The present study highlights a novel concept for estimating the performability of automatic or unattended train operation. This need has been identified through supporting strategies concerning the implementation of Automatic Train Operation (ATO) atop diverse Grade of Automation (GoA). In addressing this challenge, the handling of delay logs supplied by train dispatchers remain a major concern as it can easily spread over the network. This task requires an integrated approach to detect, transmit and resolve difficulties caused by unplanned events. Therefore, we addressed the detectability aspects through the introduction a Joint Cognitive System (JCS) approach relying on a context-aware methodology with the aim to maximize the train driver interaction and resolution of performability issues with technical and safety competency. We proposed a Novelty Detection K-means algorithm for defining with sensory measurements, potential unplanned events and visual image processing for handling track related abnormalities on higher GoA levels. For transmission, we integrated the JCS concept in mainline railway and its context with satellite-based communication. This approach was incorporated into an optimization performability framework for mitigating uncertainty on critical dependability parameters. The validation strategy was exemplified by means of a model-based evaluation compliant with operational and regulatory authority demands.

Mining operations face increasing challenges related to workforce shortages, safety-critical work, and costly equipment downtime(1). Conventional training and maintenance practices are often insufficient to address these constraints, particularly in complex and hazardous operational contexts. Augmented Reality (AR) technologies have demonstrated potential across industrial domains, yet evidence relevant to mining remains fragmented and difficult to operationalise. This study synthesises existing empirical research on AR applications for training and maintenance, focusing on their effectiveness and practical readiness for mining-related contexts. A systematic literature review was conducted covering peer-reviewed journal publications from 2015 to 2025, resulting in 54 studies. The analysis focused on four dimensions: performance outcomes (e.g., task time, errors), learning effects (e.g., retention, transfer), human factors (e.g., workload, usability), and implementation readiness (e.g., acceptance, integration constraints). A structured narrative synthesis was used to address heterogeneity in study designs and outcome measures.

The findings indicate that AR systems can improve procedural accuracy, learning outcomes, and task performance, particularly for complex, unfamiliar, and safety-critical tasks. Evidence also suggests that AR-supported learning can lead to durable competence development rather than short-term tool dependence. However, benefits are task- and context-dependent, and conventional methods may remain preferable for simple or routine activities. Device modality significantly influences effectiveness, usability, and acceptance. Key barriers to large-scale deployment include environmental robustness, ergonomics, complexity of content authoring, system integration, and limited evidence on long-term reliability and safety impacts. Overall, the study suggests that AR should be implemented as a socio-technical intervention.

While technology provides the foundation for economic efficiency in manufacturing industries, human capital and knowledge are also critical for creating new knowledge for manufacturing. Previous studies have focused extensively on the integration and collaboration of business functions such as manufacturing and human resources, particularly on finding the talent required in the digital transformation process. The present study aims to investigate the level of readiness in organisations based on both human and technological factors related to digital transformation. It also presents the most significant factors essential to establishing effective collaboration between human and technological aspects. In general, we question how organisations should ensure effective digital transformation by considering the optimum partnership between human and technological factors.

Following a comprehensive literature review, detailed mixed-method research was conducted to study the factors affecting digital transformation readiness identified in the literature review. Seventy professionals with experience and exposure to digital transformation responded through a questionnaire. The data were analysed based on Structural Equation Modelling (PLS-SEM). Interviews conducted with nine experts were analysed using Thematic Modelling. The results showed that the level of existing smart infrastructure, change management and communication, knowledge, skills and abilities, leadership and culture are the factors that primarily influence readiness. It was also revealed that the level of innovation adoption, support and engagement, and efficiency of technology have minimal influence on the success of transformation.

The growing reliance on AI-powered EdTech solutions has prompted educators at all levels to rethink teaching and learning methodologies. This shift has fostered a renewed partnership among teachers, students, and society, repositioning AI from a passive support tool into a proactive agent in the classroom. This transformation calls for teachers to exercise leadership and judgement in guiding students’ use of AI, emphasising both responsible practices and ethical considerations within their broader socio-cultural contexts. To harness this potential, we leveraged AI-based solutions within the AECT academic association to reinterpret UNESCO’s four foundational pillars of learning, thereby impacting the broader educational community. This initiative underscores literacy in educational communities emerging from intra-national and international inequity. Hence, it is imperative to examine the exigency of fundamental rights in relation to ethics and norms to uphold the innovative opportunities of AI in education globally. In this regard, this study connects the Pedagogical AI-Tact concept to bridge the gap between theory and practice, fostering both interest and ethical engagement across diverse educational communities. This study valuably upholds Margaret Mead’s proposal that every child deserves universal educational rights, a principle in harmony with justice and freedom.

