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To improve the problem of collapsibility of loess, adding industrial materials such as cement is common engineering treatment, but this seriously damages the reclamation performance of soil. Calcium lignosulfonate (CLS) from paper plant waste fluids is a natural bio-based polymer with good application prospects as a soil improver. In this paper, the collapsibility and mechanical properties of CLS improved loess were investigated using a collapsibility test, gray correlation analysis, and an unconfined compressive strength test (UCS). In addition, the strengthening mechanism of CLS-improved loess was also explored based on scanning electron microscopy (SEM), microstructure parameters, and X-ray diffraction. The collapsibility coefficient decreased rapidly after CLS was admixed, and the single and double-oedometer methods showed the same change trend. The order of grey correlation degree of collapsibility on each index from large to small was: moisture content, pore ratio, dry density, and CLS content. The dosage of CLS greatly influenced the mechanical properties and collapsibility of stabilized loess. The optimum amount of CLS for Xi'an loess was 3%, at which the collapsibility coefficient was reduced by more than 95%, and the 28 d UCS increased by 180.01%. From the microstructure and mineral composition analysis perspective, CLS plays a role in filling pores and linking soil particles. After the protonation and ion exchange effect of CLS, the grain size and double electric layer thickness of mineral composition were reduced, and the structural compactness was increased. These research results are of great scientific significance for the ecological modification of soils. [ABSTRACT FROM AUTHOR]

Excessive particle concentrations during heating periods, which greatly affect people's physical and mental health and their normal lives, continue to be a concern. It is more practical to understand and analyze the relationship between the fractal dimension and particle size concentration distribution of atmospheric particulate matter before and after adjusting heating energy consumption types. The data discussed and analyzed in this paper were collected by monitoring stations and measured from 2016 to 2018 in Xi'an. The data include fractal dimension and particle size concentration changes in the atmospheric particulate matter before and after adjusting the heating energy consumption types. The results indicate that adjusting the heating energy consumption types has a significant impact on particulate matter. The average concentration of PM2.5 decreased by 26.4 μg/m3. The average concentration of PM10 decreased by 31.8 μg/m3. At the same time, the different particle sizes showed a downward trend. The particles ranging from 0.265 to 0.475 μm demonstrated the maximum decrease, which was 8.80%. The heating period in Xi'an mainly involves particles ranging from 0 to 0.475 μm. The fractal dimensions of the atmospheric particulate matter before and after adjusting the heating energy consumption types were 4.809 and 3.397, respectively. After adjusting the heating energy consumption types, the fractal dimension decreased by 1.412. At that time, the proportions of particle sizes that were less than 1.0 μm, 2.0 μm, and 2.5 μm decreased by 1.467%, 0.604%, and 0.424%, respectively. This paper provides new methods and a reference value for the distribution and effective control of atmospheric particulate matter by adjusting heating energy consumption types. [ABSTRACT FROM AUTHOR]

The mode of urban renewal in China has changed from incremental expansion to a value-added stage, and the development of cities has increasingly focused on the human experience and quality improvement. However, Cultural Street Vending and the unique street spaces in the historic districts that bear important connotations to the city have shown a trend of rapid decline and even disappearance. Therefore, how to identify the characteristics and connotations of such street vending spaces, grasp the relationship between perception of locality and built environment elements in different states and formulate targeted protection and renewal strategies is presently an urgent problem to be solved. Many studies have now discussed in detail the identification of elements, street perception and preservation strategies for historic districts. However, the Cultural Street Vending space, which carries special urban memory connotations, has been neglected, especially the characterisation of this type of space in different time dimensions. This paper takes the Cultural Street Vending space as a research object and focuses on the perceptual differences between its market day and non-market day, aiming at grasping the perceptual characteristics and constituent elements of this type of street space in different time states, as well as the patterns of changes they undergo. This paper took the Baxian Temple, a typical Cultural Street Vending space in a historic district of Xi'an, as the research object and took 30 architecture students as the evaluators to score 33 pairs of adjectives and recall the elements of nine streets. This paper compared and analysed the differences in the structure of people's psychological perception of the street in the state of market day and non-market day by SD method. It was found that the activities of the vendors obviously promoted people's positive emotions, and three commonality factors including impression, vitality and morphosis were extracted through the factor analysis. Moreover, through the element recall method to understand the change in element perception on the market day, we found that the range of people's perception was smaller on the market day and summarised the element map of the space and the element components of high, medium and low characteristics. The correlation analysis between psychological quantities and environmental elements revealed that people's positive psychology has a positive correlation with vendors, goods and street components and a negative correlation with greening, colour and texture. This study can provide an important research basis for the development of conservation and renewal strategies for this type of Cultural Street Vending space. [ABSTRACT FROM AUTHOR]

Islam is widely spread throughout every corner of China, with the Hui people, the largest Muslim ethnic group in China, numbering over 10 million people, serving as its main carrier. Their culture types and local features exhibit great diversity across different provinces. The ceremony of Prophet's Day or Mawlid al-Nabi in China, as one of the three fundamental festivals of the Hui people alongside Eid al-Fitur and Eid al-Qurban, appears to be more comprehensive, open, and localized. Drawing from fieldwork in three Hui communities—Xi'an in Shaanxi province, Najiaying in Yunnan province, and Hezhou in Gansu province—this paper approaches the topic from the perspective of inculturation and cultural innovation. It aims to describe the ritual processes observed in these three different Hui communities and discuss how the Hui people integrate Islam with traditional Chinese culture in their local contexts, with the intention of forming and preserving their own cultural characteristics. [ABSTRACT FROM AUTHOR]

With the development of urban population aging in China, enhancing the quality of community living environments for the elderly has become crucial. Traditional residential planning focused on functionality, neglecting the elderly's active participation and mutual aid needs. This paper proposes the development of urban community environments promoting "living mutual aid" to improve elderly life quality and practice active aging. Using qualitative and quantitative methods, the study identifies key components of mutual aid, explores the relationship between mutual aid behaviors and spatial composition, and outlines strategies for designing community environments that support mutual aid. Based on "active aging" theory, the study qualitatively summarizes the concept of mutual aid among the elderly through literature and policy analysis. Surveys, interviews, and observations in Xi'an's typical communities were conducted, with results analyzed using factor and frequency analysis. The study categorizes mutual aid activities and behavior characteristics, and explores the relationship between behavior and spatial needs using environmental behavior theory. It identifies mutual aid space units and suggests types, paths, strategies, and methods for integrating these units into community environments. The findings provide scientific guidance for urban community planning and valuable references for creating elderly-friendly urban habitats. [ABSTRACT FROM AUTHOR]

Research on the identification of urban functional regions is of great significance for the understanding of urban structure, spatial planning, resource allocation, and promoting sustainable urban development. However, achieving high-precision urban functional region recognition has always been a research challenge in this field. For this purpose, this paper proposes an urban functional region identification method called ASOE (activity–scene–object–economy), which integrates the features from multi-source data to perceive the spatial differentiation of urban human and geographic elements. First, we utilize VGG16 (Visual Geometry Group 16) to extract high-level semantic features from the remote sensing images with 1.2 m spatial resolution. Then, using scraped building footprints, we extract building object features such as area, perimeter, and structural ratios. Socioeconomic features and population activity features are extracted from Point of Interest (POI) and Weibo data, respectively. Finally, integrating the aforementioned features and using the Random Forest method for classification, the identification results of urban functional regions in the main urban area of Xi'an are obtained. After comparing with the actual land use map, our method achieves an identification accuracy of 91.74%, which is higher than other comparative methods, making it effectively identify four typical urban functional regions in the main urban area of Xi'an (e.g., residential regions, industrial regions, commercial regions, and public regions). The research indicates that the method of fusing multi-source data can fully leverage the advantages of big data, achieving high-precision identification of urban functional regions. [ABSTRACT FROM AUTHOR]

