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With the popularity of shared bicycles in urban areas, more and more residents choose this fast and convenient mode of transportation for short-distance travel. By optimizing the layout of shared bicycle parking areas and delivery quantity, the investment cost of shared bicycle enterprises can be effectively reduced, and the convenience of residents' travel can be improved at the same time. In this paper, we develop a collaborative optimization model for the layout of the shared bicycle parking area and delivery quantity, aiming at minimizing the walking distance of residents and the investment cost of enterprises, while considering the constraints of the parking area's attractive range and the number of bicycles placed. Aiming at the characteristics of this mixed integer nonlinear problem, an improved genetic algorithm incorporating symmetric individual precision control mechanism is designed. Finally, taking the planned area between the Second Ring Road and the Third Ring Road in the northern part of Jin-niu District, Chengdu as the background, the proposed collaborative optimization model for the layout of shared bicycle parking areas and delivery quantity is applied to a real scene. The results show that after optimization, the number of parking areas is reduced by 2, and the total investment cost is reduced by about 12.2%. [ABSTRACT FROM AUTHOR]

Smart cities can effectively improve urban life quality. But, with the rise in population size, there is an increase in the use of vehicles for transportation. In smart city development, traffic control and route planning are the primary tasks to address the problem of travel time estimation. It has become complex due to concerns of wrapped spatio-temporal data on dynamic real-time traffic conditions. The existing methods failed to estimate travel time efficiently due to not considering the spatio-temporal features and lack of computing resources. There is a need for a system like intelligent transportation system to monitor and accurately predict traffic flow to avoid traffic congestion and reduce the impact on the ecological system. This paper developed a novel hybrid deep learning model to estimate optimized travel time and possible trajectories. In this work, U-Net used to reduce the number of feature points for each temporal data and GNN is used to build the graph with connectivity between vehicular nodes. This hybrid model helps us predict traffic flow and aims to estimate accurate travel time from one location (node) to another. The model's performance is evaluated on the standard benchmark datasets Q-Traffic, TaxiBJ, and Chengdu. The experimental results show that the proposed framework significantly improves performance in extracting travel patterns and provides an optimal route with an estimated travel time than existing methods with RMSE 4%, MAE 20.49%, and MAPE 18%. The proposed model has accurately predicted the estimation of travel time of the vehicle for the given urban traffic data. [ABSTRACT FROM AUTHOR]

The recommended bearing capacity of medium weathering mudstone foundation is less than the capacity of the rock structure to withstand loads in Southwest China. A comprehensive failure characterization of medium weathering mudstone in Chengdu has been performed including bearing plate test (BPT), binocular vision measurement (BVM) test, uniaxial compressive strength test, trial trench test of shallow rock surface and 3D imaging in this paper. Failure behavior of rock has been modeled with 3D imaging algorithm that utilizes Zhang's calibration method in BVM system combination with trial trench test of shallow rock surface. The bearing capacity of medium weathering mudstone foundation were extracted from uniaxial experiments and BPT-BVM test by fitting relevant material properties to the data. The results revealed that: Bearing capacity of medium weathering mudstone of layered isotropic in Chengdu is undervalued. Specifically, the characteristic load carrying value is in the range 1500–2500 kP, that is 50% higher than in the local standard system. Failure process is different from Hoek–Brown Failure Criterion, presenting a wave peak transfer phenomenon of the increment displacement into the distance. Thus, it can be reduced to that of punching failures for thin bedded structures of Moudstone foundations. Compressive strength of soft rock proves to be main factor limiting the bearing capacity, a clear correlation between the uniaxial compressive strength reduction coefficient and the bearing capacity has been used to establish, leading to the proposal of a load bearing capacity prediction model. [ABSTRACT FROM AUTHOR]

This paper aimed to explore the potential factors of the coronavirus disease 2019 (COVID-19) pandemic on Chinese undergraduates' psychological distress (PD), as well as the moderating impact of coping styles and social support in this relationship. 5638 Chinese college students in Chengdu were randomly selected for an online survey. 10-item Kessler Psychological Distress Scale (K10), the Simplified Coping Style Questionnaire (SCSQ) and the Social Support Rating Scale (SSRS) were used in this paper. In SPSS 17, one-way ANOVA, multiple linear regression and 95% confidence were used to observe the relationship between sociodemographic characteristics, COVID-19 exposure, coping styles, social support and PD of college students. The PD prevalence rate of our sample during the pandemic was 45.5%. Males, students with a romantic relationship, those spending more time on COVID-19, worrying about getting infected, those whose cohabitants were nervous about COVID-19, higher scores of negative coping style, lower positive coping style and social support scores had a higher risk of experiencing PD. The relationship between the nervousness of cohabitants about COVID-19 and the occurrence of PD was moderated by positive coping. Based on the serious psychological condition of Chinese college students during COVID-19. There is an urgent need to enhance the positive coping styles of college students, and systematic support for their mental health is crucial. This article provides theoretical research guidance for students and schools to further prevent and intervene in PD among college students. [ABSTRACT FROM AUTHOR]

Based on the analysis of the spatial distribution characteristics and influencing factors of 2879 attractions POI in Chengdu, this paper studies the spatial distribution types, spatial concentration, and equilibrium of attractions by using standard deviation ellipse, geographic concentration index, and kernel density estimation. Buffer analysis, near analysis, correlation analysis, and grey relation analysis are used to study the influencing factors of tourism in Chengdu. The results show that: (1) The overall attractions POI in Chengdu is in an east–west direction, and except for other types of attractions POI, the remaining types are also in an east–west direction. (2) The spatial agglomeration areas of different types of attractions POI in Chengdu were quite different. Among them, parks and city squares were mainly concentrated in the central urban areas, namely Jinjiang, Qingyang, Jinniu, Wuhou, and Chenghua, forming a prominent gathering area. (3) There were differences in the influence degree of each factor on the spatial distribution of attractions POI. Topography and drainage, transportation, tourist source market, and other factors significantly correlated with the distribution of attractions, which were the main factors affecting the spatial distribution of attractions. Industrial development and economic population were also important factors affecting the distribution of attractions. Tourism is an important thrust for urban development. The study of the spatial distribution of tourism and its influencing factors has clear guiding significance for later tourism development, which can help optimize the integration of tourism resources, promote the cooperation of regional tourism development and provide a basis for decision-making for tourism development. [ABSTRACT FROM AUTHOR]

Chengdu-Chongqing economic circle (hereinafter referred to as "Chengyu Region") is a key construction region of China's major development strategy. The development of regional tourism plays an important role in the optimization of regional economy and industrial structure. In this paper, ArcGIS 10.5 was used as the main analysis tool to analyze the temporal and spatial distribution of A-level tourist attractions in Chengyu Region, and makes factor analysis and interactive analysis on the factors affecting the distribution of tourist attractions by geographic detector model. The results show that: 1. The distribution of tourism attractions in Chengyu Region is mainly concentrated type, and the distribution of the natural landscape, cultural landscape, rural pastoral and modern entertainment in Chengyu Region are all concentrated type. 2. In terms of the distribution characteristics of kernel density, there is a significant deviation between the spatial distribution of A-level tourist attractions and tourism income in Chengyu Region. Through the analysis of the dynamic development of A-level tourist attractions in 2010, 2015 and 2021, tourism in Chengyu Region show a good situation of "driven by two cities and blooming in many places." Among them, Chengdu and Chongqing have obvious advantages, and Yibin has become an important city second only to Chengdu and Chongqing. 3. In terms of spatial correlation, the spatial distribution of A-level tourist attractions in Chengyu Region has a significant spatial autocorrelation. The local spatial autocorrelation of A-level tourist attractions includes H–H (high-high), H–L (high-low) and L–H (low–high) clustering types. 4. In terms of influencing factors, traffic location, water system, topography and social and economic development level are the important factors affecting the spatial distribution of regional A-level tourist attractions. Among them, the level of social and economic development has the greatest impact on regional tourism. Finally, based on relevant theories, this paper puts forward countermeasures and suggestions for regional coordinated development, so as to guide the sustainable development and management innovation of regional tourism industry. [ABSTRACT FROM AUTHOR]

