Evaluation of the urban industrial coupling strategy based on the global production networks theory: A case study of the smart phone industry in the Guangdong-Hong Kong-Macao Greater Bay Area.

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.

Analysis of railway accessibility in Fujian Province and the influence of economic development on its spatial differentiation.

Understanding railway accessibility supports railway regulation and development, but few studies consider different perspectives. We study the spatial distribution of accessibility indicators at the county (city) scale in Fujian Province by spatiotemporal syntax and weighted average travel time using railway timetable data. Export trade, rich commercial activities, and high-speed rail had a significant positive effect on objective accessibility. Fuzhou, Sanming, and Longyan were main transfer centers. The most accessible nodes based on weighted average travel time formed a "U"-shaped corridor along the coast. The county-wide average accessibility was 1.72 h. According to spatiotemporal syntax, local general public budget expenditure (0.758993) and export volume of goods-total retail sales of consumer goods (0.956257) had the most interactive impact, while according to weighted average accessibility, import volume of goods (0.618447) and per capita gross regional product-import volume of goods (0.878573) did. These results provide reference for transportation planning and regional development in Fujian Province.

Clinical Severity of SARS-CoV-2 Variants during COVID-19 Vaccination: A Systematic Review and Meta-Analysis.

Due to the variation in the SARS-CoV-2 virus, COVID-19 exhibits significant variability in severity. This presents challenges for governments in managing the allocation of healthcare resources and prioritizing health interventions. Clinical severity is also a critical statistical parameter for researchers to quantify the risks of infectious disease, model the transmission of COVID-19, and provide some targeted measures to control the pandemic. To obtain more accurate severity estimates, including confirmed case-hospitalization risk, confirmed case-fatality risk, hospitalization-fatality risk, and hospitalization-ICU risk, we conducted a systematic review and meta-analysis on the clinical severity (including hospitalization, ICU, and fatality risks) of different variants during the period of COVID-19 mass vaccination and provided pooled estimates for each clinical severity metric. All searches were carried out on 1 February 2022 in PubMed for articles published from 1 January 2020 to 1 February 2022. After identifying a total of 3536 studies and excluding 3523 irrelevant studies, 13 studies were included. The severity results show that the Delta and Omicron variants have the highest (6.56%, 0.46%, 19.63%, and 9.06%) and lowest severities (1.51%, 0.04%, 6.01%, and 3.18%), respectively, according to the four clinical severity metrics. Adults over 65 have higher severity levels for all four clinical severity metrics.

Evaluation of the industrial cooperation of the Guangdong Hong Kong Macao Greater Bay Area: Based on the Origin-Destination pairs of industrial parks and coupling model efficiency.

The industrial cooperation of Guangdong Hong Kong Macao Greater Bay Area (GBA) is one of the leading regional development strategies of this world-class urban agglomeration. This study constructed the industrial cooperation network based on the travel Origin-Destination (OD) connections among industrial parks. A multi-dimensional industrial cooperation and industrial development calculation index system were also set up to measure the nonlinear interaction relationship between them. The research found that an industrial collaboration network has been basically formed in the GBA, particularly presented by major cities. Some undeveloped cities may receive more benefits in the industrial collaboration network. The Covid-19 pandemic has had an impact in terms of within city connection instead of cross-city industrial cooperation. In addition, the degree of coupling between urban industrial coordination and urban industrial development has improved significantly over one decade and taking industrial collaboration as the input variables, industrial collaboration efficiently leads to industrial development outputs in almost every city in the GBA. Practically, decision makers should encourage and support intercity industrial collaboration, particularly between cities with closer geographic proximity, as it has been found to result in stronger cooperation and better economic enhancement. In addition, although industrial collaboration does not guarantee industrial development, when the collaboration systems and policies are enhanced, the synergy and coordination between them gradually improve. This highlights the potential benefits of continued investment in industrial collaboration for economic development.

Spatiotemporal evolution and characteristics of worldwide life expectancy.