The risk level of the NIMBY (Not In My Back Yard) phenomenon is crucial for the safety and economy of transmission and transformation projects which is rarely studied, especially for site selection and the construction of transmission lines and substations. In order to effectively evaluate the risk level to solve the dilemma caused by the NIMBY phenomenon, an evaluation method for quantifying the level of the NIMBY phenomenon is proposed. In this paper, thirty-one evaluation criteria and a risk model are put forward according to relevant laws and regulations that should be followed in the transmission and transformation project in China, then the scores corresponding to these criteria are obtained by a questionnaire survey. The radar chart method and minimum area method are applied to determine the weights of the element and unit layers. Furthermore, the overall risk level is evaluated by the fuzzy comprehensive evaluation method. In addition, a transmission and transformation project in Xi'an City, China, is used as an example to verify the correction of the risk model and its evaluation method. The results show that the weaknesses in the transmission and transformation project are analyzed, and suggestions for decreasing the risk level are put forward to minimize losses due to the NIMBY phenomenon. [ABSTRACT FROM AUTHOR]

Metropolitan areas shoulder the crucial task of regional and even national economic development. Analyzing the spatial patterns and influencing factors of metropolitan traffic dominance can provide a scientific basis for the optimization of its transportation and industrial layout, which is conducive to the development of its economy. Previous studies on traffic dominance paid little attention to metropolitan areas and even less so to study these areas from the perspective of town units, even though these are the basic units that narrow the gap between urban and rural areas and thus achieve regional economic integration. The traffic dominance model can comprehensively and wholly reflect regional traffic conditions, due to its multidimensional characteristics (including traffic network density, traffic arterial influence and accessibility). Consequently, taking the Xi'an metropolitan area as an exemplar and the town as the basic unit, this paper employs this model and other methods to study the spatial pattern and influencing factors of its traffic dominance. The results show the following: (1) the traffic network density, traffic arterial influence and accessibility had different distribution patterns; however, they were the same in that their superiorities were relatively high in the main urban area of Xi'an city or along and on both sides of the high-speed railways (HSRs), whereas relatively low in the peripheral areas; (2) the integrated traffic dominance consistently displayed a "point-axis" pattern, with greater superiority in the east–west axis areas within 30 km of Xi'an city, especially in the main urban area of Xi'an city; (3) the integrated traffic dominance between towns had stable agglomeration correlation in the global areas and formed three major modes in the local areas: high–high, low–low and low–high aggregation. High–high mode was concentrated in the main urban areas of Xi'an and Xianyang city, low–low mode was mainly distributed in the Weibei hilly and gully areas and the Qinling mountain areas and low–high mode always nested on the edge of high–high areas; and (4) the location, GDP and elevation had a greater impact, whereas construction intensity, population and slope had a relatively small influence on the town's traffic dominance, and their influence ability had a decreasing trend from 2010 to 2022. Finally, this paper discusses the theoretical implications, practical values and some prospects based on the research results. [ABSTRACT FROM AUTHOR]

Low-carbon travel is an important part of low-carbon cities and low-carbon transportation, and low-carbon transportation is an inevitable choice to slow down the growth of carbon emissions in China. All countries in the world are actively promoting new energy vehicles and attach great importance to the application of the new energy industry in urban transportation. Commuting is an important part of urban life, and the choice of travel behavior has an important impact on traffic and environmental protection. Taking the Xi'an metropolitan area as an example, this paper expounds on the integrated development path of the industrial chain of new energy + travel in the metropolitan area and clarifies the energy transformation model of the integrated development of low-carbon transportation and energy. From the perspective of green and low-carbon, 1000 commuters were interviewed using a questionnaire survey, and the cumulative prospect model was used to verify the internal mechanism affecting commuters in metropolitan areas to choose new energy commuting. The results of the study show that new energy transportation modes play an important role in the low-carbon economy, and under different scenarios and assumptions, there are significant differences in the cumulative prospect values of the subway, new energy buses and fuel private cars, and corresponding optimization measures are proposed to increase the proportion of new energy commuting trips. The results will help further promote the development of a low-carbon economy and energy integration in the field of transportation and provide a reference for the sustainable development of public transportation. [ABSTRACT FROM AUTHOR]

Thermal environment deterioration has seriously threatened urban habitat quality and urban sustainable development. The evolution of the urban built environment (UBE) is an important cause for urban thermal environment variation. However, the dynamic effect of the UBE on the land surface temperature (LST) is rarely studied by combining the local climate zone (LCZ) theory and spatio-temporal heterogeneity. Based on a case study of Beilin District in Xi'an, China, this paper identified LCZ types of Beilin District in 2010, 2015, and 2020 using the GIS method. It also analyzed the spatial–temporal characteristics of the LST in summer based on the remote sensing retrieval method and explored the effects of the built environment on the LST by Geodetector and geographically weighted regression (GWR). The results showed the following: (1) The area share of dense building zones in Beilin District was greater than that of open building zones and natural surface zones, while the share of mid- and high-rise dense building zones continued to increase and the share of low-rise dense building zones continued to decrease during the study period. (2) The LST of different LCZ types in Beilin District was obviously different, and the LST of dense building zones was generally higher than that of open building zones and natural surface zones. Meanwhile, the LST of mid- and low-rise dense building zones increased gradually, and the LST of high-rise open building zones decreased gradually, but the overall warming area was obviously more than the cooling area. (3) The effects of the UBE factors on the LST varied greatly, with their interaction having an enhancement effect. The direct and interactive influence of the two-dimensional (2D) UBE indicators on the LST were greater than those of the three-dimensional (3D) indicators, but there was a gradual decrease in the force of the 2D indicators and a simultaneous diminution, enhancement, and invariance of the force of the 3D indicators. (4) Vegetation cover (VC) and floor area ratio (FAR) acted negatively, and the building height (BH) was changing from a positive to a negative role, with the average action intensity of VC changing from −0.27 to −0.15, FAR from −0.20 to −0.16, and BH from 0.05 to −0.04. The impervious surface area (ISA), building area (BA), and space congestion (SC) acted positively, with the average action intensity of the ISA changing from 0.12 to 0.20, BA from 0.12 to 0.19, and SC was stable at 0.04. The framework enables a deeper portrayal of LST changes in different LCZs, reflecting the direct and interactive effects of different UBE indicators on LST, as well as local variations in the impact effects and provides a basis for urban managers or planners to improve urban heat resilience. [ABSTRACT FROM AUTHOR]

At present, there are many methods to construct a vehicle driving cycle, such as the micro-trip-based method and the Markov chain method. Different methods have different advantages and disadvantages. To compare these methods, this paper uses the micro-trip-based method, the Markov chain method, and the method combining micro-trips and Markov chains to construct the representative driving cycle of a Xi'an urban bus based on the driving data of the Xi'an No.2 bus. Firstly, the driving data is collected and preprocessed. Then, representative driving cycles are constructed based on different methods. Finally, different driving cycles based on different methods are compared. By calculating and comparing characteristic parameters, velocity distributions, acceleration distributions, and vehicle-specific power distributions between different representative driving cycles, this paper shows the advantages and disadvantages of different construction methods. [ABSTRACT FROM AUTHOR]

