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Invasive species have had substantial impacts on global mangrove forests. Apple snails (Pomacea canaliculata) have invaded mangrove forests in China. To clarify the potential detritivorous diet of P. canaliculata, the growth and feeding indicators of invasive juvenile snails collected from mangroves in Guangzhou, China, were studied using decaying leaf litter from five mangrove species, including Acanthus ilicifolius, Acrostichum aureum, Kandelia candel, Aegiceras corniculatum, and Sonneratia apetala. The growth indicators of the survival ratio and specific growth rate were calculated by measuring the live weight of the snails and the number of dead snails after 30 days. The feeding indicator of the weight-specific daily feeding rate (WDR) was calculated by measuring the snail weight and the amount of leaf litter ingested after 120 h. A multiple-choice experiment was performed on the snails by providing the decaying leaf species together, while a no-choice experiment was performed using a single species of decaying leaf litter. The survival and specific growth ratio of P. canaliculata feeding on decaying leaf litter of A. ilicifolius were higher than those for A. aureum. The WDR values of P. canaliculata feeding on the decaying leaf litter of A. ilicifolius and S. apetala were both significantly higher than those for A. corniculatum, A. aureum, and K. candel. The lowest WDR value of P. canaliculata feeding on decaying leaf litter was observed for A. aureum in the no-choice experiment. P. canaliculata mainly fed on decaying leaf litter of A. ilicifolius and S. apetala. The phosphorous contents and ash of the decaying leaf litter positively affected the WDR values of P. canaliculata obtained in the multiple-choice and no-choice experiments. The contents of lignin, tannin, and flavonoid negatively affected the WDR values of P. canaliculata. The potential diet of invasive P. canaliculata in mangroves was closely tied to the chemical characteristics of the decaying leaf litter. P. canaliculata can invade A. ilicifolius and/or S. apetala mangroves by utilizing the debris on the mangrove ground. Understanding the potential detritivorous diet of P. canaliculata in invaded mangroves can help us to assess this species' dispersal risk and provide support for mangrove management. [ABSTRACT FROM AUTHOR]

The rapid expansion of metro networks, e.g., in many cities of China, continuously introduces the operation of new stations every year. Due to the lack of historical data and complicate variations of short-term passenger flow in the early stage of operation, it is difficult to accurately predict inbound and outbound passenger flows of new metro stations in the short term, which would be the database for train scheduling for new stations before operation, dynamic capacity optimization for new stations under operation, short-term prediction of cycle sharing demands near new stations, and so on. Traditional methods usually failed to exactly reflect the complicate rules or were unusable without the new station's historical data. In order to solve the above problems, this paper proposes a short-term inbound and outbound passenger flow prediction model for new metro stations at the early stage of operation by combining the K-means clustering algorithm, an improved spatiotemporal long short-term memory model (Sp-LSTM), and a real-time feedback error model (mean absolute error, MAE), where passenger flows' spatial-temporal characteristics and land-use relevance are considered. The application in Guangzhou Metro, China, where Line 21 is regarded as a new line, shows that the proposed K-Sp-LSTM model has the best prediction accuracy compared with traditional methods. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of spacing control between adjacent trains in train formation and proposes a distributed train-formation speed-convergence cooperative-control algorithm based on barrier Lyapunov function. Considering practical limitations such as communication distance and bandwidth constraints during operation, not all trains can directly communicate with the leader and obtain the expected trajectory it sends, making it difficult to maintain formation consistency as per the predetermined ideal state. Furthermore, to address the challenge of unknown external disturbances encountered by trains during operation, this paper designs a distributed observer deployed on each train in the formation. This observer can estimate and dynamically compensate for unknown reference trajectories and disturbances solely based on the states of adjacent trains. Additionally, to ensure that the spacing between adjacent trains remains within a predefined range, a safety hard constraint, this paper encodes the spacing hard constraint using barrier Lyapunov function. By integrating nonlinear adaptive control theory to handle model parameter uncertainties, a barrier Lyapunov function-based adaptive control method is proposed, which enables all trains to track the reference trajectory while ensuring that the spacing between them remains within the preset interval, therefore guaranteeing the asymptotic stability of the closed-loop system. Finally, a practical example using data from the Guangzhou Metro Line 22, specifically the route from Shiguang Road Station to Chentougang Station over three stations and two sections, is utilized to validate the effectiveness and robustness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

With the expansion of the metropolitan area, the application of express/local mode is gradually increasing. In contrast to the normal mode, the express/local mode has advantages in reducing energy consumption and saving total travel time by having express trains skipping some stops. This paper aims to minimize the total energy consumption of express and local train throughout the day by optimizing the train operation strategy in the same power supply section and increasing the overlap time between train traction acceleration and train regenerative braking to obtain the optimal energy‐efficient timetable. As the consumed energy of a train is highly dependent on the rolling stock weight and the on‐board passengers' weight. An integer programming model is proposed with on‐board passengers considered accurately, in which the dwell times, departure headway, and total turnaround time of express and local trains are determined. An improved grey wolf algorithm is designed by improving convergence factor and incorporating differential evolution to solve the proposed problem. The real data on Guangzhou Metro Line 18 is adopted for numerical studies. The results show that the optimized timetable increases the regenerative energy utilization rate by 21.37% and reduces the total energy consumption by 5.02% compared to the operational timetable. This paper aims to minimize the total energy consumption of express and local train throughout the day by optimizing the train operation strategy in the same power supply section and increasing the overlap time between train traction acceleration and train regenerative braking to obtain the optimal energy‐efficient timetable. An integer programming model is proposed with on‐board passengers considered accurately, in which the dwell times, departure headway, and total turnaround time of express and local trains are determined. [ABSTRACT FROM AUTHOR]

The park-level integrated energy system (PIES) can realize the gradient utilization of energy and improve the efficiency of energy utilization through the coupling between multiple types of energy sub-networks. However, energy analysis and exergy analysis cannot be used to evaluate the economics of PIES. In addition, conflicts of interest among integrated energy suppliers make the economic scheduling of the PIES more difficult. In this paper, we propose a multi-objective collaborative game-based optimization method based on exergy economics, in which the introduction of exergy economics realizes the economic assessment of any link within the PIES, and the optimization model constructed based on the potential game solves the problem of conflict of interest among multiple energy suppliers and improves the benefits of each supplier. Finally, taking a PIES in Guangzhou as an example, the rationality of the optimization scheme proposed in this paper is demonstrated by comparing it with the classical optimization scheme. [ABSTRACT FROM AUTHOR]

In order to address the dynamic changes in vessel preferences for berth lines caused by the deployment of shore-based power equipment in major ports and the collaborative scheduling problem of berthing and towing assistance, this paper quantifies the environmental costs of pollutants from the main engines of tugs and auxiliary engines of container ships using an environmental tax. Additionally, considering the economic costs such as vessel delay and shore power cable connection, a two-layer mixed-integer linear programming model is constructed using the task sequence mapping method. This model integrates the allocation of continuous berths at container terminals with coordinated towing scheduling for shore power selection. A solution approach is designed by combining the commercial solver (CPLEX) and the immune particle swarm optimization algorithm (IAPSO). The proposed scheme is validated using the example of the Nansha Phase IV Terminal at the Port of Guangzhou. The results show that compared to the traditional first-come-first-served and adjacent scheduling schemes, the collaborative scheduling scheme proposed in this paper reduces the total cost by 21.73%. By effectively utilizing berth resources and shore power equipment while densely arranging collaborative tasks and appropriately increasing the number of tugs, the port can convert the economic cost of leasing a small number of tugs (increased by 10.63%) into environmental benefits (decreased by 33.88%). This approach provides a reference for addressing nearshore pollution emissions in ports. [ABSTRACT FROM AUTHOR]

