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The Metaverse, a virtual reality (VR) space where users can interact with each other and digital objects, is rapidly becoming a reality. As this new world evolves, Artificial Intelligence (AI) is playing an increasingly important role in shaping its development. Integrating AI with emerging technologies in the Metaverse creates new possibilities for immersive experiences that were previously impossible. This paper explores how AI is integrated with technologies such as the Internet of Things, blockchain, Natural Language Processing, virtual reality, Augmented Reality, Mixed Reality, and Extended Reality. One potential benefit of using AI in the Metaverse is the ability to create personalized experiences for individual users, based on their behavior and preferences. Another potential benefit of using AI in the Metaverse is the ability to automate repetitive tasks, freeing up time and resources for more complex and creative endeavors. However, there are also challenges associated with using AI in the Metaverse, such as ensuring user privacy and addressing issues of bias and discrimination. By examining the potential benefits and challenges of using AI in the Metaverse, including ethical considerations, we can better prepare for this exciting new era of VR. This paper presents a comprehensive survey of AI and its integration with other emerging technologies in the Metaverse, as the Metaverse continues to evolve and grow, it will be important for developers and researchers to stay up to date with the latest developments in AI and emerging technologies to fully leverage their potential.

This research highlights the significant impact of robotic exoskeletons on improving industrial operations through the prevention of repetitive strain injuries and increased productivity. Utilizing 3D scanning technology enabled customization of the exoskeleton to fit individual users' an-atomical specifications precisely, enhancing comfort and functionality. The iterative design pro-cess was crucial in refining the exoskeleton, addressing issues like structural weaknesses and sizing problems, leading to the development of prototypes with improved features. Advanced sensors, including flexible capacitive pressure sensors and tactile arrays, allowed for real-time monitoring of user interactions, ensuring optimal pressure distribution and preventing discom-fort. The transition to active support with artificial muscles marks a milestone in wearable robotics development for industrial use, enhancing task efficiency while reducing physical strain on workers. Future research should focus on further optimizing the exoskeleton's design for enhanced comfort and functionality, including refining artificial muscle dimensions and materials, and integrating more advanced control systems for improved adaptability.

The manufacturing industry faces a trend in which employees’ work processes are being redesigned into simple, repetitive tasks that maximize performance and efficiency. This neo-Tayloristic business model reduces social interactions and stifles relationship building, leading to disgruntled employees and raising questions about leaders’ moral obligation as to the mechanisms they use to enhance employees’ performance at work. As an alternative to redesigning work processes, we contend that servant leaders can enhance employees’ overall performance by cultivating positive interpersonal dynamics at work where social connectedness flourishes. Integrating insights from self-determination theory with servant leadership’s moral foundations, we investigate the degree to which servant leadership fosters two elements of a relationally supportive social context, interactional justice climate and coworker support, that facilitate its influence on followers’ intrinsic motivation and, subsequently, their voice and in-role performance. Temporally-separated data collected from a sample of 296 employees and their supervisors situated in 44 teams yielded results that support our hypotheses. Results underscore the importance of servant leadership cultivating a positive relational context to increase employees’ intrinsic motivation and improve their behaviors at work.

Sustaining operational productivity in the completion of repetitive tasks is critical to many organizations' success. Yet research points to two different work-design-related strategies for accomplishing this goal: specialization to capture the benefits of repetition and variety (i.e., working on different tasks) to keep workers motivated and provide them opportunities to learn. In this paper, we investigate how these two strategies may bring different productivity benefits over time. For our empirical analyses, we use two and a half years of transaction data from a Japanese bank's home loan application-processing line. We find that over the course of a single day, specialization, as compared to variety, is related to improved worker productivity. However, when we examine workers' experience across a number of days, we find that variety helps improve worker productivity. Additionally, we show that part of this benefit results from workers' cumulative experience with changeovers. Our results highlight the need for organizations to transform specialization and variety into mutually reinforcing strategies rather than treating them as mutually exclusive. Overall, our paper identifies new ways to improve operational performance through the effective allocation of work. This paper was accepted by Christian Terwiesch, operations management.

The capabilities of multidimensional mechanomyography (MMG) via PVDF sensors were explored to characterize flexor digitorum superficialis (FDS) fatigue during a 30% MVC, 1 Hz dynamic grasp task—representative of industrial activities yet underexplored in MMG research. This study aimed to delineate fatigue progression, evaluate 30-second micro-rest efficacy, and elucidate gender/hand dominance differences, rationale being their known influence on neuromuscular control and fatigue resistance, with FDS-specific responses in this context unclear. Twenty-four healthy right-handed subjects (12 males, 12 females) completed the task, with MMG and Borg CR-10 data collected. Significant fatigue was confirmed via 19.7% MVC decline and 15-fold Borg score rise. MMG analysis revealed IMMG reduction, while frequency (e.g., MPF) and nonlinear (e.g., LLE) features showed group effects. Muscle contraction rise time correlated strongly with MVC decline and Borg scores, emerging as a potential fatigue indicator. Females exhibited greater MVC reduction, higher Borg scores, and unique sample entropy responses; non-dominant hands showed faster perceived exertion increases. Micro-rests were insufficient for recovery. These findings clarify MMG dynamics in dynamic fatigue, address gaps in FDS individual variability research, and inform personalized assessment and ergonomic interventions.

