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Drug crime is a serious global problem requiring attention. This study focuses on the spatial characteristics and factors influencing drug crimes at the provincial level. Understanding these factors is crucial to combating drug crime and maintaining social stability. In the past, most studies analyzed and discussed drug crimes at the macro and micro scales; however, research on the meso scale is still relatively lacking, and the special geographical location and complex socioeconomic conditions near the border of Myanmar in Yunnan Province had a high incidence of drug crimes, so it was still necessary to study drug crimes at the meso scale in Yunnan Province. This study considers drug crime cases from 129 counties and districts in Yunnan Province and employs Geographic Information System (GIS) statistical analysis, spatial autocorrelation analysis, and a spatial gravity model to examine the spatial difference patterns and spatial correlation network characteristics of drug crime in the province. Additionally, an indicator system for drug crime-influencing factors was constructed, which included economic level, income level, urbanization level, education level, floating population, impact of drug source areas, and terrain complexity. A regression analysis using a Spatial Durbin Model was conducted to analyze the relationship between these factors and drug crimes. First, the drug crime rate in Yunnan Province exhibits a notable spatial variation pattern, wherein clusters of high crime rates are primarily concentrated along the China-Myanmar border. Second, drug crimes in different districts and counties of Yunnan Province exhibit notable spatial correlation and agglomeration patterns on a global scale. Considering the spatial distribution, two main groups with strong spatial correlation networks were identified. The first group includes Kunming's central urban area and its surrounding districts and counties. The second group consists of districts and counties along the Yunnan border. This spatial distribution aligns with the cubic function curve depicting the relationship between distance from Myanmar and the density of drug crime rates. Third, among the influencing factors, the economic level, income level, urbanization level, and drug source area have a significant impact on the drug crime rate in Yunnan Province. Notably, factors related to the source of drugs had the most significant influence, displaying a significant negative correlation. The relationship between the distance from the China-Myanmar border (the source of drugs) and the drug crime rate follows an elongated "inverted S" shaped distribution curve. It demonstrated a significant initial decrease, followed by a slight increase and then a subsequent downward trend. Additionally, the economic level has a significant negative impact on the variation in drug crimes in Yunnan Province, whereas income and urbanization levels have a positive impact. In conclusion, this study focused on the research area of Yunnan Province, which is known for its high incidence of drug crimes, making it a suitable and significant region for this study. It conducted a quantitative analysis of the spatial differentiation characteristics and influencing factors of drug crimes in the Yunnan Province at a provincial mesoscale. Analyzing the exploration of the direction of these influencing factors contributes to the advancement of research on criminal geography.

Against the background of the increasing separation of natural and human geography, gradual disintegration of the comprehensive disciplinary characteristics of geography, and weakening of the social influence of geographers, the domestic geography community has recently been discussing the possibility of integrating natural and human geography and the possible paths for doing so. In response, this study proposes an analysis framework of Ecological Economic Geography conducive to the integration of physical and human geography. Furthermore, this study advocates a focus on the dynamic change of "human" as a giant system with complex links of economy, technology, and institutional systems, and its two-way feedback relationship with the ecosystem. By exploring the coupling and regulation mechanisms of human and natural systems in the context of environmental and technological change, this study seeks the best answer to human sustainable development in the comprehensive balance. To clarify the research perspective and ideas of Ecological Economic Geography, we select the following three cases: i) the centennial evolution of the ecological economic system of Mulberry-dyke and Fish-pond System, ii) the systematic cascade of the "digital-energy-water" in data centers, and iii) the humanistic perspective of ecological restoration planning. With a focus on the analytical framework of the "pattern-process-relationship-pathway," this study proposes four research topics on which Ecological Economic Geography needs to focus, specifically, the coupling pattern of ecosystems and economic systems, process and impact of different factor flows between different systems, regional complexity of ecological and economic coupling systems, and sustainable development pathway of the ecological economic system. Accordingly, the development of Ecological Economic Geography may strengthen the mutual collaboration between scholars of the natural world and the humanities, promote the integration of geographic disciplines, and enhance the ability of geography to solve extensive problems.