Predicting carbon prices is crucial for the growth of China's carbon trading industry. This paper proposes a residual correction model that considers multiple influencing factors. First, the best historical data and main external factors input by the model are determined by using the partial autocorrelation function and Spearman correlation analysis, and the carbon price forecasting index system is constructed. Second, the whale optimization algorithm (WOA) is utilized to determine the optimal parameters of the extreme gradient boosting (XGBoost), and the WOA‐XGBoost model is built to perform preliminary carbon price forecasts and obtain the residual series. Finally, the carbon price residual series undergoes decomposition into multiple components utilizing the complete ensemble empirical mode decomposition for subsequent forecasting and the aggregation of outcomes. Experiments are conducted to predict two carbon trading markets in Hubei and Guangzhou, and a feature importance analysis is performed. The results indicate that the proposed hybrid model consistently outperforms the comparative models in terms of prediction accuracy. Furthermore, it is revealed that historical carbon prices and European Union carbon prices are the key factors influencing the prediction of carbon market prices. [ABSTRACT FROM AUTHOR]

With a large number of new energy vehicles being put into use, it is the general trend for traditional fuel vehicles to withdraw from the market in an orderly manner. Determining the optimal ratio between them in this process is of great significance to the low-carbon sustainable development of cities. Therefore, considering the constraints of urban automobile development planning and air pollution prevention and control policies, a multi-objective model to minimize pollutants and costs is constructed in this paper. Through model calculation and sensitivity analysis of dynamic impact relationship of different types of vehicles, it is determined that when new energy vehicles account for around 36% in Beijing, 57% in Shanghai and 46% in Guangzhou, the pollutant emissions can be minimized without causing a significant increase in social costs. Additionally, compared with 2030, Beijing, Shanghai and Guangzhou can achieve emission reductions of 320,000 tons, 200,000 tons and 250,000 tons, respectively, in 2050 if they implement the policy of banning the sale and delisting of fuel vehicles, which could provide suggestions for the guidance of the low-carbon development plan of the automobile industry. [ABSTRACT FROM AUTHOR]

Urbanization is an important process in China's urban development, significantly contributing to resource allocation and the cooperative development of neighboring cities. In recent years, remote-sensing technology has emerged as a powerful tool in urbanization research. However, the disparity in development between urban and rural areas poses challenges in evaluating the degree of urbanization within a region. This paper addresses this issue by using LCZ (Local Climate Zone) data to provide a unified framework for analyzing a human settlement environmental geographic dataset. This study focuses on the spatial development and transformation of the Guangzhou–Foshan urbanization from 2000 to 2020. The LCZ data offer a suitable framework for examining urban–rural gradients, facilitating the analysis of spatial characteristics under varying development conditions. This unified framework enables a comprehensive analysis of the spatiotemporal characteristics of urban spatial integration. The results show that the analysis of the Guangzhou–Foshan metropolitan area reveals that the region has maintained a "core–edge" spatial structure over the past 20 years. The development rate has decelerated following policy changes in 2010, with the adjacent area experiencing significantly slower development compared to the overall study area. LCZ data are effective for comparative analysis of internal spatial development within urban areas, offering a novel approach to studying spatial integration amid urban development. [ABSTRACT FROM AUTHOR]

The treatment of Africans in Guangzhou, China in 2020 during the COVID-19 pandemic - here referred to as the "Guangzhou episode" - generated strong criticisms and made news headlines within and outside Africa. This paper analyzes the reportage of the episode in four online African newspapers: two each from Nigeria and Ghana. Specifically, it sheds light on how the episode was framed, comparing coverage between both countries. Using a discourse analysis that prioritizes language, source, and focus, the paper demonstrates that while Western media were important influences and sources for the newspapers, the African migrants' experiences in the episode were largely framed within (ahistorical) victimhood. Yet the idea of "African" migrants had a noticeable Nigerian dimension. [ABSTRACT FROM AUTHOR]

Mobile Differential Optical Absorption Spectroscopy measurements of SO2 and NO2 were performed in the Guangzhou Eastern Area (GEA) during the Guangzhou Asian Games 2010 from November 2010 to December 2010. Spatial and temporal distributions of SO2 and NO2 in this area were obtained and emission sources were determined by using wind field data. The NO2 vertical column densities were found to agree with OMI values. The correlation coefficient (R2) was 0.88 after cloud filtering. During the Guangzhou Asian Games and Asian Paralympics (Para) Games, the SO2 and NO2 emissions in the area were quantified using averaged wind speed and wind direction. For times outside the Games the average SO2 emission was estimated to be 9.50±0.90 tons per hour and the average NO2 emission was estimated to be 3.50±1.89 tons per hour. During the phases of the Asian and Asian Para Games, the SO2 and NO2 emissions were reduced by 53.5 and 46 %, respectively, compared to the usual condition. We also investigated the influence of GEA on Guangzhou University Town, the main venue located northwest of the GEA, and found that SO2 concentrations here were about tripled by emissions from the GEA. [ABSTRACT FROM AUTHOR]

Given the complex interplay between economic and cultural–historical factors, this paper explores scene perception and its mechanism in individual and collective cognition of historical commercial streets. Based on a perception model constructed from scene theory, the study utilizes user scene experience feedback from Beijing Road, a commercial pedestrian street in Guangzhou. It conducts a systematic assessment using hierarchical analysis (AHP) across three dimensions: authenticity, theatricality, and legitimacy. The findings reveal the following: (1) according to visitors, traditional cuisine, cultural and creative arts, and Lingnan's intangible cultural heritage received low ratings; (2) historical relics and traditional cuisine are dominant factors, highlighting public attention to cultural heritage, but the role of historical–cultural characteristics and festival activities is relatively marginalized; (3) cultural–historical relics and traditional cuisine are the leading factors that contribute to an authentic experience, while historical context and festival activities constitute secondary factors; (4) cultural landscapes and arts are central to theatrical experiences, with modern visual elements playing a lesser role; (5) diversified commercial formats and public services are the core factors influencing legitimacy experience, reflecting the role of market diversity and policy orientation in building consumer trust. The design of historical and cultural streets should prioritize the preferences of those experiencing them to promote cultural identity and historical continuity. Additionally, the synergy between commercial diversity and policy orientation should be strategically emphasized to form a business ecosystem supporting sustainable development. Future commercial street renewals should focus on the key role of visual narrative in shaping brand culture. This paper offers insights into the dynamic process of constructing scene experience from perspectives of spatial materialization and emotional empowerment to cultural identity, providing references for strategies in historical place renewal. [ABSTRACT FROM AUTHOR]

