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The research intends to explore how Artificial Intelligence (AI) and computing technology can be used to create a more immersive and enjoyable experience within the context of a museum visit. Specifically, the study aims to identify ways in which AI and computing technologies can be leveraged to enrich the visitor’s experience, including by providing interactive content, automated personalization, and real-time access to relevant information. Additionally, the research will assess the potential for AI and computing technology to support improved data analytics and utilization of resources within museums, such as enhanced curation, digital preservation, and increased engagement with audiences. The study employed a qualitative methodology, utilizing interviews with museum professionals and surveys of museum visitors to collect data on visitor experiences. An analysis of the data was conducted to identify current and potential uses of AI and computing technology in art museums. The findings reveal that AI and computing technology are currently being used to facilitate access to collections, tour guidance, and educational activities while emerging technologies show promise for providing even more immersive and personalized visitor experiences. The results of this study suggest that AI and computing technology can play an important role in enhancing the visitor’s museum experience. The research provides recommendations for art museums to leverage AI and computing technology to optimize visitor engagement and foster more meaningful connections with works of art.

This study focuses on the potential application of Artificial Intelligence (AI) in healthcare and hospitals to improve the quality of services for patients. The research objectives include the investigation of existing AI use cases in healthcare, exploration of potential areas in which AI can best be applied, and identification of the challenges to successful AI application. This research utilizes both primary and secondary data sources to investigate the potential of AI in healthcare and hospitals. The primary data is collected through published research papers, technical reports, and industry news to gain an understanding of the current state of AI applications in healthcare. The secondary data is gathered from expert opinions with experienced healthcare professionals such as physicians, hospital administrators, and IT experts to gain insights into existing use cases and potential applications of AI in healthcare and hospitals. The results of the study demonstrate that AI has a significant potential to deliver enhanced outcomes in various aspects of healthcare and hospitals, including diagnosis, treatment, and management. However, the successful integration of AI requires overcoming numerous challenges such as regulatory standardization, privacy protection, and data availability. To foster a positive development of AI in healthcare, it is recommended that healthcare organizations enhance their digital capabilities, enable secure data sharing and collaboration, and use AI tools to deliver a more comprehensive and personalized patient care experience.

PhoP-PhoR, one of the 12 two-component systems (TCSs) that empower M. tuberculosis to sense and adapt to diverse environmental conditions, remains essential for virulence, and therefore, represents a major target to develop novel anti-TB therapies. Although both PhoP and PhoR have been structurally characterized, the signal(s) that this TCS responds to remains unknown. Here, we show that PhoR is a sensor of acidic pH/high salt conditions, which subsequently activate PhoP via phosphorylation. In keeping with this, transcriptomic data uncover that acidic pH- inducible expression of PhoP regulon is significantly inhibited in a PhoR-deleted M. tuberculosis. Strikingly, a set of PhoP regulon genes displayed a low pH-dependent activation even in the absence of PhoR, suggesting the presence of non-canonical mechanism(s) of PhoP activation. Using genome-wide interaction-based screening coupled with phosphorylation assays, we identify a non-canonical mechanism of PhoP phosphorylation by the sensor kinase PrrB. To investigate how level of P~PhoP is regulated, we discovered that in addition to its kinase activity PhoR functions as a phosphatase of P~PhoP. Our subsequent results identify the motif/residues responsible for kinase/phosphatase dual functioning of PhoR. Collectively, these results uncover that contrasting kinase and phosphatase functions of PhoR determine the homeostatic mechanism of regulation of intra-mycobacterial P~PhoP which controls the final output of the PhoP regulon. Together, these results connect PhoR to pH-dependent activation of PhoP with downstream functioning of the regulator. Thus, PhoR plays a central role in mycobacterial adaptation to low pH conditions within the host macrophage phagosome, and a PhoR-deleted M. tuberculosis remains significantly attenuated in macrophages and animal models. Author summary: Virulence-associated PhoP-PhoR of M. tuberculosis represents an attractive target to develop anti-tubercular therapy, but to date, the signal(s) that this regulatory system responds to remains unknown. We discovered that acidic pH and high salt conditions activate PhoP using a PhoR-dependent mechanism. Thus, pH inducible PhoP regulon expression is significantly impacted in a PhoR-depleted M. tuberculosis H37Rv. Our subsequent investigations reveal that homeostatic mechanism of regulation of P~PhoP relies on kinase/phosphatase dual functioning of PhoR, which determines mycobacterial pH homeostasis by controlling the final output of the PhoP regulon. Unexpectedly, global regulatory studies uncover that there can be PhoR-independent mechanism(s) of in vivo activation of PhoP. While probing for a non-canonical mechanism, we demonstrate that the sensor kinase (SK) PrrB phosphorylates PhoP. These results connect two SKs with signal-dependent activation of PhoP. [ABSTRACT FROM AUTHOR]