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With the rapid development of the world city network, the traditional location theory has gradually been disproven, and the advantages of the flow space over the traditional vertical organizational structure are gradually being revealed. Therefore, from corporate branch networks and corporate investment networks, 21 cities in urban agglomerations of Guangdong are taken as case studies for this paper. Furthermore, in this paper, 5 representative types of corporate contact data (catering service, financial service, life service, sports and leisure and accommodation service) are selected, the social network analysis (SNA) method is used to quantitatively analyze the network structure characteristics of urban agglomerations, and a spatial interaction model is constructed to explore the factors influencing. The results indicate that secondary networks have developed in Guangdong. The financial service network is the most complex, followed by the life services, sports and leisure and catering networks. The accommodation service network structure is the simplest. Among all kinds of networks, Guangzhou and Shenzhen have the highest status. The catering and accommodation corporations in Yangjiang in the west have a relatively major external development. Shantou in the east has many branches of various types, while most of the capital exchange in the region is concentrated in Heyuan and Qingyuan in the north. The coefficients of geographical proximity and the urban development level play a significant role in promoting the development of networks. However, administrative capacity limits the attractiveness of origin cities to a certain extent. [ABSTRACT FROM AUTHOR]

Scientific and technological innovation and ecological progress are important forces for China's high-quality development. Nevertheless, the current body of research seldom explores the mutual dependence and evolutionary patterns of the two regional systems when considering both historical and future perspectives. This paper aims to enhance the current theoretical research framework by focusing on the coastal region of China. It analyzes and predicts the co-evolution and space–time distribution process of two systems by constructing a coupled model and a gray prediction model. The results show the following: (1) the coupling and coordinated development level of the two coastal systems has basically reached the stage of good coupling and coordinated development, and the level has increased, but the gap has gradually increased, and Jiangsu and Guangdong have reached the leading level; (2) the spatial distribution in coastal areas is uneven, showing a convex spatial pattern of "high in the middle and low at both ends"; (3) during the forecast period, the overall coupling and coordination level of the two systems will continue to improve, but individual cities still cannot jump out of the development state of slow development processes. With the aim of fostering the harmonious growth of both systems at both regional and national levels, this paper proposes practical recommendations concerning the establishment of a sustainable interaction mechanism, the evolution of the industrial structure towards ecological sustainability, and the economic contribution to scientific and technological innovation. Furthermore, this article serves as a valuable reference for advancing the sustainable development of other nations. [ABSTRACT FROM AUTHOR]

This paper investigates the economic development within the Guangdong-Hong Kong-Macao Greater Bay Area from two perspectives--spatial pattern and influencing factors--to promote coordinated development across the area. This paper employs Moran's I test and local Getis-Ord G statistic from spatial statistics. Furthermore, it constructs a hierarchical spatial econometric model to facilitate empirical investigation. It is found that the overall economic development of the Guangdong-Hong Kong-Macao Greater Bay Area exhibits a "mountain-shaped" spatial pattern of the high-level homogeneous regions with "high-high correlation" and the low-level homogeneous regions with "low-low correlation." The internal difference in economic density is moderate, with an obvious trend of decrease year by year. Economic density shows a significant spatial positive correlation, with the expansion of the scope of areas exhibiting "high-high correlation." The differences in economic density between hotspots and sub-hotspots have decreased, but the economic density of cold spots has failed to keep up with the development of other regions. The difference in factor input density among the influencing factors explains most of the differences in economic density among different regions. The results from the R&D capital investment coefficient indicate that in recent years, the effect of investments in urban scientific and technological innovation factors has been more extensive and uniform among the regions under its jurisdiction, but the spatial spillover effect of innovation factors at both layers is not significantly positive. Apart from the city's location within the Greater Bay Area, the relative location of the jurisdictions within the city equally influences the economic development configuration of the Greater Bay Area. Although economic density in regions adjacent to cities outside the Greater Bay Area is notably lower than in other regions, their growth rate and production efficiency remain on par with other regions. T-test and model results underscore the rapid development of the areas encircling the bay. The coefficient of location dummy variables in areas adjacent to cities in the Greater Bay Area varies among cities. At a particular factor input density, some cities have higher output efficiency in areas contiguous to cities in the Greater Bay Area. This study uniquely adopts low-level city jurisdictions and high-level cities to shape a two-tiered hierarchical dataset with nested geographic units. This innovative approach fully leverages insights from distinct layers, delving into spatial interdependence and interplay across layers. This paper aims to explore the spatial pattern and influencing factors steering economic development in the Guangdong-Hong Kong-Macao Greater Bay Area. In doing so, it aims to identify problems and present pertinent policy recommendations. [ABSTRACT FROM AUTHOR]

As development progresses over time and changes in the environment take place, carbon finance development has become a very interesting research topic for many scholars worldwide. This paper proposes a hybrid MCDM method that combines the distance solutions of the TOPSIS and VIKOR methods. The contribution of this paper combines TOPSIS and VIKOR, incorporating AISM models to obtain the development ranking of Chinese carbon finance pilot cities as related to the Chinese carbon finance development pilot provinces and cities. The conclusion notes that Guangdong and Beijing are the most preferred investment locations for carbon investors. In addition, technological innovation, financial sector development, and an active ETS market can effectively drive the level of local carbon finance. Additionally, the MCDM methodology in this paper provides new ideas in environmental and economic development assessment. [ABSTRACT FROM AUTHOR]

In the face of an increasingly complex and unstable external development environment, enhancing economic resilience has become a key task in the construction of the Guangdong-Hong Kong-Macao Greater Bay Area. This paper analyzes the changes in the economic resilience of the Guangdong-Hong Kong- Macao Greater Bay Area and its constituent cities after the 2008 global financial crisis by virtue of the regional economic resilience assessment method proposed by Martin et al. It constructs an economic connection network for the Guangdong-Hong Kong- Macao Greater Bay Area using the data from corporate headquarters and branches of A-share listed companies to analyze its impact on the economic resilience of the Area. The study reveals the three following conclusions. Firstly, the economic resilience of the Guangdong-Hong Kong-Macao Greater Bay Area generally outperforms the national average level, seeing a rapid boost over the recent years and exceeding the level witnessed during the 2008 financial crisis. However, there are marked disparities in the economic resilience of various cities within the Greater Bay Area, with Shenzhen, Guangzhou, and Dongguan emerging as the most robust in this regard. Secondly, the economic connection network has a positive impact on the economic resilience of the cities in the Guangdong-Hong Kong-Macao Greater Bay Area. Specifically, there is a positive correlation between a city's economic resilience and its centrality in the economic connection network. Such centrality exerts a positive spillover effect on the economic resilience of surrounding cities. Thirdly, from the perspective of industry-specific networks, circulation and service industry networks are more conducive to improving the economic resilience of a city. Given the significant role of the economic connection network in shaping regional and urban economic resilience, it is imperative for the Guangdong-Hong Kong-Macao Greater Bay Area to prioritize ensuring economic development security and enhancing economic resilience, promote the development of the economic connection network, and enhance the network centrality of its constituent cities. This can improve the economic resilience of itself and its constituent cities in an effective manner. [ABSTRACT FROM AUTHOR]

The Guangdong-Hong Kong-Macao Greater Bay Area comprises a regional economy encompassing nine cities located in the Pearl River Delta region, in addition to the two special administrative regions of Hong Kong and Macao. The process of regional economic integration within the Guangdong-Hong Kong- Macao Greater Bay Area traces its origins back to the commencement of China's reform and opening up policies in 1978. It evolves from an initially spontaneous collaborative model, where front-end commercial activities are paired with rear-end manufacturing facilities, to a deliberate form of collaboration underpinned by institutional interventions. This paper examines the fundamental characteristics of the regional economic integration within the Guangdong-Hong Kong-Macao Greater Bay Area. It specifically delves into an extensive analysis of the construction and development of this area. The discussion encompasses four significant theoretical and practical facets that shape the progress of the Greater Bay Area's construction. These aspects include the synchronization of market integration within the Greater Bay Area, the harmonization of institutional frameworks, the convergence of the eastern and western sections of the Pearl River Estuary, and the amalgamation of regional innovations. Furthermore, the paper engages in an exploration of strategies designed to propel the advancement of the Greater Bay Area's development. These strategies encompass collaborative initiatives, such as the joint development of the Shenzhen-Hong Kong adjacent region, the cooperative advancement of Hengqin Island by Zhuhai and Macao, the approach to integrating adjacent areas, and the interlock strategy aiming to connect the two pivotal urban centers of Guangzhou and Shenzhen. [ABSTRACT FROM AUTHOR]