Strategic spatial planning plays a pivotal role in effectively providing solutions for urban issues. In 2000, Guangzhou took the pioneering step of formulating China's first strategic spatial plan, known as the Guangzhou Strategic Plan. However, existing research has predominantly focused on the content of the "Guangzhou Strategic Spatial Plan" while lacking attention to its implementation effects. To address this empirical gap, this paper analyzes Guangzhou's current spatial structure from the perspectives of facilities, population, and industry. The results reveal that: (1) the effectiveness of the "Southern Expansion" strategy outlined in the Guangzhou Strategic Spatial Plan has been limited. It has not achieved the expected results in terms of facility construction, population attraction, industrial clustering, and value-added growth; (2) due to inherent limitations and a lack of planning support, the development of the new town presents a dilemma. Considering the current spatial structure, this paper reflects on the reasons for the failure of Guangzhou's strategic spatial planning, aiming to provide insights for the implementation of a new round of strategic spatial planning. [ABSTRACT FROM AUTHOR]

Health assessment for point machines is crucial to the safety of rail systems. The operation of the point machine is a typical multi‐stage process, each with its own characteristic features that allow a health assessment. Therefore, to segment various phases self‐adaptively is quite essential to assess the health state of the point machine. Besides, the degradation of the point machine is characterized as non‐linear. However, these issues are barely discussed when assessing the degradation degree. By converting it into a multi‐classification problem, this paper proposes a novel phase segmentation method based on dimensionless time‐domain features and characteristics of time series by utilizing the adaptive Multiclass Mahalanobis Taguchi System (aMMTS) to segment the signal self‐adaptively. Furthermore, this paper proposes a novel algorithm named Non‐linear Dynamic Time Warping (NLDTW), which modifies the conventional Dynamic Time Warping (DTW) by using a non‐linear distance to overcome the lack of global consistency in the non‐linear degradation assessment. Finally, a modified formula of confidence value is presented to assess the actual degradation degree. The efficiency and feasibility of the proposed framework have been verified by the actual data collected from the point machines of Guangzhou Metro. [ABSTRACT FROM AUTHOR]

Terminal airspace is the convergence area of air traffic flow, which is the bottleneck of air traffic management. With the rapid growth of air traffic volume, the impact of convective weather on flight operations is becoming more and more serious. To change the conditions and improve the utilization of terminal area airspace, a convective weather terminal area capacity (CWTAC) model is developed to quantify the effect of convective weather on the capacity of the terminal area in this paper. The airspace of the terminal area is divided into major airspace, minor airspace and no-impact airspace according to the distribution of the air traffic flow. Under convective weather, their permeabilities are calculated and used as input features, and the actual availability rate is set to label. Three machine learning algorithms, support vector regression (SVR), random forest (RF), and artificial neural network (ANN), are used to predict the availability rate. Then, the terminal airspace capacity under convective weather can be calculated. The historical operation data of the Guangzhou terminal area and the Wuhan terminal area are taken to test machine learning algorithms and verify the CWTAC model. It shows that all three machine learning algorithms are practical, and ANN is the best one based on mean squared error (MSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). The predicted capacity of the CWTAC model accords well with the actual flight number in the terminal airspace under convective weather. The reasons why they are not entirely consistent are also analyzed. [ABSTRACT FROM AUTHOR]

In 2019, triggered lightning was used to directly strike phase C of a 1.5 km, 10 kV double‐circuit distribution line in Guangzhou, China, with 2 flashes (13 return strokes) recorded. This paper presents the characteristics of induced voltage at the closest pole on the parallel line. The induced voltage is bipolar, which can be divided into 3 stages: negative increase stage, fast and positive transition stage and slowly returning to zero stage. The positive peak value of phase A voltage ranges from 111.4 to 228.9 kV and that of phase C voltage is from 90.1 to 200.9 kV, corresponding to lightning current from −8.9 to −29.9 kA. The positive peak value of the induced voltage is approximately 3 to 10 times the negative peak value. The negative peak, positive peak and positive 10%–10% duration time of induced voltage show a good linear relationship with the peak value of the return stroke current. There was no flashover occurred during the whole process. The result in this paper can provide data support for numerical simulation and line protection analysis. [ABSTRACT FROM AUTHOR]

In the planning and design of natural and urban environments, visualization plays an increasingly important role. It has become a core component of communication and dissemination within the various formats of project representation, environmental assessment, workshops, and stakeholder involvement in general. However, as a practical technology, the outputs of our visualizations are, too often, regarded as a static product rather than as a living and evolving tool in and of itself, often due to the inherent restrictions present in both the analog and digital technologies used in data curation and visualization creation. In this paper, we argue that with the increasing complexity and usability of digital technologies, we are now capable of bringing a heightened level of interactive dynamism to planning and design, improving the communicative power of landscape visualization. We introduce a theoretical adaptive visualization (AV) framework, designed to support project meetings and stakeholder interactions with iterative planning and design elements. To demonstrate the merits of the framework, we develop an augmented reality application following AV principles; we discuss the novel design interactions afforded by integrating alongside traditional analog and digital data sources, in an interactive and dynamic application. This is highlighted by a case study from the Pearl River Delta region, with a focus on planning and design for flood risk mitigation. [ABSTRACT FROM AUTHOR]

The results of traditional vegetation-measuring methods are mostly two-dimensional data, which can only convey limited information. The greening situation of many cities or regions in the world cannot be fully assessed by these results. In this regard, this paper proposes the use of the air–ground integrated point cloud data acquisition mode for measuring vegetation. This mode combines a backpack-mounted laser scanning system, a vehicle-mounted laser scanning system, and UAV tilt photography technology to collect greening data in a comprehensive park and along a municipal road in Guangzhou, China. To classify the collected greening data, we propose the BiFPN-KPointNet-CBAM model, which was derived from PointNet. The model was introduced to analyze the distribution of green plants in study areas. The experimental findings indicate that our model achieved a notable enhancement in the overall accuracy by approximately 8% compared with other state-of-the-art models. Compared with the traditional greening survey method, this method obtained three-dimensional and more accurate greening data, and thus, provides higher quality greening data for urban managers. [ABSTRACT FROM AUTHOR]

Historic timber structures face substantial fire loads and complex fire risks. Subsequent renovations and utilization may influence their fire safety performance. Therefore, accurately predicting indoor fire development in historic buildings and assessing their fire safety performance is crucial. Numerical fire simulation is currently at the forefront of analyzing and assessing fire risks in historic buildings. However, there is a shortage of globally accessible historic building fire data. This paper proposes a method to determine fire scenarios, peak heat release rates, and development curves of indoor fires in wooden historic buildings through a fire load investigation. Using the Guangzhou ancestral hall as an example, PyroSim fire dynamics simulation software is employed to calculate fire development and assess the available safe evacuation time. The simulation results are subsequently input into the Pathfinder evacuation simulation software to ascertain the required safe evacuation time for indoor occupants. A comparative assessment is conducted to evaluate the fire safety performance before and after the renovation of historic buildings. The research findings indicate that installing closed glass curtain walls in the courtyards of ancestral hall buildings in Guangzhou accelerates the infiltration of smoke during fires, leading to rapid fire spread and long-distance ignition, significantly reducing the time available for safe evacuation. Therefore, when renovating and utilizing the ancestral hall buildings in Guangzhou, the installation of ventilation and smoke extraction systems should be prioritized to slow down fire development. Additionally, controlling the number of indoor occupants is an effective management measure to mitigate fire damage in historic buildings. [ABSTRACT FROM AUTHOR]

