This study explores the complex dynamics of handling augmented reality (AR) data in higher education in the United Arab Emirates (UAE). Although there is a growing interest in incorporating augmented reality (AR) to improve learning experiences, there are still issues in efficiently managing the data produced by these apps. This study attempts to understand the elements that affect AR data management by examining the relationship between the investigated variables: faculty readiness, technological limits, financial constraint, and student engagement on data management in higher education institutions in the UAE, building on earlier research that has identified these problems. The research analyzes financial constraints, technological infrastructure, and faculty preparation to understand their impact on AR data management. The study collected detailed empirical data on AR data management in UAE higher education environments using a quantitative research methods approach, surveys. The reasons for choosing this research method include cost-effectiveness, flexibility in questionnaire design, anonymity and confidentiality involved in the chosen methods. The results of this study are expected to enhance academic discourse by highlighting the obstacles and remedies to improving the efficiency of AR technology data management at higher education institutions. The findings are expected to enlighten decision-making in higher education institutions on maximizing AR technology’s benefits for improved learning outcomes.

This study aimed to examine the compliance of post-disaster emergency assembly areas with their planning criteria in the Battalgazi district of Malatya province. This district is one of the settlements that was most affected by the two big earthquakes that occurred in Türkiye on 6 February 2023. The emergency assembly areas were evaluated qualitatively based on the criterion of “appropriateness”, with the sub-variables of “usability”, “accessibility”, and “safety”. They were also evaluated quantitatively based on the criterion of “adequacy” with the sub-variable “per capita m²”. There are a total of 103 neighborhoods in the district. However, there are only eight emergency assembly areas in total within its boundaries. According to the results of this study, only 7.5% of the current population of the district resides within 500 m of the emergency assembly areas. The fact that four emergency assembly areas (Hürriyet Park, Şehit Kemal Özalper High School, the Community Garden, Battalgazi Municipality) are situated next to each other and there are emergency assembly areas in only six of the 103 neighborhoods within the municipal boundaries shows that were significant problems in the decisions made regarding their locations. In addition, it was determined that there were disadvantages in terms of accessibility and usability within the criterion of appropriateness, while there were some positive aspects in terms of safety. When examined with regard to the criterion of adequacy, it was determined that the emergency assembly areas at Mişmiş Park, the Community Garden, Battalgazi Municipality, and Şehit Kemal Özalper High School were most adequate, while the emergency assembly areas at Hürriyet Park, Fırat Neighborhood Mukhtar, Nevzat Er Park, and 100 Yıl İmam Hatip Secondary School were least adequate.

This paper critically reviews the prevailing generalizations in current research on Generation Z (Gen-Z) travel behavior. While various studies have characterized Gen-Z’s transportation preferences as leaning towards sustainable and technology-integrated modes of transport, this paper argues that the findings are largely based on observations from developed countries and may not accurately reflect behavior in developing countries. This paper is written using a narrative literature study approach. Through a comprehensive literature review, the paper highlights the differences in Gen-Z travel patterns across different geographical regions, emphasizing the need for context-specific analysis. The paper addresses often overlooked factors such as economic limitations, infrastructure challenges, and cultural nuances that shape mobility choices. The aim is to dissect the cohort effect and look at its validity across different socio-economic landscapes through existing literature. As such, the paper provides nuanced insights into the heterogeneity of Gen-Z travel behavior and suggests cautioning against over-generalization, as well as advocating for a more localized approach in transportation policy and planning. The paper also encourages similar research in developing countries to gain a more comprehensive understanding of Gen-Z travel behavior globally.

