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The accurate extraction of urban residential space (URS) is of great significance for recognizing the spatial structure of urban function, understanding the complex urban operating system, and scientific allocation and management of urban resources. The traditional URS identification process is generally conducted through statistical analysis or a manual field survey. Currently, there are also superpixel segmentation and wavelet transform (WT) processes to extract urban spatial information, but these methods have shortcomings in extraction efficiency and accuracy. The superpixel wavelet fusion (SWF) method proposed in this paper is a convenient method to extract URS by integrating multi-source data such as Point of Interest (POI) data, Nighttime Light (NTL) data, LandScan (LDS) data, and High-resolution Image (HRI) data. This method fully considers the distribution law of image information in HRI and imparts the spatial information of URS into the WT so as to obtain the recognition results of URS based on multi-source data fusion under the perception of spatial structure. The steps of this study are as follows: Firstly, the SLIC algorithm is used to segment HRI in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) urban agglomeration. Then, the discrete cosine wavelet transform (DCWT) is applied to POI–NTL, POI–LDS, and POI–NTL–LDS data sets, and the SWF is carried out based on different superpixel scale perspectives. Finally, the OSTU adaptive threshold algorithm is used to extract URS. The results show that the extraction accuracy of the NLT–POI data set is 81.52%, that of the LDS–POI data set is 77.70%, and that of the NLT–LDS–POI data set is 90.40%. The method proposed in this paper not only improves the accuracy of the extraction of URS, but also has good practical value for the optimal layout of residential space and regional planning of urban agglomerations. [ABSTRACT FROM AUTHOR]

The informational domain related to COVID-19 reflects the degree of uncertainty and pace of evolution of the pandemic. This places a burden on peoples' searches for information to guide their choices, importantly including for COVID-19 vaccines. Thus, it is important for health communications that support vaccination campaigns to attenuate vaccine hesitancy to be accessible, including in terms of readability, and adapted to the evolving pandemic. This paper aims to understand internet searches on COVID-19 vaccination, specifically the mix of sources and readability of the sources over a two-year period (2021–2023) in Singapore, Hong Kong, and the Philippines, for search results in English, as English is a main language for each of these locations. The sources accessed through online searches in June 2021 and May 2023 were categorized by type of source and whether they were from one of the focal locations or elsewhere. The readability of information from web-search results was assessed using a set of readability tests (Flesch–Kincaid Reading Ease, Flesch–Kincaid Grade Level, Gunning Fog Index, Coleman–Liau Index, and Simple Measure of Gobbledygook Grade level). Over the two-year period there was an increase in government sources and reduction in mass media sources with distinct local patterns. Local government sources increased in Singapore whereas foreign government and multi-lateral organization sources increased in Hong Kong, with the Philippines being an intermediate pattern. In contrast to the changing mix of sources, the readability tests indicate a low proportion of URLs scoring within recommended readability thresholds across locations and types of sources over the two years. Information on COVID-19 vaccine development and deployment is an important part of health communications that includes internet search. The paper contributes to understanding health communications during a pandemic, including mix of local and non-local sources and contingency on local social and health context. [ABSTRACT FROM AUTHOR]

This paper examines the role of standard block and modular dwelling designs in Hong Kong's public housing provision since the mid-1950s. It explores how standard types have evolved in relation to housing policies, demographic and socio-economic changes, and minimum space requirements. In contrast to other countries, Hong Kong lacks defined space or room standards. In the absence of space standards, Hong Kong relies on a living density standard. This paper studies the historical development of Hong Kong's public housing in terms of dwelling size as a measure of housing quality, questioning the effectiveness of standard block and dwelling designs as housing design controls and highlighting the contextual nature of dwelling usability and size. The analysis is based on public housing design projects, policies, and data implemented or presented by the Hong Kong government, particularly the Hong Kong Housing Authority. [ABSTRACT FROM AUTHOR]

Super Typhoon Saola (2309) skirted past south-southeast of Hong Kong within 40 km on the night of 1 September 2023, posing a significant storm surge threat to Hong Kong. Given the close proximity of Saola with a peak intensity of about 210 km/h within 300 km of Hong Kong, a close call of the "super typhoon direct-hit" scenario, this case provides valuable insights from a hindcast review of storm surge forecasts and warning operation using the Sea, Lake and Overland Surges from Hurricanes (SLOSH) model, which is the operational storm surge model adopted by the Hong Kong Observatory (HKO). The performance of the HKO's PRobabilistic Inundation Map Evaluation System (PRIMES) using both statistical and model ensemble approaches was also reviewed in this paper. Saola was a challenging case for operational forecasting of a compact TC structure with changes in storm size and intensity when it came close to Hong Kong. With major observations of storm structure using weather radar and dense automatic weather station, tide gauge and water level gauge networks, the high sensitivity of storm surge forecasts to the storm size parameter and the distance of closest approach was clearly revealed in the case of Saola. Even with a circularly symmetric TC parametric model like SLOSH, the hindcast review results illustrated that the model outputs were reasonably accurate during the closest approach of Saola given an accurate storm size and distance of closest approach were input, and using a highly computationally efficient storm surge model made it possible for the nowcasting of storm surges to handle compact and intense TC direct-hit cases in operational TC forecasting. Taking a nowcasting approach not only helps provide more reliable storm tide forecasts, but also facilitates the formulation of a better warning strategy when making final-call decisions in emergency response actions, based on the more frequent real-time analysis of TC position, intensity and storm size and the more accurate prediction of these parameters. A nowcasting workflow for storm surge operation was proposed in this paper. [ABSTRACT FROM AUTHOR]

This paper takes the freezing project of the North Arch Tunnel of the Hong Kong–Zhuhai–Macao Bridge as an example. Based on Darcy's law and the theory of heat transfer in porous media, using the coupled module of the temperature field and seepage field in the COMSOL Multiphysics software, numerical simulations of the freezing reinforcement of the new pipe curtain freezing method are conducted to study the influence of different factors on this method under seepage conditions. The research shows that an increase in the groundwater flow velocity will affect the development of frozen soil curtains, prolonging the formation time of frozen soil curtains. A rise in the initial ground temperature will increase the time required for the formation of frozen soil curtains during the freezing process, resulting in a slight increase in the temperature of the final frozen soil curtains. With an increase in the salinity of the groundwater, the temperature at the temperature measurement point upstream of the freezing pipe increases, while the temperature at the temperature measurement point downstream of the freezing pipe decreases. The average temperature of the frozen soil curtain also increases with an increase in the salinity of the groundwater. This study is expected to provide a valuable reference for similar projects in the future. [ABSTRACT FROM AUTHOR]