Exploring global differences in life expectancy can facilitate the development of strategies to narrow regional disparities. However, few researchers have systematically examined patterns in the evolution of worldwide life expectancy over a long time period. Spatial differences among 181 countries in 4 types of worldwide life expectancy patterns from 1990 to 2019 were investigated via geographic information system (GIS) analysis. The aggregation characteristics of the spatiotemporal evolution of life expectancy were revealed by local indicators of spatial association. The analysis employed spatiotemporal sequence-based kernel density estimation and explored the differences in life expectancy among regions with the Theil index. We found that the global life expectancy progress rate shows upward then downward patterns over the last 30 years. Female have higher rates of spatiotemporal progression in life expectancy than male, with less internal variation and a wider spatial aggregation. The global spatial and temporal autocorrelation of life expectancy shows a weakening trend. The difference in life expectancy between male and female is reflected in both intrinsic causes of biological differences and extrinsic causes such as environment and lifestyle habits. Investment in education pulls apart differences in life expectancy over long time series. These results provide scientific guidelines for obtaining the highest possible level of health in countries around the world.

The Nonlinear Impact of Mobile Human Activities on Vegetation Change in the Guangdong-Hong Kong-Macao Greater Bay Area.

Vegetation is essential for ecosystem function and sustainable urban development. In the context of urbanization, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), as the typical urban-dominated region, has experienced a remarkable increase in social and economic activities. Their impact on vegetation is of great significance but unclear, as interannual flow data and linear methods have limitations. Therefore, in this study, we used human and vehicle flow data to build and simulate the indices of mobile human activity. In addition, we used partial least squares regression (PLSR), random forest (RF), and geographical detector (GD) models to analyze the impact of mobile human activities on vegetation change. The results showed that indices of mobile human and vehicle flow increased by 1.43 and 7.68 times from 2000 to 2019 in the GBA, respectively. Simultaneously, vegetation increased by approximately 64%, whereas vegetation decreased mainly in the urban areas of the GBA. Vegetation change had no significant linear correlation with mobile human activities, exhibiting a regression coefficient below 0.1 and a weight of coefficients of PLSR less than 40 between vegetation change and all the factors of human activities. However, a more significant nonlinear relationship between vegetation change and driving factors were obtained. In the RF regression model, vegetation decrease was significantly affected by mobile human activity of vehicle flow, with an importance score of 108.11. From the GD method, vegetation decrease was found to mainly interact with indices of mobile human and vehicle inflow, and the highest interaction force was 0.82. These results may support the attainment of sustainable social-ecological systems and global environmental change.

Predicting the minimum scale of urban ecological space based on socio-ecological systems analysis.

Determining the minimum scale of ecological space that is sufficient for sustainable urban development is one of the difficult tasks in quantitative urban ecological research. In this study, we first expounded on the basic concept of the minimum scale of urban ecological space and reviewed the research status. Supported by the theory of "aggregation and dispersion" in landscape ecology, we converted the task of scale prediction into spatial accounting-oriented scenario simulation. We then proposed a method to predict the scale, based on an analysis of socio-ecological systems, and constructed a research framework of "construction constraint analysis - ecological importance evaluation scale prediction." The rules to discriminate the optimal scenario and the characteristics indices of the network were also proposed. Second, we selected Shenzhen City as a representative study object and constructed 87 ecological networks under different scenarios, based on the construction constraints and spatial distribution of ecosystem services, identified from the multi-source data in the study area. By calculating and comparing the network efficiency and clustering coefficient, we concluded that the network under the m39 scenario has the optimal connection efficiency and structural stability. We finally obtained a threshold of 48.85 % as the minimum proportion of ecological land in Shenzhen. We expect that this result can help improve the rationality of decision-making in urban spatial planning and governance.

An integrated cognitive framework for understanding modern cities.

Modern urban development urgently requires a new management concept and operational mechanism to encourage the exploration of frameworks for cognizing and studying urban characteristics. In the present study, modern cities are first understood from the perspective of their basic theoretical evolution. Each modern city is seen as a complex system of organic life forms. Urban information science propels modern urban research in the direction of rationality. This paper also presents the new characteristics of modern cities (and how they have changed) in relation to external structure and internal functions. It examines the generation of urban problems and governance adaptability. On this basis, this paper proposes a cognitive model for studying modern cities, integrating basic theoretical, methodological support, and governance systems. It discusses the basic rationale and core idea for constructing each of these three systems. The research aims to guide and implement modern urban construction and sustainable development in a more effective way.

Optimizing COVID-19 surveillance using historical electronic health records of influenza infections.