The international non-tariff trade protection against China has gradually increased since 2018, hindering technology trade. Under the impact of the new trade protection, we still know little about how the electronic communication industry (as one of the strategic high-tech industries)changes the innovation cooperation relationship and the innovation performance. Owing to the failure of geographical research to integrate trade protection into the existing research framework from an institutional perspective, the trade protection literature and the innovation geography literature do not intersect. However, the trade geography literature has not paid enough attention to the evolution of industrial innovation in China in recent years and has not taken into account the heterogeneity of the industry-college-institute cooperation and innovation relationship and its impact on regional industrial innovation performance. Based on the 2014-2021 US Export Control Regulations and the invention patent data of the electronic communication industry in the Pearl River Delta, this study uses descriptive statistics, a Quadratic Assignment Procedure, and a negative binomial regression model. It explores both the mechanism and effect of a new round of trade protection on industry-college-institute cooperation and their joint impact on cooperative innovation performance. The study finds that the structure of the industry-college-institute cooperative innovation relationship in the electronic communication industry of the Pearl River Delta has gradually decentralized, and its heterogeneity growth tends to stall. The new round of trade protection significantly regulates geographical proximity, deteriorating the geographical scale of cooperative innovation. The regression results show that under the impact of trade protection, the heterogeneity of industry-college-institute cooperation changes from positive to negative, and the inverted U-shaped relationship has reached a significant level. Trade protection changes the influence of social and cognitive proximities and of geographical proximity on cooperative innovation performance, and the moderating effect of trade protection is highlighted by the positive effect of strengthening geographical proximity on industry-college-institute cooperation and innovation performance. The above findings remind us of the need to further refine and optimize innovation support policies. Therefore, the study puts forward some targeted policy suggestions, namely, to formulate innovation support policies suitable for the internal and externalized innovation transaction costs of different types of enterprises, strengthen the dominant role of enterprises in innovation, and promote cross-regional cooperation. To a certain extent, it can inform the decision-making by China's regional strategic industries around ending the international technology trade blockade and achieving high-quality independent innovation and technical cooperation.

Inter-city Venture Capital (VC) exchange is a micro-embodiment of the cross-regional flow of innovative elements such as capital and technology, and also an important driving force for shaping the network of VC cities. Compared with other types of investment activities, VC has more advantages in promoting the development of innovative industries, especially high-tech industries, and then driving urban economy and regional development; hence, it is widely regarded as a "catalyst" for economic growth and technological innovation. The study of VC networks is helpful in understanding the financial activity links between cities across the country and provides key support for further rational allocation of financial resources between cities. The existing research rarely uses the actual investment amount of VC transaction events between cities to construct the city network. The analysis of the continuous dynamic evolution research and the influencing factors of the overall spatial network structure over a long period of time needs to be strengthened. To compensate for the shortcomings in the above research, this study uses the data of China's inter-city VC flow between 2000 and 2018 to construct the Chinese urban VC network. The long-term spatial evolution characteristics and overall network structure influencing factors of the national inter-city VC network are discussed based on complex network analysis, GIS spatial technology analysis, multiple linear regression model, and so on. This study derives the following results: (1) The connection between cities tends to be closer, and the agglomeration degree of the national VC network increases, displaying obvious characteristics of high aggregation and small-world network. However, the cyber spatial structure of investors/start-ups tends to be flattened, there is a trend of decentralization. (2) The VC connection between cities has expanded from the eastern coastal axis to the central and western regions as a whole, exhibiting obvious characteristics of path dependence and distance attenuation. Additionally, the VC connection continues to sink from the three major urban agglomerations to other marginal cities, and the core node cities of the network also display a tendency of quantitative expansion and power transfer. (3) The city's entrepreneurial foundation, VC industry development level, financial environment, and urban accessibility all have differentiated impacts on the spatial structure of the national VC network. Moreover, the aforementioned are affected by various mechanisms such as multi-dimensional proximity, urban economy, and path dependence, which promote the construction of national and regional VC networks and the formation and evolution of regional capital centers.