The study of clan paintings reveals a shift in perspective from art aesthetics to cultural connotations to cultural identity, yet literature seldom discusses the relationship between art and kinship culture. Taking the murals of ancestral hall architecture in Guangzhou as an example, this paper utilizes text mining to identify factors influencing its decorative art. It reveals the traditional rites' artistic expression through dimensions of characters' demeanor and the transmission of content values, offering a fresh perspective for heritage value research. Findings: (1) themes and implications are mostly oriented towards positive value transmission, transitioning from idealistic layman life to the realism of lower-class existence, emphasizing humanization; (2) the extroverted portrayal of characters contrasts with the dignified, restrained etiquette of traditional rites, with some characters' portrayal and facial expressions exuding approachability; (3) murals conveying positive emotions are mostly related to longevity, auspiciousness, fortune, and heroic deeds, while those conveying negative emotions mainly involve elderly male figures, reflecting a content bias related to characters; (4) historical allusion murals with complex content reduce the emotional resonance and arousal efficiency of the viewer; (5) incomplete mural content increases negative emotions in perceivers, highlighting the impact of mural preservation on emotional resonance. To delve into the formation of clan painting art, it is essential not only to interpret the diversity of its patterns but also to demonstrate the representation of its social attributes in decorative art. The formation of clan painting decorative art exhibits kinship cultural attributes, epitomizing the essence of traditional ceremonial thought. [ABSTRACT FROM AUTHOR]

Drawing from seven months of fieldwork among independent artists and their communities in Guangzhou, China, in 2020–2021, this paper investigates the feminist alternative practices in response to the experiences of gender marginalisation of independent artists. Along with being sexualised and discouraged by some of their art colleagues and the public, there has been an emergence of alternative practices among female independent artists in Guangzhou, including alternative art production, space cultivation, and community development. Alternative art practices have not only diversified the expression and representation of female artists; they have also helped female and non-binary people connect to discuss gender-related issues and provide mutual support. Altogether, these expanding feminist practices, spaces, and communities have yielded everyday life strategies to negotiate and contest existing patriarchal conventions and imbalanced power relationships. My account also offers a view of changing gender politics within art communities in Guangzhou's independent art field. [ABSTRACT FROM AUTHOR]

Rapid urbanization in China has shifted the logic and needs of rural resource allocation, prompting a transformative approach toward rural revitalization and sustainable development through comprehensive land consolidation. This paper offers a theoretical framework for understanding the driven adjustments in rural power, capital, and social structures facilitated by comprehensive land consolidation. It discusses how the construction of pastoral complexes influences the diversification of rural land use and ecological restoration through dynamic adjustments in power structures. This study illustrates that in Guangzhou, comprehensive land consolidation is indispensable for ensuring food security and fostering diverse rural industries. Furthermore, it facilitates the resource and commercialization of land, balances governmental social responsibilities with rational capital pursuits, and enriches the livelihood structures of social entities to ensure rural social equity. The pastoral complex model achieves a harmonious integration of rural socio-economic and natural systems. Innovations in paths of social participation help eliminate the effects of social inequality within the environment, while the theory of political ecology clearly analyzes the internal reasons for the interaction and strategic plays among diverse actors under this model. The case studies of the pastoral complex present the practice of national–capital–land–social relationships and changes in land benefits, showcasing a Chinese approach to rural development and social justice. This provides a new perspective for political ecology research and enriches its empirical content. [ABSTRACT FROM AUTHOR]

​​​​​​​As a crucial constituent of fine particulate matter (PM2.5), secondary organic aerosols (SOAs) influence public health, regional air quality, and global climate patterns. This paper highlights the use of hydrophilic interaction liquid chromatography (HILIC) which effectively retains strongly polar analytes that might exhibit incomplete or no retention in reverse chromatography, resulting in superior separation efficiency. A HILIC column was used to analyze six standards, environmental standards (1648a and 1649b), and samples collected in urban environments in Guangzhou in the Pearl River Delta region, which serve as valuable reference points for evaluating the organic composition of the atmospheric environment. The results indicate a high degree of accuracy in the analytical method. Sodium octyl- d17 sulfate serves as the internal standard, with a linear correlation coefficient of the six standards, boasting a linear correlation coefficient r ranging from 0.993–0.9991 and a slope, k , of the linear equation from 0.966–1.882. The instrument detection limits (IDLs) are established at 0.03–0.20 µgmL-1 , while the method detection limits (MDLs) fall within the range of 0.30–1.75 ngm-3 , demonstrating the method's exceptional sensitivity. Since isoprene-derived organosulfates (iOSs) are highly polar due to containing a hydrophilic bond to the hydroxyl group and a hydrophobic bond to the sulfate, and as such showed strong retention using this method, this technique employs sodium ethyl sulfate and sodium octyl sulfate standards for semi-quantitative compound analysis of iOSs. The error in sample analysis (EA) ranged from 12.25 %–95.26 %, and the two standards maintained a consistent recovery rate between 116 %–131 % and 86.4 %–127 %. These findings indicate a high level of precision when semi-quantifying compounds with similar structural characteristics, affirming the analysis method's minimal relative error and underscoring its repeatability, process stability, and the reliability of its results for iOSs. To enhance the method's reliability assessment, the study analyzed polar organic components of standard particulate matter samples (1648a and 1649b), providing precise determinations of several iOSs using this method. Methyltetrol sulfate (m/z 215, C5H11SO7-) is the highest concentration in the ambient samples, up to 67.3 ngm-3 in the daytime. These results serve as valuable reference points for assessing the organic composition of the atmospheric environment. [ABSTRACT FROM AUTHOR]

To enhance comprehension of the improved arch cover construction method for underground metro stations and provide guidance for future construction techniques and programs, the paper examines the indoor improved arch cover method of construction in the underground concealed excavation station of Tianhe Road Station of Guangzhou Metro Line 10, China. It includes a similar model test of the key technology and an analysis of the evolution law of the surrounding rock stress, the law of the ground settlement, and the law of the arch top deformation after the tunnel excavation. The study found that increased over-support can decrease arch settlement, with the maximum settlement occurring near the arch. Ground settlement typically occurs in the same areas as arch settlement, but arch settlement may occur earlier. The excavation of the arch cover has little impact on the overlying soil pressure, and the supporting structure is more effective in controlling soil deformation. The upper part of the arch cap experiences mainly extrusion stress, with the maximum stress occurring near the middle of the arch. The stresses in the arch's base decrease significantly during the excavation of the side drifts but show an increasing trend during the excavation of the lower rock mass. The presence of the central column significantly affects both the settlement of the arch and the ground, as it bears most of the compressive stress of the arch. This stress decreases initially and then increases. The amplitude of deformation is more pronounced when the dismantled central column is closer to the middle of the arch. [ABSTRACT FROM AUTHOR]