Targeting surveillance resources toward individuals at high risk of early infection can accelerate the detection of emerging outbreaks. However, it is unclear which individuals are at high risk without detailed data on interpersonal and physical contacts. We propose a data-driven COVID-19 surveillance strategy using Electronic Health Record (EHR) data that identifies the most vulnerable individuals who acquired the earliest infections during historical influenza seasons. Our simulations for all three networks demonstrate that the EHR-based strategy performs as well as the most-connected strategy. Compared to the random acquaintance surveillance, our EHR-based strategy detects the early warning signal and peak timing much earlier. On average, the EHR-based strategy has 9.8 days of early warning and 13.5 days of peak timings, respectively, before the whole population. For the urban network, the expected values of our method are better than the random acquaintance strategy (24% for early warning and 14% in-advance for peak time). For a scale-free network, the average performance of the EHR-based method is 75% of the early warning and 109% in-advance when compared with the random acquaintance strategy. If the contact structure is persistent enough, it will be reflected by their history of infection. Our proposed approach suggests that seasonal influenza infection records could be used to monitor new outbreaks of emerging epidemics, including COVID-19. This is a method that exploits the effect of contact structure without considering it explicitly.

Circulating MMP-12 as Potential Biomarker in Evaluating Disease Severity and Efficacy of Sublingual Immunotherapy in Allergic Rhinitis.

Background: Allergic rhinitis (AR) is a highly heterogeneous disease, and allergen-specific immunotherapy (AIT) is an effective treatment. This study aims to evaluate the circulating mas-related G protein-coupled receptor-X2 (MRGPRX2) and matrix metalloproteinase-12 (MMP-12) levels in evaluating disease severity and predicting efficacy of SLIT in AR patients. Methods: We enrolled 110 moderate-severe persist AR patients (AR group) and 40 healthy controls (HC group). Circulating levels of MRGPRX2 and MMP-12 were measured, and their associations with disease severity were evaluated. All AR patients were assigned to receive sublingual immunotherapy (SLIT), and the efficacy was evaluated, and serum samples were collected at 1 year and 3 years after treatment. The correlations between serum MRGPRX2 and MMP-12 and clinical efficacy were assessed. Results: The serum concentrations of MRGPRX2 and MMP-12 were significantly higher in the AR group than the HC group, and the elevated MMP-12 levels were correlated with VAS and TNSS, and serum MRGPRX2 levels were correlated with VAS. Finally, 100 and 80 patients completed 1-year and 3-year follow-up and were classified into effective and ineffective groups. Serum MRGPRX2 and MMP-12 levels were lower in the effective group than the ineffective group. Although serum MRGPRX2 and MMP-12 levels did not significantly change after 1 year SLIT, serum MMP-12 levels were decreased 3 years post-SLIT than baseline and 1 year post-SLIT levels. Receiver operating characteristic (ROC) showed that serum MMP-12 was a potential biomarker for predicting the efficacy of SLIT. Conclusion: Serum MRGPRX2 and MMP-12 appeared to be promising biological indicators in reflecting disease severity in AR patients. Moreover, circulating MMP-12 might serve as a reliable predictor for clinical responsiveness of SLIT.

A diagrammatic method for the identification and resolution of urban spatial conflicts.

Spatial conflicts are formed in the process of urbanization and become the primary drivers of urban ecological and environmental problems. The defining trait of a spatial conflict is the occupation of ecological or agricultural spaces by construction spaces. This work presents a classification scheme for spatial conflicts in China, including source-area conflicts, corridor conflicts, safety conflicts, and farmland conflicts. Also, it constructs a model for the determination of spatial conflicts and conflict intensity using diagrammatic method. Based on a case study performed using our methods on Shenzhen, we proposed a timeline and policy roadmap for the resolution of spatial conflicts in Shenzhen according to the severity and characteristics of spatial conflicts in the city. The results show that the total spatially conflicted area of Shenzhen is 10.57 km2, and the percentage of construction land-use in these areas is 1.37%. The spatial conflicts are mainly source-area or corridor conflicts, and minor conflicts account for approximately 60% of the total conflicted area. Most of the spatial conflicts are either "easy to resolve" or "moderately easy to resolve". Overall, in terms of the severity of spatial conflict, Shenzhen remains at the "stable and under control" level. Considering the primary aim of spatial conflict resolution is to revert built-up lands into urban green spaces, we proposed a timeline for the resolution of spatial conflicts in Shenzhen over the next 15 years, as well as a system of supporting policies. The results of this study shall serve as a guide for the optimization of urban spatial structures and the promotion of sustainable urban development.