Rapid urban expansion gives rise to smart cities which pose immense logistical and supply chain challenges. The COVID-19 pandemic transformed the holistic system identified by Zhao et al. in 2021. The system encompasses logistics and supply chain integral to the concept of smart cities, with a focus on sustainability. This transformation requires an in-depth study on challenges of a common framework of policies for smart cities in countries comprising the Organisation for Economic Cooperation and Development (OECD). The study employs an extensive literature analysis for the period 2020–2022. an approach which contextualizes the model. The model identifies the causes, impact, and spillovers of new trends in logistics and supply, including the sustainability of adopted technologies. The study includes the variables involved, and barriers to creating a shared model. The results reveal that the two elements affecting the supply chain and transport in smart cities are Industry 4.0 and 5.0 technologies supporting specific sectors. The resilience of small and medium-sized enterprises positively impacts the sustainability of large urban centres. The study presents both factors that help and hinder the adoption of environmental, social, and economic sustainability technologies.

The use of autonomous weapons systems (AWS) has led to several opposing legal opinions regarding their violations of international law. The responsibility of the state, individuals, and corporations as producers, designers, and programmers is all being taken into consideration. If the decision to kill humans without “meaningful human control” is transferred to computers, it would be hard to attribute accountability for the actions of AWS to their corporations. Consequently, this means that corporate actors will enjoy impunity in all cases. The present paper indicates that the most significant problem arising from the use of AWS is the attribution of responsibility for its violation. Corporations are not subject to liability for the legitimate use of weapons under international law. The main problem with corporate responsibility, according to article 25 (4) of the Rome Statute, is that the provision only relates to individual criminal responsibility and that the ICC shall only have jurisdiction over natural persons. Nevertheless, corporations may be held accountable under aspects of international law. The paper proposes a more positive view on artificial intelligence, raising corporations’ accountability in international law by historically linking the judging of business leaders. The article identifies aiding and abetting as well as co-perpetration as the two modes of accountability under international law potentially linked to AWS. The study also explores the main ambiguity in international law relating to corporate aiding and abetting of human rights violations by presenting the confusion on determining the standards of these 2 modes of liability before the ICC and International ad doc Tribunal. Moreover, with the new age of war heavily dependent on AI and AWS, one cannot easily and precisely ascertain who must be held accountable for war crimes because of the unanticipated facts in decision-making combined with the aiding or abetting of violations of international law. International law prioritizes the goal of ending impunity for the individual and largely neglects the need to achieve the same goal for corporate complicity. In sum, progress to regulate the use of AWS by corporate actors could be enormously helpful to the cause of ending impunity.

Resisting the adoption of medical artificial intelligence (AI), it is suggested that this opposition can be overcome by combining AI awareness, AI risks, and responsibility displacement. Through effective integration of public AI dangers and displacement of responsibility, some of these major concerns can be alleviated. The United Kingdom’s National Health Service has adopted the use of chatbots to provide medical advice, whereas heart disease diagnoses can be made by IBM’s Watson. This has the ability to improve healthcare by increasing accuracy, efficiency, and patient outcomes. The resistance may be due to concerns about losing jobs, anxieties about misdiagnosis or medical mistakes, and the consciousness of AI systems drifting more responsibility away from medical professionals. There is hesitancy among healthcare professionals and the general public about the deployment of AI, despite the fact that healthcare is being revolutionised by AI, its uses are pervasive. Participants’ awareness of AI in healthcare, AI risk, resistance to AI, responsibility displacement and ethical considerations were gathered through questionnaires. Descriptive statistics, chi-square tests and correlation analyses were used to establish the relationship between resistance and medical AI. The study’s objective seeks to collect data on primary and public AI awareness, perceptions of risk and feelings of displacement that the professionals have regarding medical AI. Some of these concerns can be resolved when AI awareness is effectively integrated and patients, healthcare providers, as well as the general public are well informed about AI’s potential advantages. Trust is built when, AI related issues such as bias, transparency, and data privacy are critically addressed. Another objective is to develop a seamless integration of risk management, communication and awareness of AI. Lastly to assess how this comprehensive approach has affected hospital settings’ ambitions to use medical AI. Fusing AI awareness, risk management, and effective communication can be used as a comprehensive strategy to address and promote the application of medical AI in hospital settings. An argument made by Chen et al. is that providing training in AI can improve adoption intentions while lowering complexity through the awareness of AI.