Search

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]

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]

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]

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]

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]

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 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]

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]

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]

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]

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]

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 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]

Sky radiative cooling is a kind of passive cooling technology that uses the "atmospheric window" to emit the object's own heat to the low temperature of outer space; this technology has low energy consumption, no pollution, and other useful characteristics, so in recent years it has attracted widespread attention. The cooling effect of the sky radiative cooler is mainly affected by the constantly changing outdoor ambient temperature. In addition, the structure of the radiative cooler itself also means that its radiative cooling power undergoes obvious changes. Here, we utilized COMSOL simulation software to establish a numerical heat transfer model for radiative cooling, aimed at investigating the influencing factors on the sky radiative cooler and methods to enhance the structure of the radiative cooling. This study discusses outdoor ambient wind speed, the inlet flow rate of the cooler, installation angle of the cooler, and different cooler structures. Based on simulation results, it is observed that, for varying wind speeds, when the ambient radiation temperature is higher than the surface temperature of the cooler, a larger ambient wind speed leads to a poorer refrigeration effect. The maximum temperature difference in surface temperature at wind speeds of 0 m/s and 4 m/s is 0.59 °C. When the ambient temperature is lower than the surface temperature of the cooler, a smaller wind speed results in a greater net refrigeration power. The maximum temperature difference in this scenario is 0.32 °C. The net refrigeration power of the radiative cooler increases with an increase in water flow rate. As the water flow rate increases from 0 L/min to 5 L/min, the net refrigeration power increases from 25 W/m2 to 200 W/m2 and gradually stabilizes. Considering the radiative impact of the cooler on the surrounding environment, as the installation angle increases from 0° to 90°, the surface temperature of the cooler first increases and then decreases, reaching its highest temperature of 29.26 °C at 45°. The surface temperature of the cooler varies with the thickness of the air sandwich, increasing from 1 cm to 12 cm, and then decreasing. The lowest temperature of 23.4 °C is achieved at a thickness of 8 cm. The increase in the fin structure on the surface of the radiative cooler leads to a decrease in its refrigeration performance, and the difference between the inlet and outlet temperatures of the radiative cooler with a flat plate structure is always greater than that of the finned plate, and the difference in the average radiance is 23.52 W/m2. Finally, the energy-saving effect of the sky radiative cooling composite system is analyzed. Taking a typical small office building as an example, an energy consumption analysis model is set up, and the energy consumption of the composite system is simulated in four cities with different climates, using EnergyPlus software (version 8.6); the system's power consumption is the largest in hot and humid climates. Compared with the traditional vapor-compression refrigeration system, the composite system reduces air conditioning power consumption by 25.7%, 32.5%, 37.1%, and 44.8% in Guangzhou, Shanghai, Jinan, and Shenyang, respectively. The main innovations of this paper include analyzing and studying the influence of the tilt angle change of the radiative plate on the refrigeration performance of the cooler and the relationship between the surrounding buildings, adding air sandwiches and ribs to the radiative cooler to analyze the influence of convective heat transfer on the refrigeration effect, which plays a guiding role in the design and research of the sky radiative cooler. [ABSTRACT FROM AUTHOR]

Out-of-hospital cardiac arrest (OHCA) causes a high mortality rate each year, which is a threat to human well-being and health. An automated external defibrillator (AED) is an effective device for heart attack-related diseases and is a panacea to save OHCA. Most relevant literature focuses on the spatial distribution, accessibility, and configuration optimization of AED devices, which all belong to the characteristics of the spatial distribution of AED devices. Still, there is a lack of discussion on related potential influencing factors. In addition, analysis of AED facilities involving multiple city comparisons is less considered. In this study, data on AED facilities in two major cities in China were obtained through the WeChat applet. Then, the AED equity at the city and block scales and its socioeconomic factors were analyzed using the Gini coefficient, Lorenz curve, and optimal parameters-based geo-graphical detector (OPGD) model. Results show that the number of AEDs in Shenzhen was about eight-times that of in Guangzhou. The distribution of AEDs in Shenzhen was more equitable with a global Gini of 0.347, higher than that in Guangzhou with a global Gini of 0.504. As for the determinants of AED equity, residential density was the most significant determinant in both Guangzhou and Shenzhen from the perspective of individual effects on AED equity. Differently, due to the aging population in Guangzhou, the proportion of the elderly in blocks was influential to local AED equity. The local economic development level was crucial to local AED equity in Shenzhen. The results of the interaction detector model illustrate that relatively equitable AED distributions were found in the high-density residential areas with a balance of employment and housing, high-aging residential areas, and high-mobility residential areas in Guangzhou. The area with a high level of local economic development, dense population, and large mobility was the area with a relatively equitable distribution of AEDs in Shenzhen. The results of this paper are conducive to understanding the equity of AEDs and its socio-economic determinants, providing scientific reference for the optimization and management of AEDs. [ABSTRACT FROM AUTHOR]