Evaluations of Spatial Accessibility and Equity of Multi-Tiered Medical System: A Case Study of Shenzhen, China.

The Chinese government has implemented a medical system reform to improve the equity of healthcare resources since 2009. We selected Shenzhen as our study area and evaluated the accessibility and equity of the multi-tiered medical system in China using a novel multi-tiered two-step floating catchment area (MT2SFCA) method. We proposed the benchmark and applied the independent variables of travel time and facility attractiveness, along with a combination of the two factors, as tolerances to determine the new logistic cumulative distribution decay functions. Community health centers (CHCs) and hospitals were included while integrating their features. Results revealed that the MT2SFCA method was able to determine the particular advantages of CHCs and hospitals in the multi-tiered medical system. The CHCs offset the lower accessibility of hospitals in suburban areas and hospitals balanced the regional inequity caused by the CHC. Travel time is the main consideration of patients who have access to CHCs, whereas facility features are the main considerations of patients who have access to hospitals. Notably, both CHCs and hospitals are crucial for the whole multi-tiered medical system. Finally, we suggested modifications in different travel modes, weights of contributing factors, and the validation of decay functions to improve the MT2SFCA method.

Spatiotemporal Transmission Patterns and Determinants of Dengue Fever: A Case Study of Guangzhou, China.

Dengue fever is one of the most common vector-borne diseases in the world and is mainly affected by the interaction of meteorological, human and land-use factors. This study aims to identify the impact of meteorological, human and land-use factors on dengue fever cases, involving the interplay between multiple factors. The analyses identified the statistically significant determinants affecting the transmission of dengue fever, employing cross-correlation analysis and the geo-detector model. This study was conducted in Guangzhou, China, using the data of confirmed cases of dengue fever, daily meteorological records, population density distribution and land-use distribution. The findings highlighted that the dengue fever hotspots were mainly distributed in the old city center of Guangzhou and were significantly shaped by meteorological, land-use and human factors. Meteorological factors including minimum temperature, maximum temperature, atmospheric pressure and relative humidity were correlated with the transmission of dengue fever. Minimum temperature, maximum temperature and relative humidity presented a statistically significant positive correlation with dengue fever cases, while atmospheric pressure presented statistically significant negative correlation. Minimum temperature, maximum temperature, atmospheric pressure and humidity have lag effects on the transmission of dengue fever. The population, community age, subway network density, road network density and ponds presented a statistically significant positive correlation with the number of dengue fever cases, and the interaction among land-use and human factors could enhance dengue fever transmission. The ponds were the most important interaction factors, which might strengthen the influence of other factors on dengue fever transmission. Our findings have implications for pre-emptive dengue fever control.

Fast and Automatic Reconstruction of Semantically Rich 3D Indoor Maps from Low-quality RGB-D Sequences.

Semantically rich indoor models are increasingly used throughout a facility's life cycle for different applications. With the decreasing price of 3D sensors, it is convenient to acquire point cloud data from consumer-level scanners. However, most existing methods in 3D indoor reconstruction from point clouds involve a tedious manual or interactive process due to line-of-sight occlusions and complex space structures. Using the multiple types of data obtained by RGB-D devices, this paper proposes a fast and automatic method for reconstructing semantically rich indoor 3D building models from low-quality RGB-D sequences. Our method is capable of identifying and modelling the main structural components of indoor environments such as space, wall, floor, ceilings, windows, and doors from the RGB-D datasets. The method includes space division and extraction, opening extraction, and global optimization. For space division and extraction, rather than distinguishing room spaces based on the detected wall planes, we interactively define the start-stop position for each functional space (e.g., room, corridor, kitchen) during scanning. Then, an interior elements filtering algorithm is proposed for wall component extraction and a boundary generation algorithm is used for space layout determination. For opening extraction, we propose a new noise robustness method based on the properties of convex hull, octrees structure, Euclidean clusters and the camera trajectory for opening generation, which is inapplicable to the data collected in the indoor environments due to inevitable occlusion. A global optimization approach for planes is designed to eliminate the inconsistency of planes sharing the same global plane, and maintain plausible connectivity between the walls and the relationships between the walls and openings. The final model is stored according to the CityGML3.0 standard. Our approach allows for the robust generation of semantically rich 3D indoor models and has strong applicability and reconstruction power for complex real-world datasets.