Owing to the development issues of the Guangdong-Hong Kong-Macao Greater Bay Area in the new domestic and international situation, the content, challenges, and paths of innovation and development of the Greater Bay Area are explored from multiple dimensions, including economic, social, cultural, and institutional. The innovation and development of the Greater Bay Area should strengthen technological and industrial innovation capabilities, improve regional resilience to cope with external shocks, increase the mobility of intraregional factors, improve the well-being of the people's livelihood, enhance the capacity of spatial governance, promote integrated urban-rural development, and optimize the regional pattern of ecological security. The conclusion is that considering the innovation and development of the Greater Bay Area from a systemic and interconnected perspective is crucial for seeking innovations in various development fields and promoting coupling and coordination among them. Therefore, the region may acquire the agency that can continuously break through bottlenecks, resolve external shocks, and unlock new paths of development. We call for the strengthening of cross-field and cross-disciplinary collaborative research to contribute the power of geography to the realization of the development goals of the Guangdong-Hong Kong-Macao Greater Bay Area.

As a typical representative of advanced producer services, banks can be used to characterize the spatial structure of urban networks through the headquarters-branch connections and the implied capital flow process, which can guide the exploration of financial market connectivity and coordinated regional development. In this paper, the financial linkages of 26 representative banks in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) were transformed from city scale to county scale urban network using the interlocking network model, and the structural characteristics and influencing mechanism of urban network are discussed using the Social Network Analysis and Geographically Weighted Regression model. The results show that: 1) The Pearl River Estuary in the GBA is a dense area of financial linkages. The level of financial linkages on the east bank of the Pearl River is generally higher than that on the west bank of the Pearl River, and the hierarchical expansion to the peripheral space is continuous or progressive. 2) The clustering and accessibility of the overall network perform well. The whole network presents a typical "small world" effect. Guangzhou Tianhe, Guangzhou Yuexiu, Foshan Nanhai, Foshan Shunde, and other nodes are of high gradability and proximity, and they are also important intermediaries for financial connections in the GBA. 3) Most of the nodes with high gradability have higher effective scale and efficiency, and have the advantage of structural holes. The peripheral spatial nodes have a high restriction degree. The network mainly relies on some nodes in the core or sub-core subgroups to generate financial linkages, while the financial linkages among most nodes of the edge subgroup are weak. 4) The variables negatively correlated with the total number of linkages are population density, economic development level, and government control behavior. The variables that are positively correlated with the total number of linkages are the degree of transportation convenience and social consumption ability. The relationship between the demand for financial services and the level of openness to the outside world and the total linkages is complex and has bidirectional effects. An additional contribution of this paper is as follows: 1) The preference for location choice of APS enterprises represented by banks is higher for geographical agglomeration in local markets, and the financial relationship at the county scale is more important for the location choice of bank branches within cities. 2) The differentiated urban network structure characteristics revealed by the heterogeneity of bank branches provide a reference value for the appeal of different types of bank branches.