The ICT service industry has become a burgeoning industry at a high and stable speed. Their equitable distribution can improve national and global positive peace. This paper aimed to verify the characteristics of spatio-temporal evolution and its influencing factors in the ICT service industry. Based on the data from 31 Provinces in China from 2015 to 2019, this paper uses location quotient, spatial autocorrelation methods and spatial econometric analysis to explore the development characteristics, evolution and influencing factors of the ICT service industry, respectively. The main results are shown as follows: (1) China's ICT service industry is mainly concentrated in Beijing, Shanghai, Zhejiang, Tibet, and Guangdong, with a trend of specialisation development. They are not only distributed in cities with relatively superior overall development but also those with superior industrial and development carrier elements. Technological relevance, aggregation, and political difference might have an impact on promoting the emergence and development of these industries. (2) ICT service industry is characterised by stable and highly concentrated development. Numbers between three to five significant provinces and types with high-high (HH) and high-low (HL) clusters of local spatio-temporal association kept stable in the period. The HH was in eastern coastal areas, including Zhejiang, Shanghai, Jiangsu, and Shandong, and the HL was in Guangdong in 2015. There is a definite spatial correlation in spatial distribution with constant strengthening. (3) TUR, NDN, MIAT and the area were shown to have a significant role in promoting the ICT service industry, while NW, GDP and ICT Employment were shown to have a significant negative impact on this industry. Correspondingly, two strategies were put forward here: (1) accelerating the inter-provincial networking development of the ICT service industry, and (2) strengthening government policy guidance for the ICT service industry. These outcomes can not only provide a scientific basis and theoretical support for the distribution of strategies and resources for these industries at the theoretical level but also improve resource integration from the national perspective and the efficiency of resource use at the practical level. [ABSTRACT FROM AUTHOR]

The combined effect of tourism economic growth has presented an important catalytic and driving role in modern urban development, especially in China's urban regeneration and industrial restructuring. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is a new attempt by China's government to comprehensively promote a new pattern of economic opening for metropolitan areas, and tourism development has assumed the role of a window to showcase the quality of the GBA's cities to the world. How to promote the coordinated development of tourism and cities is particularly important in shaping new industries and enhancing the quality of urban development in the GBA. This paper constructs an evaluation index system and uses the improved entropy-weighted Topsis model to calculate the Coordinated Level between Tourism and Urban Development (TUDCL) and applies it to analyze the impact of tourism on promoting urban development in the GBA. The study finds that the TUDCL changes steadily from 2000 to 2019 and currently remains at a medium level, with large differences between cities of different levels, and that there is more room to improve the TUDCL of peripheral cities in the GBA such as Huizhou, Jiangmen, and Zhaoqing. When the tourism industry grows to a certain size, it can in turn lead to the synergistic growth of other industries in the city. Different cities need to formulate appropriate optimization policies according to their own industry type, tourism resource endowment, economic openness, and location conditions. This study proposes a scientific and effective evaluation index system to identify the level of coordination between tourism and urban development in the GBA and distils the contribution of different factors and the time sequence of their influence in stages, which is of positive significance in understanding the synergistic relationship between tourism and urban development and provides theoretical reference for planning a quality living circle suitable for living, working, and traveling in the GBA. [ABSTRACT FROM AUTHOR]

The variation in the urban spatial structure (USS) has profound impacts on carbon emissions. Studying the relationship between the two can provide guidance for carbon neutrality strategies and the construction of low-carbon cities in China. However, there is currently a lack of comparative research on the different regions within a province. In this paper, the spatiotemporal evolution of the USS and carbon emissions, at five-year intervals from 2000 to 2020, is investigated in 21 prefecture-level cities in Guangdong Province, China, and the overall relationship of the USS to carbon emissions and their spatiotemporal variations are analyzed by using a two-way fixed-effects model and a geographically and temporally weighted regression model, respectively. The results show that, first, over the past twenty years, the scale of cities has continued to expand, with increasing continuity and aggregation in the built-up areas, while the complexity and fragmentation of their shapes have gradually decreased. Second, the gap in carbon emissions between the Pearl River Delta and other regions in Guangdong shows a trend of first decreasing and then increasing, with high values concentrated in the Pearl River Delta region and the city of Shantou in the east. Third, compared to socio-economic factors, the USS has a more direct and pronounced impact on carbon emissions. Urban expansion and the increased complexity of land patches promote carbon emissions, whereas improving urban spatial continuity and compactness can reduce carbon emissions. Fourth, the dominant spatial structure indicators of carbon emissions differ among the regions of eastern, western, and northern Guangdong and the Pearl River Delta. This study proposes spatial optimization strategies for the low-carbon development of cities in Guangdong Province, providing a new perspective for integrating urban layout and emission reduction policies. [ABSTRACT FROM AUTHOR]

In the context of global environmental changes, the frequency of various disasters and extreme events is increasing, and enhancing urban resilience has become an important guide for current urban development. Previous studies have mainly focused on changes in urban resilience, with less consideration for the impact of spatial spillover effects on urban resilience. Therefore, this paper aims to analyze the temporal and spatial evolution of urban resilience and its spatial spillover effects in Guangdong from 2012 to 2020 based on the urban resilience assessment model, the Getis-Ord Gi* model, and the improved Capello model. The results are as follows: Affected by COVID-19, the urban resilience of Guangdong Province declined from 2019 to 2020, and 42.86% of the cities demonstrated negative growth in their urban resilience. Urban resilience exhibited significant spatially non-equilibrium characteristics among different cities. The urban resilience of the cities in eastern, northern, and western Guangdong, which are the "collapse zone" of urban resilience, was lower than 0.229 from 2012 to 2020. The intensity of urban resilience spillover in Guangdong presented a typical three-level circle structure of "core-subcore-periphery", which decreased from the core circle to the surrounding circle. COVID-19 caused a 27.21% decrease in the total urban resilience spillover in Guangdong from 2019 to 2020. Finally, we identified critical driving factors of urban resilience using the optimal-parameters geographical detector model. This study can provide a scientific reference for the Chinese government to build resilient cities and improve sustainable urban development. [ABSTRACT FROM AUTHOR]

This paper examines how four indicators of economic/financial openness, namely, trade openness, actual tariff rate, financial openness, and investment openness have shaped the world's four major bay area's urban agglomerations. The study considers four key bay areas, New York, Tokyo, San Francisco and Guangdong-Hong Kong-Macao, over the period 2005–2018. Using the panel data fixed effect model analysis, our study finds that: the interaction of comprehensive openness, investment openness, trade openness and comprehensive openness plays a positive role in economic growth, while the actual tariff rate and financial openness play a negative role. In the long run, each bay area should expand their opening-up to the outside world and promote economic growth. [ABSTRACT FROM AUTHOR]

Synergistic development is the only way which must be passed and a key point to achieve high-quality economic development. This paper regards regional synergetic development as a composite system, builds up the evaluation indicator system, and calculates the level of economic synergetic development of Guangdong-Hong Kong-Macao Greater Bay Area Urban Agglomeration, by using the collaborative degree model of composite system. The results show that each subsystem of the composite system has a high degree of order from 2007 to 2019, but compared with Beijing-Tianjin-Hebei urban agglomeration and Yangtze River Delta urban agglomeration, the level of economic collaborative development of Guangdong-Hong Kong-Macao Greater Bay Area urban agglomeration in 2008–2019 is relatively low and has large spatial differences. The main reason is that under the background of "one country, two systems" policy, the institutional differences between Guangdong, Hong Kong, and Macao have not been effectively linked up and synergetic, Greater Bay Area urban agglomeration has not yet formed an organic whole, and the synergy effect of mutual support and promotion is relatively weak. Based on this, we should seize the great historical opportunity of the construction of Guangdong-Hong Kong-Macao Greater Bay Area, accelerate the construction of the mechanism for the synergetic economic development of the three areas, accelerate the establishment of an integrated market, build a reasonable division of labor system and collaborative innovation system, and jointly promote the synergetic economic development of Greater Bay Area. [ABSTRACT FROM AUTHOR]