The regional energy system (RES) is a system that consumes multiple forms of energy in the region and achieves coordinated and efficient utilization of energy resources. The RES is composed of multiple micro energy systems (MESs); however, due to the mismatch of energy resources and different energy consumption within each MES, a large amount of clean energy is wasted, and each MES has to acquire extra energy. This significantly increases operation costs and contributes to environmental pollution. One of the promising ways to solve this problem is to deploy an energy storage system in the RES, which can make use of its advantages to transfer energy in space-time and fulfill the demand for loads in different periods, and conduct unified energy management for each MES in the RES. Nevertheless, a large number of users are deterred by the high investment in energy storage devices. A shared energy storage system (SESS) can allow multi-MESs to share one energy storage system, and meet the energy storage needs of different systems, to reduce the capital investment of energy storage systems and realize efficient consumption of clean energy. Taking multiple MESs as the object, this paper proposes a model and collaborative optimal strategy of energy management for the RES to accomplish high utilization of clean energy, environmental friendliness, and economy. First, the paper analyzes the internal energy supply characteristics of the RES and develops a model of the RES with an SESS. Then, the paper poses the management concept of load integration and unified energy distribution by using the operational information of each subsystem. An optimal operation strategy is established to minimize daily operation costs and achieve economic, environmentally friendly, and efficient operation of the RES. Third, by setting up scenarios such as no energy storage system and an independent energy storage system (IESS) of each MES and SESS, a case of a science and education park in Guangzhou, China, is illustrated for experiments. Numerical experiment results show that with an SESS built by the investor in the RES and applying the mentioned energy management strategy, the utilization of clean energy can be 100%, the operation costs can be reduced by up to 9.78%, the pollutant emission can be reduced by 3.92%, and the peak-to-valley difference can be decreased by 20.03%. Finally, the influence of energy storage service fees and electricity tariffs on daily operation costs is discussed, and the operation suggestions of the SESS are proposed. It validates the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

This paper explores the specific "authoritarian" type of adaptive governance of urban regeneration using the example of Guangzhou city as the frontier of China's reforms. As opposed to the "democratic" type of adaptive governance with its bottom-up policy initiations, community autonomy, polycentric power, participation in decision making, and self-organized policy actors, adaptive governance in Guangzhou is based on top-down decision making and implementation of public authorities' solutions with the high role of political considerations. By analyzing data collected from policy documents, interviews, secondary data, and participative observations, this paper reveals three phases of urban regeneration in Guangzhou between 2009 and 2019: two of them based on "Three Old Redevelopment" policy implementation and the third one based on the local micro-regeneration initiative. Tradeoffs among urban regeneration, land leasing income and micro-regeneration are the key means of policy adaptation which differ from the described phases. Methodologically, the paper does not limit itself by answering only the traditional research questions in regeneration studies of "what" has changed and "why" these changes have happened. Instead, the main focus includes "how" such changes have occurred, which is less researched in the literature. Social–political mechanisms, including limited check-and-balance, selective feedback, and the social learning capacity of the local state, are crucial governance factors to enable adaptation. [ABSTRACT FROM AUTHOR]

Global climate change is one of the major challenges facing the world, and the spatial optimization of land use patterns has been regarded as critical in realizing carbon mitigation. In this study, the linear programming model and the Markov Chain model are integrated in different scenarios to optimize land use structure for low-carbon development. The land use pattern is then simulated through the adjusted convolutional neural network and cellular automata model, taking Guangzhou City as the case study area. The results reveal that construction land with high economic efficiency will increase its area, and the reaming types will experience slight changes, in 2035 in the natural development scenario and the economic priority scenario. Ecological land such as forest land, grassland, and water is partly occupied by construction land in the urban–rural fringe areas. The total carbon emissions decrease by 2.32% and 1.57% in these two scenarios. In the low-carbon-oriented scenario, the expansion of construction land is restricted, and the forest land and grassland undergo great expansion. The total carbon emission decreases by 18.95%—a figure much larger than that in the natural development scenario and the economic priority scenario. Our paper embeds the needs and constraints in land spatial planning into the spatial optimization of the land use pattern, which provides valuable references for low-carbon city development in the future. [ABSTRACT FROM AUTHOR]