The exploitation and utilization of shallow geothermal energy are of great significance to realizing China's "double carbon" goal and promoting a green economy and social development. However, many projects using ground source heat pumps to exploit shallow geothermal energy have disrupted the thermal balance of the geothermal field due to insufficient preliminary research, affecting the sustainable utilization of shallow geothermal energy. Therefore, a 3D groundwater–thermal coupling model was established in this paper using the geotemperature data of a ground source heat pump system in Xi'an. This study investigated the response characteristics of the groundwater–thermal system to the ground source heat pump system using the numerical simulation method and discussed the optimal layout scheme of the system on this basis. After years of simulation, it was found that long-term operation of the ground source heat pump system under actual operation produces "cold accumulation". In addition to artificial intervention of the groundwater flow field, the effects of the system operating parameters and layout settings are also investigated to alleviate this cold accumulation. The results show that changing the operating parameters so that the heat transfer is the same in winter and summer, cross-locating the cooling holes with the heating holes, and placing multiple pumping and recharge wells downstream can alleviate the cold accumulation in the heat exchange zone. The results of this numerical simulation study provide an important reference for solutions to mitigate the accumulation of ground cold and heat in developing shallow geothermal energy using borehole heat exchangers and to suppress the downstream geotemperature disturbance via the ground source heat pump system. [ABSTRACT FROM AUTHOR]

Interchanges are the key nodes of the freeway. Due to the existence of weaving behavior, the traffic flow situation is more complicated for small spacing interchanges. Continuous auxiliary lanes are usually used to connect the entrance and exit to form a compound interchange to reduce the interference of weaving behavior. However, when it comes to the design of auxiliary lane forms, China lacks relevant design specifications and research in this area. As a result, there often exists the phenomenon of mismatch between the design form and the traffic volume. In this paper, we took a compound interchange in Xi'an as the research object, proposing four auxiliary lane design schemes and using VISSIM (2022 student) software to establish the simulation model. Additionally, various traffic conditions were simulated through sensitivity analysis. Finally, using the factor analysis method and entropy method, we comprehensively assigned weights to the indexes. By obtaining the weighted scores for various schemes, it became possible to determine the applicability of each scheme under different traffic conditions. The results indicate that the gradient auxiliary lane can be applied to most traffic conditions and has a smaller land occupation than the traditional design, which is an optimization and improvement for the traditional design form. [ABSTRACT FROM AUTHOR]

Buddhist monasteries have played important roles in the development of both the culture of and urban planning in ancient Chinese cities. In this paper, the Buddhist monasteries in the city of Xi'an, Shaanxi Province, during the Song (宋), Yuan (元), Ming (明), and Qing (清) dynasties are collated from historical documents. The characteristics of the spatial distribution of Buddhist monasteries are analyzed by using kernel density estimation (KDE), and the evolution of that spatial distribution is explored by documentary analysis. The results show that Buddhist monasteries are closely surrounded by cultural buildings and warehouses, discretely surrounded by administrative buildings. The spatial distribution evolution of Buddhist monasteries has evolved evenly during the expansion of the Xi'an city area, through the Song, Yuan, Ming, and Qing dynasties. This study provides a reference for the preservation of Buddhist monastery spaces in the historical context of Xi'an city area. [ABSTRACT FROM AUTHOR]

It is of great significance to understand the particle distribution characteristics at different heights to effectively control particle pollution. Based on fractal theory, the fractal dimension of outdoor particles in a high-rise building in Xi'an and its relationship with the concentration of particles with different particle sizes are discussed and analyzed in this paper. The results indicate that the atmosphere in Xi'an is mainly composed of fine particles and that the average proportion of particles ranging from 0 to 1.0 µm is approximately 99.885% of the total particulates. The fractal dimension of particles in the atmosphere at different heights ranges from 5.014 to 5.764, with an average fractal dimension of 5.456. In summer, the fractal dimension of the outdoor particles on the 17th floor was the largest, at 5.764. The fractal dimension in summer is relatively high, being 0.158 higher than that in winter on average. The larger the fractal dimension, the higher the proportion of fine particles. In addition, the fractal dimension can characterize the adsorption of toxic and harmful gases by particles well. It provides parameter support for understanding particle distribution and the effective control of atmospheric particles at different heights and application values. [ABSTRACT FROM AUTHOR]

In China, as statutory non-cultural relic buildings, the conservation and reuse of historic buildings have received increasing attention in recent years. Among them, the investigation and value evaluation of historic buildings are the basis and core of the conservation work, and many cities have explored related technologies and methods according to local conditions. This paper takes the historic building resources in Xi'an as the research object, with the core of historic building registration and the principles of scientificity and operability. It proposes the methods and basic processes for investigating historic building resources and constructs a step-by-step evaluation system for the historic buildings in Xi'an. This research first formulates a registration standard for the identification and evaluation of historic buildings, then applies the analytic hierarchy process, Delphi method, and fuzzy comprehensive evaluation method to assess the comprehensive value of historic buildings. Finally, it was recognized that the historic building resources are primarily modern and contemporary buildings, playing a significant role in the cultural continuity of the ancient capital, Xi'an. In its value evaluation, emphasis should be placed on the environmental landscape value and socio-cultural value. At the same time, it is necessary to consider the comprehensive value and sub-indicators of historic buildings so that they can guide conservation and adaptation practices in a targeted manner. [ABSTRACT FROM AUTHOR]

Leisure and tourism spaces are shared by both residents and tourists seeking a higher quality of life. Most of the literature focuses only on the study of a particular type of leisure or tourism space in cities and lacks an overall exploration of the distribution patterns of urban leisure and tourism formats. Based on the leisure and tourism point of interest (POI) data of 11 districts in Xi'an, this paper uses geospatial analysis to examine the spatial patterns of leisure and tourism facilities and their influencing factors in Xi'an. It is found in this study that the distributions overall and the various types of leisure and tourism spaces in Xi'an show the characteristics of central urban agglomeration and sparse dispersion in the surrounding urban areas. Different types of leisure and tourism patterns have obvious spatial scale dependence, but there are differences in the scope of spatial selection. In general, the core agglomeration area has limited radiation and driving effects on the peripheral areas, and there is a prominent phenomenon of imbalance in the distribution of leisure and tourism facilities following a single industrial structure. The formation of the spatial patterns of leisure and tourism is the result of a combination of dominant factors, driving factors, safeguarding factors, and other triggering factors. Urban leisure and tourism spaces are intertwined, and the spatial balance and industrial diversification of leisure and tourism can be promoted through scientific spatial planning. This study aims to provide services for urban land planning and policy-making by revealing the spatial distribution principles of leisure and tourism sites in tourist cities as represented by Xi'an. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has greatly affected the mobility of individuals everywhere. This has been especially true in China, where many restrictions, including lockdowns, have been widely applied. This paper discusses the impact of the pandemic on walkability, an important factor in promoting urban neighborhoods, in the main urban area of Xi'an, China, one of China's four great ancient capitals. Based on the street view data obtained before and after the pandemic, the paper quantitatively compares changes in specific components of selected streetscapes through a deep learning (DL) street view analysis. The aim is to identify the impact of the pandemic on walkability and determine the elements that influence increased walkability in Xi'an's historical area, using a walkability evaluation model based on a regression analysis involving three factors (streetscape components, walkability check scores, and street connectivity of space syntax for every image). Although Xi'an's urban structure did not change significantly, the pandemic has clearly impacted street vitality, especially in terms of reducing pedestrian flow and commercial value. Based on study results, the street environment has great room for improvement, especially in the city's historical blocks, by reconsidering safety measures to pedestrians and the important role of atmospheric aspects on the streets. [ABSTRACT FROM AUTHOR]

Based on an underground structure located at a soft loess site in Xi'an as the engineering background, this paper investigated a seismic response and damage model of subway stations at a soft loess site using a large-scale shaking table test, considering the different characteristics of ground motions. The quantitative analysis of the acceleration response and the seismic subsidence of the soft loess site were subjected to different earthquake excitations; based on the experimental results and the corresponding analysis, the development and distribution of seismic structural damage were studied, and the damage mechanism of underground structures in a soft loess area under a strong earthquake was explored. The results indicate that the peak accelerations of the site soil first remained unchanged then increased significantly along the soil height, and the amplification effect of the acceleration response was the most significant at the soil surface. The soft loess soil underwent significant subsidence, and the underground structure was raised compared to both sides of the cover soil; the collapsibility of the soft loess soil was sensitive to strong earthquakes with vertical components. The underground structures in soft loess suffered heavy damage, which rapidly entered the elastic–plastic stage. The composite effect of the collapsibility and vertical seismic excitation impaired the load-carrying capacity of the middle columns, and the strong horizontal seismic excitation enlarged the lateral force and accelerated structural damage development; the underground structure reached failure when plastic damage expended most of the middle columns and structural joints. These results are significant for the seismic design of underground structures in adverse soil conditions. [ABSTRACT FROM AUTHOR]