Insulator string leakage current-monitoring sensor based on fiber Bragg grating.

A novel insulator string leakage current-monitoring sensor based on a fiber Bragg grating (FBG), cantilever beam, and spiral coil is demonstrated. The spiral coil is used to convert the leakage current into the force exerted on the cantilever structure, which is obtained by measuring the strain of the FBG. Experimental results show that the linear regression correlation coefficient is 0.99964. In addition, although the leakage current measurement is not sufficiently accurate, the 50-Hz component measurement is accurate. The sensor is suitable for use as an insulator string flashover warning and has promising prospects for future grid security protection applications.

Geometric Integration of Hybrid Correspondences for RGB-D Unidirectional Tracking.

Traditionally, visual-based RGB-D SLAM systems only use correspondences with valid depth values for camera tracking, thus ignoring the regions without 3D information. Due to the strict limitation on measurement distance and view angle, such systems adopt only short-range constraints which may introduce larger drift errors during long-distance unidirectional tracking. In this paper, we propose a novel geometric integration method that makes use of both 2D and 3D correspondences for RGB-D tracking. Our method handles the problem by exploring visual features both when depth information is available and when it is unknown. The system comprises two parts: coarse pose tracking with 3D correspondences, and geometric integration with hybrid correspondences. First, the coarse pose tracking generates the initial camera pose using 3D correspondences with frame-by-frame registration. The initial camera poses are then used as inputs for the geometric integration model, along with 3D correspondences, 2D-3D correspondences and 2D correspondences identified from frame pairs. The initial 3D location of the correspondence is determined in two ways, from depth image and by using the initial poses to triangulate. The model improves the camera poses and decreases drift error during long-distance RGB-D tracking iteratively. Experiments were conducted using data sequences collected by commercial Structure Sensors. The results verify that the geometric integration of hybrid correspondences effectively decreases the drift error and improves mapping accuracy. Furthermore, the model enables a comparative and synergistic use of datasets, including both 2D and 3D features.

Spatio-Temporal Pattern of the Urban System Network in the Huaihe River Basin Based on Entropy Theory.

As complex systems, the spatial structure of urban systems can be analyzed by entropy theory. This paper first calculates the interaction force between cities based on the gravity model, the spatial relationship matrix between cities is constructed using the method of network modeling, and the spatial network modeling of urban system can be calculated. Secondly, the Efficiency Entropy (EE), Quality Entropy (QE), and System Entropy (SE) of urban system network are calculated and analyzed by information entropy. Finally, taking the Huaihe River Basin (HRB) as a case study, model verification and empirical analysis are performed. It is found that the spatio-temporal pattern of the urban system network structure in the basin is uneven: in space, the urban system network in the HRB presents a layer-by-layer spatial distribution centered on the core city of Xuzhou; meanwhile, the overall urban system network in the basin presents an orderly development trend. This study has certain theoretical and practical value for the planning of urban and urban systems and the coordinated development of regions.

Ecological control line: A decade of exploration and an innovative path of ecological land management for megacities in China.

Ecological control line is a system innovation in the field of ecological environment protection in China and it has become as an important strategy of national ecological protection. Ten years have passed since the first ecological control line in Shenzhen was delimited in 2005. This study examines the connotations of ecological control line and the current study status in China and abroad, and then takes a brief description about the delimitation background and existing problems of the ecological control line in Shenzhen. The problem-solving strategy is gradually transforming from extensive management to refined management. This study proposes a differential ecological space management model that merges the space system, management system, and support system. The implementation paths include the following five aspects: delimiting ecological bottom lines to protect core ecological resources; formulating access systems for new construction projects to strictly control new construction; implementing construction land inventory reclamation assisted by market means; regulating boundary adjusting procedures and processes; and constructing ecological equity products by using multiple means to implement rights relief. Finally, this study illustrates the progress of the implementation and discusses the rigorousness and flexibility problems of ecological control line and calls for the promotion of the legislation. The management model and implementation paths proposed in this study have referential significance for developing countries and megacities to achieve ecological protection and sustainable development.