Biodiversity plays an important role in providing ecosystem services and maintaining ecosystem stability, which are closely related to human welfare. The identification of biodiversity hotspots and analysis of their threats provide effective ways for biodiversity conservation and restoration. Current studies generally combine species diversity and its threat situation to determine hotspots for priority protection. However, in-depth analysis of threats to biodiversity hotspots is still lacking. Guangdong Province is one of the key biodiversity areas in the world, but it faces great challenges in biodiversity preservation. To understand biodiversity hotspots and their threats in Guangdong Province more completely, this study developed a heat index for terrestrial biodiversity by considering plant species diversity, animal species diversity, and landscape diversity based on multi-source data of plant and animal species, ecosystem stand types, and land use. Then, the heat index was used to identify biodiversity hotspots, and their threat levels and controlling factors were analyzed according to the major threats to biodiversity. The results showed that areas with high values of terrestrial biodiversity heat index were mainly distributed in mountainous regions with relatively few human disturbances, whereas most areas with low values were concentrated in estuarine plains and intermontane basins with heavy human activities. Based on the zonation of the heat index, four biodiversity hotspots were identified, Yunwu Mountain, Nanling Mountain, Luofu Mountain, and Lianhua Mountain, with area percentages of 15.54%, 44.90%, 17.66%, and 21.90%, respectively. The area of biodiversity hotspots was 59,931.82 km2, accounting for 33.58% of the total land area of Guangdong Province. The 122 nature reserves within hotspots had an area of 6,594.39 km2, covering 61.33% of the whole area of the total 204 terrestrial nature reserves in Guangdong Province. This proportion gradually decreased with reduction of nature reserve grade, indicating that the nature reserves in hotspots were principally at a higher grade (nation and province levels) rather than at a lower grade (city and county levels). However, the area of these nature reserves in hotspots was only 11.00% of the whole area of hotspots, and most of the nature reserves that were not distributed in hotspots were located in the northeastern cities of Heyuan and Meizhou. Therefore, a large number of potential demands for biodiversity conservation still exist. For the four hotspots, the biodiversity in Yunwu Mountain was primarily under moderate to severe stress, with the intensity of economic development as the controlling factor. The biodiversity of the other three hotspots mainly underwent slight to moderate stress. The most important threat was the extensive economic development of the central part of Nanling Mountain and the southern parts of Luofu Mountain and Lianhua Mountain, whereas the periphery of Nanling Mountain and the northern parts of Luofu Mountain and Lianhua Mountain were more threatened by habitat quality or geological hazards. In addition, extreme stress on biodiversity occurred in all four hotspots, although within very small areas. Thus, more targeted management strategies for biodiversity should be proposed according to the stress levels and controlling threats. The results of this study provide a scientific reference for the comprehensive conservation and precise restoration of biodiversity hotspots in Guangdong Province.

The rapid development of global transportation network and information communication technology has an important impact on regional economy and social spatial structure, and promotes the transformation of regional research paradigm. The coordinated development of urban agglomeration and regional functional linkage from the perspective of flow space has become an important issue in urban regional research. Different from the traditional central place theory that emphasizes the differences in scale and level of cities within the region, the flow space perspective helps to understand how the regional factor flow organizes cities of all scales and levels in the form of network with the background of space-time compression, and promotes the functional linkage and coordinated development within the region on the basis of reshaping the urban spatial relationship. Based on the literature review of relevant research at home and abroad, this paper constructs an analytical framework for the relationship between regional spatial factor flow and function collaboration, and discusses the regional function collaborative mechanism of urban agglomeration from three aspects: "how to reshape the regional spatial network by factor flow", "how to restructure the urban hierarchy by infrastructure connectivity" and "how to strengthen the regional functional linkage by functional complementarity". On this basis, taking the urban agglomeration of San Francisco Bay Area as an example, this paper discusses the evolution progress of San Francisco Bay Area from "single center agglomeration development" to "double-core symbiotic evolution", "polycentric development" and "generic network functional linkage development" from three aspects of liquidity, connectivity and complementarity. The study found that: 1) In the first stage (before the 1930s), fact flow strengthened the connection between San Francisco and Oakland, connectivity improved the status of Oakland, and functional complementarity promoted the symbiosis of the two cities. 2) In the second stage (1940s-1980s), the flow and converge of factors towards the south bay promoted the tripartite growth of San Francisco, Oakland and San Jose, transport connectivity strengthened the core-peripheral connection, and factor convection and functional reciprocity promoted the multi-center linkage development. 3) In the third stage (since 1980s), factor distribution and transportation network connectivity contributed to the generic network spatial structure, dislocation and complementary development strengthened the regional circulation and realized the functional linkage of the Bay Area. Based on the perspective of flow space, this paper reviews the basic situation of the development of world-class bay area urban agglomerations and excavates the internal mechanism of regional functional coordinated development driven by factor flow, which has reference significance for guiding China's cities from competition to competition and cooperation and establishing a new mechanism of regional coordinated development. The research shows that to promote the development of China's bay area in the future, we should: 1) Comply with the law of factor flow, innovate the mechanism and remove barriers to factor mobility, and promote the free flow of factors inside and outside the region; 2) Give play to the guiding role of the government and non-governmental organizations to improve the connectivity of software and hardware infrastructure within the region; 3) Explore the regional consultation mechanism, break through the regional administrative barriers, and formulate the regional development strategy of functional complementation and linkage with the help of multiple subject forces.