Twenty-five years ago, robotics guru Joseph Engelberger had a mission to motivate research teams all over the world to design the ‘Elderly Care Giver’, a multitasking personal robot assistant for everyday care needs in old age. In this article, we discuss how this vision of omnipotent care robots has influenced the design strategies of care robotics, the development of R&D initiatives and ethics research on use of care robots. Despite the expectations of robots revolutionizing care of older people, the role of robots in human care has remained marginal. The value of world trade in service robots, including care robots, is rather small. We argue that the implementation of robots in care is not primarily due to negative user attitudes or ethical problems, but to problems in R&D and manufacturing. The care robots currently available on the market are capable of simple, repetitive tasks or colloquial interaction. Thus far, also research on care robots is mostly conducted using imaginary scenarios or small-scale tests built up for research purposes. To develop useful and affordable robot solutions that are ethically, socially and ecologically sustainable, we suggest that robot initiatives should be evaluated within the framework of care ecosystems. This implies that attention has to be paid to the social, emotional and practical contexts in which care is given and received. Also, the political, economic and ecological realities of organizing care and producing technological commodities have to be acknowledged. It is time to openly discuss the drivers behind care robot initiatives to outline the bigger picture of organizing care under conditions of limited resources.

In the search to enhance ergonomic risk assessments for upper limb work-related activities, this study introduced and validated the efficiency of an inertial motion capture system, paired with a specialized platform that digitalized the OCRA index. Conducted in a semi-controlled environment, the proposed methodology was compared to traditional risk classification techniques using both inertial and optical motion capture systems. The inertial method encompassed 18 units in a Bluetooth Low Energy tree topology network for activity recording, subsequently analyzed for risk using the platform. Principal outcomes emphasized the optical system’s preeminence, aligning closely with the conventional technique. The optical system’s superiority was further evident in its alignment with the traditional method. Meanwhile, the inertial system followed closely, with an error margin of just ±0.098 compared to the optical system. Risk classification was consistent across all systems. The inertial system demonstrated strong performance metrics, achieving F1-scores of 0.97 and 1 for “risk” and “no risk” classifications, respectively. Its distinct advantage of portability was reinforced by participants’ feedback on its user-friendliness. The results highlight the inertial system’s potential, mirroring the precision of both traditional and optical methods and achieving a 65% reduction in risk assessment time. This advancement mitigates the need for intricate video setups, emphasizing its potential in ergonomic assessments.

Artificial intelligence (AI) has had a significant impact on the accounting industry by improving accuracy, automating repetitive tasks, and increasing efficiency. In addition to financial automation, auditing, tax compliance, and predictive analysis, advanced AI technologies like machine learning (ML), robotic process automation (RPA), and natural language processing (NLP) are becoming more and more integrated into various accounting functions. These innovations enable businesses to reduce operational costs and help more educated and appropriate decision-making. Despite its benefits, AI still has some disadvantages. Worries about different problems still persist, including the “black box” problem, the lack of transparency in AI decision-making, job displacements, threats to data security, and professional limitations. This report examines the benefits and drawbacks of AI for the accounting industry. Additionally, it looks at how accountants can reevaluate their roles, effectively integrate AI-driven tools, and acquire new skills. Organizations should strike a balance between AI techniques and human expertise in order to maximize the benefits of AI while reducing its challenges. This report addresses the importance of ensuring AI applications adhere to market standards and ethical requirements while supporting compliance.

This article examines how the integration of ChatGPT, Python, and Microsoft Excel can significantly enhance the productivity of medical librarians. These tools provide a powerful framework for automating tasks, processing large datasets, and generating actionable insights. ChatGPT, with its advanced natural language processing, helps automate Python script generation and improve data processing in Excel, streamlining workflows and enabling more precise service delivery. Practical applications demonstrate improvements in information retrieval, data management, and research support. The results show that, despite some integration challenges, these technologies have the potential to greatly elevate the efficiency and effectiveness of librarians in managing healthcare data.

Artificial Intelligence is a rapidly emerging technology which promises profound changes in computer productivity and power, as well as society. By using computer systems to perform tasks involving decision-making hitherto done by humans, it will make many tasks quicker, more accurate, and more influential. On the plus side, AI promises 10 automate repetitive tasks, improve decision-making, and reduce human error. But it might impact interpersonal communication, economics, politics, war fighting, sales and political influence, personal privacy, and other areas in potentially dangerous or malicious ways. Coupled with AI, the mapping of the human genome has given humans unprecedented potential to modify humanity itself. This essay explores some implications of applying AI to DNA modification, highlighting ideas for safeguarding humanity from the malign effects and encouraging the salubrious effects of these powerful new tools in the human toolbox