A novel insulated gate bipolar transistor with Semi-Insulated POly Silicon (SIPOS) is presented in this paper and analyzed through TCAD simulation. In the off state, the SIPOS-IGBT can obtain a uniform electric field distribution, which enables a thinner drift region under the same breakdown voltage. In the on state, an electron accumulation layer is formed along the SIPOS, which can increase the injection level of the "PiN region" in the device, and the carrier concentration in the drift region is also increased due to the charge balance effect. Moreover, the SIPOS-IGBT can achieve a quick and thorough depletion in the drift region during the turn-off transient, which can greatly reduce the turn-off loss of the SIPOS-IGBT. These advantages improve the tradeoff between the conduction and switching losses. According to the simulation results, the SIPOS-IGBT obtained a 58% lower turn loss than that of a field-stop (FS) IGBT and 30% lower than an HK-IGBT with the same on-state voltage. [ABSTRACT FROM AUTHOR]

As one of the four major bay areas in the world, the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is a highly integrated mega urban agglomeration and its unparalleled urbanization has induced prominent land contradictions between humans and nature, which hinders its sustainability and has become the primary concern in this region. In this paper, we probed the historical characteristics of land use and land cover change (LUCC) in the GBA from 2005 to 2015, and forecasted its future land use pattern for 2030, 2050, and 2070, using a cellular automata–Markov (CA–Markov) model, under three typical tailored scenarios, i.e., urban development (UD), cropland protection (CP), and ecology security (ES), for land use optimization. The major findings are as follows: (1) The encroachments of build-up land on the other land uses under rapid urbanization accounted for the leading forces of LUCCs in the past decade. Accordingly, the urban sprawl was up to 1441.73 km2 (23.47%), with cropland, forest land, and water areas reduced by 570.77 km2 (4.38%), 526.05 km2 (1.76%), and 429.89 km2 (10.88%), respectively. (2) Based on the validated CA–Markov model, significant differences are found in future land use patterns under multiple scenarios, with the discrepancy magnified over time and driven by different orientations. (3) Through comprehensive comparisons and tradeoffs, the ES scenario mode seems optimal for the GBA in the next decades, which optimizes the balance between socio-economic development and ecological protection. These results serve as an early warning for future land problems and can be applied to land use management and policy formulation to promote the sustainable development of the GBA. [ABSTRACT FROM AUTHOR]

Chlorophyll-a (Chl-a) concentration monitoring is very important for managing water resources and ensuring the stability of marine ecosystems. Due to their high operating efficiency and high prediction accuracy, backpropagation (BP) neural networks are widely used in Chl-a concentration inversion. However, BP neural networks tend to become stuck in local optima, and their prediction accuracy fluctuates significantly, thus posing restrictions to their accuracy and stability in the inversion process. Studies have found that metaheuristic optimization algorithms can significantly improve these shortcomings by optimizing the initial parameters (weights and biases) of BP neural networks. In this paper, the adaptive nonlinear weight coefficient, the path search strategy "Levy flight" and the dynamic crossover mechanism are introduced to optimize the three main steps of the Artificial Ecosystem Optimization (AEO) algorithm to overcome the algorithm's limitation in solving complex problems, improve its global search capability, and thereby improve its performance in optimizing BP neural networks. Relying on Google Earth Engine and Google Colaboratory (Colab), a model for the inversion of Chl-a concentration in the coastal waters of Hong Kong was built to verify the performance of the improved AEO algorithm in optimizing BP neural networks, and the improved AEO algorithm proposed herein was compared with 17 different metaheuristic optimization algorithms. The results show that the Chl-a concentration inversion model based on a BP neural network optimized using the improved AEO algorithm is significantly superior to other models in terms of prediction accuracy and stability, and the results obtained via the model through inversion with respect to Chl-a concentration in the coastal waters of Hong Kong during heavy precipitation events and red tides are highly consistent with the measured values of Chl-a concentration in both time and space domains. These conclusions can provide a new method for Chl-a concentration monitoring and water quality management for coastal waters. [ABSTRACT FROM AUTHOR]

Rapid urbanisation has generated numerous environmental consequences, particularly regarding open space fragmentation. Open space fragmentation is the transformation of open space from a state of homogeneity, integration, and continuity to a state of heterogeneity, division, and incoherence. Nevertheless, one main obstacle to understanding this issue is how to address the spatial heterogeneity of the impact of urbanisation on open space fragmentation. Thus, this paper provides a comprehensive framework for the mechanistic associations between open space fragmentation and urbanisation in Hong Kong's built-up area. The results illustrate that both open space fragmentation index and urbanisation index values are noticeably higher in dense urban areas. Land urbanisation, represented by the percentage of construction land in total land, has the highest explanatory power for spatial differentiation in open space fragmentation, followed by social and population urbanisation factors. Furthermore, the relational interrelations of open space fragmentation drivers are the bivariate and nonlinear enhancement interactions. Social urbanisation and land urbanisation have the strongest bivariate enhancement interaction for the use fragmentation form and the largest nonlinear enhancement interaction for the internal fragmentation form. Based on initial urban planning, open space fragmentation is an adaptation outcome of population, land, and social urbanisation factors, and this self-organisation phenomenon has been further emphasised in the historical process. These insights significantly enrich our understanding of how urbanisation affects open space fragmentation and provide valuable guidance for better open space strategies. [ABSTRACT FROM AUTHOR]