The dynamics of innovation in geographical space is closely related to the regional development trajectory. Evolutionary economic geography points out the path dependence characteristics of regional development, and emphasizes that the direction of regional development is rooted in the original industrial and technological structure characteristics. Therefore, the geographical pattern of technological innovation and the identification of its diversity characteristics are of significance to the realization of regional innovation and the evolution of industrial structure. From the perspective of strategic industry, this paper aims to reveal the geographical pattern and diversity characteristics of technological innovation in strategic industry in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). Based on the point scale spatial data of invention patents in the GBA and by means of connecting strategic industry with national economy industry classification code and patent IPC classification code, the invention patents of six major industries in the GBA are extracted, which are the new generation of electronic information industry, automobile industry, green petrochemical industry, new energy industry, advanced material industry and intelligent robot industry. And the nuclear density analysis, standard deviation tail value test, entropy method and average nearest neighbor distance analysis are used to identify the spatial distribution characteristics and differences of multiple types of technological innovation in the GBA. The results show that the geographic pattern of technological innovation in the GBA presents a significant spatial imbalance. At the regional scale, Guangzhou and Shenzhen are the two agglomeration cores. There is a large gap in the innovation ability between the east and west sides of the Pearl River. The accumulation of technological innovation on the east bank is much higher than that on the west bank. The innovation profile line on the east bank has formed two obvious peaks in Guangzhou and Shenzhen. The high value of the innovation profile line on the west bank is mainly concentrated in Guangzhou and Zhuhai, and the peak value is far lower than that on the east bank. The location of technological diversity is mainly distributed in the core areas of the GBA, mainly including Yuexiu District and Tianhe District in Guangzhou, Nanshan District and Futian District in Shenzhen, Binhai District in Dongguan and Xiangzhou District in Zhuhai. And the distribution characteristics of technological innovation data of different industrial types are different. The innovation of the new generation of electronic information industry, advanced materials industry and green petrochemical industry accounts for 51.67% of the total innovation in the GBA. The innovation of different technological types shows obvious spatial differentiation. The innovation agglomeration degree of the new generation electronic information industry is the highest, with the R value of 0.0576. And its observed value of the average nearest neighbor distance between invention patents is 32.03 m, which belongs to the minimum value in the selected analysis industries, showing strong agglomeration characteristics. There are differences in the distribution characteristics of the agglomeration core of the six major industries in the GBA. The common ground is that they have formed the largest two agglomeration cores in the core areas of Guangzhou and Shenzhen, covering Yuexiu-Tianhe area in Guangzhou and Futian-Nanshan-Luohu area in Shenzhen. And the spatial distribution is mainly concentrated in the core areas of Guangzhou, Shenzhen, Dongguan and Zhuhai. Among them, the spatial agglomeration degree of the new generation of electronic information industry innovation is the highest. Agglomeration and multi-dimensional proximity, diversity and path dependence are the main mechanisms for the formation of the geographical pattern of technological innovation in the GBA, and these two key mechanisms promote the formation of current multi-type technological innovation space in the GBA.