Due to the limited space in urban area, subway tunnels have to be designed and constructed with marginal clearance between each other. In the construction of subway tunnels, the installation and dismantling of temporary lining prone to affect the existing subway and new subway. In this paper, based on the Nijiaqiao Station Project in Chengdu Metro, stress state and deformation of the existing subway and the new subway, induced by dismantling of temporary lining, are compared and analyzed. It is found that different installation sequence of lining and dismantling temporary lining will affect the deformation of the subway, especially in the floor. The deformation and stress conditions of the structure are the least affected when all secondary linings are constructed in the first place and then all temporary linings are dismantled; and condition II is the worst and leads to excessive deformation and stress. Based on the analysis of the construction efficiency and influence of dismantling temporary lining, it is suggested that the combination form of divisional lining and dismantling temporary lining (i.e., condition III) can be adopted for the construction of closely-undercrossing subway. Finally, it is found that the field monitoring results are basically consistent with the simulation results, which verifies the validity of the numerical simulation. The results obtained in this paper can provide some vital references for the design and construction of similar projects (i.e., closely-undercrossing cases) in the future. [ABSTRACT FROM AUTHOR]

Estimated time of arrival (ETA) is an estimate of the vehicle travel time from the origin to destination in the roadworks. From the perspective of travel planning or resource allocation, accurate ETA is significantly important. In recent years, deep learning-based methods represented by recurrent neural networks has been widely used in travel time prediction tasks, but such methods cannot effectively learn data association at different moments. At the same time, the existing methods do not effectively leverage local traffic information. Targeting these challenges, this paper proposes a new model TransETA to predict vehicle travel time. The model includes three modules: the input feature transformation module uses graph convolutional network (GCN) to extract the local congestion feature, the deep forest module mainly deals with static trajectory data, and ETA-Transformer module processes the feature extraction of dynamic trajectory data. Finally, we conducted experiments on two large trajectory datasets. The experimental results show that the proposed hybrid deep learning method, TransETA, outperforms the state-of-the-art models. On the Chengdu and Porto datasets, our proposed method shows an improvement of 6s and 9s in mean absolute error compared to the current best performing method, respectively. Also the average absolute percentage error is reduced by 2.34% and 3.64% respectively. The effectiveness of each module was approved through ablation experiments. Specifically, local congestion information representation can effectively improve the accuracy of the prediction. ETA-Transformer module is more effective in extracting spatio-temporal feature correlation than the LSTM-based method. [ABSTRACT FROM AUTHOR]

Despite growing scholarly attention on the role of urban networks for understanding regional dynamics, there has been limited research examining the impact of cities' transportation network connections on regional market integration. This paper analyzes China's four major urban agglomerations: the Yangtze River Delta, the Pearl River Delta, Beijing-Tianjin-Hebei, and Chengdu-Chongqing. Applying a spatial Durbin model to cross-sectional datasets for 2019, we provide insight into the role of cities' transportation network connections in promoting regional market integration, considering both the potentially heterogeneous impact of network connections and the interplay between network and agglomeration externalities. Our results indicate that: (1) cities' transportation network connections have an inverted 'U'-shaped effect on regional market integration; (2) transportation network connections have spatial spillover effects; (3) the positive impact of transportation network connections on regional market integration becomes more pronounced as city size decreases; and (4) there are neither complementary nor substitution effects between network and agglomeration externalities. We reflect on the broader implications of our empirical findings for regional development strategies and discuss possible avenues for further research. [ABSTRACT FROM AUTHOR]

China's foreign capital R&D network has become a core component of the high-quality development of the national innovation ecosystem. Narrowing the spatial difference in the foreign R&D network is considered an essential strategy to improve China's holistic innovation capability. Previous studies only examined the internal factors of the system while mostly ignoring the quantitative analysis of the spatial differences diffusion. Based on the dissipative structure theory, the current paper demonstrates the construction of positive and negative entropy indexes of foreign capital R&D networks in China. Rested on a survey dataset of 340 foreign R&D institutions in 21 Chinese provinces from 2016 to 2017, this paper analyzes the spatial differences and driving factors of the innovation development of foreign capital R&D networks across the country using the Brusselator model. The results show that China's entire deviation degree of foreign capital R&D networks is small. Still, there are significant spatial differences in the deviation between the entropy value and the ideal status of dissipative structure in foreign R&D networks, with the minor deviation-value areas located in the eastern regions. In addition, the central and western regions where the late-mover layout of the foreign R&D network deviates are far from the ideal status. Among them, the western (i.e., Xi'an and Chengdu) foreign R&D network is significantly better than the central innovation performance. It is found that policy traction of talent advantage and intellectual property rights protection positively impact the negative entropy flow of foreign R&D networks in China, which becomes an influential driving force for the future system equilibrium. The paper concludes with several policy implications to guide China's innovation and ecological optimization of foreign capital R&D networks. [ABSTRACT FROM AUTHOR]

Detection of subsurface hydrodynamic anomalies plays a significant role in groundwater resource management and environmental monitoring. In this paper, based on data from the groundwater level, atmospheric pressure, and precipitation in the Chengdu area of China, a method for detecting outliers considering the factors affecting groundwater levels is proposed. By analyzing the factors affecting groundwater levels in the monitoring site and eliminating them, simplified groundwater data is obtained. Applying sl-Pauta (self-learning-based Pauta), iForest (Isolated Forest), OCSVM (One-Class SVM), and KNN to synthetic data with known outliers, testing and evaluating the effectiveness of 4 technologies. Finally, the four methods are applied to the detection of outliers in simplified groundwater levels. The results show that in the detection of outliers in synthesized data, the OCSVM method has the best detection performance, with a precision rate of 88.89%, a recall rate of 91.43%, an F1 score of 90.14%, and an AUC value of 95.66%. In the detection of outliers in simplified groundwater levels, a qualitative analysis of the displacement data within the field of view indicates that the outlier detection performance of iForest and OCSVM is better than that of KNN. The proposed method for considering the factors affecting groundwater levels can improve the efficiency and accuracy of detecting outliers in groundwater level data. [ABSTRACT FROM AUTHOR]

The development of urbanization has changed the original land cover and exacerbated the urban heat island effect, seriously affecting the sustainable development of the ecological environment. Research on urban heat island characteristics and land cover changes in five major urban agglomerations in China to provide a reference for preventing thermal environmental risks and urban agglomeration construction planning. This paper estimates the surface urban heat island intensity (SUHII) of the five major urban agglomerations in China from 2003 to 2019 based on Google Earth Engine (GEE) through the urban–rural dichotomy, analyzes their trends through the Sen + M–K trend analysis method, and combines the detrending rate matrix to analyze the impact of land cover type shift on urban heat island change. Research shows that (1) the land cover types of the five major urban agglomerations in China have changed considerably from 2003 to 2019, and all five major urban agglomerations in China experienced varying degrees of urban expansion. (2) The annual average value of SUHII decreases in Beijing-Tianjin-Hebei, Yangtze River Delta, and middle reaches of the urban agglomerations, while the annual average value of SUHII increases in Chengdu-Chongqing and Pearl River Delta urban agglomerations. (3) The spatial composition of land cover types in the five major urban agglomerations in China is highly spatially correlated with urban heat islands, with urban land and bare land urban heat islands being the most pronounced. (4) The land cover type shift has the most significant heat island impact on Beijing-Tianjin-Hebei, Yangtze River Delta, and Chengdu-Chongqing urban agglomerations. (5) The land cover change (LCC) with an increasing trend in SUHII is mainly bare land converted to arable land, and water bodies, grassland, forest land, and arable land converted to urban land. [ABSTRACT FROM AUTHOR]