In order to accomplish the calibration and validation (Cal/Val) of altimeters, the Wanshan calibration site (WSCS) has been used as a calibration site for satellite altimeters since its completion in August 2019. In this paper, we introduced the WSCS and the dedicated equipment including permanent GNSS reference stations (PGSs), acoustic tide gauges (ATGs), and dedicated GNSS buoys (DGB), etc. placed on Zhi'wan, Wai'ling'ding, Dan'gan, and Miao'Wan islands of the WSCS. The PGSs data of Zhi'wan and Wai'ling'ding islands were processed and analyzed using the GAMIT/GLOBK (Version 10.7) and Hector (Version 1.9) software to define the datum for Cal/Val of altimeters in WSCS. The DGB was used to transfer the datum from the PGSs to the ATGs of Zhi'wan, Wai'ling'ding, and Dan'gan islands. Separately, the tidal and mean sea surface (MSS) corrections are needed in the Cal/Val of altimeters. We evaluated the global/regional tide models of FES2014, HAMTIDE12, DTU16, NAO99jb, GOT4.10, and EOT20 using the three in situ tide gauge data of WSCS and Hong Kong tide gauge data (No. B329) derived from the Global Sea Level Observing System. The HAMTIDE12 tide model was chosen to be the most accurate one to maintain the tidal difference between the locations of the ATGs and the altimeter footprints. To establish the sea surface connections between the ATGs and the altimeter footprints, a GPS towing body and a highly accurate ship-based SSH measurement system (HASMS) were used to measure the sea surface of this area in 2018 and 2022, respectively. The global/regional mean sea surface (MSS) models of DTU 2021, EGM 2008 (mean dynamic topography minus by CLS_MDT_2018), and CLS2015 were accurately evaluated using the in situ measured data and HY-2A altimeter, and the CLS2015 MSS model was used for Cal/Val of altimeters in WSCS. The data collected by the equipment of WSCS, related auxiliary models mentioned above, and the sea level data of the hydrological station placed on Dan'gan island were used to accomplish the Cal/Val of HY-2B, HY-2C, Jason-3, and Sentinel-3A (S3A) altimeters. The bias of HY-2B (Pass No. 375) was −16.7 ± 45.2 mm, with a drift of 0.5 mm/year. The HY-2C biases were −18.9 ± 48.0 mm with drifts of 0.0 mm/year and −5.6 ± 49.3 mm with −0.3 mm/year drifts for Pass No. 170 and 185, respectively. The Jason-3 bias was −4.1 ± 78.7 mm for Pass No. 153 and −25.8 ± 85.5 mm for Pass No. 012 after it has changed its orbits since April 2022, respectively. The biases of S3A were determined to be −16.5 ± 46.3 mm with a drift of −0.6 mm/year and −9.8 ± 30.1 mm with a drift of 0.5 mm/year for Pass No. 260 and 309, respectively. The calibration results show that the WSCS can commercialize the satellite altimeter calibration. We also discussed the calibration potential for a wide swath satellite altimeter of WSCS. [ABSTRACT FROM AUTHOR]

In this study, the ill-conditioning of the iterative method for nonlinear models is discussed. Due to the effectiveness of ridge estimation for ill-conditioned problems and the lack of a combination of the H-K formula with the iterative method, the improvement of the LM algorithm is studied in this paper. Considering the LM algorithm for ill-conditioned nonlinear least squares, an improved LM algorithm based on the H-K formula is proposed for image distortion correction using self-calibration. Three finite difference methods are used to approximate the Jacobian matrix, and the H-K formula is used to calculate the damping factor in each iteration. The Brown model, quadratic polynomial model and Fourier model are applied to the self-calibration, and the improved LM algorithm is used to solve the model parameters. In the simulation experiment of space resection of a single image, we evaluate the performance of the LM algorithm based on the gain ratio (LMh) and the improved LM algorithm based on the H-K formula (LMHK), and the accuracy of different models and algorithms is compared. A ridge trace analysis is carried out on the damping factor to illustrate the effects of the improved algorithm in handling ill-conditioning. In the second experiment, the improved algorithm is applied to measure the diameter of a coin using a single camera. The experimental results show that the improved LM algorithm can reach the same or higher accuracy as the LMh algorithm, and it can weaken the ill-conditioning to a certain extent and enhance the stability of the solution. Meanwhile, the applicability of the improved LM algorithm in self-calibration is verified. [ABSTRACT FROM AUTHOR]

The study examines the return performance and resilience to market volatility of the recently introduced environment, social/sustainable, and governance (ESG) weight-tilted Hang Seng index compared to its parent, the Hang Seng index. The ESG-infused index has a higher mean return and lower return volatility than the parent index, although the differences are statistically and economically insignificant, a result consistent with the high correlation between the two index returns. Most importantly, the ESG weight-tilted index is more resilient to volatility spikes than the parent index and, therefore, has lower downside risks. The overall results show that stocks with high ESG ratings are less susceptible to trading pressures triggered by volatility-induced turnovers. The paper contributes to the literature by providing significant incremental information on the emerging market for ESG-related equity products in Hong Kong. [ABSTRACT FROM AUTHOR]

Hong Kong was under the direct hit of Severe Typhoon Koinu (2314) on 8 and 9 October 2023, necessitating the issuance of the Increasing Gale or Storm Signal, No. 9. Koinu was a very challenging case for TC forecasting and warning services due to its compact size and erratic movement over the northern part of the South China Sea. This paper reviews the difficulties and challenges of the forecasting aspect of the severe typhoon. The predicted tropical cyclone track and intensity from both conventional models and emerging artificial intelligence models are examined, as well as local wind and rainfall forecast. Experience in this case study showed that while deterministic global models only performed moderately and were not able to adequately support early warning, a regional model and AI models could more effectively support decision making for an operational tropical cyclone warning service. [ABSTRACT FROM AUTHOR]

Increased glycolysis is a key characteristic of malignant cells that contributes to their high proliferation rates and ability to develop drug resistance. The glycolysis rate-limiting enzyme hexokinase II (HK II) is overexpressed in most tumor cells and significantly affects tumor development. This paper examines the structure of HK II and the specific biological factors that influence its role in tumor development, as well as the potential of HK II inhibitors in antitumor therapy. Furthermore, we identify and discuss the inhibitors of HK II that have been reported in the literature. [ABSTRACT FROM AUTHOR]