Regional coordinated development is a complex, systematic and scientific issue advancing with the time which has attracted much attention. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) aims to develop into a world-class bay area and urban agglomeration. The development of GBA depends on regional coordinated development to enhance its international competitiveness. At present, the process of globalization has experienced multiple turning points, the regional governance system has been continuously optimized, and the technological innovation has evolved rapidly. The coordinated development of the GBA is facing institutional changes. Therefore, through the systematic analysis of the connotations and mechanisms of the coordinated development of the GBA, this paper describes the three stages of regional coordinated development since 1978, including the integration of regional production factors represented by the ‘front shop, back factory’ mode (1978-1996), the regional system integration led by institutional cooperation (1997-2014), and the regional all-round integration guided by national strategy (2015- ). In the meantime, the paper analyzes the five dimensions of the coordinated development of the GBA in the new period, including industrial collaborative innovation, environmental collaborative governance, resource collaborative allocation, service collaborative sharing and institutional collaborative arrangement. These five dimensions are helpful to understand the key areas to promote the coordinated development of the GBA in the coming decades. Furthermore, this paper holds that the regional coordinated development of the GBA is undergoing mechanism changes at four levels, which are mainly reflected in the transformation of globalization, the integration of the internal and external market, the rescaling of governance, and the energization of regional in-depth development facilitated by the new infrastructure. These institutional changes have the potential to generate a new model for the coordinated development of the GBA. This paper takes into account the retrospective review and forward-looking prospect on the coordinated development of the GBA, aiming to provide an entry perspective and analysis framework for related issues.

On the basis of fully understanding the scientific connotation of coordinated development of urban agglomeration in the Guangdong-Hong Kong-Macao Greater Bay Area, the evaluation index system of coordinated development is constructed from four dimensions: industrial coordinative innovation, environmental coordinative governance, service coordinative sharing and institutional coordinative arrangement. The theory and method of space of flows, big data, network analysis and interlocking network model are comprehensively used to quantitatively analyze the interurban relationship, liquidity, connectivity and boundary effect. The research shows that: 1) Interurban capital flow is concentrated between Guangzhou and Shenzhen, and interurban knowledge flow is concentrated among Hong Kong, Guangzhou and Shenzhen. Macao, Zhuhai, Zhongshan and Jiangmen have higher level of collaborative environmental governance, while Shenzhen-Dongguan-Huizhou and Guangzhou-Foshan have lower level of collaborative environmental governance. The interurban service coordination sharing level of infrastructure such as transportation, communications, logistics and banking is higher among cities of Guangzhou-Shenzhen, Guangzhou-Foshan and Shenzhen-Dongguan. And Hong Kong and Macao have institutional advantages in cross-border regional coordination. 2) Guangzhou and Shenzhen, Guangzhou and Foshan, Shenzhen and Dongguan, and Hong Kong and Shenzhen have the best level of coordinated development in the Guangdong-Hong Kong-Macao Greater Bay Area. At the same time, Guangzhou and Dongguan, Shenzhen and Foshan show a linkage trend. Although the de-boundary trend is obvious and the interurban liquidity is enhanced, the coordinated development level of the Guangdong-Hong Kong-Macao Greater Bay Area is generally not high. 3) The collaborative capacity of Guangzhou and Shenzhen is the strongest, and there is still much room for improvement in the collaborative capacity of the two international cities, Hong Kong and Macao. It is of great practical value to deeply understand the typical characteristics and potential trends of the coordinated development of urban agglomeration in the Guangdong-Hong Kong-Macao Greater Bay Area for the construction of international first-class bay area and world-class urban agglomeration.