The classification of urban functional areas plays an important role in urban planning and resource management. Although previous studies have confirmed that different urban functional areas have different morphological structures and Land Surface Temperature (LST) characteristics, these two types of characteristics have rarely been fully integrated and used for functional area classification. In this paper, a new framework for classifying urban functional areas is proposed by combining urban morphological features and LST features. First, metrics are constructed from three levels, namely, building, road and region, which are used to portray urban morphology; LST is retrieved using thermal infrared remote sensing to reflect LST features with four metrics: the average temperature, maximum temperature, temperature difference and standard deviation of temperature. Then, the functional areas are classified into four categories: service/public land, commercial land, residential land and industrial land. A random forest algorithm is used to effectively fuse the features of these two categories and classify the functional areas. The effectiveness of the proposed framework is tested in the study area of Shenzhen City, Guangdong Province. The results show that the combined classification accuracy of the proposed classification method is 0.85, which is 0.26 higher than that of the classification model based on urban morphology and 0.1 higher than that of the classification model based on LST features. The proposed framework verifies that the integration of LST features into urban functional area classification is reliable and effectively combines urban morphology and LST features for functional area classification. [ABSTRACT FROM AUTHOR]

Background: Severe acute respiratory syndrome (SARS) is a form of atypical pneumonia which took hundreds of lives when it swept the world two decades ago. The pathogen of SARS was identified as SARS-coronavirus (SARS-CoV) and it was mainly transmitted in China during the SARS epidemic in 2002-2003. SARS-CoV and SARS-CoV-2 have emerged from the SARS metapopulation of viruses. However, they gave rise to two different disease dynamics, a limited epidemic, and an uncontrolled pandemic, respectively. The characteristics of its spread in China are particularly noteworthy. In this paper, the unique characteristics of time, space, population distribution and transmissibility of SARS for the epidemic were discussed in detail. Methods: We adopted sliding average method to process the number of reported cases per day. An SEIAR transmission dynamics model, which was the first to take asymptomatic group into consideration and applied indicators of R0, Reff, Rt to evaluate the transmissibility of SARS, and further illustrated the control effectiveness of interventions for SARS in 8 Chinese cities. Results: The R0 for SARS in descending order was: Tianjin city (R0 = 8.249), Inner Mongolia Autonomous Region, Shanxi Province, Hebei Province, Beijing City, Guangdong Province, Taiwan Province, and Hong Kong. R0 of the SARS epidemic was generally higher in Mainland China than in Hong Kong and Taiwan Province (Mainland China: R0 = 6.058 ± 1.703, Hong Kong: R0 = 2.159, Taiwan: R0 = 3.223). All cities included in this study controlled the epidemic successfully (Reff<1) with differences in duration. Rt in all regions showed a downward trend, but there were significant fluctuations in Guangdong Province, Hong Kong and Taiwan Province compared to other areas. Conclusion: The SARS epidemic in China showed a trend of spreading from south to north, i.e., Guangdong Province and Beijing City being the central regions, respectively, and from there to the surrounding areas. In contrast, the SARS epidemic in the central region did not stir a large-scale transmission. There were also significant differences in transmissibility among eight regions, with R0 significantly higher in the northern region than that in the southern region. Different regions were able to control the outbreak successfully in differences time. [ABSTRACT FROM AUTHOR]

Copyright of Ecological Science is the property of Ecological Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

While rapid urbanization promotes social and economic development, it exacerbates human outdoor thermal comfort, which increases the risks to human health. This paper uses four thermal comfort indices and multiple satellite observations to explore the urbanization effect on summer heat stress in Guangdong from 1979–2018, a coastal province of China. Two types of thermal comfort index are used here, namely the direct thermal comfort index (Heat Index, HI; Temperature–Humidity Index, THI; Discomfort Index, DI) and the physiological thermal comfort index (Universal Thermal Climate Index, UTCI). We compare the differences in the urbanization effects on the changes in the three direct thermal comfort indices (HI, THI, and DI) and a physiological thermal comfort index (UTCI). The results show that all four thermal comfort indices indicate an overall warming trend. Of them, urban sites show a higher warming trend than rural sites, indicating that heat stress changes are significantly influenced by urbanization from 1979–2018, which is consistent with the effect of urbanization on surface air temperature. However, except for the UTCI, this warming of direct thermal comfort indices affected by urbanization has become insignificant under the regional vegetation greening from 2004–2018 (also consistent with surface air temperature). This is primarily attributed to the different effects of wind speed on the physiological thermal comfort index in urban and rural areas: Decreasing wind speeds in urban areas lead to an increase in UTCI, while wind speeds in rural areas increase instead and decrease UTCI, thus widening the UTCI differences between urban and rural areas. Our results indicate that urbanization has a different effect on thermal comfort indices. When using the thermal comfort index, it is necessary to consider that different thermal comfort indices may bring different results. UTCI considers more factors that affect human heat perception, so it can better describe human outdoor thermal comfort. It also highlights the importance of urban ventilation and urban greenness in mitigating urban outdoor thermal comfort in the sustainable construction of future urbanization in coastal cities. [ABSTRACT FROM AUTHOR]

The Guangdong–Hong Kong–Macao Greater Bay Area urban agglomeration, one of the world's four largest bay area urban agglomerations, occupies an important position in China's national development. In this paper, the expansion hotspot model, an urbanization index, a gravitation model, and a socioeconomic location model are used to explore changes in the characteristics of the urban agglomeration in the Guangdong–Hong Kong–Macao Greater Bay Area. The research results can provide decision support for government urban agglomeration planning. The research reveals the following. (1) In the skeleton maps of the expansion hotspots in the Guangdong–Hong Kong–Macao Greater Bay Area, Jiangmen shows an irregular shape, Shenzhen shows an irregular H-shape, Dongguan and Hong Kong show a shape somewhat between a circle and a star, Zhongshan shows a gourd-shape, and Guangzhou, Foshan, Huizhou, Zhaoqing, and Zhuhai show a polygon shape. (2) In 2000, 2010, and 2018, the urbanization index for the urban agglomerations were 41.78%, 50.87%, and 54.41%, respectively. The level of economic development, household registration policy, and urban planning are important factors affecting the development of urbanization. (3) The city quality and spatial connection strength of urban agglomeration have significant spatial nonequilibrium distribution characteristics. The total city quality of Shenzhen, Hong Kong, and Guangzhou accounted for more than 41.5% of the total city quality of the city cluster at the same time, and that of the east coast of the Pearl River is much stronger than the west coast. (4) There are "faults" in the socioeconomic location of the 11 cities in the urban agglomeration, with significant polarization. The socioeconomic locations of Jiangmen, Huizhou, and Zhaoqing have been below the reasonable socioeconomic location range in the past 20 years. [ABSTRACT FROM AUTHOR]

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Catalyzed by global change and human activities, social and ecosystems are constantly under increasingly dynamic transformations. The Guangdong–Hong Kong–Macau Greater Bay Area (GBA), bordering the South China Sea and located in the Pearl River Delta Plain, is a typical region of complex SESs with rapid socioeconomic development but severe ecosystem degradation. Therefore, based on the relevant data of 11 GBA cities from 2010–2020, this paper constructs an indicator system for assessing land–sea SESs by extracting from three aspects: exposure, sensitivity, and adaptive capacity. Through the construction of a vulnerability assessment indicator system, via the explicit spatial vulnerability indicator calculation model, and vulnerability factor diagnostic model, this study comprehensively analyzes vulnerability levels, spatiotemporal evolution, and SES vulnerability factors. The study found that, since 2010, the SES vulnerability of the GBA has shown an overall trend of alleviation, and the overall geographical distribution of classified vulnerability levels is rather concentrated, with cities around the Pearl River Estuary relatively less vulnerable. The augmentation of per-capita fiscal expenditure, per-capita gross regional product, and decent air quality rate are the critical ingredients to remedy the vulnerability in the GBA. [ABSTRACT FROM AUTHOR]