In response to the rapid urban expansion and the burgeoning number of landfill sites, managing water infiltration in these areas has become a critical challenge, especially in cities like Shenzhen, Hong Kong, and Singapore where traditional cover materials such as silt, clayey gravel, and sand are scarce. A three-layer (silt/gravelly sand/clay) capillary barrier cover system has been proposed to address this issue in humid climates. As an alternative to scarce traditional materials, using local soils and construction waste (CW) for this system presents a viable solution. However, the real-world performance of this adapted three-layer system, constructed with local soils and CW under natural rainfall conditions, remains to be fully evaluated. This paper presents a field test evaluating the water infiltration behavior of a three-layer capillary barrier landfill cover system under natural conditions. The tri-layered system is comprised of a 0.6 m loose local unscreened soil layer, covered by a 0.4 m CW layer and topped by a 0.8 m heavily compacted local screened soil layer. Monitoring findings reveal that, during the wet season, infiltration through the top two layers was staved off until the third rainfall, after which these layers retained moisture until 15 September 2016. The fluctuation in pore water pressure in the topmost layers showed each rainfall was contingent not only on the day's precipitation but also the hydraulic state. Beyond the hydraulic state's influence, a deeper tensiometer showed resulted in a diminished correlation between the surge in pore water pressure and daily rainfall. This declining correlation with depth can be attributed to the capillary effect and the reduced permeability of the screened soil layer. Rainfall patterns significantly affect percolation, with the combination of a short-duration, intense rainfall and prolonged weak rainfall resulting in a marked increase in percolation. In the foundational screened soil layer, the pore water pressure remained relatively low, with the cumulative percolation over six months (June to December) registering approximately 10 mm. These findings suggest a promising performance of the three-layer capillary barrier cover system, integrating local soils and CW, in the year of the study conducted in a humid environment. [ABSTRACT FROM AUTHOR]

This study uses time series regression models and dynamic panel models of five-class housing to investigate the dynamics of the housing price-vacancy relationship in Hong Kong, offering insights distinct from previous cross-sectional analyses that take new housing completions as a supply proxy, without considering vacant homes as a source of housing supply. Two major contributions emerge: first, the results support the hypothesis that housing vacancies exert a negative impact on housing prices, holding other factors constant. Second, new builds supply is found to have a positive effect on housing prices, which is in line with many previous studies, but it contradicts the prediction. The results challenge the use of land supply or new housing completions as the proxy of housing supply and put forward a novel suggestion of including vacant homes in the housing price analysis. Advanced approaches to collecting housing vacancy data are also discussed. These findings have significant implications for policymakers, urban planners, and real estate investors, providing valuable insights for crafting targeted interventions and informing investment decisions. This is one of the first time series and dynamic panel analyses of housing vacancy's effect on prices. [ABSTRACT FROM AUTHOR]

Urban parks enhance residents' quality of life and health by fostering a harmonious relationship between people and nature, so effective park design needs to prioritize ecological protection, sustainable landscapes, and practical spatial structures to achieve these benefits. This study takes the typical case of urban park renovation and reconstruction—Kowloon Walled City Park—as an example to conduct research and divides the interior of the park into four types of areas: contemporary built-up area; historical relic area; natural–folk custom area; and ecological conservation area. Based on 405 valid questionnaire data for respondents, this study conducts empirical research using a combination of the Semantic Differential (SD) method, Importance Performance Analysis (IPA) model, and unordered multivariate logit choice model, comprehensively describes and analyzes individual spatial perception and preferences, and further discusses the potential factors affecting individual perception preferences. The results show that there are differences in many characteristics between different areas in Kowloon Walled City Park. At the same time, people generally prefer park areas that integrate modern and traditional elements, natural and cultural environments, and pay attention to the balance between naturalness and sociality in park design. These results provide useful information for planners, developers, and others, as well as data for designing urban park construction with higher practical value and natural benefits. [ABSTRACT FROM AUTHOR]

Depression is one of the most prevalent mental disorders worldwide. This study examined the effect of a spiritual connectivity intervention on individuals with depression in a randomized waitlist-controlled trial. Fifty-seven participants with mild or moderate depressive symptoms were randomly assigned to either the intervention group (n = 28) or the waitlist control group (n = 29). The intervention comprised eight weekly sessions focusing on divine connection, forgiveness and freedom, suffering and transcendence, hope, gratitude, and relapse prevention. The outcome measures included depressive symptoms, anxiety, hope, meaning in life, self-esteem, and social support. Participants completed self-administered questionnaires at baseline (week 0), post-intervention (week 8), and 3-month follow-up (week 20). Repeated-measures ANOVA and one-way ANCOVA were used to compare the within-group and between-group differences in the changes in outcome variables. Participants in the intervention group showed significant improvements in depression, anxiety, spiritual experience, hope, self-esteem, and perceived social support after the intervention. Effect size statistics showed small to large differences (Cohen's d, 0.308 to −1.452). Moreover, 85.71% of participants in the intervention group also experienced clinically significant reductions in PHQ-9 scores from baseline to immediate post-intervention. This study highlights the effectiveness of a low-cost, accessible intervention suitable for community implementation by clergy and faith-based organizations. [ABSTRACT FROM AUTHOR]

The atmosphere exhibits variability across different time scales. Currently, in the field of atmospheric science, statistical filtering is one of the most widely used methods for extracting signals on certain time scales. However, signal extraction based on traditional statistical filters may be sensitive to missing data points, which are particularly common in meteorological data. To address this issue, this study applies a new type of temporal filters based on a one-dimensional convolution neural network (1D-CNN) and examines its performance on reducing such uncertainties. As an example, we investigate the advantages of a 1D-CNN bandpass filter in extracting quasi-biweekly-to-intraseasonal signals (10–60 days) from temperature data provided by the Hong Kong Observatory. The results show that the 1D-CNN achieves accuracies similar to a 121-point Lanczos filter. In addition, the 1D-CNN filter allows a maximum of 10 missing data points within the 60-point window length, while keeping its accuracy higher than 80% (R2 > 0.8). This indicates that the 1D-CNN model works well even when missing data points exist in the time series. This study highlights another potential for applying machine learning algorithms in atmospheric and climate research, which will be useful for future research involving incomplete time series and real-time filtering. [ABSTRACT FROM AUTHOR]

Estimating city–scale emissions using gridded inventories lacks direct, precise measurements, resulting in significant uncertainty. A Kalman filter integrates diverse, uncertain information sources to deliver a reliable, accurate estimate of the true system state. By leveraging multiple gridded inventories and a Kalman filter fusion method, we developed an optimal city–scale (3 km) FFCO2 emission product that incorporates quantified uncertainties and connects global–regional–city scales. Our findings reveal the following: (1) Kalman fusion post–reconstruction reduces estimate uncertainties for 2000–2014 and 2015–2021 to ±9.77% and ±11.39%, respectively, outperforming other inventories and improving accuracy to 73% compared to ODIAC and EDGAR (57%, 65%). (2) Long–term trends in the Greater Bay Area (GBA) show an upward trajectory, with a 2.8% rise during the global financial crisis and a −0.19% decline during the COVID-19 pandemic. Spatial analysis uncovers a "core–subcore–periphery" emission pattern. (3) The core city GZ consistently contributes the largest emissions, followed by DG as the second–largest emitter, and HK as the seventh–highest emitter. Factors influencing the center–shift of the pattern include the urban form of cities, population migration, GDP contribution, but not electricity consumption. The reconstructed method and product offer a reliable solution for the lack of directly observed emissions, enhancing decision–making accuracy for policymakers. [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]