The demand for transportation among urban residents in China is increasing in tandem with the nation's population growth, rising consumption levels, and increasing car ownership rates. Breaking the existing high-carbon travel practices and reshaping positive low-carbon awareness represents an inevitable way to change existing transportation structures and reduce urban traffic congestion and carbon emissions. A mediating effect model was employed and we found that community satisfaction is an essential variable in the effect of traffic accessibility and travel behavior on low-carbon awareness. First, the impact of residents' zero and low-carbon actions on their low-carbon awareness is mediated by community satisfaction. Furthermore, compared to high-income groups, community satisfaction exerts a robust mediating influence on low-income groups. The mediating effect of community satisfaction on the relationship between residential proximity to commercial centers and low-carbon awareness among individuals with low incomes is evident. Based on these findings, this paper explores the heterogeneity and associated measures of low-carbon awareness among residents. The conclusion of this study provides suggestions to promote residents' low-carbon awareness by improving their travel experience from the perspective of community construction, providing scientific reference and a basis for the formulation of transportation policies for low-carbon city construction. [ABSTRACT FROM AUTHOR]

The accurate prediction of passenger flow is crucial in improving the quality of the service of intercity high-speed railways. At present, there are a few studies on such predictions for railway origin–destination (O-D) pairs, and usually only a single factor is considered, yielding a low prediction accuracy. In this paper, we propose a neural network model based on multi-source data (NN-MSD) to predict the O-D passenger flow of intercity high-speed railways at different times in one day in the short term, considering the factors of time, space, and weather. Firstly, the factors that influence time-varying passenger flow are analyzed based on multi-source data. The cyclical characteristics, spatial and temporal fusion characteristics, and weather characteristics are extracted. Secondly, a neural network model including three modules is designed based on the characteristics. A fully connected network (FCN) model is used in the first module to process the classification data. A bi-directional Long Short-Term Memory (Bi-LSTM) model is used in the second module to process the time series data. The results of the first module and the second module are spliced and fused in the third module using an FCN model. Finally, an experimental analysis is performed for the Guangzhou–Zhuhai intercity high-speed railway in China, in which three groups of comparison experiments are designed. The results show that the proposed NN-MSD model can predict many O-D pairs with a high and stable accuracy, which outperforms the baseline models, and multi-source data are very helpful in improving the prediction accuracy. [ABSTRACT FROM AUTHOR]

High-rise building areas (HRBs) provide significant social and environmental services and play a crucial role in modern urbanization. The large-scale and long-term spatial distribution of HRBs is of great interest to many fields, such as urban planning and local climate analysis. While previous studies have confirmed the value of Sentinel-2 images in extracting HRBs and their changes, current work is limited to relatively local areas and short-term analysis. One reason is due to the fact that the earliest Sentinel-2 image can only date back to 2015. To address this research gap, this paper proposes an efficient procedure to intelligently extract HRBs and their changes from multitemporal Landsat-7 and Sentinel-2 images, using a specifically designed fully convolutional network. To validate the proposed method, we selected four typical cities in China, namely, Beijing, Shanghai, Guangzhou, and Zhengzhou, as study areas. We utilized Landsat-7 images acquired in 2000 and 2010, along with Sentinel-2 images acquired in 2020, as experimental data. We extracted and analyzed three periods of HRBs and their changes in the four cities, along with urban rail terminal data and gross domestic product (GDP) data in the same period. The results show that the proposed method can efficiently extract HRBs and their changes in the four cities over the past 20 years, with an overall accuracy of more than 90%. HRBs changes are primarily driven by urban planning policies and geographical factors. There is a strong positive correlation between the increase in HRBs and the increase in rail terminals, both in terms of quantity and spatial distribution. Additionally, there is a positive correlation between HRBs increase and GDP increase in terms of quantity, but the trend varies in different cities due to their diverse developing modes. Overall, the results indicate that the proposed method can be a potential operational tool to extract large-scale and long-term HRBs and their changes in China. [ABSTRACT FROM AUTHOR]