Accurate and fast traffic prediction is the data-based foundation for achieving traffic control and management, and the accuracy of prediction results will directly affect the effectiveness of traffic control and management. This paper proposes a new spatiotemporal periodic polynomial model for road traffic, which integrates the temporal, spatial, and periodic features of speed time series and can effectively handle the nonlinear mapping relationship from input to output. In terms of the model, we establish a road traffic speed prediction model based on polynomial regression. In terms of spatial feature extraction methods, we introduce a maximum mutual information coefficient spatial feature extraction method. In terms of periodic feature extraction methods, we introduce a periodic trend modeling method into the prediction of speed time series, and effective fusion is carried out. Four strategies are evaluated based on the Guangzhou road speed dataset: a univariate polynomial model, a spatiotemporal polynomial model, a periodic polynomial model, and a spatiotemporal periodic polynomial model. The test results show that the three methods proposed in this article can effectively improve prediction accuracy. Comparing the spatiotemporal periodic polynomial model with multiple machine learning models and deep learning models, the prediction accuracy is improved by 5.94% compared to the best feedforward neural network. The research in this article can effectively deal with the temporal, spatial, periodic, and nonlinear characteristics of speed prediction, and to a certain extent, improve the accuracy of speed prediction. [ABSTRACT FROM AUTHOR]

Information on the 4th International Symposium on Heat Transfer and Energy Conservation (ISHTEC2012) held in Guangzhou, China on January 6-9, 2012 is presented. It says that the conference was organized by Key Laboratory of Heat Transfer and Energy Conservation at the Education Ministry of the South China University of Technology. Moreover, a warm response from researchers in the heat transfer was received by the conference.

Along with reducing traffic congestion, electric car-sharing (ECS) can also solve travel demand, utilize idle resources, and enhance forms of transportation. Accordingly, university students are identified in Guangzhou, China as a promising customer group for ECS companies. Although university students in Guangzhou, China are unique in the context of ECS, few researchers have studied the factors that influence their willingness to use such services. Hence, this paper investigates the key determinants that affect university students' behavioral intention (BI) to use ECS in Guangzhou, China. Based on an extension of the unified theory of acceptance and use of technology (UTAUT), this paper examines the effects of the constructs on BI to use ECS and the moderating role of trust in ECS. Based on results from a questionnaire of 486 university students in Guangzhou, China, conditional value (CV) was the most critical driver of BI, followed by personal attitude (PA) and sustainability (SUST). The moderating analysis showed that taking gender, education, and driving experience of university students as control variables, trust was found to have a significant positive moderating impact on the relationship between PA and BI to use ECS, and a significant negative moderating effect of trust on the relationship between CV and BI to use ECS. The implications of these findings are discussed. [ABSTRACT FROM AUTHOR]

The role of the transparent envelope in energy savings is crucial as it accounts for a significant proportion of the total energy loss (between 30 and 40%). This paper focuses on the identification of reasonable parameters for the transparent envelope in different climatic regions. To achieve this goal, typical urban office buildings from four different climatic regions are used as research objects. A total of 1600 scenarios were simulated to investigate the variation of energy use intensity, including transparent envelope parameters, meteorological parameters and different types of glazing. The results show that for south-facing transparent envelope facades, type D glazing is the most energy efficient in severe cold regions, type C in colder regions and type B in the other two climatic regions. No solar shading is required in the very cold region. Horizontal shading can be an effective method for saving energy in colder climates, while comprehensive shading can be beneficial in other regions. Deep shading is particularly energy efficient if it meets lighting requirements. For example, in Guangzhou, energy savings of 13.46%, 15.47%, 7.01% and 7.02% can be achieved in the east, west, south and north directions, respectively, using B-type glazing and a comprehensive shading depth of 900 mm. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive analysis of digitized specimen data and relevant literature to investigate the vascular plant diversity in Guangzhou City, China. Specimen data were collected from various sources, including the China Digital Herbarium (CVH), the National Specimen Resource Sharing Platform (NSII), Global Plants on JSTOR, and the Global Biodiversity Information Facility (GBIF). Following data standardization, the study identified 41,890 vascular plant specimens, encompassing 248 families, 1563 genera, and 4536 species, including subspecies and cultivated plants. Among them, the native plants of Guangzhou city accounted for 60.6% of the species. The temporal analysis identified three distinct peaks in specimen collection: 1916–1920, 1928–1936, and 1950–1964. Collection activities were primarily concentrated between the months of April and November. The distribution of collected specimens exhibited significant variation among different species, with families such as Fabaceae, Poaceae, and Myrtaceae having the highest number of specimens. Similarly, genera such as Eucalyptus, Ficus, and Citrus were well-represented. The most frequently collected species included Litchi chinensis, Eucalyptus robusta, and Cycas taiwaniana. Remarkably, 21 species had specimen counts exceeding 100. Unfortunately, approximately three-quarters of the species had fewer than 10 recorded specimens. Alarmingly, 1220 species were represented by only one specimen. Geographically, the majority of specimens originated from the former suburbs of Guangzhou, Conghua Delta Mountain, and Liuxi River areas, while other regions had limited representation. In terms of specimen collections, the Herbarium of South China Botanical Garden of the Chinese Academy of Sciences (IBSC) recorded the highest number of specimens (13,828 specimens), followed by the Tree Herbarium of South China Agricultural University (CANT; 3869 specimens) and the Herbarium of Sun Yat-sen University (SYS; 3654 specimens). The collection history in Guangzhou spans nearly 300 years and can be broadly divided into two distinct periods. The first period extends from the late 13th century to 1949, primarily encompassing the collection efforts of foreign visitors in Guangzhou, and represents the pioneering phase of plant taxonomy research in China. The second period, from 1949 to the present, is characterized by extensive investigations and collection activities conducted by local scholars, with a specific emphasis on native plant resources. By meticulously organizing and verifying information derived from historical documents and specimens, the paper effectively summarizes the plant collection and research history of Guangzhou, providing detailed profiles of the key collectors. These findings furnish reliable historical reference materials for the study of plant taxonomy and diversity in Guangzhou. [ABSTRACT FROM AUTHOR]

This paper studies the spatial forms and cultural sustainability of the Damazhan and Xiaomazhan historical area, the only area that reflects the development of the assembled-clan hall culture in Guangzhou. In the face of modernization and reconstruction, traditional culture plays an increasingly crucial role in modern cities, determining the expression of architectural uniqueness and continuous development that adapts to social needs. Therefore, preserving cultural characteristics is more relevant than ever. This study combines historical literature research with typo-morphological analysis to establish analytical strategies that link cultural sustainability with spatial evolution from the perspective of sustainable development. The analytical framework consists of three parts: First of all, through historical literature research, a thorough analysis is conducted on the cultural and social influencing factors from the Dynasties of Song, Yuan, Ming, Qing and the Republic of China to the reform and opening up period. Secondly, feature elements of the location are extracted, and a typo-morphological approach is used to analyze the sustained changes in spatial forms. Finally, the relationship between changes in block form and building types and the inheritance and development of traditional culture are demonstrated. The analytical results indicate that the continuity of cultural characteristics is embodied in the continuity of the block and architectural spatial characteristics, while cultural transformation and man-made social factors affect the changes in spatial forms. This paper combines the perspective of cultural sustainability analysis with the traditional typo-morphological approaches of urban spatial analysis, supplementing the existing typo-morphological methodology. In addition, guiding the development of urban morphology from the perspective of cultural sustainability is of prominent practical significance. [ABSTRACT FROM AUTHOR]