Maritime transportation plays a pivotal role in the global merchandise trade. To improve maritime safety and protect the environment, every state must effectively control ships flying its flag, which is called flag state control (FSC). However, the existing FSC system is so inefficient that it cannot perform its intended function. In this study, we adopt an optimization method to tackle this problem by constructing an integer programming (IP) model to solve the FSC officer routing and scheduling problem, which aims to maximize the total weight of inspected ships with limited budget and human resources. Then we prove that the IP model can be reformulated into a partially relaxed IP model with the guarantee of the result optimality. Finally, we perform a case study using the Hong Kong port as an example. The results show that our model can be solved to optimality within one second at different scales of the problem, with the ship number ranging from 20 to 1000. Furthermore, our study can be extended by considering the arrangement of working timetables with finer granularity and the fatigue level of personnel. [ABSTRACT FROM AUTHOR]

Energy consumption is an important indicator for measuring economic development and is closely related to the atmospheric environment. As a demonstration zone for China's high-quality development, the Guangdong–Hong Kong–Macao Greater Bay Area imposes higher requirements on ecological environment and sustainable development. Therefore, accurate data on energy consumption is crucial for high-quality green development. However, the statistical data on local energy consumption in China is insufficient, and the lack of data is severe, which hinders the analysis of energy consumption at the metropolitan level and the precise implementation of energy policies. Nighttime light data have been widely used in the inversion of energy consumption, but they can only reflect socio-economic activities at night with certain limitations. In this study, a random forest model was developed to estimate metropolitan-level energy consumption in the Guangdong–Hong Kong–Macao Greater Bay Area from 2000 to 2020 based on nighttime light data, population data, and urban impervious surface data. The estimation results show that our model shows good performance with an R2 greater than 0.9783 and MAPE less than 9%. A long time series dataset from 2000 to 2020 on energy consumption distribution at a resolution of 500 m in the Guangdong–Hong Kong–Macao Greater Bay Area was built using our model with a top-down weight allocation method. The spatial and temporal dynamics of energy consumption in the Greater Bay Area were assessed at both the metropolitan and grid levels. The results show a significant increase in energy consumption in the Greater Bay Area with a clear clustering, and approximately 90% of energy consumption is concentrated in 22% of the area. This study established an energy consumption estimation model that comprehensively considers population, urban distribution, and nighttime light data, which effectively solves the problem of missing statistical data and accurately reflects the spatial distribution of energy consumption of the whole Bay Area. This study provides a reference for spatial pattern analysis and refined urban management and energy allocation for regions lacking statistical data on energy consumption. [ABSTRACT FROM AUTHOR]

Background: The rapidly aging global population has increased the demand for caregivers. Many caregivers simultaneously engage in paid employment, and the dual role makes the needs of caregiver employees conceivably more remarkable. However, there is a gap in the literature about the specific needs of caregiver employees. Method: Caregiver employees (n = 1205) across Hong Kong caring for those ≥65 years were recruited for a cross-sectional face-to-face survey from December 2021 to January 2022, to evaluate mental well-being measured by the Short Warwick –Edinburgh Mental Well-being Scale. Univariate and multivariate analyses were conducted; significant variables (p < 0.05) were included in multiple linear regression, along with caregiver-friendly workplace policies' availability, to understand their association with their mental well-being. Findings: The mean score of the Short Warwick–Edinburgh Mental Well-being Scale among caregiver employees in this study was 24.9, with 7.2% indicative of probable clinical depression and 10.0% possible mild depression. In addition, the current study showed that 30.2% of the caregiver employees felt distressed about the caregiving role. Among external factors, family support (measured by the Lubben Social Network Scale) and workplace culture (measured by the Marshall Supervision Subscale) positively correlated with mental well-being with regression coefficients of 0.252 (p < 0.001) and 0.482 (p < 0.001), respectively. In the fully adjusted model, a negative regression coefficient was observed for overall spillover (−0.050, p < 0.001) and Short Warwick–Edinburgh Mental Well-being Scale scores, while positive regression coefficients were observed for overall self-rate (0.041, p < 0.001), Lubben (0.124, p < 0.001), and corporate culture (0.365, p < 0.001). Better Short Warwick–Edinburgh Mental Well-being Scale scores were observed when caregiver-friendly workplace policies were clearly stated than when they were made on a case-by-case discretionary basis. Conclusions: Caregiver-friendly workplace policies may be critical to Hong Kong's sustainable future, both economically and socially, as they ensure a healthy and productive workforce to support an aging population. [ABSTRACT FROM AUTHOR]

Situated in the unique historical context of Hong Kong—a contact zone between East and West—this study explores how Christianity's introduction through British colonialism and missionary efforts has intertwined with and influenced Chinese cultural traditions. By examining selected works of Xu Dishan and Chen Zanyi, this study reveals the dynamic negotiations of identity and values between these two cultural and religious traditions. These literary works not only depict the complexities of cultural hybridity but also provide insights into the evolving nature of cultural identity in Hong Kong, illustrating how global religions and local traditions can merge and transform each other. This study contributes to understanding the intricate dance of religious exchange, conflict, and compromise in Hong Kong's cross-culture setting, suggesting that such literary explorations can bridge Christianity with the socio-economic, cultural, and historical fabric of Chinese society. [ABSTRACT FROM AUTHOR]