Using the CRITIC method, comprehensive index evaluation method, VAR model, coupling coordination model and other methods, this paper evaluates the comprehensive development of the population economy and eco-geological environment composite system in the twin-city economic circle of Chengdu–Chongqing region from 2000 to 2020, verifies the dynamic coupling relationship between subsystems and measures the coupling coordination degree of complex system. Meanwhile, the differences in the development process of each subsystem are discussed and the spatial–temporal evolution characteristics and laws of coupling coordination of the composite system during the research period are analyzed. The results reveal the following: (1) There is a long-term coordinated relationship between population, economy and eco-geological environment in Chengdu–Chongqing region, which have the conditions for emergence and generation. (2) The subsystems of population, economy and eco-geological environment in Chengdu–Chongqing region show an overall upward trend, among which the Sichuan part obviously outperforms the Chongqing part. Besides, the growth rate of the economy subsystem is significantly higher than that of the population, eco-geological environment subsystem. (3) The coupling coordinated development of the composite system has shown a benign upward development trend, gradually changing from "composite spiral structure" to "two cores outstanding, peripheral collapse, the west superior to the east", while the main coordination state has developed from "Basic synergy—Economic lag" in 2000 to "Basic synergy—Population lag" in 2022. In addition, Cheng-De-Mian and Yuzhong districts with the better level of economic development have shown "Advanced synergy—Ecological lag". [ABSTRACT FROM AUTHOR]

We investigate a deep foundation pit for urban substation construction in Chengdu, China. The pit was excavated in a sandy gravel layer and has a depth of 24.6 m. Detailed field surveys and monitoring were carried out to investigate the deformation characteristics of the foundation pit and its supporting structure related to excavation. Flac3D software was used to analyze the influence of pile anchor design parameters, including pile diameters, pile spacing, anchor cable prestress, anchor angle, and the number of rows of anchor cables, on deformation of the deep foundation pit. The results showed the pile diameter was the most critical influencing factor for pile deformation. The influences of anchor cable prestress and anchor angle on the horizontal displacement of the pile were inferior to the influence of the pile diameter and the number of anchor cable rows. The results reported in this paper provide guidance for the optimal design of foundation pits in settings with similar geological conditions. [ABSTRACT FROM AUTHOR]

The classical multi-period inventory routing problem (MIRP) combines inventory management and vehicle routing problems, attempting to maintain customer inventory levels via autonomous deliveries, with the assumption that stock-out never occurs at the supply side. While this is no more the truth when a common third-party logistics company operates a central warehouse for a group of small and medium sized retailing companies. Procurements have to be made to refill inventory at the central warehouse. This study thus extends the traditional MIRP by incorporating procurement decisions (MIRP-PD) and tries to minimize the total cost of procurement, inventory holding and transportation. To our knowledge, this paper is among the first to formally describe MIRP-PD and model it as a mixed integer linear program. A hybrid two-level heuristic is proposed to address large-scale instances. The upper level of the algorithm determines the visiting schedule while the lower level works out procurement and routing decisions accordingly. Components from tabu search and adaptive threshold acceptance are also embedded to help escape from local optima. Extensive numerical instances are generated from a real case in Chengdu (China), based on which the computational results reveal the effectiveness and efficiency of the proposed algorithm compared with the commercial solver CPLEX. The comparison between MIRP and MIRP-PD has demonstrated the cost advantage of incorporating procurement decisions into inventory and routing plans. Impacts on costs of key factors including delivery frequency and buffer size of stores have also been examined to provide managerial implications to practitioners. [ABSTRACT FROM AUTHOR]

Shield tunneling method is widely used in urban metro construction. The construction stability is closely related to the engineering geological conditions. Sandy pebble strata have a loose structure and low cohesion, resulting in great engineering-induced stratigraphic disturbance. Meanwhile, the high water-abundance and strong permeability are extremely detrimental to construction safety. It is of great significance to evaluate the dangerousness of shield tunneling in water-rich pebble strata with large particle size. In this paper, risk assessment of engineering practice is carried through with Chengdu metro project in China as a case study. Referring to the special engineering situations and assessment workload, seven evaluation indices, including compressive strength of pebble layer, boulder volume content, permeability coefficient, groundwater depth, grouting pressure, tunneling speed and tunnel buried depth are selected to establish an evaluation system. A complete risk assessment framework is established based on the cloud model, AHP and entropy weight method. Further, the measured surface settlement is taken as the risk degree characterization to verify the results. This study can provide reference for method selection and evaluation system establishment in the risk assessment of shield tunnel construction in water-rich sandy pebble strata, and contribute to proposing safety management in similar engineering projects. [ABSTRACT FROM AUTHOR]

Travel time forecasting has become a core component of smart transportation systems, which assists both travelers and traffic organizers with route planning, travel schedule adjustments, ride-sharing, navigation applications, and efficient traffic management. However, timely and accurate travel time forecasting still remains a critical challenge owing to the complex nonlinear and dynamic fluctuations of spatial–temporal dependencies. Also, spatial sparseness is a big issue in traffic forecasting, since adopting the implicit interactions between the close traffic regions leads to superficial characterization of spatio-temporal dependences. In this paper, we propose a new deep learning-based framework (STTG-TTE) that addresses these drawbacks and improves the travel time estimation. First, we build a geo-hashing algorithm for the data sparsity issue that incorporates fluctuations of nearby and distant traffic situations in terms of spatio-temporal dependencies. Second, a new spatio-temporal correlation modeling method is proposed to fully leverage large-scale spatial and temporal traffic patterns using temporal convolutional networks integrated with a gated multi-modality mechanism. Then, for external factors' representation, a new dual-gated Res-Net multi-modality-based module is proposed. Finally, we fuse these representations of multi-components dynamically and utilize the transformer model, which is conducive to learning intersections among these multiple factors for obtaining accurate prediction results. Experiments on two large-scale real-world traffic datasets from two different urban regions (Chengdu taxi-datsets and NYC-Bike datasets) demonstrate that the proposed model is superior to state-of-the-art baseline models. [ABSTRACT FROM AUTHOR]

Bronchopneumonia is the most common infectious disease in children, and it seriously endangers children's health. In this paper, a deep neural network combining long short-term memory (LSTM) layers and fully connected layers was proposed to predict the prevalence of bronchopneumonia in children in Chengdu based on environmental factors and previous prevalence rates. The mean square error (MSE), mean absolute error (MAE), and Pearson correlation coefficient (R) were used to detect the performance of the deep learning model. The values of MSE, MAE, and R in the test dataset are 0.0051, 0.053, and 0.846, respectively. The results show that the proposed model can accurately predict the prevalence of bronchopneumonia in children. We also compared the proposed model with three other models, namely, a fully connected (FC) layer neural network, a random forest model, and a support vector machine. The results show that the proposed model achieves better performance than the three other models by capturing time series and mitigating the lag effect. [ABSTRACT FROM AUTHOR]