Simple Summary: Adhesive tapes are as effective as baits and pitfall traps in monitoring Solenopsis invicta and Tapinoma melanocephalum in urban areas in southern China. However, adhesive tapes detected less ants and fewer species of non-target ants than baits and pitfall traps. Our study demonstrated that tape-paving behavior can potentially be used in developing more specific monitoring methods for S. invicta and T. melanocephalum in urban areas in southern China. Our previous study discovered that two urban pest ants, red imported fire ants, Solenopsis invicta Buren (Formicidae: Myrmicinae), and ghost ants, Tapinoma melanocephalum (Fabricius) (Formicidae: Dolichoderinae), can pave viscose surfaces with particles to facilitate food search and transport. We hypothesize that this paving behavior can be applied to monitor S. invicta and T. melanocephalum. In the present study, 3998 adhesive tapes, each with a food source (sausage), were placed in 20 locations around Guangzhou, China (181–224 tapes per location), and their efficiency to detect S. invicta and T. melanocephalum was compared with two traditional ant-monitoring methods, baiting and pitfall trapping. Overall, S. invicta was detected by 45.6% and 46.4% of baits and adhesive tapes, respectively. In each location, the percentage of adhesive tapes detecting S. invicta and T. melanocephalum was similar when compared to baits and pitfall traps. However, significantly more non-target ant species showed up on bait and pitfall traps. Seven non-target ant species—Pheidole parva Mayr (Formicidae: Myrmicinae), Pheidole nodus Smith (Formicidae: Myrmicinae), Pheidole sinica Wu & Wang (Formicidae: Myrmicinae), Pheidole yeensis Forel (Formicidae: Myrmicinae), Carebara affinis (Jerdon) (Formicidae: Myrmicinae), Camponotus nicobarensis Mayr (Formicidae: Formicinae), and Odontoponera transversa (Smith) (Formicidae: Ponerinae)—also showed tape paving behavior, but they can be easily distinguished morphologically from S. invicta and T. melanocephalum. Our study showed that the paving behavior occurs in different subfamilies of ants (i.e., myrmicinae, dolichoderinae, formicinae, and ponerinae). In addition, paving behavior can potentially be used to develop more specific monitoring methods for S. invicta and T. melanocephalum in urban areas in southern China. [ABSTRACT FROM AUTHOR]

Based on the panel data of 41 cities along and around the Guangzhou Zhuhai intercity railway (GZR) from 2005 to 2018 and taking the opening of the GZR as a natural experimental scenario, the difference-in-difference (DID) method was used to empirically test the impact of the opening of the GZR on the innovation of cities along the line. The research results show that the opening of GZR has had a statistically positive effect on the innovation of cities along the route—that is, the innovation dividend of high-speed railway (HSR)cities exists, which improves the level of urban innovation—and further, there is time dynamics and regional heterogeneity in the innovation dividend. The research results of this paper have significant policy implications for optimizing China's HSR network. [ABSTRACT FROM AUTHOR]

As a development form of the creative industry, the Artist Village is a high concern of the Chinese government, and it has achieved rapid developments in China in recent years. However, many Artist Villages come to an untimely end a short period after their birth and fail to realize sustainable development. In this study, an empirical analysis on 80 Artist Villages in China was carried out. A field investigation and research on eight Artist Villages was implemented. Attention was paid to thoroughly analyze three typical Artist Villages of Guangzhou Xiaozhou Artist Village, Chongqing Gujianshan Artist Village and Beijing Songzhuang Artist Village. It has been found from studies that the development of Artist Villages in China has experienced initiation, development and maturity stages. The development of Artist Villages in China generally has many problems, such as an insufficient endogenous impetus, the excessive intervention of government, market capital "squeezing out" the original artists, and so on. This paper proposed a sustainable development model for Artist Villages during urbanization in China based on the findings and conclusions of this study. This study not only enriches research contents in this field, but can also provide meaningful references for the sustainable development of Artist Villages in China. [ABSTRACT FROM AUTHOR]