There has been an increasing awareness of indoor air quality (IAQ) management in green building designs, driven by the need to mitigate potential health risks and create sustainable and healthy indoor environments. The COVID-19 pandemic has further highlighted the critical role of ventilation and IAQ in reducing the risk of indoor airborne transmission. Governments and organisations worldwide have responded to this growing concern by implementing ventilation requirements and updating IAQ standards and guidelines. In the case of Hong Kong, a developed and densely populated city characterised by high-rise buildings, this study aims to provide a strategic framework for non-governmental agencies to address IAQ issues effectively. A comprehensive review of policies, regulations, and guidelines by international bodies and individual governments, along with an examination of the current IAQ management scheme in Hong Kong, has been conducted. Drawing inspiration from successful IAQ management strategies, the study aims to identify insights and potential pathways for the city's future development of IAQ management strategies. Overall, this research highlights the importance of proactive IAQ management for buildings and offers a roadmap for Hong Kong's pursuit of healthier indoor environments. [ABSTRACT FROM AUTHOR]

The present study aims to validate the 40-item and the brief 17-item Washoe County School District Social–Emotional Competency Assessment (WCSD-SECA), a self-report measure of social–emotional competencies, among Chinese school-aged children residing in Hong Kong. A total of 349 children (M = 9.86 years, SD = 1.22; 45.82% girls) and their parents (77.84% mothers) completed a set of questionnaires independently. The factor structure of both versions of the WCSD-SECA was assessed via confirmatory factor analyses. Structural equation models were then conducted to examine the predictive validity of the WCSD-SECA. The findings indicated that both the 40-item and the 17-item versions of the WCSD-SECA fit the data adequately. Both versions were also associated with self-reported positive and negative affect and parent-reported internalizing problems and externalizing problems. Additionally, social–emotional competencies as measured by the 40-item version were significantly associated with parent-reported prosocial behavior, whereas those as measured by the 17-item version were associated with prosocial behavior with a marginal significance. The findings demonstrated an adequate factor structure and predictive validity of the full version and the brief version of the WCSD-SECA in assessing social–emotional competencies. Hence, they serve as a useful tool for researchers, educators, and mental health practitioners to evaluate school-aged children's social–emotional competencies in the Chinese context. [ABSTRACT FROM AUTHOR]

Tracking long-term tidal flat dynamics is crucial for coastal restoration decision making. Accurately capturing the loss and gain of tidal flats due to human-induced disturbances is challenging in the micro-tidal areas. In this study, we developed an automated method for mapping the annual tidal flat changes in the micro-tidal areas under intense human activities, by integrating spectral harmonization, time series segmentation from dual spectral indices, and the tide-independent hierarchical classification strategy. Our method has two key novelties. First, we adopt flexible temporal segments for each pixel based on the dual full-time series spectral indices, instead of solely using a fixed period window, to help obtain more reliable inundation frequency features. Second, a tide-independent hierarchical classification strategy based on the inundation features and the Otsu algorithm capture the tidal flat changes well. Our method performed well in Guangdong, Hong Kong, and Macao (GHKM), a typical area with micro-tidal range and intense human activities, with overall accuracies of 89% and 92% for conversion types and turning years, respectively. The tidal flats in GHKM decreased by 24% from 1986 to 2021, resulting from the loss of 504.45 km2, partially offset by an accretion of 179.88 km2. Further, 70.9% of the total loss was in the Great Bay Area, concentrated in 1991–1998 and 2001–2016. The historical trajectories of tidal flat loss were driven by various policies implemented by the national, provincial, and local governments. Our method is promising for extension to other micro-tidal areas to provide more scientific support for coastal resource management and restoration. [ABSTRACT FROM AUTHOR]

Industry 5.0 is expected to solve the issue of job insecurity and reluctance to adopt emerging technologies in Industry 4.0 through increased workforce participation. To achieve that, proactive training should be afforded to enable the workforce to co-work with new technologies. Drones are an emerging technology increasingly adopted in construction, which has enormous data collection and safety implications when operational skills are inadequate. Yet, current drone training programs appear to be generic, and their ability to equip operators for flying tasks is questioned. This study aims to answer this question by assessing the adequacy of existing drone training programs and proposing training needs and strategies for drone operators in the construction industry. Data collected using semi-structured interviews from 22 purposively selected respondents in Hong Kong and desk research of websites were subjected to inductive content and thematic analysis using MAXQDA Analytics Pro 2022 software and narrative review. It was deduced that drone training courses in Hong Kong were mostly generic (UAS Pilot Training—Level 1, FPV operation). Interviewees considered existing drone training/training courses as inadequate for four reasons, including "lack of context-fitting considerations", "incompetence of drone operators", and "lack of demand/interest". Regarding the need for specialized drone training courses, two barriers and two training ecosystem themes emerged, with the high cost of specialized courses being a potential barrier to adoption since they could hamper enrolment. The training ecosystem themes were consistent with the "the training is inadequate" theme. This study proposes two drone operation training strategies: "competence-based training" and a "train-the-trainer" model. Drone training courses or programs under each training strategy should include (i) training content such as "safety training" and off-GPS training and (ii) knowledge and skill maintenance measures such as mandatory continuous professional development and retraining techniques. The proposed training strategies will equip operators to work efficiently and safely with drones. The study offers valuable references for training organizations and government authorities. [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]

In old urban districts with tenement buildings, street markets address the working class's social and economic needs. They are pivotal in fostering supportive communities, in particular for low-income residents in sub-standard housing. However, their outdated overall environment impedes the delivery of adequate support to residents. Prior research on street markets has focused on those in the Americas and Europe, and has revealed the societal support values of these markets. However, studies on street markets in high-density cities like Hong Kong are lacking. This study introduces an evaluation framework to assess the impact of street markets on the development of supportive communities for Hong Kong's sub-divided apartment residents. Employing the Pei Ho Street market in Sham Shui Po as a case study, an importance-performance analysis highlights critical but underperforming factors including public facilities, activity venues, commerce, and employment. Based on these findings, the study proposes four improvement strategies for the renewal of street markets in high-density communities, which could apply to other cities with similar high-density urban environments. It concludes that street markets in Hong Kong display unique spatial characteristics shaped by low-income lifestyles in a high-density urban environment, enriching daily social life and promoting sustainable community development. [ABSTRACT FROM AUTHOR]