The coordinated development of urban quality and technology innovation is an important element of China's technology innovation development strategy in the new era. Based on entropy TOPSIS, coupling coordination models, the gravity center and standard deviation ellipse method, the geographic probe, the GWR, and other methods, we explore the spatial variation and influencing factors of the coupling coordination relationship between urban quality and technology innovation in the Guangdong-Hong Kong-Macao Greater Bay Area from 2011 to 2020. It is found that: (1) the spatial distribution of the coupling coordination shows a characteristic of "high in the middle and low in the surroundings," and (2) the level of benign interaction in the central region is becoming more prominent. The center of gravity of coupling coordination moves toward the northeast, and the standard deviation ellipse shows a contraction trend away from the southwest. (3) Agglomeration capacity, human capital, cultural development, and infrastructure can significantly drive the improvement of the coupling coordination of urban quality and technology innovation, and the two-factor influence is significantly increased after the interaction. (4) The feedback effects of the coupling and coordination states of different cities on each factor have significant spatial differences and show the characteristics of hierarchical band distribution. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central China Normal University is the property of Huazhong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper explores the question of extended urbanization by arguing for the need to overcome dualistic views to properly address the political specificities of urbanization in China. To this end, this paper understands state-territorial relations as a process of étatization by drawing on the particular literature on the role of the party-state in urbanization. Through a brief history of Guangdong, it elaborates on the political modalities of territorialization through China's administrative rank system. This has enabled the party-state to mediate the production of urban space. From this, I arrive at the concept of "territorially-nested urbanization", moving beyond limited accounts of hierarchical state powers in Chinese urban studies. Next, from a short periodization of Dongguan's urbanization, the paper exemplifies how a particular mode of territorialization has evolved into tense relationships between the city and towns in the ongoing dilemma of multi-centered versus concentrated direction of urbanization. Based on insights from in-depth fieldwork, the last part of this paper illustrates the contradictory mobilization of village collectives within extended state power through local government, and the development of villagers' politics and activism in contested land transformations. [ABSTRACT FROM AUTHOR]

Sci-tech innovation is an important measure for the Guangdong– Hong Kong–Macao Greater Bay Area to achieve high-quality economic development. theoretically, there is a coupling coordination relationship between sci-tech innovation and high-quality economic development, and coordinating the relationship between the two is beneficial to building the Guangdong– Hong Kong–Macao Greater Bay Area into an international innovation and technology hub and promoting high-quality economic development. At present, the Guangdong–Hong Kong–Macao Greater Bay Area has seen a year-on-year increase in both the level of sci-tech innovation and the level of high-quality economic development, with a sound development trend. Its coupling coordination degree between sci-tech innovation and high-quality economic development has steadily improved from a slightly uncoordinated stage to a primarily coordinated stage, but the overall degree of coordination is still not high, with some gaps from realizing the excellently coordinated stage. From the perspective of spatial distribution, the internal development of the Guangdong-Hong Kong–Macao Greater Bay Area is unbalanced, with obvious differences in development level and coupling coordination degree among cities. e convergence analysis shows that the differences in the coupling coordination degree among the cities in the Guangdong Hong Kong–Macao Greater Bay Area have stabilized after narrowing during the study period. However, the difference among the cities with higher coupling coordination degrees tends to widen in recent years. therefore, necessary measures should be taken to promote the coordination between sci-tech innovation and high-quality economic development in the Guangdong–Hong Kong–Macao Greater Bay Area. [ABSTRACT FROM AUTHOR]

When considering the economic growth of the Greater Bay Area, digital transformation stands out as a crucial catalyst. Given its significance, it is imperative to delve into both the theoretical and empirical aspects of how digital transformation affects the region's position in the global value chain. Theoretical hypotheses are put forward regarding the impact and mechanisms of digital transformation on the global value chain position of the Greater Bay Area based on a global value chain perspective. A three-tier nested input–output table that incorporates the Greater Bay Area is constructed, and trade decomposition and global value chain position measurement models specific to the area are developed for analyzing its current state in terms of global value chain position. Empirical testing was conducted to examine how digital transformation impacts this position. Digital transformation will significantly enhance the position of the Greater Bay Area in the division of global value chains, mainly through enhancing technological innovation transformation capabilities and value added by exports from the Greater Bay Area. Digital transformation within the Greater Bay Area has had a more substantial positive impact than the digital transformation in other provinces in China and digital transformation from foreign sources. In terms of city heterogeneity, it is evident that the global value chain from Hong Kong and Macao has experienced a more significant impact from digital transformation compared to cities in the Pearl River Delta. Therefore, the Greater Bay Area should increase the use of both digital transformation and differentiated use of digital transformation. PRD cities should actively learn from Hong Kong and Macao's forms of digital construction and promote the Greater Bay Area's global value chain status. [ABSTRACT FROM AUTHOR]

• A method based on Neural Network is proposed for provincial-level CO 2 emissions estimation. • An autoencoder is proposed to downscale the provincial-level CO 2 emissions to city-level. • A complete city-level CO 2 emissions inventory of GBA and surrounding cities is complied. • Spatial dependence and agglomeration characteristics of CO 2 emissions are analyzed. • Spatio-temporal heterogeneity of factors affecting CO 2 emissions is investigated. Significant attention has been given to the issue of CO 2 emissions worldwide, especially for China as the largest emitter. Cities, as the main carriers of China's economic development, account for up to 85 % of CO 2 emissions from energy use in the country. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) and surrounding cities play important leading roles in low-carbon development. However, compiling city-level CO 2 emissions is challenging due to the limited availability of data. In this paper, a new idea is proposed by using SSA-BP for estimating provincial-level CO 2 emissions and downscaling provincial-level CO 2 emissions to city-level CO 2 emissions by reconstructing missing values of city-level CO 2 emissions with an autoencoder. This study compiles a city-level CO 2 emissions inventory and conducts a spatio-temporal analysis of CO 2 emissions in the GBA and surrounding cities. The results show that CO 2 emissions exhibit a spatial distribution pattern with spatial dependence. Furthermore, according to the analysis of spatio-temporal heterogeneity, GDP influenced CO 2 emissions the most within the five influencing factors, and the influences of GDP, population, and energy intensity were mainly positive, while the influence of patents was mainly negative, and that of trade was both positive and negative. [ABSTRACT FROM AUTHOR]

In the context of the digital information era, the impact of "The Internet Plus," "Big Data," and other technologies on urban social development has been far beyond any preceding era, under the influence of information technology, urban agglomeration space exhibits a new layout. Based on the search engine data of eleven cities in the Guangdong-Hong Kong-Macao Greater Bay Area from 2012 to 2021, this research constructs the inter-city information network strength linkage matrix to examine the evolution characteristics of city network structure and its driving causes. The results reveal that (1) the overall information linkage strength exhibits a pattern of steadily growing the radiating effect from the leading cities of Guangdong, Shenzhen, and Hong Kong to the surrounding cities, and a closer and more balanced information linkage network is gradually built. (2) Guangzhou-Shenzhen-Hong Kong-Guangdong-Hong Kong-Macao Greater Bay Area information linkage absolute control advantage, four cities Foshan, Dongguan, Zhuhai, Macao regional hub position steadily highlighted. The entire information connection network of the urban agglomerations tends to be flat and polycentric at the same time. (3) The regional core-edge hierarchy is well established, with the four cities of Guangzhou, Dongguan, Shenzhen, and Hong Kong creating a northwest-southeast orientation. The core metropolis regions of Guangdong, Hong Kong, and Macao in the Greater Bay Area increasingly exert a radiation spreading effect to the northeast and southwest. (4) The urban economy, transportation distance, and information infrastructure have substantial effects on the information connection intensity network of urban clusters. [ABSTRACT FROM AUTHOR]

Introduction: The characteristic of human immunodeficiency virus type 1 (HIV-1) is its susceptibility to erroneous replication and recombination, which plays a crucial role in the diverse and dynamic variation of HIV-1. The spread of different subtypes in the same population often leads to the emergence of circulating recombination forms (CRFs). At present, the main recombinant subtypes of HIV-1 in China are CRF07_BC, CRF01_AE, CRF08_BC and B' subtypes, while CRF55_01B has become the fifth major epidemic strain in China after rapid growth in recent years since it was first reported in 2013. In this study, we obtained five nearly full-length genomes (NFLGs) and one half-length genome from five different cities in Guangdong. Here, we focused on analyzing their characteristics, parental origin and drug resistance. Methods: Plasma samples were collected from six HIV-1 infected patients in Guangdong Province who had no epidemiological association with each other. The NFLGs of HIV-1 were amplified in two overlapping segments by the near-terminal dilution method. The positive products were sequenced directly to obtain genomic sequences. The recombinant patterns and breakpoints of the NFLGs were determined using the Simplot software and confirmed by the maximum likelihood trees for segments using the IQ-TREE and BEAST software. The genotypic resistance profiles of the protease reverse transcriptase and integrase were resolved by the Stanford HIV drug resistance database. Results: The six genomes shared highly similar recombinant pattern, with the CRF55_01B backbone substituted by CRF07_BC segments, therefore assigned as CRF156_0755. The evolutionary analysis of the segments showed that CRF07_ BC segments were not clustered with the Chinese MSM variants in the CRF07_ BC lineage. All the five NFLGs were identified with the non-nucleoside reversetranscription inhibitors (NNRTIs) resistance mutation V179E. Discussion: With the accumulation and evolution of recombination between CRF55_01B and CRF 07_BC, the prevalence of more recombinant strains of CRF55_01B and CRF 07_BC may occur. Therefore, it is necessary to strengthen the identification and monitoring of the recombination of CRF55_01B and CRF 07_BC. [ABSTRACT FROM AUTHOR]