Time-varying passenger flow is the input data in the optimization design of intercity high-speed railway transportation products, and it plays an important role. Therefore, it is necessary to predict the origin-destination (O-D) passenger flow at different times of the day in combination with the stable time-varying characteristics. In this paper, three neural network-based hybrid forecasting models are designed and compared, named Variational Mode Decomposition-Multilayer Perceptron (VMD-MLP), Variational Mode Decomposition-Gated Recurrent Unit Neural Network (VMD-GRU), and Variational Mode Decomposition-Bidirectional Long Short-Term Memory Neural Network (VMD-Bi-LSTM). First, the time-varying characteristics of passenger travel demand under different time granularities are analyzed and extracted by the VMD method. Second, three neural network prediction models are constructed to predict the passenger flow sequence after VMD decomposition and reconstruction. Experimental analysis is performed on the Guangzhou Zhuhai intercity high-speed railway in China, and the passenger flow at different time periods of the day under different time granularities is predicted. The following results were found: (i) The number of hidden neurons and the number of iterations of the hybrid forecasting model have a great impact on the prediction accuracy. The error of the VMD-MLP model fluctuates less and it performs more smoothly than both the VMD-GRU model and the VMD-Bi-LSTM model. (ii) The VMD-MLP, VMD-GRU, and VMD-Bi-LSTM models can basically reduce the MAPE error to less than 10%. With the increase of time granularity, RMSE and MAE errors tend to gradually increase, while the MAPE error tends to gradually decrease. (iii) For passenger flow under a smaller time granularity, the prediction accuracy of the VMD-MLP model is higher, while for passenger flow under a larger time granularity, the prediction accuracy of the VMD-GRU and VMD-Bi-LSTM models is higher. (iv) The proposed neural network-based hybrid models outperform the existing models and the hybrid models perform better than the single models. [ABSTRACT FROM AUTHOR]

With the process of increasing urbanization, there is great significance in obtaining urban change information by applying land cover change detection techniques. However, these existing methods still struggle to achieve convincing performances and are insufficient for practical applications. In this paper, we constructed a new data set, named Wenzhou data set, aiming to detect the land cover changes of Wenzhou City and thus update the urban expanding geographic data. Based on this data set, we provide a new self-attention and convolution fusion network (SCFNet) for the land cover change detection of the Wenzhou data set. The SCFNet is composed of three modules, including backbone (local–global pyramid feature extractor in SLGPNet), self-attention and convolution fusion module (SCFM), and residual refinement module (RRM). The SCFM combines the self-attention mechanism with convolutional layers to acquire a better feature representation. Furthermore, RRM exploits dilated convolutions with different dilation rates to refine more accurate and complete predictions over changed areas. In addition, to explore the performance of existing computational intelligence techniques in application scenarios, we selected six classical and advanced deep learning-based methods for systematic testing and comparison. The extensive experiments on the Wenzhou and Guangzhou data sets demonstrated that our SCFNet obviously outperforms other existing methods. On the Wenzhou data set, the precision, recall and F1-score of our SCFNet are all better than 85%. [ABSTRACT FROM AUTHOR]

During accelerated urbanization, the lack of attention to environmental protection and governance led to the formation of black-odor water. The existence of urban black-odor water not only affects the cityscape, but also threatens human health and damages urban ecosystems. The black-odor water bodies are small and hidden, so they require large-scale and high-resolution monitoring which offers a temporal and spatial variation of water quality frequently, and the unmanned aerial vehicle (UAV) with a multispectral instrument is up to the monitoring task. In this paper, the Nemerow comprehensive pollution index (NCPI) was introduced to assess the pollution degree of black-odor water in order to avoid inaccurate identification based on a single water parameter. Based on the UAV-borne multispectral data and NCPI of sampling points, regression models for inverting the parameter indicative of water quality were established using three artificial intelligence algorithms, namely extreme gradient boosting (XGBoost), random forest (RF), and support vector regression (SVR). The result shows that NCPI is qualified to evaluate the pollution level of black-odor water. The XGBoost regression (XGBR) model has the highest fitting accuracy on the training dataset (R2 = 0.99) and test dataset (R2 = 0.94), and it achieved the best retrieval effect on image inversion in the shortest time, which made it the best-fit model compared with the RF regression (RFR) model and the SVR model. According to inversion results based on the XGBR model, there was only a small size of mild black-odor water in the study area, which showed the achievement of water pollution treatment in Guangzhou. The research provides a theoretical framework and technical feasibility for the application of the combination of algorithms and UAV-borne multispectral images in the field of water quality inversion. [ABSTRACT FROM AUTHOR]