Unlike previous ecological restoration programs, the main focus of ecological restoration of national land space has changed from a single element in the natural ecology to the whole social-ecological system. The approach of this ecological restoration has changed from applying the pipe-end treatment to a single process to employing system restoration of the community of life consisting of mountains, rivers, forests, fields, lakes, and seas. Additionally, the aim has evolved from improving the health and stability of the ecological system to building a complex system in which humans and nature can coexist and develop a harmonious relationship. As the research on ecological restoration of national land space is developing a systemic and comprehensive view, it urgently requires support from multidisciplinary theories and methodologies. Ecological restoration planning of national land space at the provincial level is an action guide and programmatic document for provinces to further promote the construction of ecological civilization in this new era. This is a new but arduous and complex strategic task that allows extensive discussion on its research theories and methods. Accordingly, multidisciplinary theories and methods and participation from different parties and places are required. This study begins with the analysis of the scientific connotation and theoretical basis of ecological restoration planning of national land space, uses the man-land relationship theoretical framework as the guidance, integrates landscape ecology and nature-based solutions, and considers the local practice of ecological restoration planning of national land space in Guangdong Province. This paper presents the ideas and methods of provincial-level ecological restoration planning of national land space by focusing on the key points and difficulties, such as targets, indicators, major patterns, regional layout, and engineering systems. This is summarized as follows: the overall thinking of "six steps," the target system of "four dimensions," the zoning task of "three spaces," the spatial layout of "three levels," and the engineering system of "three scales." The study enriches the research on the method of ecological restoration planning of national land space by refining thoughts and methods and providing a reference for the ongoing ecological restoration planning of provincial-level national land space in China.

Recently, new-type infrastructure construction has been intensively deployed as national strategies to underpin the cultivation of emerging industry chain development. Given the inadequacies in understanding of spatiotemporal heterogenous influences of new-type infrastructure construction on emerging industry chain development at the city-level, this paper seeks to portray the spatiotemporal development characteristics of new-type infrastructure construction and artificial intelligence industry chain development in major cities of China from 2011 to 2022, and to reveal the spatiotemporal heterogeneous influences of new-type infrastructure construction on artificial intelligence industry chain development. It is found as follows. ➀ Since 2011, the new-type infrastructure construction and artificial intelligence industry chain of major cities in China have achieved rapid development, forming spatial agglomeration in nationally central cities and core cities of high-level urban agglomerations. ➁ It is empirically verified that new-type infrastructure construction effectively facilitates the development of artificial intelligence industry chain in cities of China, with the most powerful promotion effects at the downstream activities, followed by the midstream and upstream activities, and the promotion effect is strengthened over time. ➂ The promotion effects of new-type infrastructure construction on artificial intelligence industry chain development of cities in China are highly agglomerated in the eastern coastal areas as well as national-level core urban agglomerations. The degree of spatial heterogeneity across urban agglomerations with different development stages exceeds that across Eastern, Central, and Western regions. It is highlighted that the first-tier urban agglomerations in China are functioning as the key spatial carriers for new-type infrastructure to empower artificial intelligence industry chain development at city-level. [ABSTRACT FROM AUTHOR]

Inverse tone mapping technique is widely used to restore the lost textures from a single low dynamic range image. Recently, many stack‐based deep inverse tone mapping networks have achieved impressive results by estimating a set of multi‐exposure images from a single low dynamic range input. However, there are still some limitations. On the one hand, these methods usually set a fixed length for the estimated multi‐exposure stack, which may introduce computational redundancy or cause inaccurate results. On the other hand, they neglect that the difficulties of estimating each exposure value are different and use the identical model to increase or decrease exposure value. To solve these problems, the authors design an exposure decision network to adaptively determine the number of times the exposure of low dynamic range input should be increased or decreased. Meanwhile, the authors decouple the increasing/decreasing process into two sub‐modules, exposure adjustment and optional detail recovery, based on the characteristics of different variations of exposure values. With these improvements, this method can fast and flexibly estimate the multi‐exposure stack from a single low dynamic range image. Experiments on several datasets demonstrate the advantages of the proposed method compared to state‐of‐the‐art inverse tone mapping methods. [ABSTRACT FROM AUTHOR]