Global energy agencies and commissions report a sharp increase in energy demand based on commercial, industrial, and residential activities. At this point, we need energy-efficient and high-performance systems to maintain a sustainable environment. More than 30% of the generated electricity has been consumed by HVAC-R units, and heat exchangers are the main components affecting the overall performance. This study combines experimental measurements, numerical investigations, and ANN-aided optimization studies to determine the optimal operating conditions of an industrial shell and tube heat exchanger system. The cold/hot stream temperature level is varied between 10 ℃ and 50 ℃ during the experiments and numerical investigations. Furthermore, the flow rates are altered in a range of 50–500 L/h to investigate the thermal and hydraulic performance under laminar and turbulent regime conditions. The experimental and numerical results indicate that U-tube bundles dominantly affect the total pumping power; therefore, the energy consumption experienced at the cold side is about ten times greater the one at the hot side. Once the required data sets are gathered via the experiments and numerical investigations, ANN-aided stochastic optimization algorithms detected the C10H50 scenario as the optimal operating case when the cold and hot stream flow rates are at 100 L/h and 500 L/h, respectively.

The construction of journalism majors contains rich ideological and political resources. As one of the practical courses, the news interview and writing course is a professional basic course for journalism students. Therefore, for professionals who will undertake journalism in the future, they should not only have the ability to produce and disseminate information, but also shoulder the responsibility of telling Chinese stories, spreading Chinese voices, and delivering Chinese excellent culture. For the teaching of news interview and writing courses, students should be guided in thought, so that they have a sense of home and country, good professional ethics and social responsibility.

This study explores the intricate relationship between emotional cues present in food delivery app reviews, normative ratings, and reader engagement. Utilizing lexicon-based unsupervised machine learning, our aim is to identify eight distinct emotional states within user reviews sourced from the Google Play Store. Our primary goal is to understand how reviewer star ratings impact reader engagement, particularly through thumbs-up reactions. By analyzing the influence of emotional expressions in user-generated content on review scores and subsequent reader engagement, we seek to provide insights into their complex interplay. Our methodology employs advanced machine learning techniques to uncover subtle emotional nuances within user-generated content, offering novel insights into their relationship. The findings reveal an inverse correlation between review length and positive sentiment, emphasizing the importance of concise feedback. Additionally, the study highlights the differential impact of emotional tones on review scores and reader engagement metrics. Surprisingly, user-assigned ratings negatively affect reader engagement, suggesting potential disparities between perceived quality and reader preferences. In summary, this study pioneers the use of advanced machine learning techniques to unravel the complex relationship between emotional cues in customer evaluations, normative ratings, and subsequent reader engagement within the food delivery app context.

This study investigates the factors influencing student satisfaction at higher education institutions in Pathum Thani Province, Thailand. The research uses structural equation modeling (SEM) to analyze the connections among College Reputation, Student Expectation, Perception Value, and Student Satisfaction based on a sample of 660 students. The results indicate that the student population is diverse, with most students enrolled in the Faculty of Business Administration in their first year. The Pearson’s correlation matrix and structural equation modeling (SEM) findings indicate significant positive correlations between the dimensions, emphasizing the crucial influence of College Reputation on both Student Expectation and Student Satisfaction. The goodness-of-fit indices validate the model’s strength, indicating a significant correspondence between the theoretical components and the observed data. This study enhances the comprehension of how student satisfaction changes in Thai higher education and offers practical suggestions for institutional policies to improve student’s educational experiences and achievements. Higher education institutions may create a more fulfilling and effective learning environment by prioritizing reputation improvement, ensuring student expectations match reality, and providing perceived value to improve education quality and equality for Thailand.

This research aims to analyze the relationship between dynamic capabilities and organizational performance, networking, and organizational performance, and to analyze the relationship between spiritual motivation variables and organizational performance. This research method is a quantitative survey. The respondent sampling technique used in this research is a purposive sampling technique, namely samples taken based on certain considerations. Responses to this study came from 567 Organization members of education. The data collection method used in this research is an online questionnaire which provides a written list of questions to respondents. The questionnaire was designed using a Likert scale of 1 to 7. In this study, the data was analyzed using the Partial Least Square (PLS) method with SmartPLS version 3.0 software. The stages of research data analysis are outer model testing, namely integrated validity and reliability testing, inner model testing, and hypothesis testing. The independent variables of this research are dynamic capabilities, collaborative networks, and spiritual motivation and the dependent variable is Organization performance. The results of this research are that dynamic capabilities have a significant and positive influence on organization performance, collaboration networks have a significant and positive influence on organization performance, and motivation has a significant and positive influence on organization performance. The managerial implication of the results of this research is that to improve the performance of educational organizations, managers can apply dynamic capability variables because dynamic variables have been proven to significantly encourage increased organizational performance. Organizations could improve the performance of educational organizations, and managers bu implement collaboration network variables because collaboration networks have been proven significantly can significantly encourage the increased performance of educational organizations. To improve the performance of educational organizations, managers can apply motivation variables because motivation variables have been proven to significantly encourage increased performance of educational organizations.

This study examines the crucial role of digital marketing in promoting sustainable tourism in the villages of Bali. It adopts a mixed methods approach, using qualitative and quantitative data collection and analysis. The qualitative data were obtained from semi-structured interviews with management teams who have experience in implementing digital marketing strategies for village tourism. The interviewees were selected using a purposive sampling technique. The quantitative data were gathered from questionnaires distributed to domestic tourists who visited the villages. The questionnaires measured the tourists’ perceptions of digital marketing as a tool for village tourism marketing. The study found that digital marketing plays a vital role in promoting tourism villages, as most tourists learned about the villages through online media. The study also identified five dimensions of digital marketing, namely website media, social media, search engines, email marketing, and online advertising, which have potential effects on the sustainability of tourism villages. The study conducted statistical tests to examine the effects of 20 indicators of digital marketing on village tourism marketing. The results showed that 16 indicators had a significant positive effect, while four indicators had no effect. These findings suggest that digital marketing is an effective way to market tourism villages and enhance their sustainability.