Traditionally, research in the field of traffic safety has predominantly focused on two key areas—the identification of traffic black spots and the analysis of accident causation. However, such research heavily relies on historical accident records obtained from the traffic management department, which often suffer from missing or incomplete information. Moreover, these records typically offer limited insight into the various attributes associated with accidents, thereby posing challenges to comprehensive analyses. Furthermore, the collection and management of such data incur substantial costs. Consequently, there is a pressing need to explore how the features of the urban built environment can effectively facilitate the accurate identification and analysis of traffic black spots, enabling the formulation of effective management strategies to support urban development. In this study, we research the Kowloon Peninsula in Hong Kong, with a specific focus on road intersections as the fundamental unit of our analysis. We propose leveraging street view images as a valuable source of data, enabling us to depict the urban built environment comprehensively. Through the utilization of models such as random forest approaches, we conduct research on traffic black spot identification, attaining an impressive accuracy rate of 87%. To account for the impact of the built environment surrounding adjacent road intersections on traffic black spot identification outcomes, we adopt a node-based approach, treating road intersections as nodes and establishing spatial relationships between them as edges. The features characterizing the built environment at these road intersections serve as node attributes, facilitating the construction of a graph structure representation. By employing a graph-based convolutional neural network, we enhance the traffic black spot identification methodology, resulting in an improved accuracy rate of 90%. Furthermore, based on the distinctive attributes of the urban built environment, we analyze the underlying causes of traffic black spots. Our findings highlight the significant influence of buildings, sky conditions, green spaces, and billboards on the formation of traffic black spots. Remarkably, we observe a clear negative correlation between buildings, sky conditions, and green spaces, while billboards and human presence exhibit a distinct positive correlation. [ABSTRACT FROM AUTHOR]

Coral-dwelling gall crabs (Cryptochiridae) are common inhabitants of scleractinian corals. Several species have been described as new in recent years, including Lithoscaptus doughnut, which was described from Hong Kong based on a single female retrieved from the coral Plesiastrea peroni. Here we extend the distribution range of L. doughnut with nine additional localities throughout the Indo-West Pacific, from the Red Sea to the Coral Triangle and Japan. We describe a male specimen of L. doughnut for the first time, based on a specimen from Malaysia, and provide photographs of life and preserved material. Haplotype networks based on COI mtDNA (n = 12) and 16 rRNA sequences (n = 12) were created. We retrieved eleven COI haplotypes and six 16S haplotypes, however no clear geographic distribution pattern was discerned. Intraspecific variation in L. doughnut was 1.4% for COI and 0.2% for 16S. Lastly, the first colour photos and records of associated parasites of this species are provided. [ABSTRACT FROM AUTHOR]

Air pollutants from traffic make an important contribution to human exposure, with pedestrians likely to experience rapid fluctuation and high concentrations on the pavements of busy streets. This monitoring campaign was on Hennessy Road in Hong Kong, a densely populated city with deep canyons, crowded footpaths and low wind speeds. Kerbside NOx concentrations were measured using electrochemical sensors with baseline correction and subsequently deconvoluted to determine concentrations at 1-s resolution to study the dispersion of exhaust gases within the first few metres of their on-road source. The pulses of NOx from passing vehicles were treated as segments of a Gaussian plume originating at the tailpipe. The concentration profiles in segments were fit to a simple analytical equation assuming a continuous line source with R2 > 0.92. Least squares fitting parameters could be attributed to vehicle speed and source strength, dispersion, and sensor position. The width of the plume was proportional to the inverse of vehicle speed. The source strength of NOx from passing vehicles could be interpreted in terms of individual emissions, with a median value of approximately 0.18 g/s, but this was sensitive to vehicle speed and exhaust pipe position. The current study improves understanding of rapid changes in pollutant concentration in the kerbside environment and suggests opportunities to establish the contribution from traffic flow to pedestrian exposure in a dynamic heavily occupied urban microenvironment. [ABSTRACT FROM AUTHOR]

With the continuous development of digital technology, the widespread use of virtual spokespersons to promote city images is becoming increasingly prevalent. This study responds to this trend by employing a factor analysis and entropy weight methodology to explore the different dimensions and priorities in shaping the image of virtual city spokespersons in China. The aim is to offer insights into the design strategies and directions for shaping the image of virtual city spokespersons. For the research, we first conducted a literature review and semi-structured interviews to investigate the requirements of users in mainland China and Hong Kong regarding the image shaping of virtual city spokespersons. Building upon this groundwork, a questionnaire was designed and distributed, and it successfully gathered 512 valid responses. Subsequently, a factor analysis was utilized to identify eight key dimensions in shaping the images of Chinese virtual city spokespersons: "Design elements", "Anthropomorphism", "Evolutionary", "Emotionalization", "Narrativity", "Culturalism", "Interactivity", and "Reliability". Then, the entropy weighting method was applied to analyze the weights of each indicator within these dimensions. The results revealed that "Design elements" have the highest priority in shaping the image of virtual city spokespersons, followed by "Anthropomorphism", "Emotionalization", "Evolutionary", "Culturalism", "Narrativity", "Reliability", and "Interactivity". Based on these findings, a series of design optimization strategies are proposed, including but not limited to shaping visually appealing images aligned with user perceptions, establishing emotional connections with users, and meeting the functional experience needs of users. These strategies not only contribute to the image shaping of virtual city spokespersons, but also provide vital guidance for innovative directions in promoting the publicity and marketing of Chinese cities. [ABSTRACT FROM AUTHOR]

The way in which different cities teach children to read in Chinese may have an impact on the skills they later utilize to acquire English word reading skills. This study examined the relative contributions of several cognitive–linguistic measures to English word reading for Chinese students learning English as a second language in two Chinese cities, one whose school system teaches Pinyin (Beijing) and one whose school system does not teach Pinyin (Hong Kong). Students in grades 2–3 completed measures on Chinese morphological awareness (MA), Chinese phonological awareness (PA), Pinyin writing, and English word reading. In the Beijing group, it was found that PA (β = 0.334, p < 0.01) and Pinyin (β = 0.257, p < 0.05) were significant predictors of English word reading. In contrast, in the Hong Kong group, only MA (β = 0.263, p < 0.05) was found to be a significant predictor of English word reading. The difference in predictors could be due to the availability of a phonological tool (Pinyin) for the Beijing students when learning Chinese, while the Hong Kong group may have relied more heavily on learning using MA and rote memory techniques. Overall, the results from this study provide data supporting the benefits of having a phonological tool like Pinyin for Chinese children when learning to read in English. [ABSTRACT FROM AUTHOR]

