The environmental issue of single-use plastic is extremely discussed due to waste accumulation and the consumption of non-renewable resources. This study aims to investigate the properties of bioplastic compared to petroleum-based plastic. Two stages of stretch blow molding were used to fabricate polyethylene terephthalate (PET) and bio-polyethylene terephthalate (Bio-PET) bottles. The shelf life extension of chili sauce paste stored in PET and Bio-PET containers with an oxygen scavenger at 45 ℃ in an accelerated condition was investigated. After twelve weeks, the chili sauce paste stored in the container bottle was observed. PET and Bio-PET bottles without oxygen scavengers were also determined as a control for comparison. The result showed that both PET and Bio-PET bottles with oxygen scavengers could prolong the quality of chili sauce paste similarly, meaning that PET could be replaced by Bio-PET as a chili sauce paste container. Other properties, such as thickness gauge, color, leak test, drop test, and close-open force of the container bottle, were also verified to check the product quality standard.
This paper investigates the transformative role of Artificial Intelligence (AI) in enhancing infrastructure governance and economic outcomes. Through a bibliometric analysis spanning more than two decades of research from 2000 to 2024, the study examines global trends in AI applications within infrastructure projects. The analysis reveals significant research themes across diverse sectors, including urban development, healthcare, and environmental management, highlighting the broad relevance of AI technologies. In urban development, the integration of AI and Internet of Things (IoT) technologies is advancing smart city initiatives by improving infrastructure systems through enhanced data-driven decision-making. In healthcare, AI is revolutionizing patient care, improving diagnostic accuracy, and optimizing treatment strategies. Environmental management is benefiting from AI’s potential to monitor and conserve natural resources, contributing to sustainability and crisis management efforts. The study also explores the synergy between AI and blockchain technology, emphasizing its role in ensuring data security, transparency, and efficiency in various applications. The findings underscore the importance of a multidisciplinary approach in AI research and implementation, advocating for ethical considerations and strong governance frameworks to harness AI’s full potential responsibly.
Purpose: This research aims to unravel the intricate dynamics that connect economic status with individuals’ engagement in dance training institutes. Focusing on the affordability of classes, access to resources, awareness, cultural background, and geographic location, the study seeks to provide a nuanced understanding of how economic considerations influence various facets of engagement within the dance community. Method: Conducted through 13 semi-structured interviews, this research adopts a qualitative approach to explore the multi-faceted relationships between economic status and dance engagement. Thematic analysis, structured in three steps, is employed to uncover patterns, themes, and insights within the qualitative data. Findings: The study uncovers a myriad of findings that illuminate the impact of economic factors on dance engagement. Affordability emerges as a significant barrier, influencing access to classes and participation in competitions or performances. Access to resources, including studio space and trained instructors, proves pivotal in shaping individuals’ experiences within dance education. Awareness and exposure play crucial roles, with limited exposure hindering engagement, while the cultural background and geographic location intersect with economic considerations, shaping preferences and opportunities within the dance community. Originality/Significance: This research contributes to the field by offering a focused exploration of economic influences within the dance community. The originality lies in its holistic approach, considering the interconnected nature of affordability, access to resources, awareness, cultural background, and geographic location. From a policy and institutional standpoint, the findings have practical implications, guiding initiatives to address disparities and foster a more accessible and supportive environment within dance training institutes.
This study aims at predicting the interrelationship between among Chat GPT with its six dimensions, tourist’s satisfaction and Chat GPT usage intention as perceived by tourist, and as well as to examine the moderating effect of traditional tour operator services on the relationships between all the variables. Data were collected from 624 tourists. The study hypotheses were tested and the direct and indirect effects between variables were examined using the PLS-SEM. The SEM results showed that Chat GPT’s six dimensions have a positive and significant direct impact on tourist’s satisfaction, and emphasis the moderating role of Traditional Tour Operator Services “TTOS” on the relationship between GPT’s six dimensions and “TS”, and on the relationship between ‘TS” and Chat GPT usage intention. These findings yield valuable insights for everyone interested in the use of IT in the tourism industry, and provide effective strategies for optimizing the use of technological applications by traditional tour operators.
Low integrity is a challenge for any organization. However, most organizations emphasize integrity without explaining what is required of an individual with high integrity. Exhibiting high integrity is necessary for academics; yet, the level of academic integrity remains unclear. Therefore, the purpose of this study is to examine the integrity level of academicians in a Malaysian public university. This paper shares the findings on the level of integrity of academics based on a questionnaire completed by 213 academicians. Data were collected by survey questionnaire and was analyzed using descriptive and inferential statistics. An overall mean score of 9.45 from a possible 10.0 indicated a high level of integrity among academics. The self-evaluation results by academics also demonstrated that they have attained integrity at a high level for their generic task, teaching and learning, research and publications and service for community with a mean score between 9.36 and 9.49. The value with the highest mean score was for “service to community”, whereas the lowest was for “research and publication”. These findings show that the university has successfully instilled values of integrity among academicians. Nevertheless, the university must continue to enhance academic integrity by exploring religiosity. Using Google Scholar, a literature search identified an Islam-based academic integrity model to explain the quantitative findings. Finally, a mixed method approach and involving all universities in Malaysia are recommended to further the findings of this study.
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