Abstract:Introduction: To assess the impact of delayed surgery on the prognosis of patients with operable stage non-small cell lung cancer (NSCLC). Methods: A retrospective review of 140 patients with clinical operable stage NSCLC (I, II, IIIA) who underwent curative surgery was conducted. Patients were divided into two groups: those who underwent surgery within 3 months of initial lung tumor detection (non-delayed group, n=82) and those with surgery beyond 3 months (delayed group, n=58). Patient characteristics, reasons for surgical delay, pathology, surgical outcomes, and long-term survival were analyzed. Results: The median time from lung tumor detection to surgery was 13.7 months (range, 3.1 months-12.1 years) in delayed group, and 0.9 months (range, 3 days-2.8 months) in non-delayed group (P＜0.001). The delayed group had a higher proportion of patients at clinical stages I and II, and a lower proportion at clinical stage IIIA as compared with non-delayed group (P=0.046). The incidence of lymphovascular invasion was significantly lower in delayed group (P=0.031). There was no significant difference between groups in terms of pathological upstaging, positive surgical margins, surgical morbidity and mortality, adjuvant treatment, disease-free survival, and overall survival. Conclusions: The prognosis for patients with delayed diagnosis or surgery for NSCLC may not necessarily be worse than for those who receive timely surgery. For these patients, in spite of previous delay, surgical resection remains an important treatment option if lung cancer is assessed as an operable stage disease preoperatively.
Abstract:Industry 4.0, integrating smart manufacturing, digital manufacturing, smart logistics, and industrial automation, has emerged as a core paradigm for industry leaders and scholars advancing sustainable development. This study develops a theoretical model to decode the key drivers influencing enterprises’ intentions to invest in smart manufacturing. The model was empirically analyzed using data from an online survey of 188 R&D and project development professionals from manufacturing and high-tech enterprises in Taiwan. The findings unveil critical insights into sustainable investment strategies for Industry 4.0, offering practical guidance for policymakers, industry stakeholders, and researchers, while paving the way for the future evolution of smart manufacturing.
Abstract:The purpose of this study is to develop a self-assessment scale designed to measure teachers’ competencies in biomimicry teaching. The sample consists of 543 teachers. The validity of the scale was established through an extensive literature review, comparisons with existing instruments, and expert evaluations. The reliability of the scale, as measured by Cronbach’s alpha coefficients, ranged from 0.74 to 0.95. Exploratory factor analysis revealed that the 27 items in the scale were grouped under six factors: attitude towards biomimicry teaching, awareness of biomimicry applications, attitude towards nature, awareness of biomimicry concepts, self-assessment of biomimicry pedagogy, and self-efficacy in biomimicry teaching. This six-factor structure accounted for 70.08% of the total variance. Confirmatory factor analysis indicated that factor loadings ranged from 0.41 to 0.98. The stability of the scale was assessed using the test-retest method. To ensure external validity, a correlation analysis was conducted between the scores of this scale and the Environmental Literacy Scale for Adults, revealing a strong positive relationship. Overall, the Self-Assessment Scale for Biomimicry Teaching has been shown to be a valid and reliable instrument for assessing teachers’ competencies in biomimicry instruction based on their self-perceptions.
Abstract:The aim of the study was to examine the differences in feedback actions and analysis between experienced and inexperienced physical education (PE) teachers. Thirty-three experienced elementary PE teachers (average age: 45 ± 6.41 years; teaching experience: 13.39 ± 9.39 years) and thirty-three inexperienced teachers (average age: 29 ± 7.75 years; teaching experience: 2.78 ± 0.47 years) participated. Data were collected via online surveys using a non-random sampling method, with the questionnaire developed in Microsoft Forms and shared through social media platforms like WhatsApp. The results indicated that no significant differences in feedback usage rates between experienced and inexperienced PE teachers. For verbal feedback related to motion, experienced teachers had an average usage rate of 4.76 ± 0.56, while inexperienced teachers had a similar rate of 4.79 ± 0.48. Visual feedback usage rates were 4.36 ± 0.90 for experienced teachers and 4.55 ± 0.56 for inexperienced teachers, with a significant difference in variance but not in average rates. Combined verbal and visual feedback usage rates were 4.15 ± 0.83 for experienced teachers and 4.00 ± 0.79 for inexperienced teachers. In consequence, the experience level of PE teachers does not significantly affect their feedback usage rates related to motion. Additionally, experienced teachers were found to be more consistent in providing feedback after each action. Both groups recognized the importance of timely and constructive feedback in the learning process.
Abstract:Green energy has become a central focus for power generation around the world. Many companies now require green energy in their production processes, which has led many countries to invest in its development. The Taiwan Strait is considered one of the top locations for offshore wind power in the world. Since 2018, Taiwan has actively promoted the development of offshore wind power. Wind power generation is intermittent and affected by climate variability, which creates significant challenges for its stability and reliability. This study collected wind power generation data from the Changhua Coastal Wind Power Station between May 2021 and June 2022. Climate data, including wind speed and wind direction, were obtained from nearby weather stations and were used to generate monthly and seasonal wind rose diagrams. Statistical analysis indicated that wind power generation in summer represented just 9.81% of the annual total, while winter accounted for 46.00%. A 24-hour generation analysis showed that the highest hourly generation percentage in summer was only 17.82%, while in winter, it consistently remained above 50% during most periods. These findings reveal a notable seasonal and daily variation in wind power generation, mainly influenced by wind speed and direction changes. To minimize the effects of periods with low power generation and to meet the peak electricity demand during the summer, it is crucial to implement large-scale energy storage systems along with effective power dispatch and management strategies. This approach will help ensure grid stability and reliability.