This paper examines how the government harnesses the development of social enterprises. Drawing on an in-depth qualitative study in Chengdu City, China, we find that institution building, financial supporting, incubation developing, systematical cultivating and resource matchmaking are the main strategies employed by the municipal government to promote the development of social enterprises, whereupon we argue that besides the role as referee and sponsor which are the governments' traditional roles in western countries, the government in China also play a role of coach in harnessing the development of social enterprises. This paper contributes to the literature by theorizing how administrative forces affect the growth of hybrid organizations and also contributes to providing empirical evidence of the institutional environment of social enterprises in China. [ABSTRACT FROM AUTHOR]

According to the problems of lack of planning and disordered layout of rural settlements in China, it is urgent to further improve the methods of optimizing the settlement pattern of towns and villages and the intensive use of land. The main purpose of this paper is to optimize the layout of rural settlements with a single land-use type and a large number of rural settlements to be relocated. This paper takes the Linpan settlements of Deyuan Town, Chengdu City, Sichuan Province as the research object and establishes the suitability evaluation system of Linpan settlements by the Entropy method. The Linpan settlements of research area are divided into the central and the non-central Linpan settlements and determine the search threshold according to the point pattern analysis method and multi-distance spatial cluster analysis. Through the study of regional preliminary central Linpan settlement selection and search threshold determination, central Linpan settlement site selection, the determination of non-central Linpan settlement's migration direction, the results show that the radiation coverage rate of the central Linpan increased by 17.3%, the number of repeated radiation Linpans decreased by 63.2%, the overlapping area decreased by 49.9%, and finally 179 Linpans were optimized and merged into 36 central Linpans. [ABSTRACT FROM AUTHOR]

The influence of large-scale unloading of soil on existing metro tunnels is a difficult problem in the operation of Metro in sandy gravel strata. In order to predict and control the tunnel deformation and ensure the safety and normal operation of the metro, three-dimensional numerical models are proposed in this study. These models based on the line 5 of Chengdu subway engineering and the adjacent unloading projects analyze the deformation of existing metro tunnels under large-scale unloading of soil. The results show that the maximum bulge after unloading excavation of foundation pit is 11.1 mm, which is lower than the limit value of foundation pit uplift proved by relevant studies; the maximum deformation value of left tunnel is 9.56 mm, and that of right tunnel is 8.33 mm, which is less than the proposed 10 mm deformation control standard. In addition, the paper analyses the restraining effect of different reinforcement measures on soil deformation, such as advanced tubal curtains and horizontal beams, anti-floating anchor cables. The results show that the deformation of soil under different reinforcement measures is greater than the specified limits, while the comprehensive reinforcement measures can restrain the deformation of soil well. The numerical simulation results in this paper verify the effective reinforcement of comprehensive reinforcement measures for large-scale unloading in sandy gravel strata, which can provide reference experience for large-scale unloading excavation construction in similar sandy gravel strata. [ABSTRACT FROM AUTHOR]

Both academics and policymakers regard publicly planned logistics nodes (PPLN) as a potential measure to promote logistics agglomeration and mitigate environmental damage caused by logistics activities. However, such measure may lead to non-linear carbon emission effect from the perspective of agglomeration economy, and empirical evidences are yet to be found to verify this inference. This paper uses DID method and mediating effect models to explore the effects and mechanisms of PPLN on CO2 emissions with panel data from 2000 to 2017 in Chengdu, China. Our findings show that PPLN promotes the agglomeration of both small and large-scale logistics enterprises and increases carbon emissions. In addition, the agglomeration of large-scale logistics enterprises can reduce carbon emissions; the opposite is true for smaller ones. Despite the continuous diminishing of the carbon emission increase, the emission-reduction effect has not been achieved through PPLN operations. Based on the results, the study recommends that the government should appropriately determine the location and scale of PPLN, advocate green construction and industrial upgrading, and adopt differentiated regulatory and incentive measures for enterprises. Logistics enterprises can increase their investment in green technologies and strengthen cooperation with their customers. [ABSTRACT FROM AUTHOR]

The ground subsidence accident caused by the instability of shield tunnel face has been a major problem that puzzles urban subway construction in weak rock. Maintaining the stability of tunnel face is the key to ensure the safety of shield construction and reduce the environmental impact. In view of the shield with a diameter of 8600 mm in Chengdu metro line 18 through the sandy cobble stratum, it is more difficult to maintain the stability of the shield tunnel face than other strata. The characteristics of the sandy pebble stratum were taken into account firstly in this paper. The analytical equation was obtained by the limit equilibrium method. The optimization of the trapezoidal bottom has been improved based on the existing 3D trapezoidal wedge model. And the optimal solution of the ultimate support pressure was obtained. The influencing factors of support pressure are also analysed. When the tunnel diameter is fixed, the deeper the ground covering depth is, the greater the required limit support pressure becomes. But the ground covering depth has almost no effect on the ultimate support pressure even if the tunnel is deep. The limit support pressure is inversely proportional to the internal friction angle of the soil and is proportional to the diameter of the tunnel. Finally, theoretical limit support pressure can be also verified by the numerical simulation results and the field monitoring results. It provides a reference for the subsequent setting value of the soil warehouse pressure. [ABSTRACT FROM AUTHOR]

The hydrodynamic changes and ground settlement induced by engineering dewatering have received much attention, and leakage between different aquifers is often neglected. Obviously, the leakage strength is crucial for the safety of underground engineering in soluble rock distribution areas. In this paper, we examined the Tianfu New Area in Chengdu, China, which contains a paste salt formation, based on numerical simulation techniques, characteristics of hydrodynamic field, leakage strength and ground settlement changes under different combinations of pumping well filter length and waterproof curtain depth were investigated. In the process of optimizing the dewatering scheme for this area, the leakage strength was innovatively included in the evaluation index. We found that as the depth of waterproof curtain increases, the trend of ground settlement and leakage strength caused by dewatering can be divided into a rapid decline phase and a gradual decline phase. However, the critical curtain depths of the two stages of ground settlement and leakage strength are different. The optimization scheme for dewatering engineering was determined under hydrodynamic, leakage strength, and ground settlement constraints. The filter length of the corresponding optimization scheme was 12 m, and the suitable depth of the waterproof curtain was 14–16 m. Our results provide an effective solution and method for optimizing the dewatering scheme in underground engineering projects with gypsum-bearing strata. [ABSTRACT FROM AUTHOR]

Heat action plans should be urgently formulated to enable urban managers, planners, and designers to take appropriate actions for mitigation and adaptation. However, few studies have been conducted to investigate the societal needs and knowledge gaps regarding heat mitigation and adaptation. To address such research gaps, this paper presents an empirical study of 574 questionnaires in Chengdu, China, to explore heat-related impacts, public responses, and driving mechanisms. The results indicated that outdoor activities and work/study were more sensitive to extreme heat than transportation, sleep/rest, and diet. Heat-related impacts on physiological health were at the same level as those on psychological health, where digestive system illness and emotional irritability were the most prevalent physiological and psychological symptoms. Respondents' knowledge of heat-related threats, adaptation awareness, and adaptation knowledge were insufficient, compared with heat severity. The payment willingness among the respondents was not strong and payment amount was not high. Poorer, healthier, and the less affected in outdoor activities were positive groups in payment willingness, while the group which experienced heat-related impacts on outdoor activities could pay more compared with other groups. Overall, these results help to shape the main contents of heat action plans. [ABSTRACT FROM AUTHOR]