In recent years, the frequent occurrence of extreme emergencies represented by heavy rainfall has posed a significant impact on urban transportation networks and caused great inconvenience to people's production and life. This paper examines the impact of heavy rainfall on the urban transportation network in Xi'an's main urban area, models the map of urban road network in the main urban area of Xi'an by applying complex network theory, quantifies and analyzes the topological and geographic structural characteristics of the affected sections (interrupted by heavy rainfall) due to heavy rainfall, as well as the impact of heavy rainfall on the functional indexes of the road network such as access efficiency and accessibility, and, finally, analyzes its formation causes and proposes targeted management countermeasures. The findings of this study serve as a valuable reference for enhancing urban traffic emergency management capabilities and fostering sustainable urban development. [ABSTRACT FROM AUTHOR]

There is a causal interaction between urban rail passenger flow and the station-built environment. Analyzing the implicit relationship can help clarify rail transit operations or improve the land use planning of the station. However, to characterize the built environment around the station area, existing literature generally adopts classification factors in broad categories with strong subjectivity, and the research results are often shown to have case-specific applicability. Taking 154 stations on 8 rail transit lines in Xi'an, China, as an example, this paper uses the data sources of multiple open platforms, such as web map spatial data, mobile phone data, and price data on house purchasing and renting, then combines urban land classification in the China Urban Land Classification and Planning and Construction La1d Standard to classify the land use in the station area using structural hierarchy. On the basis of extracting fine-grained factors of the built environment, a semi-parametric Geographically Weighted Poisson Regression (sGWPR) model is used to analyze the correlation and influence between the variation of passenger flow and environmental factors. The results show that the area of Class II residential land (called R2) is the basis for generating passenger flow demand during morning and evening peak periods; The connection intensity between rail transit station area and bus services has a significant impact on commuters' utilization level of urban rail transit. Furthermore, two scenarios in practical applications will be provided as guidance according to the research results. This study provides a general analytical framework using urban multi-source data to study the internal relationship and impact between the built environment of urban rail transit stations and passenger flow demand. [ABSTRACT FROM AUTHOR]

The urban ecological environment is crucial to the quality of life of residents and the sustainable development of the region, and the assessment and prediction of the ecological environment quality can provide a scientific guidance for ecological environment management and improvement. We proposed a novel approach to assess and simulate the urban ecological environment quality using the Geographic Information System Ecological Index (GISEI). First, we calculated the remote sensing ecological index (RSEI) for Xi'an in 2020. Second, we selected land use data, mean annual temperature, and mean annual relative humidity as ecological indicators. We regressed these indicators on the RSEI to obtain the GISEI of Xi'an in 2020. Finally, we simulated the GISEI of Xi'an in 2030 by predicting the ecological indicators and analyzed the changes in the ecological environment quality. The results of the study show that the ecological environment quality in Xi'an in 2020 is better overall. By 2030, most of the ecological environment quality in Xi'an will be worse, and the proportion of the excellent area will decrease from 42.8% to 3.8%. The more serious ecological degradation is mainly located in the regions bordering the Qinling Mountains and the Guanzhong Plain, and the ecological environment quality in most areas of the Qinling Mountains will deteriorate from excellent to good. [ABSTRACT FROM AUTHOR]

In this paper, L-band sounding and surface observation data are used to calculate the boundary layer height (BLH) and evaluated CMA (China Metrological Administration Numerical Forecast System) and ERA5 in Xi'an for 2017–2021 using the Richardson (Ri) and Nozaki methods. For different PM2.5 pollution levels, the correlation between the vertical profile of meteorological factors and BLH is explored. There is a certain negative correlation between BLH and PM2.5 concentration. The BLH mean values of Nozaki, Ri, ERA5, and CMA from high to low are ~980 m, ~640 m, ~410 m, and ~240 m, respectively. The highest correlation is between ERA5 and CMA BLH with r2 > 0.85 for all pollution processes, while it between other methods is significantly lower (r2 < 0.58). The observational BLH is generally higher than the model results. Nozaki has a good adaptability on the light pollution, while Ri is more applicable to the stable boundary layer. In moderate and higher pollution, the ERA5 has a slightly better performance than CMA in BLH, while in light pollution there is a significant underestimation for both. Overall, the correlation between any two BLH methods gradually increases with increasing pollution level. In this study, there is about ~30% probability of polluted weather when BLH < 200 m and only <7% probability when BLH > 2000 m. It is difficult to simulate the neutral boundary layer and inversion processes for CMA and ERA5, but ERA5 has higher forecasting skills than CMA. This study can provide the data and theoretical support for the development of haze numerical forecast. [ABSTRACT FROM AUTHOR]

In the world, with the continuous development of modern society and the acceleration of urbanization, the problem of air pollution is becoming increasingly salient. Methods for predicting the air quality grade and determining the necessary governance are at present most urgent problems waiting to be solved by human beings. In recent years, more and more machine-learning-based methods have been used to solve the air quality prediction problem. However, the uncertainty of environmental changes and the difficulty of precisely predicting quantitative values seriously influence prediction results. In this paper, the proposed air pollutant quality grade prediction method based on a hyperparameter-optimization-inspired long short-term memory (LSTM) network provides two advantages. Firstly, the definition of air quality grade is introduced in the air quality prediction task, which turns a fitting problem into a classification problem and makes the complex problem simple; secondly, the hunter–prey optimization algorithm is used to optimize the hyperparameters of the LSTM structure to obtain the optimal network structure adaptively determined through the use of input data, which can include more generalization abilities. The experimental results from three real Xi'an air quality datasets display the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The wind environment in residential areas can exert a direct or indirect influence on the spread of epidemics, with some scholars paying particular attention to the epidemic prevention and control of residential areas from the perspective of wind environments. As a result, it is urgent to re-examine the epidemic prevention response of residential spaces. Taking high-rise residential areas in Xi'an as an example, the article defines the air flow field area based on on-site wind environment measurements, crowd behavior annotation, and CFD simulation. Using the double-effect superposition of crowd behavior and risk space, the paper undertook a multiple identification strategy of epidemic prevention space. The identification methods and management and control strategies of epidemic prevention in high-rise residential areas are proposed. Additionally, the living environment of residential areas is optimized, and a healthy residential space is created. The transformation from concept and calls for action to space implementation is made to provide a reference for improving the space management and control capabilities in high-rise residential areas in China. The results of this study can be used as a guideline for future residential planning and design from the perspective of preventing airborne diseases. [ABSTRACT FROM AUTHOR]

There is limited evidence concerning the association between air pollution and different outpatient visits in moderately polluted areas. This paper investigates the effects of moderate-level air pollution on outpatient visits associated with six categories of clinic department. We analyzed a total of 1,340,791 outpatient visits for the pediatric, respiratory, ear-nose-throat (ENT), cardiovascular, ophthalmology, and orthopedics departments from January 2016 to December 2018. A distributed lag nonlinear model was used to analyze the associations and was fitted and stratified by age and season (central heating season and nonheating season). We found SO 2 had the largest effect on pediatrics visits (RR = 1.105 (95%CI: 1.090, 1.121)). Meanwhile, PM 2.5 and SO 2 had greater effects on ENT visits for people under 50 years old. The results showed a strong association between O 3 and cardiovascular outpatient visits in the nonheating season (RR = 1.273, 95% CI: 1.189,1.358). The results showed every 10 μ g / m 3 increase in SO 2 was associated with a lower number of respiratory outpatient visits. Significant different associations were observed in PM 2.5 , NO 2 , CO, and O 3 on ophthalmology visits between the heating and nonheating seasons. Although no significant association has been found in existing studies, our findings showed PM 2.5 and NO 2 were significantly related to orthopedic outpatient visits for people under 60 (RR = 1.063 (95%CI: 1.032, 1.095), RR = 1.055 (95%CI: 1.011, 1.101)). This study also found that the effect-level concentrations of air pollutants for some clinic departments were lower than the national standards, which means that people should also pay more attention when the air quality is normal. [ABSTRACT FROM AUTHOR]