In the context of uncertain economic environments urban agglomerations play a crucial role in economic development, reshaping industrial chains and fostering inter-city cooperation. This study employs the Global Production Network (GPN) theory to enhance our understanding of how cities integrate into regions, emphasizing the often-overlooked governmental influence in strategic coupling processes. In examining the evolution of China's smartphone industry within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) this research categorizes 19,599 smartphone companies into five distinct groups. Through analyzing their spatial distribution and geographical linkage the study identifies four strategic coupling modes based on the localization of assets, considering spatial influence and technological complexity along horizontal and vertical dimensions. Structural and institutional elements within these modes are also explored. The research uncovers unique integration patterns among nine cities in the GBA's mobile industry, revealing distinct spatial clusters rooted in technological, resource and innovation factors. Crucially, local policies play a pivotal role. Cities such as Shenzhen and Dongguan emerge as technology hubs, contrasting with Foshan and Zhongshan, which leverage resource advantages. The spatial impact, contingent on specific assets, underscores the necessity for nuanced top-down coupling methods in regional development. Moreover, the study emphasizes the significance of nurturing innovation links, not only between leading companies but also among midstream and downstream enterprises, enhancing cities' strategic coupling capabilities. [ABSTRACT FROM AUTHOR]

Megaregion has emerged as a global urban form, typically based on the polycentric strategy to enhance regional development. How to measure megaregional spatial structure and discriminate different roles of cities has become increasingly important to enrich the knowledge of the formation of a megaregion. Meanwhile, various indices have been used to identify vital nodes in the field of complex network. Which indices, however, are suitable for megaregion analysis remain unsolved. To address this requirement, this study first reviewed the typical indices for identifying vital nodes in the complex network theory, and pointed out that in a weighted city network scenario, weighted degree centrality, hub & authority score, and S-core decomposition (which represent network centrality, connectivity, and structures, respectively) are suitable for analyzing megaregional spatial structures. Then, we explored the city hierarchies and spatial structure in Guangdong Province, China, using the three indices. The hierarchical structure of the weighted city network in Guangdong Province had been identified using S-core decomposition. From the perspective of polycentric structure, Guangzhou and Shenzhen have the strongest node degrees and strength of mobility flows, while the Guangzhou-Dongguan-Shenzhen corridor has been identified via the hub & authority score which is designed to evaluate the connectivity in a weighted network. Moreover, we conducted a comparison analysis of three indices. The findings of this study not only enrich the understanding of city hierarchies and the structure of a megaregion, but also highlight that although various indices are available, they should be applied selectively in accordance with the study context. [ABSTRACT FROM AUTHOR]

The aim of this study is to comprehensively evaluate the economic network patterns and their influencing factors of the Guangdong–Hong Kong–Macao Greater Bay Area (GHMGBA) in China, considering population scale, economic development level, and land-resource endowment. By employing a modified gravity model and a social-network method, we quantitatively analyzed urban agglomeration integrity indices, such as network density, edge–core structure, cohesive-subgroup index, and urban individual index (e.g., centrality degree) of this region, encompassing nine cities in Guangdong Province and two special administrative regions. The results revealed significant changes in the economic network patterns within the GHMGBA over time. Furthermore, the quadratic assignment procedure correlation analysis index was used to identify the various factors affecting the strength of the economic interaction. The findings demonstrated an annual increase in the strength of economic interaction between cities and regions within the GHMGBA over the past 20 years, along with the emergence of a polycentric economic development pattern. The results also suggest that the spatial location and level of economic development are key determinants influencing the strength of economic linkages in this area. This study supports the conclusion that deepening exchanges and cooperation among core cities, bolstering economic development in sub-core cities, and facilitating the construction of an integrated regional transportation network will expedite the process of economic integration. [ABSTRACT FROM AUTHOR]

The imbalance between the population, transportation, and construction is an important factor affecting coordinated regional development in China. Using transportation land area and population data from 2010, 2015, and 2020 in 121 counties (cities and districts) of Guangdong Province, this study analyzes the spatiotemporal changes in transportation land and population structure. It explores the relationship between transportation land and population size changes using exploratory spatial data analysis (ESDA) and decoupling models. Research suggests the following: (1) From 2010 to 2020, the per capita transportation land in various districts and counties of Guangdong Province showed a hierarchical structure of "low center and high periphery". Conversely, the proportion of transportation land to construction land displayed a "high center and low periphery" characteristic. (2) During the same period, the total amount of transportation land in the peripheral areas of the Pearl River Delta was higher than that in the PRD (the Pearl River Delta) and the gap widened each year. Meanwhile, the proportion of transportation land to construction land in the peripheral areas of the Pearl River Delta was consistently higher than that in the PRD. (3) From 2010 to 2015, the relationship between population growth and transportation land in Guangdong Province showed a hierarchical pattern, while from 2015 to 2020, the pattern became more complex, and regional imbalance intensified. The decoupling results of PRD showed weak decoupling and expanding negative decoupling from 2010 to 2020. The peripheral areas of the Pearl River Delta are characterized by strong negative decoupling and expanding negative decoupling. Research has shown that although Guangdong Province is one of the most developed provinces in China, the mismatch between transportation land and population size in economically underdeveloped areas has become increasingly severe, with changes in the provincial population distribution pattern. The decoupling phenomenon between the transportation land and population is very obvious, and the policy of achieving regional balanced development through transportation infrastructure construction needs to be reviewed. [ABSTRACT FROM AUTHOR]

This study investigated the spatiotemporal evolution of economic development in 23 cities across Guangdong Province, Hong Kong, and Macau from 1990 to 2022. The results indicated a general growth trend in overall economic development, with substantial fluctuations in absolute differences and a significant reduction in relative differences. The economic development appeared to be balanced both within and between cities. Spatially, the study revealed an increasing agglomeration effect, evident polarization in economic levels, and a distinct core–periphery structure, with central cities in the Greater Bay Area exerting a growing influence on their peripheries. Nevertheless, the peripheral cities, despite their economic strides, necessitate augmented policy interventions and capital influx to bridge regional chasms. The study's outcomes serve as a foundational reference for sharpening policy decisions, fostering regional amalgamation, and invigorating urban blueprinting and city-to-city synergies. This research provides an in-depth analysis of economic development trends across 23 cities in Guangdong, Hong Kong, and Macau over 32 years. For policymakers, urban planners, and business leaders, the findings present a clearer picture of the region's economic landscape. Notably, while central cities within the Greater Bay Area have become influential economic hubs, surrounding cities still face challenges. These insights suggest a need for more targeted policies and investments, especially in peripheral cities, to promote more uniform growth across the region. By understanding these dynamics, governments and businesses can make more informed decisions that foster city-to-city collaborations and develop better urban and regional strategies. [ABSTRACT FROM AUTHOR]

The citizenization of peasant migrants is key to understanding China's long-term urban-rural imbalance and ongoing rural transformations. The majority of existing literature focused on structural/institutional or agentive/subjective factors, while an integrated perspective examining both structural and agentive factors related to the citizenization process is rarely seen. Borrowing theories from the strategic-relational approach, this paper unfolds the matching and mismatching mechanisms between the policy design and peasant migrants' intentions of citizenization. Drawing on a case study in China's Guangdong Province, this study finds that: (1) citizenization policies prefer to offer citizenship to the new generation of peasant migrants, which matches the age structure of peasant migrants; (2) although municipal governments are prone to attract young peasant migrants with high educational level and strong competitiveness, peasant migrants generally have a relatively low educational level and weak professional training; (3) the high threshold of citizenization in mega-metropolitan and metropolitan cities mismatches peasant migrants' preference towards the first-tier cities. This paper describes the matching and mismatching mechanisms between structure and agency associated with the citizenization of peasant migrants. The policy reflections proposed by this study point towards enhancing nearby urbanization and in situ urbanization, so as to increase the attraction of young peasant migrants by ordinary cities. Besides, this paper calls for the promotion of rural-urban co-governance, making rural revitalization an alternative and supplement to the urbanization driven by rural-urban migration. • The strategic-relational approach is a critical perspective for understanding citizenization. • As a progressive and dynamic process, the citizenization of peasant migrants intersects with local strategies of urbanization. • Governments should realize that ordinary cities are critical places for most peasant migrants to realize citizenization. [ABSTRACT FROM AUTHOR]