During the shield-based construction of a large-diameter subway tunnel crossing sandy cobble strata in the Chengdu region, a number of problems are encountered: the large particle size, high strength, loose structure of cobbles and boulders, difficulty in discharging slag and soil from the shield, and serious wear of the cutter head. It is necessary to adopt a dynamic control method to reduce material consumption using multiple groups of residue improvement experiments. Unlike other methods, we propose two improvement schemes and a dynamic control process in this paper. A dynamic control scheme combined with shield parameter feedback is proposed, using different proportions of modifiers to improve the sandy cobble strata. [ABSTRACT FROM AUTHOR]

Due to the rapid urbanization and climate change, one of the pressing problems confronting Chinese cities lies in air pollution. Especially during recent years, most cosmopolitan cities in China suffer from thick smog caused by PMs. It is reported that such air pollution has close relations with traffic-related pollutants, such as NO2. Meteorological condition contributes significantly to long-range transport sources and has remarkable influences on the distribution of the above pollutants. Thus, it is necessary to quantitatively analyze such influential patterns. In this paper, taking Chengdu as an illustrative example, the meteorological and pollutant statistics in 4947 h are collected and fitted with 8 meteorological parameters of PM2.5, PM10, and NO2 through linear regression method. And data is analyzed and compared on the hourly, daily, weekly, and monthly basis, respectively. Results show that hourly and daily data focus on fluctuations that affected by multiple interferences other than meteorological influences. When hourly values of PM2.5, PM10, and NO2 exceed 175 μg/m3, 250 μg/m3, and 125 μg/m3, respectively, discrete values that cannot be explained by meteorological influences increase notably, while weekly and monthly variations illustrate more tendencies, and communicable patterns that decisively influenced by meteorology can be extracted among 3 pollutants. By comparing the results in 4 timescales, respectively, similar principal meteorological factors are involved in fitting processes. Thirdly, visibility (V), wind speed (WS), precipitation (P), and cloud condition (CC) are the most influential factors and served as main parameters in linear regressions within 4 timescales. Air temperature (AT) and dew temperature (DT) are less influential factors by daily and weekly data but are served as main parameters when it goes to hourly and monthly data and function as variables that signify tendency variances in linear regressions, while relative humidity (RH) and barometric pressure (BP) are lest influential factors and have limited effect on fitting results. This work can provide guidance and reference for urban planning optimization and air environment protection in cities with air quality control considerations impacted by local climatic conditions. [ABSTRACT FROM AUTHOR]

Under the background that electric vehicles cause enormous supply pressure on the grid, the application of vehicle-to-grid (V2G) technology can effectively alleviate supply pressure and also bring more economic benefits. Considering conditions for participating in V2G, pure electric logistics fleets have the advantages of stable work end time and large remaining power. In this paper, the economic benefits of the pure electric logistics fleet participating in V2G and the influence factors of the V2G profit are studied. Firstly, the travel data of a pure electric logistics fleet in Chengdu, China is collected. Secondly, the V2G profit model is established to quantify the economic benefits. Then, 4 V2G scenario modes are proposed based on window duration, window start time, SOC lower limit and discharge price. Finally, the change law and influence factors of the V2G profit in each V2G scenario mode are studied from the perspective of the discharge revenue, charge cost and battery loss cost. The results show that the V2G profit increases with the extension of window duration, the delay of window start time, the decrease of SOC lower limit and the increase of discharge price. The average profit of logistics fleets ranges from 3.94 RMB/(vehicle·day) to 65.54 RMB/(vehicle·day). [ABSTRACT FROM AUTHOR]

This paper studies the influence of water systems and roads on the distribution of the western Sichuan Linpan in Deyuan Town of Chengdu City in China. The amount and ratio of Linpan in a specific buffer zone were calculated and analyzed by buffer analysis, and the specific distance that each density distribution zone of Linpan away from water systems and roads was determined. Based on these above data, the effects of the distribution of water systems and roads on the distribution of Linpan were studied quantitatively. It is found that most of the Linpans are distributed in the area of 0–60 m from the water system and 0–40 m from the road. Linpan tends to be located close to the water systems and roads. And through analysis, it is found that the optimal distribution distance of Linpan is 10–20 m and 30–40 m from the water system and less than 5 m from the road. Through quantitative analysis of the impact of water systems and roads on the distribution of Linpan settlements, it provides important theoretical support for the further guiding the site selection of the Linpan center, the construction of surrounding villages, and township land planning and improvement. [ABSTRACT FROM AUTHOR]

Tree-based and deep learning methods can automatically generate useful features. Not only can it enhance the original feature representation, but it can also learn to generate new features. This paper develops a strategy based on Light Gradient Boosting Machine (LightGBM or LGB) and Gated Recurrent Unit (GRU) to generate features to improve the expression ability of limited features. Moreover, a SARIMA-GRU prediction model considering the weekly periodicity is introduced. First, LightGBM is used to learn features and enhance the original features representation; secondly, GRU neural network is used to generate features; finally, the result ensemble is used as the input for prediction. Moreover, the SARIMA-GRU model is constructed for predicting. The GRU prediction consequences are revised by the SARIMA model that a better prediction can be obtained. The experiment was carried out with the data collected by Ride-hailing in Chengdu, and four predicted indicators and two performance indexes are utilized to evaluate the model. The results validate that the model proposed has significant improvements in the accuracy and performance of each component. [ABSTRACT FROM AUTHOR]

The high environmental pollution load caused by the massive pollutant emissions and the accumulation of endogenous and cross-regional pollution has become an important obstacle to the current ecological civilization construction in the Yangtze River Economic Belt (YREB) in China. Taking the YREB as an example, by using four environmental pollutant emission indicators, including chemical oxygen demand (COD), ammonia nitrogen (NH3-N), sulfur dioxide (SO2), and nitrogen oxides (NOx), this paper established an environmental pollution load index (EPLI) based on the entropy-based measurement. Moreover, the Spatial Durbin Model was used to quantitatively analyze the drivers and spatial effects of environmental pollution load. Finally, specific scientific references were provided for formulating environmental regulations of pollution source control in the YREB. The results showed that: 1) During 2011–2015, the EPLI in the YREB was reduced significantly and the environmental pollution load increased from upstream to downstream. Among them, the pollution load levels in the Upper Mainstream subbasin, Taihu Lake subbasin, and Lower Mainstream subbasin were the most prominent. 2) The environmental pollution load situation in the YREB was generally stable and partially improved. High load level areas were mainly concentrated in the Yangtze River Delta Region and the provincial borders in upstream, midstream, and downstream areas. The high load level areas already formed in Chengdu and Chongqing were also the key regulatory points in the future. 3) The degree of local environmental pollution load was apparently affected by the adjacent cities. The population size, industrialization level, and the fiscal decentralization not only drove the increase of the local environmental pollution load level, but also affected the adjacent areas through the spatial spillover effects. The land development intensity mainly drove the increase in the local EPLI in the YREB. While factors such as economic development level and agricultural economic share could only act on the environmental pollution load process in adjacent cities. 4) According to the differentiation characteristics of drivers of each city, the YREB was divided into seven zones based on k-medoids cluster method, and targeted zoning control policy recommendations for alleviating environmental pollution load in the YREB were proposed. [ABSTRACT FROM AUTHOR]