The urban road network is a large and complex system characterized by significant heterogeneity arising from different spatial structures and traffic demands. To facilitate effective management and control, it is necessary to partition the road network into homogeneous sub-areas. In this regard, we aim to propose a hybrid method for partitioning sub-areas with intra-area homogeneity, inter-area heterogeneity, and similar sizes, called CSDRA. It is specifically designed for bidirectional road networks with segment weights that encompass traffic flow, speed, or roadside facility evaluation. Based on community detection and spectral clustering, this proposed method comprises four main modules: initial partition, partitioning of large sub-areas, reassignment of small sub-areas, and boundary adjustment. In the preliminary partitioning work, we also design a road network reconstruction method which further helps to enhance the intra-area homogeneity and inter-area heterogeneity of partitioning results. Furthermore, to align with the requirement for comparable work units in practical traffic management and control, we control the similarity in the size of sub-areas by enforcing upper and lower bound constraints on the size of the sub-areas. We verify the outperformance of the proposed method by an experiment on the partitioning of an urban road network in Guangzhou, China, where we employ sidewalk barrier-free score data as segment weights. The results demonstrate the effectiveness of both the road network reconstruction method and the CSDRA proposed in this paper, as they significantly improve the partitioning outcomes compared with other methods using different evaluation indicators corresponding to the partitioning objectives. Finally, we investigate the influence of constraint parameters on the evaluation indicator. Our findings indicate that appropriately configuring these constraint parameters can effectively minimize sub-region size variations while having minimal impact on other aspects. [ABSTRACT FROM AUTHOR]

This paper proposes an intelligent modeling and optimization method to set up the smart energy hub model for the multiple energy system and optimize the operation of its associated energy hub model automatically. The core idea of the proposed method is to divide the complex energy hub model into several simple energy hub models. In this paper, the proposed computerized algorithm, which is applied to the smart energy hub model division, includes an energy loop intelligent searching method, a real nodes arrangement method, and a virtual nodes insertion method. One case study for the multiple energy system of a residential district in Guangzhou city is performed to validate the effectiveness of the proposed method. Compared with the traditional calculation method, the proposed method guarantees global optimal operation decision for the whole multiple energy system and the computational burden is significantly reduced. [ABSTRACT FROM AUTHOR]

The relationship between social factors and the formation of exported mug designs is blurred. This study addresses how they influence material design. Based on a quantitative typological analysis, this paper interprets the cultural relationships underlying the evolution of mug designs exported during the Ming and Qing dynasties. The study reveals: (1) the typology and handle styles of mugs can be categorized into six types, with a predominance of Cylindrical bodies and Ear-shaped handles. Notably, artistic emphasis is concentrated on Bulbous cup bodies and Tail outward curved handles; (2) the design of mugs in the eighteenth century exhibited diversity, morphological similarities, and feature continuity, evolving from representational (Ming Dynasty) to abstract and then to minimalistic styles (Qing Dynasty), particularly evident in the three-dimensional modeling of handles for ergonomic comfort (transitioning from a singular Outward curved form to Ear-shaped form, and then to Entwined branch form); (3) the body shape of mugs transformed from Arc-barrel bodies to Bulbous bodies (focusing on heat retention), and eventually to Cylindrical bodies (prioritizing heat retention, practicality, and cost-efficiency).; (4) the volume of mugs steadily increased from the early eighteenth century, generally classified into large volume (≥ 500 ml), medium volume (200-499 ml), and small volume (< 200 ml); (5) considering the extreme range of volume (11090 ml) and height (25 cm), it indicates that these two variables do not necessarily have a direct positive correlation; (6) the low center of gravity in handle design (average width of 3.4 cm against an average height of 9.9 cm for the body) reflects considerations for the distribution of liquid weight and operational convenience. The volume of sample-10 (11127 ml) notably exceeds the typical range for tea-drinking utensils, revealing the mechanism of wealth and status symbolism. Market demand orientation emerged as the primary driver for the evolution of export mug designs during the Ming and Qing Dynasties, with adjustments in the merchant system playing a secondary role. The transformation in mug design reflects the interplay of multiple factors, with the trend toward minimalist design being a response to market demands. [ABSTRACT FROM AUTHOR]

Recent advances in knowledge graphs show great promise to link various data together to provide a semantic network. Place is an important part in the big picture of the knowledge graph since it serves as a powerful glue to link any data to its georeference. A key technical challenge in constructing knowledge graphs with location nodes as geographical references is the matching of place entities. Traditional methods typically rely on rule-based matching or machine-learning techniques to determine if two place names refer to the same location. However, these approaches are often limited in the feature selection of places for matching criteria, resulting in imbalanced consideration of spatial and semantic features. Deep feature-based methods such as deep learning methods show great promise for improved place data conflation. This paper introduces a Semantic-Spatial Aware Representation Learning Model (SSARLM) for Place Matching. SSARLM liberates the tedious manual feature extraction step inherent in traditional methods, enabling an end-to-end place entity matching pipeline. Furthermore, we introduce an embedding fusion module designed for the unified encoding of semantic and spatial information. In the experiment, we evaluate the approach to named places from Guangzhou and Shanghai cities in GeoNames, OpenStreetMap (OSM), and Baidu Map. The SSARLM is compared with several classical and commonly used binary classification machine learning models, and the state-of-the-art large language model, GPT-4. The results demonstrate the benefit of pre-trained models in data conflation of named places. [ABSTRACT FROM AUTHOR]

Efficient monitoring of water quality parameters (WQPs) is crucial for environmental health. Drone hyperspectral images have offered the potential for the flexible and accurate retrieval of WQPs. However, a machine learning (ML)-based multi-process strategy for WQP inversion has yet to be established. Taking a typical urban river in Guangzhou city, China, as the study area, this paper proposes a machine learning-based strategy combining spectral preprocessing and ML regression models with ground truth WQP data. Fractional order derivation (FOD) and discrete wavelet transform (DWT) methods were used to explore potential spectral information. Then, multiple methods were applied to select sensitive features. Three modeling strategies were constructed for retrieving four WQPs, including the Secchi depth (SD), turbidity (TUB), total phosphorus (TP), and permanganate index (CODMn). The highest R2s were 0.68, 0.90, 0.70, and 0.96, respectively, with corresponding RMSEs of 13.73 cm, 6.50 NTU, 0.06 mg/L, and 0.20 mg/L. Decision tree regression (DTR) was found to have the potential with the best performance for the first three WQPs, and eXtreme Gradient Boosting Regression (XGBR) for the CODMn. Moreover, tailored feature selection methods emphasize the importance of fitting processing strategies for specific parameters. This study provides an effective framework for WQP inversion that combines spectra mining and extraction based on drone hyperspectral images, supporting water quality monitoring and management in urban rivers. [ABSTRACT FROM AUTHOR]