As the population and industries continue to gather in cities, such cities face acute shocks caused by various natural disasters and high pressure caused by human interference. The means of accurately assessing and improving the level of urban resilience (UR) to cope with disturbances and shocks, enhance regional resilience, and improve sustainable urban development has become a hot topic. In this study, we constructed an UR assessment framework using "social-economic-institutional-ecological-engineering" to explore the dynamic evolution of spatial and temporal patterns in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China, to reveal the main factors influencing the evolution of this spatial pattern and the strength and interaction mechanisms among such influencing factors and to dynamically simulate the spatial and temporal evolution characteristics in the next 16 years. The results show that from 2000 to 2019, the difference in UR level in the GBA is obvious. Hong Kong and Macao are obviously ahead of other cities, and the comprehensive resilience level of Guangzhou and Shenzhen cities in the mainland is developing rapidly. The difference in per capita consumption capacity, industrial structure optimization, foreign trade vitality, infrastructure support and other factors are the main causes of the spatial differentiation of UR in the GBA. In the future, the UR level of the GBA urban agglomeration will show an overall upwards trend. The three development poles of Guangzhou-Foshan, Shenzhen-Hong Kong, and Zhuhai-Macao have obvious advantages in spatial distribution. The results of the study can enrich regional UR research, and also provide theoretical references to facilitate the high-quality development of the area. [Display omitted] • We constructed a "social-economic-institutional-ecological-engineering" urban resilience assessment framework. • The paper developed an evaluation system for the urban resilience to reveal its spatial and temporal evolution patterns. • The main factors influencing the evolution of the spatial patterns of urban resilience is investigated. • Our results provide a basis for the development of comprehensive management framework for urban resilient. [ABSTRACT FROM AUTHOR]

Background: The latest national survey on the distribution of human parasites in China demonstrated that Guangdong was among the endemic provinces with the highest Clonorchis sinensis infection rates. High-resolution, age- and gender-specific risk maps of the temporal and spatial distributions are essential for the targeted control work. Methods: Disease data on the prevalence of C.sinensis infection from 1990 onwards, either age- and gender-specific or aggregated across age and gender, were collected through systematic review and four large-scale surveys in Guangdong Province. Environmental and socioeconomic variables were obtained from open-access databases and employed as potential predictors. A Bayesian geostatistical model was developed to estimate the C.sinensis infection risk at high spatial resolution. Results: The final dataset included 606 surveys at 463 unique locations for C.sinensis infection. Our findings suggested that following an initial increase and stabilization, the overall population-adjusted prevalence had declined to 2.2% (95% Bayesian credible interval: 1.7–3.0%) in the period of 2015 onwards. From 2015 onwards, moderate and high infection risks were found in the northern regions (e.g. Heyuan and Shaoguan cities) and the southern Pearl River Delta (e.g. Foshan, Zhongshan, Zhuhai and Jiangmen cities), respectively. Age- and gender-specific risk maps revealed that males had a higher infection risk than females, and the infection risk was higher in adults compared to children. Conclusions: Our high-resolution risk maps of C. sinensis infection in Guangdong Province identified the spatial, temporal, age and gender heterogeneities, which can provide useful information assisting tailored control strategies. [ABSTRACT FROM AUTHOR]

In recent times, a new wave of scientific and technological advancements has significantly reshaped the global economic structure. This shift has redefined the role of regional innovation, particularly in its contribution to developing the Guangdong–Hong Kong–Macao Greater Bay area (GBA) into a renowned center for science, technology, and innovation. This study constructs a comprehensive evaluation system for the Regional Innovation Ecosystem (RIE). By applying the coupling coordination degree model and social network analysis, we have extensively analyzed the spatial structure and network attributes of the coupled and coordinated innovation ecosystem in the GBA from 2010 to 2019. Our findings reveal several key developments: (1) There has been a noticeable rightward shift in the kernel density curve, indicating an ongoing optimization of the overall coupling coordination level. Notably, the center of gravity for coupling coordination has progressively moved southeast. This shift has led to a reduction in the elliptical area each year, while the trend surface consistently shows a convex orientation toward the center. The most significant development is observed along the 'Guangdong–Shenzhen–Hong Kong–Macao Science and Technology Innovation Corridor', where the level of coupling coordination has become increasingly pronounced. (2) The spatial linkages within the GBA have been strengthening. There are significant spatial transaction costs in the regional innovation ecological network. In the context of the 2019 US-China trade war, the cities of Jiangmen and Zhaoqing experienced a notable decrease in connectivity with other cities, raising concerns about their potential marginalization. (3) Guangzhou, Shenzhen, and Hong Kong have emerged as core nodes within the network. The network exhibits a distinctive "core–edge" spatial structure, characterized by both robustness and vulnerability in various aspects. [ABSTRACT FROM AUTHOR]

Complex interaction between urbanization and climate change has been showing significant impacts on natural and human ecosystems. Increasing urban flooding and waterlogging are associated with urbanization. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) experiences a rapid and extensive urbanization, leading to intensified land use and cover changes. Concurrently, the frequent occurrence of extreme precipitation events pose great challenges of urban flood control and water resource management to GBA. This research statistically analyzes the spatiotemporal evolution characteristics of precipitation extremes from 1979–2018 which relates to the urbanization in GBA using various statistical methods including the Mann-Kendall test, bivariate Moran's test, and Spearman correlation analyses. The findings indicate that the impervious surface area in GBA exhibited a nonlinear growth trend from 1985–2018, particularly concentrated in the five major cities, i.e., Guangzhou, Foshan, Dongguan, Shenzhen, and Zhongshan. GBA urbanization can be categorized into three stages including Stage I (pre-1990, no urbanization), Stage II (1991–2009, rapid urbanization), and Stage III (2010–2018, slow urbanization). Compared to cities with low urbanization, the highly urbanized areas of GBA, including Guangzhou, Foshan, Zhongshan, and Dongguan, show statistically significant increases in precipitation extremes. The increasing trends of seven extreme precipitation indices show significant positive, spatiotemporal correlations with the change rate of urbanization in GBA. Moreover, the influence of urbanization on precipitation extremes in highly urbanized regions of the GBA is progressively strengthened along with urban development. During the stage of slow urbanization, urbanization contributes to 56.13% of increase in annual precipitation totals in GBA, and its contribution to increases in precipitation extremes ranges from 20–80%. [ABSTRACT FROM AUTHOR]

Background: Since the Non-pharmaceutical Intervention (NPI) by COVID-19 emerged, influenza activity has been somewhat altered. Objectives: The aim of this study was to explore changes in influenza activities in the context of COVID-19 based on the sentinel hospitals/units in Guangdong, southern China. Methods: The surveillance data in influenza-like illness (ILI) were collected from 21 cities in Guangdong between September 2017 and August 2021, while 43 hospitals/units were selected to analyze the predominant types of influenza, population characteristics, and seasonal features by three methods (the concentration ratio, the seasonal index, and the circulation distribution), based on a descriptive epidemiological approach. Results: During the four consecutive influenza seasons, a total of 157345 ILIs were tested, of which 9.05% were positive for influenza virus (n = 14238), with the highest positive rates for both IAV (13.20%) and IBV (5.41%) in the 2018–2019 season. After the emergence of COVID-19, influenza cases decreased near to zero from March 2020 till March 2021, and the dominant type of influenza virus changed from IAV to IBV. The highest positive rate of influenza existed in the age-group of 5 ~ < 15 years in each season for IAV (P < 0.001), which was consistent with that for IBV (P < 0.001). The highest annual positive rates for IBV emerged in eastern Guangdong, while the highest annual positive rates of IAV in different seasons existed in different regions. Furthermore, compared with the epidemic period (ranged from December to June) during 2017–2019, the period ended three months early (March 2020) in 2019–2020, and started by five months behind (April 2021) during 2020–2021. Conclusion: The highest positive rates in 5 ~ < 15 age-group suggested the susceptible in this age-group mostly had infected with infected B/Victoria. Influenced by the emergence of COVID-19 and NPI responses, the epidemic patterns and trends of influenza activities have changed in Guangdong, 2017–2021. [ABSTRACT FROM AUTHOR]