To improve urban seismic resilience, a reasonable seismic retrofitting scheme for buildings is required. Urban cities contain a large number of buildings, making it challenging to precisely assess the seismic retrofitting benefits of each one. This paper proposes a cost–benefit assessment framework that takes into account seismic risk, seismic damage, retrofit costs, economic losses, and cost–benefit analyses for the city-scale seismic retrofitting of buildings. The proposed framework adopts readily available building parameters, including the number of stories, construction year, total height, structural type, floor area, and response spectrum for structural design. It makes use of empirical seismic retrofitting models and a newly developed story-level seismic loss assessment method combining the physical mechanism and empirical loss ratios. For city-scale cost–benefit analysis, the framework can strike a good balance between data accessibility, computational workload, level of result details, and result accuracy. It can adapt nimbly to earthquake-induced indirect losses and budgetary constraints on retrofitting. The analysis of 98,618 buildings in Xi'an city, China, is carried out. The findings indicate that, when potential indirect economic loss ratios of buildings are neglected, the retrofitting benefits of unreinforced masonry and old buildings are the most significant. [ABSTRACT FROM AUTHOR]

Non-motorized vehicles have become one of the most commonly used means of transportation for people due to their advantages of low carbon, environmental protection, convenience and safety. Frequent interaction among non-motorized vehicle users in the shared space will bring security risks to their movement. Therefore, it is necessary to adopt appropriate means to evaluate the traffic efficiency and safety of non-motorized vehicle users in the passage, and using a micro model to conduct simulation evaluation is one of the effective methods. However, some existing micro simulation models oversimplify the behavior of non-motorized vehicle users, and cannot reproduce the dynamic interaction process between them. This paper proposes a modified social force model to simulate the dynamic interaction behaviors between non-motorized vehicle users on the road. Based on the social force model, a new behavioral force is introduced to reflect the three dynamic interaction behaviors of non motor vehicle users, namely, free movement, following and overtaking. Non-motorized vehicle users choose which behavior is determined by the introduced decision model. In this way, the rule-based behavior decision model is combined with the force based method to simulate the movement of non-motorized vehicles on the road. The modified model is calibrated using 1534 non-motorized vehicle trajectories collected from a road in Xi'an, Shaanxi, China. The validity of the model is verified by analyzing the speed distribution and decision-making process of non-motorized vehicles, and comparing the simulation results of different models. The effects of the number of bicycles and the speed of electric vehicles on the flow of non-motorized vehicles are simulated and analyzed by using the calibrated model. The relevant results can provide a basis for urban management and road design. [ABSTRACT FROM AUTHOR]

In the age of the digital economy, the data center is the most crucial piece of infrastructure. The issue of the excessive power consumption of a data center's cooling system needs to be addressed as the national objective of "peak carbon and carbon neutrality" is increasingly promoted. In this study, a microchannel-separated heat pipe-cooling system with evaporative condensation is introduced. The system may switch between three modes of operation in response to changes in outdoor air quality parameters, thereby maximizing the utilization of natural cooling sources while lowering data centers' cooling costs. The purpose of this paper is to analyze the energy-saving potential of the hybrid system through experimental tests. The results show that 114.4% is the ideal liquid-loading rate for the heat pipe system. Under working conditions in Xi'an, the annual operating hours of the three modes accounted for 47.2%, 6.1%, and 46.7%. The hybrid cooling system may save 62.04% of the energy used annually compared to the standard cooling system and the cooling system in the server room thanks to its yearly average COP of 9.43. [ABSTRACT FROM AUTHOR]

One of the primary aims of China's territory spatial planning is to control the urban sprawl of local municipals and prevent regional competition and the negative consequences on the environment—which emphasizes the top-down spatial regulation. Indeed, the traditional cellular automaton (CA) model still has limitations when applied to the whole administration area since it may ignore the differences among cities and towns. Thus, this paper proposed a CM-CA (clustering, multi-level logit regression, integrated with cellular automaton) framework to simulate urban growth boundaries for cities and towns simultaneously. The significant novelty of this framework is to integrate several urban growth modes for all cities and towns. We applied our approach to the city of Xi'an, China, and the results showed satisfactory simulation accuracy of a CM-CA model for multiple cities and towns, and the clusters' effects contributed 74% of the land change variance. Our study provides technical support for urban growth boundary delineation in China's spatial planning. [ABSTRACT FROM AUTHOR]

During the different periods of a day, the imbalanced distribution of inbound ridership, that is related to land use, results in extreme flow, which makes metro management challenging. The causes of imbalanced passenger flow from the perspective of land use in metro station areas are studied in this paper. More specifically, based on site classification, the impact of land use, including the floor area ratio and gross floor area on passenger flow, was explored by using a multiple linear regression model. The results first indicate that the impact intensities of the floor area ratio on peak hourly flow were 0.41, 0.21, and 0.20 around business, residential, and mixed sites, respectively. Second, for the abovementioned sites, the types with the greatest impact intensities of gross floor area on peak hourly flow were commercial and business facilities (B), residential (R), as well as administration and public services (A), which were 0.73, 0.32, and 0.87, respectively. Finally, for the land-development-control schemes for business, residential, and mixed sites, the maximum values of the floor area ratio were roughly 7.2, 5.3, and 8.2, respectively. The results presented in this study provide guidance for land development in metro station areas and contribute to avoiding the emergence of extreme passenger flow. [ABSTRACT FROM AUTHOR]

There are multiple seismic fault zones near Xi'an in China, among which the Li Piedmont Fault has multiple slip surfaces. A 3D finite element dynamic Soil–Fault–Tunnel model was established based on the engineering background of the Xi'an Metro tunnel orthogonally crossing the Li Piedmont Fault. The input seismic loads used the Chi-Chi, El-Centro, and artificial seismic waves, and the latter was artificially synthesized based on seismic conditions and site conditions of actual engineering. The Chi-Chi seismic wave with larger PGV/PGA and wider acceleration-sensitive area is a near-field seismic wave, while the others are far-field seismic waves. The seismic loads were transformed into the equivalent nodal force on the boundary nodes of the model, and nonlinear dynamic calculation was carried out to obtain the longitudinal seismic response of the structure. The main results show that the fault amplifies the seismic response of the tunnel, and the tunnel at the position of the fault slip surfaces is more vulnerable to failure, especially near the slip surface between the hanging wall and the fault, where the maximum acceleration, soil pressure, and internal force of the tunnel structure occur. In addition, the seismic response of the tunnel and soil caused by near-field seismic motion is significantly stronger than that caused by far-field seismic motion. [ABSTRACT FROM AUTHOR]