Busy, complex railway stations that serve as origin and termination points for a significant proportion of trains are essential to regional railway networks. Resolving conflicts between arrival–departure operations and shunting operations of cross-line trains and originating or terminating passenger trains in the throat area is important for safety in these multidirectional stations. The main task of this paper is to study the train platforming problem, and we consider the integration of track and route allocation with shunting route allocation on the basis of the traditional TTP problem, so as to formulate a strong anti-interference track allocation plan for busy, complex railway stations. Therefore, in view of the complex characteristics of train operation in busy, complex railway stations, we extensively examine the technical operational characteristics of various trains in multidirectional stations, which are the key constraints of the model, and establish a mixed-integer linear programming model. This model aims to balance the buffer time for track occupation and optimize the routing and scheduling of trains in stations. Furthermore, an improved genetic algorithm is proposed to effectively implement the developed model. In the case study of Guangzhou Station, the occupation analysis after the optimization of the method in this paper indicates that the shunting operations significantly interfere with arrival–departure operations in throat areas. The optimization of buffer times and track utilization times resulted in notable reductions of 30.55% and 77.82%, respectively, in quadratic differences. These outcomes provide empirical evidence supporting the feasibility of the proposed model and algorithm for addressing train platforming problems, particularly in complex, multidirectional, and heavily trafficked railway stations. [ABSTRACT FROM AUTHOR]

Port-centric intermodal transshipment hubs are significant nodes in the global freight network and are likewise the gateway to a country's external communications. It is vital to increase the service capacity of PCITHs, and it is necessary to assess the service capacity of port-centric intermodal transshipment hubs to respond to the growth of economies and global freight needs. This study provides a detailed definition of port-centric intermodal transshipment hubs through a review of relevant kinds of works from the literature and analyzes their primary functions. Based on the research perspective of sea–rail intermodal transportation, the three evaluation dimensions of service capacity of port-centric intermodal transshipment hubs are divided into radiation scale capacity, transportation connection capacity, and resource integration capacity, focusing on the functions of cargo aggregation, cargo transfer, and connection of different transportation modes. The service capacity evaluation indicators were then selected based on the three dimensions. The subjective and objective weightings were calculated by the G1 weighting method and the modified CRITIC method, and the combination weightings were determined based on game theory. The service capability of port-centric intermodal transshipment hubs was evaluated by the fuzzy matter element method, and the evaluation results were quantified by the Euclidean closeness degree. Finally, through the barrier degree model, the current indicators of PCITHs that urgently need improvement were explored, and targeted improvement suggestions are proposed in this paper. The results show that Tianjin Port has the highest service capacity, followed by Ningbo Zhoushan Port. The port rail dedicated line mileage is the most critical area that needs attention in Ningbo Zhoushan Port and Qingdao Port. Tianjin Port needs to improve the container sea–rail transportation volume, while Guangzhou Port and Xiamen Port need to improve the sea–rail container handling capacity. [ABSTRACT FROM AUTHOR]

This paper summarizes the results of an effort aimed at improving train operation schedules on Wuhan-Guangzhou high-speed railway (WG-HSR). The real-record train operation and passenger tickets-booking records of WG-HSR are used for statistical analysis on the train service quality and passenger distribution. More specifically, the train service frequency and interval time at each station are analyzed. Based on this, the temporal and spatial distribution of capacity utilization in each section are investigated. In order to get a holistic view of passenger flow characteristics, the passenger volume during different time periods and between several origin and destination (OD) pairs are investigated to characterize travellers' spatial-temporal preferences. The passenger distributions on some long-distance trains are shown to get the number and proportion of cross-line passengers travelling on the WG-HSR. Moreover, for a better understanding of the seat capacity utilization of trains, the load rates of trains in various sections and time periods are investigated. Specifically, the relationship between the average load rate of trains and trains' running distance is explored, finding that the longer the non-cross-line train travels is, the higher the average load rate is. This study provides insightful findings that help understanding HSR operation and conducting further research. [ABSTRACT FROM AUTHOR]

Nowadays more private car trips have caused worse congestion due to the Covid-19 pandemic in many cities. Congestion charging is one of the taxes that is levied on vehicle owners to reduce urban traffic congestion. One of the most important reasons congestion charging is not accepted by the public is the high cost. Monitoring the state of traffic congestion in real time requires a lot of expensive installations. The purpose of this paper is to make congestion charging more accurate and acceptable using artificial intelligent algorithm. Massive real-time Global Positioning System (GPS) data provides new data for road congestion charging. The queuing length at intersections is an important measurement for the degree of traffic congestion, and it is also the basis for road congestion pricing. GPS positioning cannot provide sufficient position accuracy for lane identification of vehicles. In this study, a comprehensive model consisting of a real-time lane identification model and a real-time queue length estimation model is developed based on the traffic shockwave theory using GPS data. The comprehensive model can identify the lane where the queuing vehicle is located and estimate the real-time queue length of the lane. The proposed models were evaluated using field-collected data in Guangzhou, China. The testing results show that the proposed comprehensive model can identify lanes and estimate queue lengths with satisfactory accuracy. The model proposed in this paper provides real-time data for road dynamic pricing in a cost-effective way, which can promote the implementation of congestion charging in cities. [ABSTRACT FROM AUTHOR]

In the course of China's rapid urbanization, rural places are brought into urban areas, forming semi-urbanization. These semi-urbanized sites suggest a dual urban–rural structure in their form and management. With the slowing down of urbanization, the Chinese government adopted heritage tourism to boost the local economy. Local historic buildings and cultural resources were regenerated and restored in this process. This paper aims at examining the role of heritage tourism in blurring the boundary of rurality and urbanity, boosting local economy, and revitalizing the areas with cultural-led development. In this paper, we analyzed the Huangpu Ancient Village's regeneration process. We argue that the Huangpu Ancient Village integrates local historical and cultural resources to boost the local economy, simultaneously adopting urban renewal and rural revival strategies. This paper contributes to the body of literature addressing villages in urban areas, breaking the duality of urbanity and rurality. [ABSTRACT FROM AUTHOR]

An airport's terminal area is the bottleneck of the air transport system. Convective weather can seriously affect the normal flight status of arrival and departure flights. At present, pilots take different flight operation strategies to avoid convective weather based on onboard radar, visual information, adverse weather experience, etc. This paper studies trajectory clustering based on the OPTICS algorithm to obtain the arrival of typical flight routes in the terminal area. Based on weather information of the planned typical flight route and flight plan information, Random Forest (RF), K-nearest Neighbor KNN (KNN), and Support Vector Machines (SVM) algorithms were used for training and establishing the Arrival Flight Operation Strategy Prediction Model (AFOSPM). In this paper, case studies of historical arrival flights in the Guangzhou (ZGGG) and Wuhan (ZHHH) terminal area were carried out. The results show that trajectory clustering results based on the OPTICS algorithm can more accurately reflect the regular flight routes of arrival flights in a terminal area. Compared to KNN and SVM, the prediction accuracy of AFOSPM based on RF is better, reaching more than 88%. On this basis, six features—including 90% VIL, weather coverage, weather duration, planned route, max VIL, and planned Arrival Gate (AF)—were used as the input features for AFOSPM, which can effectively predict various arrival flight operation strategies. For the most frequently used arrival flight operation strategies under convective weather conditions—radar guidance, AF changing, and diversion strategy—the prediction accuracy of the ZGGG and ZHHH terminal areas can exceed 95%, 85%, and 80%, respectively. [ABSTRACT FROM AUTHOR]