A large number of villages are distributed on the vast land of China. In the course of urbanization in recent decades, plenty of labor, capital and materials have been migrated from rural areas to urban areas, resulting in many problems such as imbalance between urban and rural development and loss of rural vitality. To this end, a rural revitalization strategy has been proposed. Industrial revitalization is an important part of rural revitalization. The convergent development of the primary, secondary and tertiary industries is the only way to achieve industrial revitalization in rural areas in the future. With Jiuling Village, Jiaoling County, Meizhou City, Guangdong Province as the object of study, this paper expounded the necessity of the convergent development of industries, explored the path of industrial convergence of rural areas, and analyzed the supporting system behind it from three aspects of land, finance and grassroots organization construction. [ABSTRACT FROM AUTHOR]

With the rapid development of urbanization, the pollution problem of rivers in cities and towns appears, which seriously affects life quality of residents around rivers. In this paper, rivers in one tourist town of Jieyang, Guangdong is taken as a research object, and pollution of inland rivers is analyzed and evaluated from industry, life and agriculture. Comprehensive improvement of ecological environment of inland rivers is conducted by combining pollution control engineering measures with ecological landscape construction. Eco-landscape rivers construction is the development trend of current rivers regulation. Combining cases of inland rivers control, ecological governance path of rivers water environment in tourist town is studied, which could provide the reference for ecological governance and landscape construction of urban rivers. [ABSTRACT FROM AUTHOR]

With the rapid development of the economy, it is important to reasonably evaluate the development status of the regional manufacturing industry. Given this, this article expands the evaluation indicators of urban advanced manufacturing (UAM) from the perspective of the push–pull-mooring (PPM). Then, it uses a machine learning (ML) method to predict the evaluation results of other cities through a small amount of sample data. The results show that: (1) From the current development status of UAM in Guangdong Province (GD), cities in the Pearl River Delta region occupy a dominant position. However, cities in eastern, western, and mountainous regions have strong development potential and lead cities. Therefore, each region has cities with high levels of development and has a demonstrative role. (2) By comparison, it was found that the overall development level of UAM in GD is not significantly different from that of the Yangtze River Economic Belt. However, due to significant differences in their extreme values, the proportion of cities above the average in the overall population is relatively small. This indirectly proves that GD's UAM not only has a phased nature, but also has a demonstrative role. (3) The prediction effect of the perceptron model is better than other methods. Although neural network models have better prediction performance than other machine learning models, they should not overly rely on complex network structure prediction data. By comparing the results, the reliability is verified. Finally, according to the life cycle theory, we propose a targeted development path for different UAM. [ABSTRACT FROM AUTHOR]

Analyzing the influencing factors of PM2.5 concentration, scenario simulations, and countermeasure research to address the problem of PM2.5 pollution in Guangdong Province is of great significance for governments at all levels for formulating relevant policies. In this study, the ChinaHighPM2.5 dataset and economic and social statistics for Guangdong Province from 2010 to 2019 were selected, and a PM2.5 pollution management compliance path formulation method based on the multi-scenario simulation was proposed by combining the differences in city types and PM2.5 concentration prediction. Based on the prediction model of PM2.5 concentration constructed by the Ridge and SVM models and facing the PM2.5 pollution control target in 2025, the urban PM2.5 pollution control scenario considering the characteristics of urban development was constructed. According to the scenario simulation results of the PM2.5 prediction model, the PM2.5 pollution control path suitable for Guangdong Province during the 14th Five-Year Plan period was explored. The coupling coordination model was used to explore the spatial and temporal pattern evolution of PM2.5 pollution collaborative governance in various prefecture-level cities under the standard path, and the policy recommendations for PM2.5 pollution control during the 14th Five-Year Plan period are proposed. The results showed the following: ① in the case of small samples, the model can provide effective simulation predictions for the study of urban pollutant management compliance pathways. ② Under the scenario of PM2.5 management meeting the standard, in 2025, the annual average mass concentration of PM2.5 in all prefecture-level cities in Guangdong Province will be lower than 22 μg/m3, and the annual average concentration of PM2.5 in the whole province will drop from 25.91 μg/m3 to 21.04 μg/m3, which will fulfil the goal of reducing the annual average concentration of PM2.5 in the whole province to below 22 μg/m3, as set out in the 14th Five-Year Plan for the Ecological Environmental Protection of Guangdong Province. ③ Under the path of PM2.5 control and attainment, the regional coordination relationship among prefecture-level cities in Guangdong Province is gradually optimized, the number of intermediate-level coordinated cities will increase, and the overall spatial distribution pattern will be low in the middle and high in the surrounding area. Based on the characteristics of the four city types, it is recommended that a staggered development strategy be implemented to achieve synergy between economic development and environmental quality. Urban type I should focus on restructuring freight transportation to reduce urban pollutant emissions. City type II should focus on urban transportation and greening. For city type III, the focus should be on optimizing the industrial structure, adjusting the freight structure, and increasing the greening rate of the city. For city type IV, industrial upgrading, energy efficiency, freight structure, and management of industrial pollutant emissions should be strengthened. [ABSTRACT FROM AUTHOR]

Background: Antimicrobial resistance (AMR) of untreatable gonococcal infection is an emerging threat, especially in Guangdong, a prosperous province in Southern China. Methods: N.gonorrhoeae was isolated from 20 cities in Guangdong and determined antimicrobial susceptibility. Through whole-genome sequencing (WGS), multilocus sequence typing (MLST), N.gonorrhoeae multiantigen sequence typing (NG-MAST), and N.gonorrhoeae sequence typing for antimicrobial resistance (NG-STAR) were obtained based on the PubMLST database (https://pubmlst.org/). Phylogenetic analysis was used for dissemination and tracking analysis. Results: Antimicrobial susceptibility was performed on 347 isolates, and 50 isolates were identified as decreased susceptibility (DS) to cephalosporins. Of which 16.0% (8/50) were ceftriaxone DS, 38.0% (19/50) were cefixime DS, and 46.0% (23/50) were both ceftriaxone and cefixime DS. In all, the dual-resistant rate of the cephalosporin-DS isolates was 96.0% for penicillin and 98.0% for tetracycline-resistant, and 10.0% (5/50) were resistant to azithromycin. All cephalosporin-DS isolates were resistant to ciprofloxacin but sensitive to spectinomycin. The predominant MLSTs were ST7363 (16%, 8/50), ST1903 (14%, 7/50), ST1901 (12%, 6/50), and ST7365 (10%, 5/50). Besides some isolates that failed genotyping (NA), NG-STAR ST1143 (n = 6) and NG-MAST ST17748 (n = 4) were the most prevalent. Twelve isolates with mosaic penA-60.001 allele retained the most elevated cephalosporin MIC (Minimum Inhibitory Concentration). Phylogenetic analysis revealed that epidemic penA-60.001 clones, either domestic or foreign, had spread to nine cities in Guangdong, and 9/12 clones were from the Pearl River Delta region. Conclusions: N. gonorrhoeae with cephalosporins-DS was extensively disseminated in Guangdong, Southern China, requiring strict surveillance. [ABSTRACT FROM AUTHOR]

Few studies have analyzed the mixed effects of city size and land factors at the macro level on migrant socio-economic integration. On the basis of survey data on migrants in the Pearl River Delta Metropolitan Region (PRDMR), this study developed a system of multidimensional indicators for analyzing the degree of migrant socio-economic integration and factors influencing it. This study demonstrated the following: (1) The overall degree of socio-economic integration of migrants in the PRDMR was low. Factors including city size, hometown landholding, year of birth, education level, gender, and migratory duration exerted effects of varying extents on the degree of the socio-economic integration of migrants. (2) Better job positions were offered and infrastructure was more developed in first-tier cities, so the degree of migrant economic integration was higher, and the sense of identity was stronger in first-tier cities. Given the low housing prices in second-tier cities, migrants therein were more likely to buy a house and achieve family integration, and the degree of their social integration was stronger. (3) In terms of source landholding factors, the degree of socio-economic integration was relatively low among the migrants who owned arable land and homesteads, and who were born outside Guangdong Province. The study tries to measure the socio-economic integration of immigrants more comprehensively and provide reference for the implementation of differentiated socio-economic integration policies and land transfer policies in the immigration and emigration areas. [ABSTRACT FROM AUTHOR]