Accurate travel time prediction between two locations is one of the most substantial services in transport. In travel time prediction, origin–destination (OD) method is more challenging since it has no intermediate trajectory points. This paper puts forward a deep learning-based model, called Gated Spatial–Temporal Attention (GSTA), to optimize the OD travel time prediction. While many trip features are available, their relations and particular contributions to the output are usually unknown. To give our model the flexibility to select the most relevant features, we develop a feature selection module with an integration unit and a gating mechanism to pass or suppress the trip feature based on its contribution. To capture spatial–temporal dependencies and correlations in the short and long term, we propose a new pair-wise attention mechanism with spatial inference and temporal reasoning. In addition, we adapt and integrate multi-head attention to improve model performance in case of sophisticated dependencies in long term. Extensive experiments on two large taxi datasets in New York City, USA, and Chengdu, China demonstrate the superiority of our model in comparison with other models. [ABSTRACT FROM AUTHOR]

Online dating has modernized traditional partner search methods, allowing individuals to seek a partner that aligns with their preferences for attributes such as age, height, location, or education. Yet traditional forms of partner selection still exist, with continued parental involvement in the matching process. In this paper, we exploit different matchmaking methods with varying degrees of youth autonomy versus parental involvement. We use a unique dataset collected in Chengdu, China, where profiles from the blind date market (n = 158) capture parental preferences and profiles from an online dating website (n = 500) capture individual preferences. Regarding gender, we find that men generally display a desire for women younger, shorter, and less educated than themselves, while women desire older and taller men of the same education as themselves. With regards to parental influences, we find parents specify a narrower range of accepted partner attributes. Further, we find an interaction effect between gender and generational influences: the preferences of parents advertising their daughters on the blind date market show a greater discrepancy in attribute preferences to the online daters than parents advertising their sons. [ABSTRACT FROM AUTHOR]

In this article the author offers gratitude to Maja J matari&#263, retired co editor-in-chief (EiC) of the journal and announces that Oussama Khatib will serve as the co editor-in-chief of the journal from January 2013. It is mentioned that the page budget per issue of the journal has been increased from 100 to 150 pages from January 2013. Further, it is mentioned that they organized their Fourth International conference on Social Robotics (ICSR) in Chengdu, China, held in October 29-31, 2012.

The Xinbaishiyan tunnel in the reconstruction Chengdu–Kunming railway Ermeishan-Mipan section mainly runs through dolomite with dolomitic limestone, with an excavation area of 260 m2, a maximum span of 22.3 m, a maximum height of 14.4 m, a vector height of 7 m, and a rise-span ratio of 0.31. The tunnel has an extra-large cross section, and it is a low flat-ration railway tunnel. This paper mainly describes the finite element analysis for this tunnel excavation that was used to guide the construction. Finite element software was used to model the tunnel according to the engineering geological conditions of the tunnel. These engineering geological conditions included the rock mass, system bolts, middle pipe shed, steel arch and shotcrete, grouting layer, second lining and so on. Nonlinear construction phase analysis was adopted. The results showed that the maximum vertical deformation of the tunnel vault and the middle of the invert was about 34 mm. The vertical deformation of the tunnel could be divided into an acceleration deformation section, linear deformation section, deceleration deformation section, and stable deformation section. The maximum horizontal deformation in the middle of the side wall was about 12.3 mm. Under the effect of the initial support, the equivalent stress of the side wall gradually increased with the excavation of the steps and the increase in the support structure. The axial force of the bolt in the middle of the side wall was larger than that in other places and the axial force of the middle pipe shed went along with the excavation of the tunnel in waves. The steel arch and the shotcrete had the maximum effective stress at the arch shoulder, which played the role of the deformation and pressure for the surrounding rock. During the construction, the length and height of the three-step method had to be set reasonably. The middle pipe shed and the system bolt supported the rock mass together. In the construction of the extra-large cross section and the flat tunnel, there was no need to set up temporary support, which was convenient for mechanical excavation. [ABSTRACT FROM AUTHOR]

With the development of the economy, developing high-technology industries and upgrading traditional industries have become a global focus. The relationship between the development of high-technology and traditional industries has also affected urban expansion. In this paper, a fractional derivative gray Lotka−Volterra model with time delay (FDGLV) is established by introducing fractional derivative and delay factor into the GLV model. The model is solved by using the fractional Adams−Bashforth−Moulton predictor−corrector algorithm. The gray correlation analysis is used to determine the time delay value of the model, and the parameters are optimized by using the whale algorithm. Then, the data of high-technology industry, traditional industry, and urban expansion in Chengdu, Changsha, and Chongqing are collected to verify the effectiveness of the model. Finally, the model is used to analyze the coopetition between industrial upgrading and urban expansion in Wuhan, and predict the development status in the next 5 years. [ABSTRACT FROM AUTHOR]

This paper principally focuses on the spatial layout features of Linpan in Deyuan Town of Chengdu City in China. The spatial shape analysis and spatial fractal analysis in studied areas was carried out by using analysis methods of Fractal Analysis, Zonal Geometry as Table, Field Calculator. The results demonstrated that densely shaped Linpan (resembling square or circle type) with starlike scattered distribution, and loosely shaped Linpan (slender type) distributed along roads or water strips, both of which are concentrated along water systems or roads and stay away from major exterior roads. It is found that Linpan in the studied area is in the state of random motion similar to the Brownian motion. The spatial pattern of the residential patch is complex and in the most unstable state. Quantitative research on the spatial layout features of Linpan is conducive to strengthening the scientific and rational understanding of Linpan. The research findings could be used as the scientific foundation for guiding the selection of rural centers, surrounding village construction, township land planning and remediation. [ABSTRACT FROM AUTHOR]

The Diexi ancient dammed lake is in the upper reaches of the Minjiang River. Six terraces with lacustrine sediments occur at the base. These terraces are the products of the graded outburst of the Diexi ancient dammed lake. The outburst of the ancient dammed lake would certainly have had an impact on the Chengdu Plain in the lower reaches of the Minjiang River. In this paper, on-site sampling and laboratory analysis were used to analyze the sediments of the Diexi ancient dammed lake and the Jinsha site in Chengdu Plain, and the environmental indicators of each sediment layer were tested. Through a comparative analysis of the environmental indicators in the sediments at the two locations, the following results were obtained: the palaeoclimatic and palaeoenvironmental characteristics at the two locations generally show consistent changes. The most important finding is that the types and content of the major pollen taxa at the two locations are similar. The Pinus content strongly proves that the soil layers at the Jinsha site was sourced from the upper reaches of the Minjiang River. Considering that the demise of the ancient culture at the Jinsha site occurred close in time to the outburst of the ancient dammed lake, this similarity suggests that the cultural change at the Jinsha site may have been related to the outburst of the Diexi ancient dammed lake. [ABSTRACT FROM AUTHOR]

Urban ecosystem has become a critical part of ecological security and draws much attention worldwide. It is both a result of natural ecological system development, and also an inevitable outcome of human ecological system development within a certain stage, with the objective of identifying the possible improvement space for unban ecological security evaluation from complex system perspective. Based on the brittle structure model and set pair theory, this paper firstly explored the main research methods of urban ecological security theory and its characteristics, then conducted a theory of complex system brittleness to analyze the urban ecological security brittle factors, brittle primitives, and brittle structure. Furthermore, it conducted a model of urban ecological system brittleness correlation entropy together with a set pair analysis method to discuss its brittleness. And finally, an ecological safety evaluation has been presented based on the empirical case in Chengdu City of China. The theoretical and empirical analysis shows that the brittle correlation entropy of natural subsystem in urban ecological security is the biggest one. The risks from natural subsystem collapse can easily trigger the brittleness of the entire urban system. The corresponding maximum brittle fluctuation entropy is from economic subsystem; it has a largest impact on the entropy change of urban ecosystem. The way of reducing the uncertainty of urban ecological risks is to lower difference degree coefficient in the system. Relevant decision makers should consider to reduce the increasing degree of entropy and eliminate the fluctuation of the brittle factors. Thus, the threats or risks of urban ecological system can be within the acceptable range and under control. An integrated system management combing with brittleness characters of natural, economics, and social subsystem is necessary. It is helpful for the ecological security construction. [ABSTRACT FROM AUTHOR]