The metaverse is an emerging technological shift that enhances collaboration, telepresence, and decision-making, and can revolutionise industrial maintenance practices. While immersive technologies, such as Extended Reality (XR) encompassing Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), are widely applied in domains like gaming, healthcare, and education, their adoption in industrial workflows remains limited. Its development and implementation carry challenges, especially from a Human-System Interaction (HSI) perspective. The purpose of this research is to understand the key technological issues and challenges associated with the implementation and use of the metaverse in industrial maintenance from an HSI perspective. This study employs a structured, systematic literature review focusing on the metaverse, as enabled by immersive technologies, in the context of industrial maintenance. The reviewed literature was analysed using thematic qualitative analysis to identify recurring HSI-related challenges and to develop a taxonomy categorising these challenges. The analysis resulted in a taxonomy comprising seven key challenge categories: usability, data management, accessibility, user experience (UX), technological performance, environmental and contextual awareness, and trust and transparency. The findings highlight UX as the core factor influencing adoption, as most challenges directly or indirectly impact user experience. The findings indicate that addressing these challenges can enable intuitive, transparent, and reliable metaverse systems tailored to industrial needs. However, advancing the industrial metaverse will require an interdisciplinary approach that combines engineering, human factors, data science, and design to deliver systems that are both technologically advanced and human-centred.

Retaining skilled workers in the mining industry is a significant challenge, particularly for maintenance personnel. This study examines the challenges and strategies associated with recruiting, training, and retaining mining maintenance workers across various roles, including technicians, mechanics, engineers, subcontractors, and researchers. The research investigates how these issues manifest differently for each maintenance role and explore implications for work system design. Five interviews were conducted with relevant personnel, and five workshops (42 participants) were held with electricians, mining vehicle operators, mining machinery operators, and engineers. The study reveals role-specific challenges and their implications for work system design, aligning with Carayon’s Systems Engineering Initiative for Patient Safety (SEIPS) model. Key findings indicate that technicians and mechanics face challenges in remote work locations and physically demanding tasks, necessitating improved onsite living conditions and safety training. Engineers struggle with limited career progression opportunities, highlighting the need for clear advancement pathways and continuous learning programs. Subcontractors experience integration and job security issues, requiring better communication and engagement strategies. Researchers encounter difficulties bridging the gap between academic knowledge and practical application, emphasising the importance of industry-academia partnerships. The study proposes tailored strategies for each role, including enhanced training programs, flexible work arrangements, and improved employee value propositions. Additionally, it suggests implementing data-driven recruitment processes, mentorship programs, and crosstraining initiatives to address role-specific challenges. These findings have significant implications for work system design in the mining industry, emphasising the need for adaptable, role-specific approaches to workforce management to improve recruitment success and employee retention across all maintenance roles.

Combat pilots are responsible for ensuring the best they can towards their service and mission accomplishment. The operation of key cognitive determinants mediates between antecedent processes including actual abilities and anticipated fulfilment of future outcomes. In assessing the vocational development construct of combat pilots, we have underlined the limitations of their perceived abilities and belief enacting self-efficacy and response to relevant task information from the environment, both spatial and temporal. The appraised cognitive determinants engaged in information processing were essentially tied for expressing subjective states of knowledge, feelings, emotions and health threat perceived with a conscious experience. We externalized their subjective states by showing mental health difficulties in the demanding high-stakes environment of air combat.

Emphasis on Artificial Intelligence (AI) development has too often been used as a way to justify prime instinct needs. These changes have been expressed in terms of humanized elements driven by emotional conflicts concealed unconsciously. Hence, we explore potential AI threat scenarios on subliminal persuasion breaking into the mind, constantly seeking positivity and security. This state inherent of the individual psyche raises ethical concerns about manipulation and deception, particularly in advertising and marketing. The ubiquity of AI online and its propensity to intrude on people’s lives have both perpetrated profound and lasting effects on psychological and physical health. Hence, online experiences have been examined in an orderly risky give and risky take form. This designation, influencing real life decisions with the pretense of seeking harmony beyond the field of being initially focused on the self, can expand to encompass a broader perspective on reality. In practice, it can broaden people’s perspectives and shape their everyday choices. In this new reality, a new self is formed, affirming all that is conceived by fostering practical onlife relations. Conversely, subliminal manipulation compels the self-attaining happiness or misery between free and constructed reality. This evidence suggests that subliminal stimuli can mask the motivational interdependency of users’ behaviors with subsequent deliberation of conscious responses.

Intelligent machines (IMs), which have demonstrated remarkable innovations over time, require adequate attention concerning the issue of their duty–rights split in our current society. Although we can remain optimistic about IMs’ societal role, we must still determine their legal-philosophical sense of accountability, as living data bits have begun to pervade our lives. At the heart of IMs are human characteristics used to self-optimize their practical abilities and broaden their societal impact. We used Kant’s philosophical requirements to investigate IMs’ moral dispositions, as the merging of humans with technology has overwhelmingly shaped psychological and corporeal agential capacities. In recognizing the continuous burden of human needs, important features regarding the inalienability of rights have increased the individuality of intelligent, nonliving beings, leading them to transition from questioning to defending their own rights. This issue has been recognized by paying attention to the rational capacities of humans and IMs, which have been connected in order to achieve a common goal. Through this teleological scheme, we formulate the concept of virtual dignity to determine the transition of inalienable rights from humans to machines, wherein the evolution of IMs is essentially imbued through consensuses and virtuous traits associated with human dignity.