To improve the energy-efficiency of transport systems, it is necessary to investigate electric trains with on-board hybrid energy storage devices (HESDs), which are applied to assist the traction and recover the regenerative energy. In this paper, a time-based mixed-integer linear programming (MILP) model is proposed to obtain the energy-saving operation for electric trains with different constraints of on-board HESDs, such as their capacity, initial state of charge (SOC), and level of degradation. The proposed integrated power flow model based on the train longitudinal dynamics, power split of on-board HESDs, and line impedance is discretized and linearized, aiming to minimize the net energy consumption (NEC). The results reveal that on-board HESDs with a higher capacity does not necessarily lead to a higher energy-saving rate; a lower or excessive initial SOC could undermine the energy-saving potential; considering the long-term train operation, the degradation of the Li-ion battery will influence the energy-saving operation for electric trains, as well as result in an energy-saving rate that ranges from 41.57% to 31.90%. The practical data from Guangzhou Metro Line 7 were applied in the simulations, which enhanced the practicality and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Previous studies on the Nanhaishen Temple 南海神廟 (Temple of the South Sea God) in Guangzhou in the Song dynasty focus mainly on its state sacrificial ritual and local temple fairs, without fully discussing the differences of the sacrificial ritual between the Southern and Northern Song dynasties or the changes of the sacrificial ritual in Lingnan after the Song dynasty. This paper aims to illuminate the following five points. First, after the reunification of the Northern Song dynasty, the sacrificial ritual to the South Sea God in Guangzhou was advanced. Second, when the South Sea God and his temple were conferred with the holy titles for the fourth time, the god's role to bless local stability was further manifested, which means the imperial power gradually permeated into the Lingnan culture. Third, the blessing of the South Sea God was more prominent than ever before because of its geographical location in the southeast of the state during the Southern Song dynasty, and thus the Nanhaishen Temple Fair was the largest of its kind in Lingnan. Fourth, the stele inscription of Liuhou Zhi Ji 六侯之記 (Records of the Six Lords) shows that local people attempted to incorporate their folk beliefs into the canonized sacrifice to the South Sea God, and thus many religious spots were built in other places in Lingnan as detached palaces (ligong 離宮) of the god who was generally endorsed by the local officialdom. Fifth, the sacrifice to the South Sea God in Guangzhou in the Song dynasty had a far-reaching influence, as the god was worshipped by the later generations in the temples which also accommodated the worship of Buddhism and Daoism. In summary, the lengthy process for the South Sea God to evolve from a national god to a local patron is the result of the country's long-term implementation of the ritual system as far as the ritual culture is concerned. [ABSTRACT FROM AUTHOR]

A precise air pollution forecast is the basis for targeted pollution control and sustained improvements in air quality. It is desirable and crucial to select the most suitable model for air pollution forecasting (APF). To achieve this goal, this paper provides a comprehensive evaluation of performances of different models in simulating the most common air pollutants (e.g., PM2.5, NO2, SO2, and CO) in Guangzhou (23.13° N, 113.26° E), China. To simulate temporal variations of the above-mentioned air pollutant concentrations in Guangzhou in September and October 2020, we use a numerical forecasting model (i.e., the Weather Research and Forecasting model with Chemistry (WRF-Chem)) and two artificial intelligence models (i.e., the back propagation neural network (BPNN) model and the long short-term memory (LSTM) model). WRF-Chem is also used to simulate the meteorological elements (e.g., the 2 m temperature (T2), 2 m relative humidity (RH), and 10 m wind speed and direction (WS, WD)). In order to investigate the simulation accuracies of classical APF models, we simultaneously compare the simulations of the WRF-Chem, BPNN, and LSTM models to ground truth observations. Comparative assessment results show that WRF-Chem simulated air pollutant (i.e., PM2.5, NO2, SO2, and CO) concentrations have the best correlations with ground measurements (i.e., Pearson correlation coefficient R = 0.88, 0.73, 0.61, and 0.61, respectively). Furthermore, to evaluate model performance in terms of accuracy and stability, the normalized mean bias (NMB, %) and mean fractional bias (MFB, %) are adopted as the standard performance metrics (SPMs) proposed by Boylan et al. The comparison results indicate that when simulating PM2.5, WRF-Chem was more effective than the BPNN but less effective than the LSTM. While simulating concentrations of NO2, SO2, and CO, the WRF-Chem model performed better than the BPNN and LSTM models. With regards to WRF-Chem, the NMBs and MFBs for the PM2.5 simulations are, respectively, 6.49% and 0.02%, –11.96% and –0.031% for NO2, 7.93% and 0.019% for CO, and 5.04% and 0.012% for SO2. Our results suggest that WRF-Chem has superior performance and better accuracy than the NN-based prediction models, making it a promising and useful tool to accurately predict and forecast regional air pollutant concentrations on a city scale. [ABSTRACT FROM AUTHOR]

