Heat transfer fluids (HTFs) are critical in numerous industrial processes (e.g., the chemical industry, oil and gas, and renewable energy), enabling efficient heat exchange and precise temperature control. HTF degradation, primarily due to thermal cracking and oxidation, negatively impacts system performance, reduces fluid lifespan, and increases operational costs associated with correcting resulting issues. Regular monitoring and testing of fluid properties can help mitigate these effects and provide insights into the health of both the fluid and the system. To date, there is no extensive literature published on this topic, and the current narrative review was designed to address this gap. This review outlines the typical operating temperature ranges for industrial heat transfer fluids (i.e., steam, organic, synthetic, and molten salts) and then focuses specifically on organic and synthetic fluids used in industrial applications. It also outlines the mechanisms of fluid degradation and the impact of fluid type and condition. Other topics covered include the importance of fluid sampling and analysis, the parameters used to assess the extent of thermal degradation, and the management strategies that can be considered to help sustain fluid and system health. Operating temperature, system design, and fluid health play a significant role in the extent of thermal degradation, and regular monitoring of fluid properties, such as viscosity, acidity, and flash point, is crucial in detecting changes in condition (both early and ongoing) and providing a basis for decisions and interventions needed to mitigate or even reverse these effects. This includes, for example, selecting the right HTF for the specific application and operating temperature. This article concludes that by understanding the mechanisms of thermal degradation and implementing appropriate management strategies, it is possible to sustain the lifespan of thermal fluids and systems, ensure safe operation, and help minimise operational expenditure.

This study explores the factors that affect consumer adoption of reusable packaging in South Korea’s food delivery market. Adopting a mixed-method that includes interviews and an online survey of 137 consumers aged 18 to 30, the analysis, using an ordered probit model, reveals key drivers of the likelihood of switching to food delivery services using reusable packaging. Positive influences include environmental concerns, intention to take action on disposable packaging, willingness to pay extra, and awareness that reusable packaging does not require washing. However, challenges such as hygiene concerns and higher delivery fees deter consumers from switching to reusable package option. Demographic factors like living arrangements and gender show minimal impact. In response to the findings, the study suggests strategic solutions, including a pilot program, to overcome barriers and effectively demonstrate the benefits of reusable containers.

Accurate demand forecasting is key for companies to optimize inventory management and satisfy customer demand efficiently. This paper aims to Investigate on the application of generative AI models in demand forecasting. Two models were used: Long Short-Term Memory (LSTM) networks and Variational Autoencoder (VAE), and results were compared to select the optimal model in terms of performance and forecasting accuracy. The difference of actual and predicted demand values also ascertain LSTM’s ability to identify latent features and basic trends in the data. Further, some of the research works were focused on computational efficiency and scalability of the proposed methods for providing the guidelines to the companies for the implementation of the complicated techniques in demand forecasting. Based on these results, LSTM networks have a promising application in enhancing the demand forecasting and consequently helpful for the decision-making process regarding inventory control and other resource allocation.

This research aims to explore the impact of government policies to promote mass tourism in Bali. Qualitative method with the support of a phenomenological approach and in-depth interviews and FGD. The Butler tourism area life cycle model theory is used to evaluate the impact of tourism on land use and cultural conflict with six stages of destination development, namely exploration, involvement, development, consolidation, stagnation, and decline or rejuvenation. The findings reveal that Bali has experienced all stages of Butler’s model. From 1960–1970, Bali was in the exploration phase, offering tourists authentic experiences. At the beginning of 1970–2000, Bali had entered five phases marked by rapid tourism growth. Now, Bali reached a consolidation phase with a focus on managing tourism quality. Now, Bali is entering a phase of stagnation, facing challenges such as overcrowding and environmental degradation. Bali is at the crossroads between phases of decline and rejuvenation, with efforts to overcome environmental problems and diversify tourism products. This study concludes that mass tourism has significant positive and negative impacts on tourist destinations. Although it can improve the local economy and preserve culture, it can also cause environmental damage and cultural conflict. The Bali government’s policy strategy for the future is to overcome cultural conflicts including tourist education, sustainable tourism development, empowerment of local communities, enforcement of regulations, and intercultural dialogue. The implementation of this policy strategy can be carried out effectively to manage cultural conflicts towards a sustainable Bali tourism future.