Featured Application: The architectural design, modeling, mechanical dynamic simulation, and corresponding analysis have been applied to a practical new construction program, a science museum located in Guangzhou, China. Heating ventilation and air conditioning systems account for over one-third of building energy usage, especially for public buildings, due to large indoor heat sources and high ventilation and thermal comfort requirements compared to residential buildings. Natural ventilation shows high application potential in public buildings because of its highly efficient ventilation effect and energy-saving potential for indoor heat dissipation. In this paper, a building design is proposed for a science museum with atrium-centered natural ventilation consideration. The floor layout, building orientation, and internal structure are optimized to make full use of natural ventilation for space cooling under local climatic conditions. The natural ventilation model is established through computational fluid dynamics (CFD) for airflow evaluation under indoor and outdoor pressure differences. The preliminary results show that such an atrium-centered architectural design could facilitate an average air exchange rate over 2 h−1 via the natural ventilation effect. Moreover, indoor thermal environment simulation results indicate that the exhaust air temperature can be about 5 °C higher than the indoor air mean temperature during the daytime, resulting in about 41.2% air conditioning energy saving ratio due to the free cooling effect of natural ventilation. This work can provide guidance and references for natural ventilation optimization design in public buildings. [ABSTRACT FROM AUTHOR]

The objective of this paper is to recommend an adjusted Susceptible-Exposed-Infectious-Removed (SEIR) model that characterizes the temporal patterns of various individuals affected by the omicron variant in an epidemic. This model considers factors such as vaccination, asymptomatic cases, indoor and outdoor air, hospitalizations, and deaths, as well as the impact of immunization and memory trace. While many recent studies overlook the complexities of multiple strains, including their diverse transmission rates and reaction to vaccines, this study introduces a new fractional derivative model to examine the spread of the omicron variant of COVID-19 and the implementation of a vaccination campaign. A thorough theoretical analysis is conducted, and the critical factor (R c r n z) is calculated using the model equations. It is demonstrated that when R c r n z is less than 1, the disease-free state is globally asymptotically stable, meaning that the epidemic diminishes. Moreover, the stability of both global and local equilibrium points is examined. Numerical simulations are employed to demonstrate the alignment between the numerical findings and theoretical characteristics. The model is adjusted to experimental data that reflect the progression of the omicron variant of COVID-19 in Guangzhou, exhibiting a satisfactory performance in predicting the number of infected individuals, thereby suggesting its capability to accurately estimate asymptomatic cases. Furthermore, to emphasize the benefits of employing fractional differential equations, the paper provides examples related to memory trace and hereditary characteristics. Moreover, the examined models are expected to be applied and expanded upon in order to contribute to the formulation of policies for disease control during times of limited vaccine availability. To summarize, the model appears to be a sufficient tool for researching and managing infectious diseases. It is projected that as the Omicron variant's prevalence declines, there will be a reduced need for respiratory-focused precautions. • An SVEIAOPHRD model is put forward to mathematically analyze the spread of the omicron variation of COVID-19. • Mathematical criteria for determining the stability of the equilibria are established. • An efficient nonstandard approach for resolving the continuous problem is suggested and examined. • The numerical simulations validate the analytical and numerical outcomes depicted in this study. [ABSTRACT FROM AUTHOR]

Guangzhou is located in the southern part of China, near the South China Sea, belongs to Guangdong Province. It serves as China's southern gateway to the world and was historically called "The Southern Treasure of the Emperor", playing a crucial role in China's maritime trade history. Throughout Chinese history, Guangzhou underwent several cycles of "closure" and "opening", policies that severely impacted trade. However, foreign merchants never ceased to request permission from the Chinese government to engage in trade. In 1757, Emperor Qianlong decreed Guangzhou as the only one official port for foreign trade. This edict led to the establishment of the one port trading system in Guangzhou, as the Qing government aimed to counter foreign influences and local uprisings while maintaining a self-sufficient small-scale agricultural economy. Western nations and their traders sought opportunities within this system, aspiring to expand trade to other regions of China, even the inland areas. The exclusive status of Guangzhou as China's only one trading port persisted until 1842, following the defeat of the Qing government in the Opium War against Britain, the Nanjing Treaty was signed. This treaty opened Guangzhou, Shanghai, Ningbo, Fuzhou, and Xiamen as trading ports, bringing an end to the one port trading system. The reasons and impacts of the establishment of this system have not been comprehensively analyzed to date. Therefore, this paper based on historical archives, analyzes both the direct and underlying reasons behind Emperor Qianlong's decision and elucidates the system's diverse impacts on various aspects of Qing-era China. [ABSTRACT FROM AUTHOR]

The rise in aging world populations poses enormous concerns, among which is the critical topic of how to promote active aging by improving the health and well-being of the elderly. Accordingly, installing elevators in old residential buildings has become a main issue in age-friendly community regeneration to make it easier for the elderly to go outside. There is limited evidence on stakeholder involvement in age-friendly community regeneration. Some studies have overlooked the fact that fostering age-friendly communities in developing countries requires innovative governance for inclusive physical and social features despite the low awareness of citizen engagement. With reference to community governance as a structure and process, a theoretical framework is proposed to understand the practice of elevator installation in age-friendly community regeneration in Guangzhou, China. This study adopted the questionnaire survey method and collected 455 valid samples (150 valid samples with installed elevators; 305 valid samples did not install elevators). The findings led to the following conclusions: (1) shared common interests lead to effective community governance and smooth elevator installation; (2) some communities failed to install elevators due to opposition from people whose interests were hindered; and (3) it is important to set up self-governing organizations and find key people in community governance for interest-based negotiation. This paper's contribution is that it makes up for the deficiency in the previous research that has neglected the elderly's participation in public affairs via age-friendly community regeneration. Finally, this study suggests further research on the dynamic processes of different types of age-friendly community regeneration affairs. [ABSTRACT FROM AUTHOR]

Accurately predicting carbon price is crucial for risk avoidance in the carbon financial market. In light of the complex characteristics of the regional carbon price in China, this paper proposes a model to forecast carbon price based on the multi-factor hybrid kernel-based extreme learning machine (HKELM) by combining secondary decomposition and ensemble learning. Variational mode decomposition (VMD) is first used to decompose the carbon price into several modes, and range entropy is then used to reconstruct these modes. The multi-factor HKELM optimized by the sparrow search algorithm is used to forecast the reconstructed subsequences, where the main external factors innovatively selected by maximum information coefficient and historical time-series data on carbon prices are both considered as input variables to the forecasting model. Following this, the improved complete ensemble-based empirical mode decomposition with adaptive noise and range entropy are respectively used to decompose and reconstruct the residual term generated by VMD. Finally, the nonlinear ensemble learning method is introduced to determine the predictions of residual term and final carbon price. In the empirical analysis of Guangzhou market, the root mean square error(RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of the model are 0.1716, 0.1218 and 0.0026, respectively. The proposed model outperforms other comparative models in predicting accuracy. The work here extends the research on forecasting theory and methods of predicting the carbon price. [ABSTRACT FROM AUTHOR]