This paper systematically studied the mass concentration levels of PM2.5 and PM10 and obtained the morphological characteristics and components of the particles through scanning electron microscopy (SEM–EDX) and discussed the sources of the particles. Meanwhile, the health risk was evaluated according to the mass concentration of particulate matter. The results showed that the average annual PM2.5 and PM10 in the eastern part of Chengdu were 101.99 μg/m3 and 168.89 μg/m3, respectively, exceeding the national second-level average annual air quality standard (GB3095-2012). Both of them were the highest in winter and the lowest in summer and had a significant positive correlation. The atmospheric particles in the study area were mainly composed of fly ash particles, soot aggregates, mineral particles (sulfate mineral particles, carbonate mineral particles, etc.), which mainly came from coal burning, dust, automobile exhaust and secondary products. The results of the health risk assessment showed that the mass concentration of PM2.5 and PM10 in the atmosphere of the eastern part of Chengdu exceeded the IT-1 target. The average annual air quality index was 185.84, and the air quality index was level 4, classified as medium pollution. PM10 and PM2.5 were both excessive pollutants, and PM10 was the primary pollutant. Relevant measures should be taken to control particulate matter sources to some extent. [ABSTRACT FROM AUTHOR]

During May 12–14, 2018, the International Conference for the Decade Memory of the Wenchuan Earthquake, in connection to the 4th International Conference on Continental Earthquakes (4th ICCE) and the 12th General Assembly of the Asian Seismological Commission (ASC), was held in Chengdu, China. There have been several outcomes of the Conference (for example, the book published jointly by Higher Education Press and Springer) as well as the present special issue. Among the 58 submissions, 34 have been accepted after peer review. Some of the papers came from the presentations during the Conference, but with additional submissions, the scope of this special issue is far beyond that of the proceedings of the meeting. [ABSTRACT FROM AUTHOR]

Analysis of the spatial–temporal pattern and trend of carbon emissions provides an important scientific basis for the development of a low-carbon economy. Based on the corrected NPP-VIIRS and DMSP/OLS nighttime light data, a carbon emission model for the Chengdu–Chongqing Economic Zone (CCEZ) in China is constructed. Furthermore, the article establishes an integrated qualitative and quantitative research system. The qualitative results show that at the city and county scales, the high carbon emission areas and counties are mainly distributed in Chengdu and Chongqing, while the low carbon emission areas are concentrated in the marginal cities of the CCEZ and the counties with low levels of industrialization around the Sichuan Basin. The high-carbon emission zone tended to expand to the north, and the low-carbon emission zone tended to expand to the south. At the grid scale, the carbon emissions of the CCEZ fluctuated and increased from 2000 to 2020, forming a trend connected with those of the central city, with high carbon emissions at the core and radiating outward expansion. Quantitative analysis revealed that carbon emissions at the county and grid scales exhibited a significant positive global spatial correlation, and the overall correlation degree exhibited an increasing trend. [ABSTRACT FROM AUTHOR]

The spatial heterogeneity and temporal variability of traffic in urban environments make traffic emissions inference challenging. To address this challenge, this study introduces a novel geographical context-based approach utilizing high-resolution taxi GPS data, incorporating multidimensional contextual factors such as road data, points of interest (POI), weather data, and population density. The proposed method can enhance the precision of traffic emissions inference compared to conventional macroscopic estimation techniques. To overcome the issue of missing data in traffic emissions inference from taxi data, three ensemble machine learning algorithms—Random Forest, Gradient Boosting Decision Trees (GBDT), and eXtreme Gradient Boosting (XGBoost)—are employed. These algorithms efficiently handle a substantial volume of taxi GPS data, achieving reduced computational time and model complexity. The proposed framework establishes localized models for each road segment, taking into consideration both geographical and external features that characterize the urban environment. This localized modeling contributes significantly to a more profound understanding of traffic dynamics. A thorough comparative analysis is conducted to assess the performance of the proposed method. Results indicate that incorporating multidimensional urban features is advantageous for traffic speed inference. Among the ensemble learning models, Random Forest outperforms others when dealing with a small missing rate or limited sample size, while XGBoost exhibits superior performance for larger missing rates or substantial sample sizes. Additionally, an analysis of the feature importance in traffic speed highlights that road network features are the most significant factors, followed by temporal characteristics, spatial attributes, POI data, and weather information. Finally, leveraging inferred traffic speed and volume information, emissions from large-scale urban road traffic are inferred based on the COPERT model. In contrast to methods relying on complex, multi-source data for emission estimation, our approach utilizes simple and easily accessible data, enabling precise estimation of emissions on a large-scale spatiotemporal basis. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to develop an emission inventory of anthropogenic air pollutants and VOCs species in Sichuan Province. Based on the anthropogenic source activity data collected in different cities of Sichuan Province and the selected emission factors, the 1 km × 1 km gridded atmospheric air pollutant emission inventory of 2015 was developed in the "bottom-up" and "top-down" approaches with the GIS technology. The results showed that the emissions of SO2, NOX, CO, PM10, PM2.5, BC, OC, VOCs and NH3 from anthropogenic sources in Sichuan Province were 444.9 kt, 820.0 kt, 3773.1 kt, 1371.6 kt, 537.5 kt, 28.7 kt, 53.1 kt, 923.6 kt and 988.0 kt, respectively. Power plants and other industrial combustion boilers contributed more than 95% of SO2 emission. Transportation, fossil fuel burning and industrial process contributed 54%, 23% and 20% of NOx emission respectively. Industrial process dominated by steel production and building material manufacturing contributed 20% of PM10 emission and 34% of PM2.5 emission. Fugitive dust dominated by road fugitive dust contributed 60% of PM10 emission and 35% of PM2.5 emission respectively. Biomass burning contributed 33% of BC emission and 51% of OC emission respectively. Solvent use of mechanical processing, building decoration, electronic equipment manufacturing, printing and furniture industry contributed 46% of VOCs emission. NH3 mainly came from the emission of agricultural sectors, such as livestock breeding and N-fertilizer application, which contributed 70% and 25% of NH3 emission respectively. The percentage of alkanes, alkenes, alkynes, aromatics, OVOCs, halohydrocarbons and other VOCs in the total VOCs emission were 17%, 9%, 2%, 23%, 22%, 4% and 23%, respectively. Ethene, m-xylene, toluene, propene, formaldehyde, o-xylene, 1, 2, 4-trimethyl benzene, 1-butene, p-xylene and ethyl benzene were the most critical chemical species for the formation of ozone pollution in Sichuan Province contributing 50% of the total OFP. Various air pollutants and OFP were mainly distributed in places with the densest population and well-developed agriculture and industry in Sichuan Basin and some areas of Panzhihua. The Chengdu Plain urban agglomerations, represented by Chengdu, Deyang and Mianyang, were the main areas with concentrated pollutant emissions in Sichuan Basin. [ABSTRACT FROM AUTHOR]

