, and the Apel 112 mobile application Romania was among the first EU countries to deploy AML and subsequent performance metrics indicate notable advancements in geolocation accuracy through hybrid handset- and network-based methods. However, despite these advancements, the adoption of the Apel 112 app has declined, raising concerns about user trust, public awareness, and accessibility. To assess system inclusiveness, this study applies the International Classification of Functioning, Disability and Health (ICF) framework. Findings reveal that persons with hearing, speech, and cognitive impairments continue to face substantial barriers due to the absence of real-time text (RTT), video relay services, and universally designed interfaces. These results support both hypotheses: Romania has strengthened its technical infrastructure for caller location (H1), yet persistent accessibility and interoperability limitations remain (H2). The study concludes that inclusive design, user education, and cross-platform compatibility must become priorities for emergency communication policy to ensure equitable access for all users.

Quality 4.0 builds on the principles of Industry 4.0 to improve quality management. Integrating Quality 4.0 into Business Process Management (BPM) examines how digital technologies enhance process efficiency and innovation. The main research question is how Quality 4.0 can be aligned with existing BPM frameworks and how the digital transformation of traditional quality management techniques facilitates efficiency. A bibliometric analysis was conducted using the Scopus database, employing keyword analysis, link mining techniques, and network mapping to identify research trends and gaps. The results show the main directions of research on integrating Quality 4.0 and BPM and highlight implementation barriers such as organizational resistance and the need for strategic alignment. The study also suggests directions for future investigation, including the development of standardized frameworks for evaluating digital BPM outcomes and exploring emerging debates around human-centric, sustainable, and resilient approaches reflected in Industry 5.0 and Quality 5.0.

This study evaluates the long-term economic feasibility of electric waste collection vehicles (EVs) as a sustainable alternative to diesel-powered counterparts in urban municipal services. Using real operational data from a Hungarian waste management company, we developed a total cost of ownership (TCO) model spanning 10 years, which incorporates investment costs, energy consumption, maintenance, depreciation, and battery replacement. Our analysis reveals that although EVs require a significantly higher upfront investment (€350,000 vs. €183,200), their lower operational and maintenance costs result in a break-even point around year 8. When accounting for a €50,000 battery replacement in year 6, the total 10-year cost of the EV remains lower (€431,769 vs. €450,914) than the diesel vehicle, resulting in a net saving of €19,145. The study emphasizes the significance of local energy prices and service structures in assessing fleet electrification. While the findings are based on Hungarian data, the proposed methodology can be adapted internationally to support data-driven decision-making in sustainable waste logistics.