In the context of frequent public emergencies, emergency logistics distribution is particularly critical, and because of the unique advantages of unmanned aerial vehicles (UAVs), the model of coordinated delivery of vehicles and UAVs is gradually becoming an essential form of emergency logistics distribution. However, the omission of start-up costs prevents the cost of UAV battery replacement and the sorting, assembly and verification of packages from being factored into the total cost. Furthermore, most existing models focus on route optimization and delivery cost, which cannot fully reflect the customer's desire for service satisfaction under emergency conditions. It is necessary to convert the unsatisfactory degree of time window into a penalty cost rather than a model constraint. Additionally, there is a lack of analysis on the mutual waiting cost between vehicles and UAVs when one of them is performing delivery tasks. Considering the effects of the time window, customer demand, maximum load capacity, and duration of distribution benefits, we propose a collaborative delivery path optimization model for vehicles and UAVs to minimize the total distribution cost. A genetic algorithm is used to obtain the model solution under the constraints of distribution subloops, distribution order, and take-off and landing nodes. To assess the efficacy of the vehicle and UAV collaborative delivery path optimization model, this paper employs a county-level district in Xi'an city as a pilot area for an emergency delivery. Compared with the vehicle-alone delivery model, the UAV-alone delivery model and vehicle-UAV collaborative delivery model, this model can significantly reduce the utilization of distribution vehicles while also significantly lowering the start-up cost, waiting cost and penalty cost. Thus, the model can effectively improve delivery timeliness and customer satisfaction. The total cost of this model is 39.2% less than that of the vehicle-alone delivery model and 16.5% less than that of the UAV-alone delivery model. Although its delivery cost is slightly higher than the vehicle-UAV collaborative delivery model, the reduction in the start-up cost and penalty cost decrease the overall cost of distribution by 11.8%. This suggests that to cut costs of all sizes and conserve half of the resources used by vehicles, employing the vehicle-UAV collaborative delivery model for emergency distribution is preferable. Moreover, the model integrating the start-up cost, penalty cost, waiting cost, etc., can more effectively express the requirements of timeliness for UAV delivery under emergency conditions. [ABSTRACT FROM AUTHOR]

The variability and inhomogeneity of solar energy limits the development of solar heating systems (SHS) in many fields. In order to improve the utilization efficiency of SHS, this paper takes three typical cities (Xi'an, Dunhuang, Lhasa) as the research object, studies the operation state of SHS in student dormitory buildings, and puts forward a corresponding optimization strategy. The research shows that the reduction of water supply temperature will improve the operation efficiency and energy saving effect of a spontaneous combustion heat pump and that there is an optimal volume of heat storage water tank (HSWT), which can make the energy saving effect of SHS run better. The optimization of the SHS shows the water supply temperature is 35 °C, and the optimal volume of HSWT is 15 m3 in the "Resource-general area (Ⅲ)" represented by Xi'an, 25 m3 in the "Resource-rich area (Ⅱ)" represented by Dunhuang, and 40 m3 in the "Resource-richer area (Ⅰ)" represented by Lhasa. With the increase in the abundance of solar energy resources in the region, the optimal volume of HSWT also increases. Meanwhile, the solar energy contribution rate of the three regions in descending order is 61.3% (Lhasa), 32.8% (Dunhuang), and 25.9% (Xi'an). After optimization, the contribution of SHS increased by about 5%. The research results will help improve the efficiency of SHS in cold areas of China and make the system more efficient and energy efficient during operation. [ABSTRACT FROM AUTHOR]

The uniformity of remolded loess samples prepared in the laboratory directly determines the reliability of various test results. While many tests have been designed to reflect the properties of undisturbed loess, there are obvious structural differences between remolded and undisturbed loess. Therefore, it is of great theoretical and practical significance to explore a non-destructive evaluation index of the uniformity and structure of loess samples for indoor geotechnical tests. In this study, the loess from the Malan loess section of the Chanhe River in Xi'an, China, was used as the experimental material to analyze the uniformity of remolded loess samples in terms of the stress distribution, stratification range, and sample variance. Based on the test results, the feasibility of using the air permeability coefficient as an index by which to evaluate the uniformity and structure of loess samples is investigated for the first time. The results demonstrate that when the overall height of the sample is fixed, the higher the designed dry density of the sample and the lower the air permeability of the sample. Moreover, when the designed dry density of the sample is constant, with the increase in the overall height of the sample, the range of the stratified dry density of the sample gradually decreases, as does the sample variance. The more uniform the sample, the greater the air permeability, and under the same conditions, the air permeability of remolded soil is lower than that of undisturbed loess. SEM images reveal that there is a considerable difference between the structures of undisturbed and remolded loess samples. Remolded loess is characterized by the greatly reduced effectiveness of cementation between skeleton particles, which causes its structure to be weaker than that of undisturbed loess. In this paper, a quantitative index of loess structure based on air permeability is proposed, and the test results show that the index can adequately reflect the loess structure. Due to its obvious advantages of non-destructiveness, high efficiency, economy, convenience, and high speed, it has a unique advantage for the evaluation of the uniformity and structure of remolded soil samples. [ABSTRACT FROM AUTHOR]

Urban regeneration is an important means for building sustainable cities and implementing China's high-quality development strategy. In this paper, a sustainable regeneration PSR (Pressure-State-Response) model was established, and a state-layer evaluation model was constructed based on the perspective of resettled residents' multidimensional welfare. Through questionnaire surveys with 210 centralized resettled households in Xi'an, China, the changes in the living conditions of resettled residents before and after the centralized resettlement were measured, the differentiation in individual changes were explored, and the sustainability of urban regeneration was evaluated, so as to optimize the sustainability of urban regeneration. The results show that, before and after urban regeneration, the changes at the state layer are not obvious on the whole. The sharp decline of social dimension welfare indicates that urban regeneration generates some new pressures while alleviating the imbalance of social development, and at the response layer, there is not sufficient attention to the residents' emotions at the social level. Changes in the state layer are different due to individual characteristics, but there is no matching differentiated response to maintain the stability of the state. The research results are of great significance for optimizing residents' welfare and solving the problems of sustainable regeneration from the perspective of humanistic welfare. [ABSTRACT FROM AUTHOR]

Air pollution is becoming a serious concern with the development of society and urban expansion, and predicting air quality is the most pressing problem for human beings. Recently, more and more machine-learning-based methods are being used to solve the air-quality-prediction problem, and gated recurrent units (GRUs) are a representative method because of their advantage for processing time-series data. However, in the same air-quality-prediction task, different researchers have always designed different structures of the GRU due to their different experiences. Data-adaptively designing a GRU structure has thus become a problem. In this paper, we propose an adaptive GRU to address this problem, and the adaptive GRU structures are determined by the dataset, which mainly contributes with three steps. Firstly, an encoding method for the GRU structure is proposed for representing the network structure in a fixed-length binary string; secondly, we define the reciprocal of the sum of the loss of each individual as the fitness function for the iteration computation; thirdly, the genetic algorithm is used for computing the data-adaptive GRU network structure, which can enhance the air-quality-prediction result. The experiment results from three real datasets in Xi'an show that the proposed method achieves better effectiveness in RMSE and SAMPE than the existing LSTM-, SVM-, and RNN-based methods. [ABSTRACT FROM AUTHOR]

Building height is one of the basic geographic information for planning and analysis in urban construction. It is still very challenging to estimate the accurate height of complex buildings from satellite images, especially for buildings with podium. This paper proposes a solution for building height estimation from GF-7 satellite images by using a roof contour constrained stereo matching algorithm and DSM (Digital Surface Model) based bottom elevation estimation. First, an object-oriented roof matching algorithm is proposed based on building contour to extract accurate building roof elevation from GF-7 stereo image, and DSM generated from the GF-7 stereo images is then used to obtain building bottom elevation. Second, roof contour constrained stereo matching is conducted between backward and forward image blocks, in which the difference of standard deviation maps is used for the similarity measure. To deal with the multi-height problem of podium buildings, the gray difference image is adopted to segment podium buildings, and re-matching is conducted to find out their actual heights. Third, the building height is obtained through the elevation difference between the building top and bottom, in which the evaluation of the building bottom is calculated according to the elevation histogram statistics of the building buffer in DSM. Finally, two GF-7 stereo satellite images, collected in Yingde, Guangzhou, and Xi'an, Shanxi, are used for performance evaluation. Besides, the aerial LiDAR point cloud is used for absolute accuracy evaluation. The results demonstrate that compared with other methods, our solution obviously improves the accuracy of height estimation of high-rise buildings. The MAE (Mean Absolute Error) of the estimated building heights in Yingde is 2.31 m, and the MAE of the estimated elevation of building top and bottom is approximately 1.57 m and 1.91 m, respectively. Then the RMSE (Root Mean Square Error) of building top and bottom is 2.01 m and 2.57 m. As for the Xi'an dataset with 7 buildings with podium out of 40 buildings, the MAE of the estimated building height is 1.69 m and the RMSE is 2.34 m. The proposed method can be an effective solution for building height extraction from GF-7 satellite images. [ABSTRACT FROM AUTHOR]