In this paper, an experimental rig of a prefabricated temporary house (PTH) was first established. Then, predicted models for the thermal environment of the PTH with and without considering long-wave radiation were developed. Next, the exterior-surface, interior-surface and indoor temperatures of the PTH were calculated by using the predicted models. The calculated results were then compared with the experimental results to study the influence of long-wave radiation on the predicted characteristic temperature of the PTH. Finally, the predicted models were used to calculate the cumulative annual hours and the intensity of the greenhouse effect of four different climate cities (Harbin, Beijing, Chengdu, Guangzhou, China). The results showed that: (1) the predicted temperature values of the model considering long-wave radiation were closer to the experimental results; (2) the effect level of the long-wave radiation on the three characteristic temperatures of the PTH from big to small was: exterior-surface temperature, interior-surface temperature, and indoor temperature; (3) the long-wave radiation had the greatest impact on the predicted temperature value of the roof; (4) under different climate conditions, the cumulative annual hours and the intensity of the greenhouse effect considering long-wave radiation were smaller than those without considering long-wave radiation; (5) the duration of the greenhouse effect considering and ignoring long-wave radiation varied significantly with the climate region, and that in Guangzhou was the longest, followed by Beijing and Chengdu, and that in Harbin was the shortest. [ABSTRACT FROM AUTHOR]

In view of the problems of rapid construction and deformation control of large cross-section tunnels in complex urban environments, the concept of "timely high-strength support" was put forward to form strong support over time and bear the load of surrounding rock in real time, and innovatively developed the spatial reticulated grid bolt-shotcrete support structure (SRGB). The research in this paper focuses on the supporting principle, bearing mechanical properties, snatch simulation test, construction process, and engineering application effects. The components of the SRGB and their respective functions were expounded in detail. The failure modes and deformation characteristics of the tested components were revealed through the indoor loading test, and the performance characteristics of the spatial reticulated grid concrete components with high strength and high rigidity were displayed. With the help of the multi-functional operation trolley, the assembly process test of the spatial reticulated grid was carried out, which verified the feasibility of mechanized construction and the rationality of structural design. Relying on the underground tunnel project of Guangzhou Metro, the spatial reticulated grid structure was successfully used as the initial support of the tunnel for the first time, forming a complete set of mechanized rapid construction technology for a large cross-section tunnel, and constructing a timely high-strength support system suitable for the complex urban environment. The research results provide a new idea and new technology for the mechanized rapid construction and efficient support of large cross-section tunnels. [ABSTRACT FROM AUTHOR]

As the largest carbon emitter in the world, China is facing increasing challenge to reduce CO2 emissions. Given this issue, exploring the influencing factors is of great significance for scientific low-carbon emission policymaking. Although previous literature has explored the effects of urbanization on CO2 emissions, the impact of the space of flow on urban carbon emissions have been less explored. Due to the increasing connection between cities, its impact on urban carbon emissions cannot be ignored. Thus, this paper takes the space of flows into account as an aspect of urbanization to supplement the existing literature and empirically examines the multiple effects of urbanization on CO2 emissions in the Pearl River Delta (PRD) urban agglomeration. By using a STIRPAT model, statistical data, and web crawler data, we examined impacts of different types of urbanization on CO2 emissions. Our empirical results show that: (1) Within the PRD urban agglomeration, urban linkage intensity is strongly connected to urban socioeconomic growth, establishing a geographical structure with Guangzhou and Shenzhen as the double core. (2) Our results show that urbanization exerts two opposite effects on CO2 emissions: positively connects carbon emissions with population urbanization, integrated urban linkage flow, and energy intensity, whereas economic urbanization and social urbanization are shown to be negatively correlated. However, spatial urbanization has no significant positive effect on urban CO2 emissions. (3) It is worth noting that urban linkage flows are the second most important factor affecting urban carbon emissions after economic urbanization. Our study could formulate effective planning suggestions for future CO2 emission reduction paths and development modes in the PRD. [ABSTRACT FROM AUTHOR]

The railway pantograph carbon contact strip (PCCS) plays a critical role in collecting the electric current from the catenary to guarantee the steady power supply for the train. The catenary contacts with the PCCS and slides from one side to another side when the train runs on the track, which generates the wear on the surface of the PCCS. The thickness of the PCCS cannot be smaller than a lower limit for the sake of safety. Therefore, the remaining useful life (RUL) prediction of the PCCS is beneficial for the pantograph maintenance and inventory management. In this paper, the wear data from Guangzhou Metro are analyzed in the first place. After that, the challenge of predicting the RUL for PCCS from the unequal interval wear data is addressed. A Wiener-process-based wear model and the unequal interval weighted grey linear regression combined model (UIWGLRCM) are proposed for the RUL prediction of the PCCS. The case studies demonstrate the effectiveness of the proposed method via a comparison of RUL prediction with another available method. [ABSTRACT FROM AUTHOR]