Based on the scale, distribution, and structure of scientific and technological resource allocation, the basic characteristics of scientific and technological resource allocation in Chengdu–Chongqing–Mianyang were analyzed, and the relevant panel data of the three places and the whole region were analyzed using the data envelopment analysis (DEA)-Malmquist index model, spanning the period of 2010–2019. The results show that the overall efficiency of scientific and technological resource allocation in Chengdu–Chongqing–Mianyang shows an upward trend during the study period, which is attributed to the significant increase in the rate of technological progress. The rapid growth in Chongqing and Mianyang is attributed to good policy support, rapid renewal of facilities and institutions, and improved management experience. The relative slowdown in the rate of technological progress in Chengdu may be due to industrial restructuring, coupled with a shift in economic technology from high growth to high quality development. At the same time, Chengdu–Chongqing–Mianyang region is more inclined to cultivate its own R&D capabilities, and the accumulation and upgrading of innovation management technologies are insufficient to meet its innovation needs. Finally, the study proposes countermeasures to improve the efficiency of science and technology resource allocation in Chengdu–Chongqing–Mianyang from macro and micro perspectives. [ABSTRACT FROM AUTHOR]

Understanding urban human mobility, particularly trip purposes, is essential for optimizing traffic management, personalized recommendations, and urban planning. However, in real-world scenarios, trip purposes cannot be directly extracted from the trajectory data. To address this issue, we propose a geometry-driven neural topic model for trip purpose inference. We integrate trajectory data with nearby POI data using a geometry-driven technique to enhance the interpretability of the results. Furthermore, our model captures the semantics and relationships of the data in a high-dimensional space and identifies latent topics representing distinct trip purposes. These learned topics are analyzed using clustering algorithms to group similar trips, enabling trip purpose inference. And we evaluate our model using the trajectory data of Shenzhen and Chengdu, and compare it with baseline models. The results demonstrate that our model performs well. Furthermore, we analyze trajectory data containing trip purpose information to gain insight into human mobility patterns and the influence of trip purposes, paving the way for potential implications and future research directions. [ABSTRACT FROM AUTHOR]

There are limited published studies on patient activation among patients with systemic lupus erythematosus (SLE) in China. Disease activity can significantly influence a patient's perception of their condition, subsequently impacting patient activation. However, the mechanisms through which disease activity influences patient activation remain poorly understood. This study aimed to investigate patient activation among patients with SLE in China and explore the influencing factors. We conducted a cross-sectional study from June to December 2021 at a rheumatology and immunology department of a tertiary hospital in Chengdu, China. Data were collected by questionnaire, including general information, disease activity, quality of chronic illness care, health literacy, self-efficacy, motivation, social support, and patient activation. A patient activation model was constructed based on the conceptual framework derived from the individual and family self-management theory. To evaluate the moderating effect of disease activity on patient activation model, participants were divided into two subgroups (low disease activity group and high disease activity group). 426 SLE patients were included. The mean score of patient activation among SLE patients was 63.28 ± 11.82, indicating that most SLE patients lacked skills and confidence to stick with health-promoting behaviors. Health literacy, social support, and self-efficacy had the greatest effect on patient activation. In the multi-group analysis, social support and health literacy contributed more to patient activation in SLE patients with high and low disease activity, respectively. Patient activation among SLE patients in China was at the third level. Healthcare professionals should help them adhere to health-promoting behaviors. Health literacy, social support, and self-efficacy are vital factors for patient activation. These factors should be prioritized based on disease activity when developing individually tailored interventions for patient activation. [ABSTRACT FROM AUTHOR]

The development of urbanization and the protection of the ecological environment are important aspects of sustainable development in urban agglomerations; thus, their coordination and synergy are crucial. Scholars in both China and other countries have conducted extensive research on the relationship between urbanization and the ecological environment from the perspective of coordinated development. However, there is a lack of research on the synergistic effects of urbanization and the ecological environment. Taking the Chengdu–Chongqing urban agglomeration as an example, this study uses the Haken model to analyze the synergistic evolution mechanism, development patterns, and future trends of urbanization and the ecological environment. This study draws the following conclusions: (1) while a synergistic development mechanism has been established between urbanization and the ecological environment, the current system is still in a stage of low-level synergy, and the control system's parameter for the direction and path of evolution is urbanization. (2) From 2001 to 2020, the level of synergistic development between urbanization and the ecological environment was relatively low, mainly moving from low-level synergy to medium–low-level synergy to medium-level synergy. (3) There is a significant spatial disparity in the levels of synergistic development, for which the leading region centers on Chengdu and Chongqing in the northwest and southeast, respectively, and the lagging region comprises the eastern part of the urban agglomeration, mainly represented by Dazhou, Kaizhou, and Yunyang. (4) The future trend of synergistic development between urbanization and the ecological environment in the Chengdu–Chongqing urban agglomeration is promising but requires increased infrastructure construction in mountainous urban areas, enhanced cooperation and circulation in transportation, logistics, information and other aspects, and balanced improvements in the level of synergistic development between urbanization and the ecological environment. The study of the synergistic development effect of urbanization and the ecological environment in urban agglomerations is of great significance for reducing the negative impact of urbanization on the ecological environment, increasing the positive interaction between the two, and promoting sustainable development in urban agglomerations. [ABSTRACT FROM AUTHOR]

The aims of this study on human papilloma virus (HPV) 6/11/16/18 infection among females in Chengdu were to provide more targeted strategies for the prevention and treatment of cervical cancer and genital warts. In this study, the infection status of 20 genotypes was analysed by gene chip technology. The prevalence rates of HPV-6, -11, -16, and -18 infection among 180,276 cases were 0.94%, 0.57%, 3.22%, and 1.28%, respectively. The prevalence of HPV 6/11/16/18 showed a bimodal U-shaped curve with age; the first and second peak occurred among females < 20 and ≥ 60 years old, respectively. As the multiplicity of infections involving HPV6/11/16/18 increases, the infection rate decreases. The ratios of HPV16 single infection showed a yearly increase. The top five genotypes with HPV-16, -18, -6, and -11 in coinfection were HPV52/58/53/51/33, HPV 52/16/53/58/51, HPV52/16/58/51/53 and HPV16/52/58/59/18, respectively, HPV16/18/6/11 were mainly coinfected with HR-HPV. In sum, among the five vaccines available, nonavalent vaccine is more suitable for Chengdu females. For young females prioritizing vaccination is essential in the current context, while HPV screening remains an effective approach for older females. Additionally, in patients with genital warts, it is necessary to assess the presence of high-risk HPV infection and manage it appropriately in patients with genital warts. [ABSTRACT FROM AUTHOR]

As an important part of urban renewal, brownfield restoration and renovation are of great significance to the sustainable development of cities. The structure-process-outcome theory was introduced into this study to improve the rationality and scientific vigor of the redevelopment assessment process and to evaluate whether brownfield sites meet the conditions for redevelopment. Based on this theory, the relationship among structures, processes and outcomes can be well elucidated. Specifically, a good structure should contribute to an effective process, which will increase the possibility of a favorable outcome. The basic conditions, practice principles, and result orientation in the whole procedure of brownfield redevelopment were comprehensively analyzed. In addition, a more complete and reasonable three-level evaluation index system for brownfield redevelopment was established. In order to reduce the subjectivity in the evaluation process, an unbiased scientific brownfield redevelopment evaluation model was constructed using the continuous ordered weighted averaging operator-topology method. The evaluation decision system was applied to the renovation of a tract project in Chengdu, China. The results proved that the model could effectively and accurately evaluate the quality level of the brownfield redevelopment project, and the proposed recommendations can provide a basis for decision-making. [ABSTRACT FROM AUTHOR]