With the tourism industry continuing to boom, the importance of tourism mascots in promoting and publicizing tourism destinations is becoming increasingly prominent. Three core dimensions, market trend, appearance design, and audience feedback, are numerically investigated for deeply iterating tourism mascot design. Further, a subjective and objective evaluation weighting model based on the hierarchical analysis method (AHP) and entropy weighting method is proposed, aiming to utilize the advantages of these methods and ensure the entireness and correctness of results. Taking the mascots of six famous tourist attractions in Xi'an as an example, the feasibility and effectiveness of the evaluation model are verified. Data analysis and modeling results confirm that the three core evaluation indexes of scalability, innovation, and recommendation should be focused on in the design of tourism mascots in the three dimensions of market trends, appearance design, and audience feedback. The evaluation index scores are 0.1235, 0.1170, and 0.1123, respectively, which further illustrates the priority of mascot design. The evaluation model constructed by the research provides decision-makers with a comprehensive evaluation tool from the perspective of tourist experience, and also effectively assists the optimization process of mascot design. In addition, the model has good versatility and adaptability in structural design and evaluation logic and can be widely used in the optimization and evaluation research of brand mascots. [ABSTRACT FROM AUTHOR]

As a catalyst for urban landscape transformation, the reuse of heritage sites plays a pivotal role in shaping contemporary urban spaces and influencing socio-economic development. However, this phenomenon is not without controversy, particularly regarding the quality of preservation and the potential risks associated with over-commodification. Consequently, there has been an increasing research focus on reconciling these conflicting aspects. This study employs a multi-value interpretation framework to delve into the reuse of heritage sites in the urban area of Xi'an within the broader context of China's urbanization. Utilizing a comparative case study method, this research specifically examines the burgeoning phenomenon of heritage parks. This exploration sheds light on how the reuse of heritage intertwines with urbanization processes, by taking into account environmental, economic, social, and cultural values. The findings suggest that a multi-value interpretation framework is crucial to address the limitations of the current heritagization. Heritage sites in Xi'an have been integrated into the urban transformation process through heritage conservation and the production of new heritage spaces. However, the evolving multi-value evaluation of these heritage sites continues to influence the city's interpretation of its significant and fading past in planning. This study highlights the dynamic nature of heritage sites in the urban context and underscores the need for nuanced approaches to balance heritage preservation with the evolving demands of contemporary urban development. [ABSTRACT FROM AUTHOR]

Metro transit construction has begun to develop rapidly in northwest China because of the acceleration of urbanization. Accordingly, metro depots are also regarded as an essential auxiliary facility for stopping, operation, and maintenance of trains. Meanwhile, many commercial buildings are constructed over metro depots to improve the utilization rate of land due to the increasingly scarce urban land resources, known as transit-oriented development (TOD). These buildings have a large covered area and transfer concentrated loads to the bases. Therefore, pile bases under metro depots have the bearing characteristics of undertaking large concentrated loads, while lesser loads are placed on the soil between the adjacent pile bases. Additionally, the main ground in northwest China is collapsible loess, so the collapsibility should also be considered. Based on the above background, this research performed static loading tests with and without immersion in a reduced scale of adjacent pile bases under a metro depot in Xi'an. The remolding process of natural loess could destroy its structure and the anisotropy of natural loess could also affect the test results. Therefore, four kinds of artificial collapsible loess with different mass ratios of barite powder, kaolin, river sand, cement, industrial salt, and calcium oxide were made by the free-drop method. This method could make the artificial loess simulate the structure of natural loess reasonably. Then, the artificial loess with the most similar properties to intact loess was selected by comparison. Finally, static loading tests with this artificial loess were implemented. The results showed that the ultimate bearing capacity was 4.5 kN. At the same time, the axial force decreased along depth, since the pile shaft friction was positive, and the load sharing ratio of pile tip force increased to 0.58 when the load exceeded 4.5 kN in the situation without immersion; the settlement of pile bases increased significantly after immersion, while the negative shaft friction occurred at the depth of −8 cm~−35 cm, and the load sharing ratio of pile tip force reached 0.92. [ABSTRACT FROM AUTHOR]

The present study aims to examine the process through which empowering leadership shapes employees' work engagement and in-role performance by facilitating job-crafting behaviors, specifically seeking resources, seeking challenges, and reducing demands. Based on the extensive data from 733 Chinese employees across various organizations located predominantly in Chongqing and Xi'an, China, we carried out different types of statistical analysis such as confirmatory factor analysis (CFA) and structural equation modeling (SEM) to examine the relationships among empowering leadership, specific job-crafting behaviors, work engagement and in-role performance, test our hypothesis and our conceptual model. The results from structural equation modeling (SEM) suggested that empowering leadership was positively related to employees' work engagement and in-role performance; empowering leadership was positively related to employees' job crafting (seeking resources, seeking challenges and reducing demands); seeking resources, seeking challenges and reducing demands were positively related to in-role performance, and seeking challenges and reducing demands were positively related to work engagement. In the relationship between empowering leadership and in-role performance, seeking resources serves as a mediating factor. Similarly, seeking challenges mediates the association between empowering leadership and both work engagement and in-role performance. Furthermore, reducing demands mediates the links between empowering leadership and both work engagement and in-role performance. The implications of these findings are subsequently discussed. [ABSTRACT FROM AUTHOR]

In recent years, China's economy has experienced rapid development, and its cities have undergone rapid expansion; however, the development of cities in the northwest region has been relatively slow due to various geographical and economic constraints. Studying the urban expansion in these regions is of significant importance for regional planning and development. This study selected the provincial capitals of five underdeveloped provinces in northwestern China as the research sample and used Landsat TM/OLI remote-sensing imagery as the primary data, supplemented by Digital Elevation Model (DEM), meteorological, and socio-economic data, the study extracted urban impervious surfaces using the ENDISI and MNDWI indices. It analyzed the spatial and temporal characteristics of urban impervious surfaces from 1990 to 2020 using indicators such as urban expansion intensity, compactness and fractal dimension, centroid migration, and standard deviation ellipse. Furthermore, the study quantified the influencing factors using Geodetectors. The findings reveal the following: (1) From 1990 to 2020, impervious surfaces in the five cities continued to expand, with Xi'an experiencing the largest expansion area at 549.94 km2 and Xining the smallest at only 132.83 km2, with an expansion intensity of merely 2.99%. However, significant disparities existed in expansion intensity and area across different periods. (2) Overall, the compactness of the cities decreased by 47.6% while the overall fractal dimension increased by 2.85%, indicating a trend towards more dispersed and complex urban forms. (3) Expansion directions varied among the cities, with Xi'an and Urumqi expanding towards the northwest, Lanzhou towards the north, Yinchuan primarily towards the east, and Xining mainly towards the west. (4) Economic, demographic, and investment factors were identified as the primary influencers of urban expansion, exhibiting changes over different periods. Analyzing the similarities and differences in city development can offer valuable insights into urban construction and sustainable development in underdeveloped areas. [ABSTRACT FROM AUTHOR]