Abstract:This study investigates the impact of industrial agglomeration patterns on green innovation efficiency within the Yangtze River Delta (YRD) urban agglomeration in China. Utilizing panel data from 41 cities spanning 2010 to 2020, the research differentiates between specialized and diversified agglomeration patterns. A super-efficiency SBM-DEA model is employed to evaluate urban green innovation efficiency, incorporating undesirable outputs into the analysis. The findings reveal that specialized agglomeration positively influences green innovation efficiency, particularly in less-developed cities, by lowering production costs and alleviating financing constraints for small and medium-sized enterprises (SMEs) within clusters. In contrast, diversified agglomeration does not significantly improve green innovation efficiency and may even hinder it in noncore and developed cities due to heightened competition and resource inefficiencies. Furthermore, environmental regulation negatively moderates the relationship between both agglomeration patterns and green innovation efficiency. The results emphasize the need to optimize regional industrial structures and promote specialized industrial clusters based on comparative advantages. They also underscore the importance of developing cross-regional coordination mechanisms to enhance the flow of innovation resources and strengthen collaboration among industry, academia, and research institutions. These insights offer valuable guidance for policymakers seeking to refine environmental regulations and industrial policies in urban agglomerations.
Abstract:To solve the network slicing placement problem, the methods based on CNN/RNN were inadequate in handling the randomness of fluctuating channel quality and bandwidth needs for each network slice. While the Monte Carlo Tree Search (MCTS) methodology effectively deals with the unpredictability of each slice’s channel quality and bandwidth request to optimize throughput, it remains time-consuming in finding an optimal solution. The cause is that MCTS relies on a uniform distribution to randomly sample one possible solution, which leads to subpar sampling efficiency. Our objective is to integrate a deep neural network (DNN) to assist MCTS. Specifically, the DNN first analyses the current allocation situation to predict probability distributions for achieving optimizing throughput. MCTS then leverages this DNN-produced probability distribution to pinpoint the best allocation scenario. Experimental results indicate that the performance of DNN-based MCTS with only 50 search iterations surpasses that of the original MCTS with 4,000 search iterations.
Abstract:This study examines the impact of sports event quality on attendees' satisfaction, word-of-mouth (WOM), and return intentions through a chain mediation analysis. Adopting a multidimensional framework, we conceptualize sports event quality across four key dimensions: game quality, interaction quality, outcome quality, and physical environment quality. The study further investigates the mediating roles of satisfaction and WOM in linking event quality to attendees' return intentions, using survey data from 338 participants from running events in Ho Chi Minh City, Vietnam. The findings reveal that event quality significantly enhances satisfaction and WOM, both of which, in turn, positively influence return intentions. Notably, WOM has a more pronounced effect than satisfaction on attendees' likelihood of returning. Additionally, this study underscores the influence of cultural factors in Vietnam, where social proof and peer recommendations play a crucial role in shaping consumer behavior. These insights offer valuable implications for sports event organizers seeking to improve attendee experiences and foster long-term engagement, particularly in emerging markets.
Abstract:The objective of the research is to analyse and explain the impact of the climate phenomenon "El Nino" on the financial profitability of Peruvian fishing and agro-industrial companies, as well as the mitigation of climate risks through the adoption of financial options. The research, which is quantitative and explanatory in nature, is based on the identification of factors affecting the profitability of these companies between 2010 and 2022. The results show the negative impact of "El Nino" on the profitability of the companies, highlighting the need to mitigate these effects through financial options, ensuring business sustainability and the food security of the Peruvian population. In conclusion, the climate phenomenon "El Nino" has a significant negative impact on the financial profitability of Peruvian fishing and agro-industrial companies. This phenomenon emphasizes the urgency of adopting mitigation strategies, such as financial options, so that companies can adapt to climate risks. Implementing these measures not only favours business sustainability but also ensures continuity in production and contributes to food security, strengthening the sector's resilience against extreme climate events.
Abstract:This paper explores the integration of carbon finance, particularly focusing on carbon emission rights pledge financing, as a pivotal instrument in attaining carbon peak targets. This integration is crucial in the context of growth stabilization and structural adjustment. The study identifies key challenges hindering the development of carbon emission rights pledge financing, such as process discrepancies, limited bank engagement, and suboptimal risk management. Addressing these issues, we propose a novel model featuring government intervention. This model employs an evolutionary game approach involving key stakeholders: power companies, carbon emission exchanges, and banks. The objective is to navigate towards a Pareto optimal outcome for the pledging of carbon emission rights. Numerical analyses reveal that appropriate government sanctions can effectively streamline the pledging process. Results show a higher compliance rate from carbon emission exchanges under stringent regulations and increased bank participation under direct government incentives. The study advocates for the establishment of a robust public disclosure mechanism for carbon emission pledge financing and urges the government to enact unified trading regulations. This proposed method not only tackles existing impediments in carbon finance but also significantly contributes to the global pursuit of sustainable development.