Since the Reform and Opening up, GDP of the cities on eastern bank of the Pearl River Estuary in Guangdong Province were higher than the eastern bank cities. Therefore, this article aims to modify the urban gravity model combines it with the entropy weight method to calculate urban quality and applies it to measure the degree of connectivity between cities over the past decades. The research aims to explore whether cities with higher economic output have a greater attraction for surrounding cities, and whether the eastern bank cities can also promote the development of the west. Through detailed data collection and analysis, this essay reveals the dynamic changes of the gravity among cities and its influence factors such as economic, transportation and urban development. The research results indicate that the strongest gravitational force between cities on the east and west banks is between Dongguan and Zhongshan, rather than between Shenzhen and cities on the west bank. This demonstrates that the connection between cities on the east and west banks is primarily constrained by geographical factors, and the geographical location of a city influences on surrounding cities significantly. In particular, Dongguan and Zhongshan play a key role in connecting the eastern and western bank of the Pearl River Estuary, rather than Shenzhen, which is traditionally considered to have the highest economic aggregate. In addition, the study also found that the COVID-19 epidemic has had a significant impact on inter-city communication, resulting in a decline in inter-city gravity in recent years.

Service composition enables the integration of multiple services to create new functionalities, optimizing resource utilization and supporting diverse applications in critical domains such as safety-critical systems, telecommunications, and business operations. This paper addresses the challenges in comparing load-balancing algorithms within service composition environments and proposes a novel dynamic load-balancing algorithm designed specifically for these systems. The proposed algorithm aims to improve response times, enhance system efficiency, and optimize overall performance. Through a simulated service composition environment, the algorithm was validated, demonstrating its effectiveness in managing the computational load of a BMI calculator web service. This dynamic algorithm provides real-time monitoring of critical system parameters and supports system optimization. In future work, the algorithm will be refined and tested across a broader range of scenarios to further evaluate its scalability and adaptability. By bridging theoretical insights with practical applications, this research contributes to the advancement of dynamic load balancing in service composition, offering practical implications for high-tech system performance.

The development of artificial intelligence (AI) and 5G network technology has changed the production and lifestyle of people. AI also has promoted the transformation of talent training mode under the integration of college industry and education. In the context of the current transformation of education, AI and 5G networks are increasingly used in the education industry. This paper optimizes and upgrades the training mode of skilled talents in higher vocational colleges by using its advanced methods and technologies of information display. This means is helpful to analyze and solve a series of objective problems such as the single training form of the current talent training mode. This paper utilizes the principles and laws of industry university research (IUR) collaboration for reference to construct and optimize the talent training mode based on the analysis of the requirements of talent training and the role of each subject in talent training. Then, the ecological talent training environment can be realized. In the analysis of talent training mode under the cooperation of production and education, the correlation coefficients of network construction, environment construction, scientific research funds, scientific research level, and policy support were 0.618, 0.576, 0.493, 0.785, and 0.451, respectively. This showed that the scientific research level had the greatest impact on talent training in the talent training mode of IUR collaboration, while policy support had less impact on talent training compared with other factors. The combination of AI and 5G network technology with the talent training mode of IUR cooperation can effectively analyze the influencing factors and problems of the talent training mode. The hybrid method is of great significance to the talent training strategy and fitting degree.

This empirical inquiry adopts the AutoRegressive Distributed Lag (ARDL) model to meticulously examine the multifaceted interconnections among innovation, globalization, and productivity across a diverse set of 76 nations, encompassing both developed and developing economies. The research employs rigorous econometric techniques within the ARDL framework to discern the short- and long-term effects of innovation and globalization on productivity levels. The findings underscore a robust and statistically significant association between innovation and productivity, as well as a constructive impact of globalization on enhancing productivity. The outcomes underscore the transformative potential of innovation and the facilitating role of globalization in fostering productivity growth. This empirical evidence contributes to the empirical literature by offering a refined understanding of the intricate relationships shaping productivity patterns on a global scale, emphasizing the joint influence of innovation and globalization in driving economic efficiency.

Brazil occupies a prominent position as one of the largest domestic air passenger markets globally. In May 2019, OAG Aviation Worldwide Limited (OAG), a renowned global travel data provider, ranked Brazil as the world’s 6th largest domestic market. This study identifies and meticulously analyses statistical trends in how service levels affect passenger demand on domestic air routes in Brazil. To that end, it employs a panel-data gravity model incorporating service as an instrumental variable. The findings confirm the influence of traditional gravity explanatory variables, while also contributing novel insights into the impact of service levels on domestic routes. The analysis reveals that, while factors such as income and distance play a fundamental role in shaping domestic demand, level of service emerges as a crucial determinant on regional connections. Overall, the statistics suggest growing divergences between Brazilian airlines and regional air transport. Accordingly, substantial changes are necessary in both government policies and the services offered by the airline industry in order to harness the full potential of Brazil’s domestic air transport passenger market and foster regional development.