Street space plays a crucial role in human activity and social life, forming an essential component of a livable and sustainable built environment. Consequently, its quality has garnered significant attention from researchers, designers, and policymakers who aim to achieve precise assessments of street infrastructure and conditions. This study presents a multi-dimensional framework for evaluating street space, considering factors such as access frequency, environmental quality, and amenity richness. By utilizing city-level path planning data, street view imagery, point of interest data, and social media check-in data, this framework assesses each street and assigns scores across these dimensions. These scores facilitate a human-centered analysis of the disparities in street usage and quality. The aggregation of results by administrative regions supports effective policy formulation and implementation. Application of this framework in Xi'an, China, reveals that only 6.95% of frequently visited streets exhibit high environmental quality and functional richness. This study underscores the potential of leveraging public data for detailed street space assessments to inform urban renewal policies. [ABSTRACT FROM AUTHOR]

Due to the increase in environmental problems and air pollution during the heating period, it is important to promote clean heating in cold regions, thereby meeting the heating demand in a green manner. In order to allocate resources more effectively and facilitate the consumption of renewable energy, this paper designs an integrated heating system that incorporates geothermal energy into the framework of an integrated energy system of electricity, heating, and gas. An analysis of the environmental and economic benefits indicates that the system reduces pollutant emissions and decreases the cost of urban heating. Using an example of central heating of residential buildings in Xi'an, the paper conducts a scenario analysis based on the gas peak-shaving ratio and the ratio of geothermal heating loads to basic heating loads. The results demonstrate that the environmental and economic benefits of the integrated heating system are higher compared to central heating using coal-fired boilers. In addition, this paper conducts a sensitivity analysis of the heat source to the price factors and the load ratios. The results show that the operating costs of the integrated heating system are most sensitive to the natural gas price and the gas peak-shaving ratio. Therefore, an optimum natural gas peak-shaving ratio can be determined. [ABSTRACT FROM AUTHOR]

The rapid pace of urbanization and the increasing concentration of populations in urban areas have generated a substantial demand for architectural structures, resulting in a significant increase in building stock and continuous material flows that interact with the environment. This study emphasizes the importance of high-spatial-resolution mapping of residential building stock for effective urban-construction resource management, planning, and waste management. Focusing on Xi'an as a case study, the research develops a comprehensive framework for mapping urban residential building stock by integrating diverse data dimensions, including temporal, spatial, network, and multi-attribute aspects. The findings indicate that between 1990 and 2020, approximately 4758 residential communities were established in central Xi'an. The analysis of seven key residential construction materials revealed that the building stock escalated from 1.53 million tons to 731.12 million tons, with a steady spatial expansion of material distribution. The study attributes this growth to factors such as population increase, economic advancement, and policy initiatives, which, in turn, have driven the demand for residential building materials and reinforced the interdependence between urban expansion and residential construction development. Remarkably, from 1990 to 2020, the population surged by 2.1-fold, the economy by 66-fold, and the stock of residential building materials by 477-fold, indicating that the growth rate of material stock consistently outpaced that of both population and economic growth. Over the past three decades, the rapid expansion of residential buildings has led to the encroachment of urban ecological spaces by concrete structures. The methodology proposed in this study for quantifying building material offers valuable insights for policymakers and urban and environmental planners to foster responsible resource consumption and supports component-level circularity in the built environment. [ABSTRACT FROM AUTHOR]

The traditional method for extracting the heights of urban buildings involves utilizing dense matching algorithms on stereo images to generate a digital surface model (DSM). However, for urban buildings, the disparity discontinuity issue that troubles the dense matching algorithm makes the elevations of high-rise buildings and the surrounding areas inaccurate. The occlusion caused by trees in greenbelts makes it difficult to accurately extract the ground elevation around the building. To tackle these problems, a method for building height extraction from Gaofen-7 (GF-7) stereo images enhanced by contour matching is presented. Firstly, a contour matching algorithm was proposed to extract accurate building roof elevation from GF-7 images. Secondly, a ground filtering algorithm was employed on the DSM to generate a digital elevation model (DEM), and ground elevation can be extracted from this DEM. The difference between the rooftop elevation and the ground elevation represents the building height. The presented method was verified in Yingde, Guangzhou, Guangdong Province, and Xi'an, Shaanxi Province. The experimental results demonstrate that our proposed method outperforms existing methods in building height extraction concerning accuracy. [ABSTRACT FROM AUTHOR]

Natural lighting in office buildings is often affected by excessive solar heat gain and discomfort glare, and the transitional seasons are no exception. Therefore, addressing the issue of natural lighting in buildings has always been a challenge in developing shading control strategies. This study designed a model-based calculation method for shading blind control indicators. The method combines existing physical models for sky conditions, solar radiation, heat transfer, thermal comfort, glare, and illuminance calculations and incorporates modifications and additions. Additionally, an equivalent energy-saving model for shading was established. A shading blind control strategy balancing indoor light and the thermal environment with energy savings during transitional seasons was proposed. In transitional seasons, this method can eliminate 100% of glare, reduce discomfort illuminance duration by 81.3% and heat discomfort duration by 87.5% and save 81.3% of lighting energy consumption when air conditioning is used. By comparing the simulation results of an office building in Xi'an with the results obtained from this calculation method, the absolute error percentage was found to be 6.83%, verifying the reliability of the calculation method. Finally, the proposed control strategy was compared with common methods such as no blinds, end-angle control, and fixed-angle control to evaluate its performance in terms of daylighting, thermal comfort, and energy savings. The results showed that the control strategy proposed in this study has significant advantages with respect to various performance indicators. [ABSTRACT FROM AUTHOR]

Predicting metro traffic flow is crucial for efficient urban planning and transit management. It enables cities to optimize resource allocation, reduce congestion, and enhance the overall commuter experience in rapidly urbanizing environments. Nevertheless, metro flow prediction is challenging due to the intricate spatial–temporal relationships inherent in the data and the varying influence of external factors. To model spatial–temporal correlations considering external factors, a novel spatial–temporal deep learning framework is proposed in this study. Firstly, mutual information is utilized to select the highly corrected stations of the examined station. Compared with the traditional correlation calculation methods, mutual information is particularly advantageous for analyzing nonlinear metro flow data. Secondly, metro flow data reflecting the historical trends from different time granularities are incorporated. Additionally, the external factor data that influence the metro flow are also considered. Finally, these multiple sources and dimensions of data are combined and fed into the deep neural network to capture the complex correlations of multi-dimensional data. Sufficient experiments are designed and conducted on the real dataset collected from Xi'an subway to verify the effectiveness of the proposed model. Experimental results are comprehensively analyzed according to the POI information around the subway station. [ABSTRACT FROM AUTHOR]

Exploring the correlation of the built environment with metro ridership is vital for fostering sustainable urban growth. Although the research conducted in the past has explored how ridership is nonlinearly influenced by the built environment, less research has focused on the spatiotemporal ramifications of these nonlinear effects. In this study, density, diversity, distance, destination, and design parameters are utilized to depict the "5D" traits of the built environment, while Shapley Additive Explanations with eXtreme Gradient Boosting (XGBoost-SHAP) are adopted to uncover the spatial and temporal features concerning the nonlinear relationship of the built environment with ridership for metro stations located in Xi'an. We conducted a K-means clustering analysis to detect different site clusters by utilizing local SHAP coefficients. The results show that (1) built environment variables significantly influence metro ridership in a nonlinear manner at different periods and thresholds, with the POI facility density being the most critical variable and the other variables demonstrating time-driven effects; (2) the variables of population density and parking lot density exhibit spatial impact heterogeneity, while the number of parks and squares do not present a clear pattern; and (3) based on the clustering results, the metro stations are divided into four categories, and differentiated guidance strategies and planning objectives are proposed. Moreover, the current work offers a more developed insight into the spatiotemporal influence of built environments on metro travel in Xi'an, China, using nonlinear modeling, which has vital implications for coordinated urban–metro development. [ABSTRACT FROM AUTHOR]