The solar absorption-subcooled compression hybrid cooling system (SASCHCS) is tech-economically feasible for high-rise buildings. Since such a system operates with no auxiliary heat source, the performance coupling of its absorption subsystem and solar collectors is sensitive to the variation of hot water flow rate. In this regard, the relationship of system performance and hot water flow rate is required to be clarified exactly. Therefore, this paper aims to illustrate the effect mechanism of hot water flow rate and to propose the corresponding decision criterion. The case study is based on a typical high-rise office building in subtropical Guangzhou. The daily working process of this system with different hot water flow rates is simulated and analyzed. Subsequently, the useful heat of collectors and cooling capacity of the absorption subsystem with the hot water flow rate is discussed in detail. The results show that the SASCHCS operates with hot water temperatures ranging from 60 °C to 90 °C. The energy saving increases with the rise of hot water flow rate, but such variation tends to be flat for the excessively high flow rate. As the collector flow rate increases from 1 m3/h to 10 m3/h, the daily energy saving improves by 21% in August. Similarly, the daily energy saving increases by 37.5% as generator hot water flow rate increases from 1 m3/h to 10 m3/h. In addition, the collector flow rate of 3.6 m3/h (13.33 (kg/m2 h)) and the generator flow rate of 5.2 m3/h (19.26 (kg/m2 h)) are optimal for the annual operation, with considering power consumption of water pumps. This paper is helpful for the improvement of SASCHCS operating performance. [ABSTRACT FROM AUTHOR]

The solar absorption-subcooled compression hybrid cooling system (SASCHCS) displays outstanding advantages in high-rise buildings. Since the performance coupling of collectors and absorption subsystems is stronger due to the absence of backup heat and the effect of generator setting temperature has not been realized adequately, it is highly important to study the relationship of SASCHCS operation and the set point temperature of hot water to prevent performance deterioration by inappropriate settings. Therefore, the paper mainly deals with the effect of collector and generator setting temperature. The investigation was based on the entire cooling period of a typical high-rise office building in subtropical Guangzhou. The off-design model of hybrid systems was built at first. Subsequently, the impact mechanism of setting temperature in two hot water cycles on facility operation was analyzed. It was found that the excessive rise of collector setting temperature deteriorated the energy saving, while the appropriate improvement of generator set point temperature was beneficial for the solar cooling. Besides, global optimization by the genetic algorithm displayed that 71.6 °C for the collector setting temperature with 64.5 °C for the generator was optimal for annual operation. The paper is helpful in enhancing the operation performance of SASCHCS. [ABSTRACT FROM AUTHOR]

Urban regeneration has become one of the most effective ways to develop urban areas that have declined. Compared with other types of urban regeneration, community micro-regeneration is characterised by scattered stakeholders. Existing studies on public participation in community micro-regeneration mainly focus on revealing the interaction between different stakeholders with less attention to the main users' social profiles in their participation process. This paper explores residents' social profiles influencing their participation in community micro-regeneration projects in China. An evaluation framework for residents' participation in community micro-regeneration projects is designed through literature research, the Delphi technique, and an analytic hierarchy process (AHP) based on the case study of Yongtai community, Guangzhou. Relative residents' social profiles with the data from the questionnaire and literature research are further verified by stepwise linear regression. The results show that residents' participation is still in the stage of tokenism with high-level passive information receipt but low-level enthusiasm for interactive activities. The older (i.e., 65-years of age and above) and middle-income groups (i.e., between 3000 and 14,999 CNY/Month) are positively associated with their participation in the Yongtai community micro-regeneration project. These findings can provide references for managers to distribute social resources. [ABSTRACT FROM AUTHOR]

Community is the foundation of modern cities, where urban residents spend most of their lifetime. Effective and healthy community design plays a vital role in improving residents' living quality. Pedestrian network is an indispensable element in the community. Successful pedestrian network design can help the residents be healthy both physically and mentally, build the awareness of "Go Green" for the society, and finally contribute to low-carbon and green cities. This paper proposes a community pedestrian network design method based on Urban Network Analysis with the help of the Rhino software. A case study of a typical community in Guangzhou, China was implemented, specifying the steps of the proposed method. The findings presented include the features of the citizens and the accessibilities of the neighbors that are obtained from the community pedestrian network simulation. The limitation and scalability of this method was discussed. The proposed method can be essential to designing healthy and sustainable communities. [ABSTRACT FROM AUTHOR]