Accurately identifying the boundary of urban clusters is a crucial aspect of studying the development of urban agglomerations. This process is essential for comprehending and optimizing smart and compact urban development. Existing studies often rely on a single category of data, which can result in coarse identification boundaries, insufficient detail accuracy, and slight discrepancies between the coverage and the actual conditions. To accurately identify the extent of urban clusters, this study proposes and compares the results of three methods for identifying dense urban areas of three major agglomerations in China: Beijing–Tianjin–Hebei, the Yangtze River Delta, and the Guangdong–Hong Kong–Macao Greater Bay Area. The study then integrates the results of these methods to obtain a more effective identification approach. The social economic method involved extracting a density threshold based on the fused nuclear density of socio-economic vitality data, including population, GDP, and POI, while the remote sensing method evaluated feature indices based on remote sensing images, including the density index, continuity index, gradient index, and development index. The traffic network method utilizes land transportation networks and travelling speeds to identify the minimum cost path and delineate the boundary by 20–30 min isochronous circles. The results obtained from the three methods were combined, and hotspots were identified using GIS overlay analysis and spatial autocorrelation analysis. This method integrates the multi-layered information from the previous three methods, which more comprehensively reflects the characteristics and morphology of urban clusters. Finally, the accuracy of each identification result is verified and compared. The results reveal that the average overall accuracy (OA) of the three areas delineated by the first three methods are 57.49%, 30.88%, and 33.74%, respectively. Furthermore, the average Kappa coefficients of these areas are 0.4795, 0.2609, and 0.2770, respectively. After performing data fusion, the resulting average overall accuracy (OA) was 85.34%, and the average Kappa coefficient was 0.7394. These findings suggest that the data fusion method can effectively delineate dense urban areas with greater accuracy than the previous three methods. Additionally, this method can accurately reflect the scope of urban clusters by depicting their overall boundary contour and the distribution of internal details in a more scientific manner. The study proposes a feasible method and path for the identification of urban clusters. It can serve as a starting point for formulating spatial planning policies for urban agglomerations, aiding in precise and scientific control of boundary growth. This can promote the rational allocation of resources and optimization of spatial structure by providing a reliable reference for the optimization of urban agglomeration space and the development of regional spatial policies. [ABSTRACT FROM AUTHOR]

The low–carbon transition of farmland use (LCTFU) is an effective measure to coordinate the development of farmland and the environment to meet China's "dual carbon" and green agricultural transformation goals. We studied the spatial–temporal evolution of the LCTFU and further explored the driving factors of the LCTFU by applying a geographically weighted regression model (GWR) to the coastal cities of Guangdong Province from 2000 to 2020. The results show that (1) temporally, the comprehensive, spatial, functional, and mode transitions of farmland use in coastal areas of Guangdong Province generally declined. The LCTFU level in most counties was low, and the difference in the LCTFU level among counties was narrowing. (2) Spatially, the LCTFU generally followed a high–to–low spatial distribution pattern, with high LCTFU values in the east and west and low values in the center. (3) The hotspots of the comprehensive, spatial, functional, and mode transitions were mainly concentrated in the eastern part of the study area, while the cold spots were in the central region, which is generally consistent with the spatial distribution of high– and low–value areas of the LCTFU. (4) The spatial migration path of the LCTFU migrated from northeast to southwest, with the main body of the standard deviation ellipse in the middle of the study area, displaying a C–shaped spatial pattern with weak expansion. (5) Economic, social, and environmental factors jointly contributed to the spatial–temporal evolution of the LCTFU, with social factors being the strongest driver. [ABSTRACT FROM AUTHOR]

Compared with the linear economy, the circular economy can solve the contradiction between social development and resource utilization, which has attracted wide attention. Although the relationship between transportation infrastructure and economic development has changed from traditional mode to spatial mode, the spatial effect of transportation infrastructure on regional circular economy is still unclear. By combining the policy changes for developing the circular economy in China, this study constructs a comprehensive index of circular economy development in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). Based on the time and space development of the circular economy in GBA, we analyze the spatial effect of transportation infrastructure on it. The results show that the regional circular economy in GBA has developed, but has not been decoupled from economic development. The development of the regional circular economy presents a positive spatial spillover effect, which is beneficial to the building of the regional recycling market. The improvement of transportation infrastructure has a positive impact on the circular economy of neighboring cities, but it may have the risk of inhibiting the development of the local circular economy. These findings provide policy recommendations for urban planners to coordinate the development of transportation infrastructure and circular economy. [ABSTRACT FROM AUTHOR]

The digital economy plays an important role in the high-quality development of cities, and low-carbon urban development is an integral part of this evolution. Therefore, it is important to explore the impact of the development of the digital economy on urban carbon emissions. By considering 21 cities in Guangdong Province as the object of the research, this study measured the levels of the digital economy from 2011 to 2019 by using an entropy weight-based TOPSIS model, analyzed the spatiotemporal changes, and used geographically and temporally weighted regression to examine the spatiotemporal heterogeneity of the impact of the digital economy on urban carbon emissions. The results showed the following: (1) The development of the digital economy in Guangdong Province in general exhibited a stable trend of growth, and the average level of its development in the 21 cities considered increased by 3.4 times during the study period. (2) The level of development of the digital economy in the Pearl River Delta was significantly higher than that in northern, western, and eastern Guangdong, with Shenzhen being the most developed city in this regard (0.8473), and Shanwei being the least developed (0.0633). (3) The impact of the development of the digital economy on carbon emissions had significant spatiotemporal heterogeneity. The benefits of the development of the digital economy in terms of a reduction in carbon emissions was the most significant in the Pearl River Delta, and regional differences were prominent. (4) The reductions in carbon emissions in cities with a highly developed digital economy were more significant than has been reported in past studies in the area. However, it had a negative effect on the urban carbon emissions in cities with a poorly developed digital economy. The results of this study can be used to guide policies related to the high-quality development of the urban digital economy. [ABSTRACT FROM AUTHOR]

Analyzing long-term variations of aerosol optical depth (AOD) is beneficial for determining high-pollutant-risk areas and formulating mitigation policies. In this study, multi-spatiotemporal trends and periodicity of AOD, as well as the persistence over the Guangdong-Hong Kong-Macao Greater Bay Area from 2001 to 2021, were investigated by the extreme-point symmetric mode decomposition (ESMD), Theil-Sen Median trend analysis and Hurst exponent. The results elucidate that AOD exhibits fluctuant variations during the 21-year period with the year 2012 as the turning point. There is a slight upward tendency (0.009 year−1) in the pre-2012 period but a pronounced downward trend (− 0.03 year−1) in the post-2012 period, suggesting an overall declining trend in the study area. The northern cities in the area present an increasing-stable-decreasing trend of monthly average AOD, whereas other cities have an increasing-fluctuating-decreasing trend over the study period. The decreasing rate in the western parts is higher than that in the eastern parts, like Zhaoqing, Jiangmen and Foshan city. A continuous decline of AOD is dominated over the study area, whereas an anti-persistence tendency is accumulated in the northeastern parts. Additionally, elevated AOD can be observed in unused land, water bodies and construction land, while grassland, cropland and woodland have lower AOD. The decreasing rate is larger when land-use types with high AOD are converted to those with low AOD; otherwise, the decreasing rate is smaller. The results have a great significance for improving the understanding of long-term variations of AOD, as well as providing a scientific basis to formulate environmental protection and mitigation practices. [ABSTRACT FROM AUTHOR]

Introduction: Although employees' silence is a common phenomenon in organizations, the mediating role of relational silence has not been studied in inclusive leadership and innovative behavior. In this study, based on the theory of social exchange, relational silence is used as a mediating variable to explore the internal mechanisms of inclusive leadership on employees' innovative behavior. Methods: Data from 263 in-service leaders and employees were collected using convenience sampling and analyzed using Amos and SPSS statistical software package via questionnaires distributed to companies in six cities in the Guangdong province of China. Results: The results showed that inclusive leadership has a significant positive predictive effect on employees' innovative behavior (β = 0.590, p < 0.01), while inclusive leadership is negative and significantly correlated with relational silence (β = -0.469, p < 0.01). More so, relational silence has a significant negative correlation with employees' innovative behavior (β = -0.408, p < 0.01), and relational silence partially mediates the relationship between inclusive leadership and employee innovation behavior. Discussion: The mediating role of relational silence between inclusive leadership and employees' innovative behavior is revealed for the first time, theoretically broadening and enriching the connotation of inclusive leadership's influence mechanism on employees' innovative behavior and providing new ideas in practice for constructing inclusive leadership styles, reducing the incidence of relational silence, and evoking employees' innovative behavior. [ABSTRACT FROM AUTHOR]