The efficiencies and performance of gas turbine cycles are highly dependent on parameters such as the turbine inlet temperature (TIT), compressor inlet temperature (T1), and pressure ratio (Rc). This study analyzed the effects of these parameters on the energy efficiency, exergy efficiency, and specific fuel consumption (SFC) of a simple gas turbine cycle. The analysis found that increasing the TIT leads to higher efficiencies and lower SFC, while increasing the To or Rc results in lower efficiencies and higher SFC. For a TIT of 1400 ℃, T1 of 20 ℃, and Rc of 8, the energy and exergy efficiencies were 32.75% and 30.9%, respectively, with an SFC of 187.9 g/kWh. However, for a TIT of 900 ℃, T1 of 30 ℃, and Rc of 30, the energy and exergy efficiencies dropped to 13.18% and 12.44%, respectively, while the SFC increased to 570.3 g/kWh. The results show that there are optimal combinations of TIT, To, and Rc that maximize performance for a given application. Designers must consider trade-offs between efficiency, emissions, cost, and other factors to optimize gas turbine cycles. Overall, this study provides data and insights to improve the design and operation of simple gas turbine cycles.

Interdependence between the United States (U.S.), European Union (EU) and Asia in the semiconductor industry, driven by specialization, can serve as a preventive measure against disruptions in the global semiconductor supply chain. Moreover, with rising geopolitical tensions, the cost-intensive nature of the semiconductor industry and a slowdown in demand, interdependence and partnership provide countries with opportunities and benefits. Specifically, by analyzing global trade patterns, developing the Interdependence Index within the semiconductor market, and applying the Grubel-Lloyd Index to the U.S., the EU, and Asian countries from 2011 to 2022, our findings reveal that interdependence enhances regional semiconductor supply chains, such as the establishment of semiconductor foundries in the U.S., Japan, and the EU; reduces dependence on a single supplier, such as the U.S. distancing from China; and increases market share in different semiconductor segments, as demonstrated by Taiwan in automobile chips. The evidence indicates that China heavily depends on foreign sources to meet its semiconductor demand, while Taiwan and South Korea specialize as foundry service providers with lower Interdependence Index values. The U.S., with a robust presence in semiconductor manufacturing and design, has a moderate dependence on semiconductor imports, whereas the EU demonstrates a higher level of interdependence because it lacks semiconductor foundries. The stage-specific analyses indicate that the U.S. and the EU rely on Asia for semiconductor devices, while China and Taiwan have a higher dependence on American intermediate inputs and European lithography machines.

Edible cutlery is a safe alternative that, if adopted, can act as a panacea to plastic pollution. Consumers who believe in a lifestyle of health and sustainability (LOHAS) can motivate others by taking the lead in this direction. This study has explored the psychological variables associated with LOHAS consumers in conjunction with the product attributes of edible cutlery to check whether these variables can influence lifestyle of health and sustainability (LOHAS) consumers to adopt edible cutlery. An empirical study on 210 LOHAS consumers using Partial Least Squares Structure Equation Modelling (PLS-SEM) and Importance Performance Matrix Analyses (IPMA) showed that social consciousness and subjective norms motivate them to adopt edible cutlery in restaurants. This finding has an implication for hospitality businesses using edible cutlery that can target LOHAS consumers with strategies that affect their social consciousness and subjective norm belief for better adoption intentions.

The purpose of this study was to assess rural students’ computational thinking abilities. The following proofs were observed: (1) Students’ abstraction affected algorithmic thinking skills; (2) Students’ decomposition influenced algorithmic thinking skills; (3) Students’ abstraction impacted evaluation skills; (4) Students’ algorithmic thinking affected evaluation skills; (5) Students’ abstraction impacted generalization skills; (6) Students’ decomposition impacted generalization skills; (7) Students’ evaluation affected generalization skills. Gender differences were observed in the relationship among the computational thinking factors of junior high school students. This included the abstraction-generalization skills; evaluation-generalization skills; and decomposition-generalization skills relationships, which were moderated by the gender of the students. 258 valid surveys were collected, and they were utilized in the study. Conducting the descriptive, reliability, and validity analyses used SPSS software, and the structural equation modeling (SEM) was also conducted through Smart PLS software to assess the hypothetical relationships. There were gender disparities in the correlation among computational thinking components of the junior high school students’ studying in rural areas. Research has shown that male and female students may have different abstractions, evaluations, and generalizations related to computational thinking, with females being more strongly associated than males in non-programming learning contexts. These results are expected to provide relevant information in subsequent analyses and implement a computational thinking curriculum to overcome the still-existing gender gaps and promote computational thinking skills.

Universities play a key role in university-industry-government interactions and are important in innovation ecosystem studies. Universities are also expected to engage with industries and governments and contribute to economic development. In the age of artificial intelligence (AI), governments have introduced relevant policies regarding the AI-enabled innovation ecosystem in universities. Previous studies have not focused on the provision of a dynamic capabilities perspective on such an ecosystem based on policy analysis. This research work takes China as a case and provides a framework of AI-enabled dynamic capabilities to guide how universities should manage this based on China’s AI policy analysis. Drawing on two main concepts, which are the innovation ecosystem and dynamic capabilities, we analyzed the importance of the AI-enabled innovation ecosystem in universities with governance regulations, shedding light on the theoretical framework that is simultaneously analytical and normative, practical, and policy-relevant. We conducted a text analysis of policy instruments to illustrate the specificities of the AI innovation ecosystem in China’s universities. This allowed us to address the complexity of emerging environments of innovation and draw meaningful conclusions. The results show the broad adoption of AI in a favorable context, where talents and governance are boosting the advance of such an ecosystem in China’s universities.

Under the concept of green development, enterprises will face more environmental constraints. Whether government environmental regulation (ER) can effectively promote corporate environmental performance (CEP) has not yet been unified among scholars, and few studies have conducted bibliometric analysis on ER and CEP. Based on the above, this study has three purposes: first, to fill the research gap by analyzing and visualizing 72 articles on ER and CEP through Biblioshiny and VOSviewer; second, to help scholars easily understand the research development and quickly find promising research directions; and lastly, to enable the government and corporate managers gain a more comprehensive view of ER’s impacts on CEP, which can assist in policy making and business management. The research found that: (a) the number of articles and citations in the field is on the rise. China is the most academically influential country in terms of publications, citations, and collaborations. Journal of Cleaner Production is the top-ranked journal. Ramanathan R, Testa F, and Zhang Y are the top three authors. Environmental management, sustainability, and China are the most popular keywords. Collaboration between authors, institutions, and countries is relatively weak and isolated. (b) ER and CEP have three emerging clusters: Climate Change, FDI, as well as Environmental Awareness, and three core clusters: Environmental Management, Data Envelopment Analysis, and Economic Analysis. The evolution of themes shows a trend from decentralized to centralized and then back to decentralized. (c) Future research can take the Regulatory Framework, Green Technological Innovation, and Environmental Management System as breaking points.