This study aims to investigate the relationship between risky sexual behavior (RSB) and psychopathy in a non-clinical sample of 714 Hong Kong adults, shedding light on sex differences. Our findings reveal that males exhibit significantly higher mean levels of RSB (general, penetrative, and nonpenetrative), as well as egocentric (Factor 1) and callous (Factor 3) traits of psychopathy, along with increased sexual desire compared to females. Regression analyses indicate that elevated levels of antisociality (Factor 2) and callousness (Factor 3) traits of psychopathy, along with sexual desire, emerge as significant risk factors for engaging in general, penetrative, and nonpenetrative RSB. Intriguingly, higher age and being in a long-term relationship are associated with RSB. The implications of this study suggest potential avenues for reducing, if not entirely preventing, the inclination to engage in RSB in the presence of psychopathic traits. [ABSTRACT FROM AUTHOR]

Precipitation nowcasting is critical for areas such as agriculture, water resource management, urban drainage systems, transport and disaster preparedness. In recent years, methods such as convolutional recurrent neural networks (ConvRNN) in deep learning techniques have been used to solve this task. Despite the effective improvement in forecasting quality, there are still problems with blurred and distorted prediction images, as well as difficulties in effectively forecasting high echo regions. To solve the above problems, this article presents a spatio-temporal long–short-term memory network model in view of multi-scale context fusion and attention mechanisms. This method fully extracts the short-term context information of different scales of radar image through the multi-scale context fusion module. The attention module broadens the time perception domain of the prediction unit so that the model perceives more historical time dynamics. Using the Hong Kong region weather radar data as a sample, the results of the experimental comparative analysis show that the spatio-temporal long and short-term memory network in view of multi-scale context fusion and attention mechanism achieves better prediction performance. Our model is effective in improving both image quality and meteorological assessment metrics with higher accuracy and more details. [ABSTRACT FROM AUTHOR]

This study on total suspended matter (TSM) in the Pearl River Estuary established a regression analysis model using Landsat 8 reflectance and measured TSM data, crucial for environmental management and engineering projects. High coefficients of determination (>0.6) were reported for the selected models. TSM concentration was notably high in 2013, peaking at 180 mg/L during the flood season and 80 mg/L in the dry season. In contrast, 2020 saw lower concentrations. Similar spatial distribution patterns were observed during dry and flood seasons, with high nearshore and low offshore TSM concentrations. Statistical analyses revealed natural factors (precipitation and runoff) as major influencers of the TSM distribution, with human activities presenting localized, limited impacts, except under long-term and large-scale conditions. Over time, the influence of large-scale water-based construction, such as the Hong Kong–Zhuhai–Macao Bridge, on TSM distribution became significant. [ABSTRACT FROM AUTHOR]

Understanding the economic impact of COVID-19 is the foundation for formulating targeted policies promoting economic recovery. This study uses panel data of the county economy in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) from 2017 to 2022. Firstly, the evolution characteristics of the economic structure in the GBA were analyzed using the standard deviation ellipse, geographical concentration, and spatial autocorrelation methods. Then, we revealed the changes in various economic indicators. Finally, a spatial Durbin model was constructed to study the factors affecting economic growth and spatial spillover effects in different periods. The results reveal that the economic distribution in the GBA presents a "core–edge" structure. The FDI, consumption, and exports of the Greater Bay Area fluctuate greatly, while investment growth is relatively stable. There is a significant spatial spillover effect in the county economy of the GBA. Investment, consumption, exports, labor, and innovation all have significant positive effects on economic growth, with investment having the greatest impact, while FDI has a significant negative impact. The impact of COVID-19 on the economy of the GBA is mainly reflected in the weakening of spatial spillovers, the strengthening of economic agglomeration, the decline in factor growth, and the change in the driving effect of factors on the economy. These findings can provide a reference for formulating targeted economic development policies. [ABSTRACT FROM AUTHOR]

The loss of life and property in economically developed areas due to geological hazards caused by intense ground subsidence is incalculable. As one of the fastest growing areas in the Guangdong-Hong Kong-Macao Greater Bay Area, the study of ground subsidence in Nansha will help to provide a scientific basis for urban planning and improve the capacity of monitoring and prevention of ground subsidence. The combination of coastal soft soil foundation and urbanization conditions creates a certain risk of land subsidence. We chose Nansha District, the geographical center of the Greater Bay Area, as the study area to analyze its surface subsidence characteristics in recent years. The 20-view Sentinel-1A data and SBAS-InSAR technique were used to monitor the ground subsidence in Nansha from 2017 to 2023. The main rate of ground subsidence in Nansha ranges from −19.4 to 7.7 mm/yr and is distributed in the urban area, along the rivers, in the construction area, and in the reclamation area. As of 4 May 2023, the average ground settlement in Nansha is 10.05 mm and the maximum settlement can be up to 142.45 mm. The 6-year total settlement at all four settlement intensities is greater than 60 mm, with the highest value exceeding 110 mm. The cumulative settlement increases with time, but inverse settlement and no settlement also occur at points where settlement is severe. For settlement caused by soft soil consolidation, it is recommended that drainage pipes be installed to accelerate drainage as a means of stabilizing settlement. For settlement caused by groundwater extraction and additional loads on the road surface, it is recommended to rationally extract groundwater and reinforce the foundation of the road surface with severe settlement. [ABSTRACT FROM AUTHOR]

The use of single-item measures of self-rated mental health (SRMH) has been increasingly valued in epidemiologic research. However, little is known about the reliability and mental health correlates of SRMH in Chinese populations. This study examined the reliability and mental health correlates of SRMH in three Chinese samples. We analyzed data collected from two convenience samples of Chinese adults from Hong Kong and/or Taiwan (Sample 1: N = 205; Sample 2: N = 377), and a random sample of Taiwan psychiatric inpatients (Sample 3: N = 100). Our results showed that the single-item measure of SRMH had moderate to good test–retest reliability (intraclass correlation [ICC] = 0.75) in Sample 1 and acceptable reliability between the self-report and interviewer-administered versions (ICC = 0.58) in Sample 3. It had a high positive correlation with self-esteem and a moderately high negative correlation with depression. It also had a consistently negative correlation with borderline personality disorder symptoms and post-traumatic stress disorder symptoms. The SRMH score was also associated with psychiatric service usage. These findings contribute to the body of knowledge regarding the use of a single-item measure of SRMH to assess overall self-perceived mental health in Chinese communities. [ABSTRACT FROM AUTHOR]