City Scale Research Articles

Deciphering the Spatial Stickiness, Co-occurrence, and Co-change of Industries at the Scale of City

This paper analyzes the location of industries in two metropolitan cities to investigate how firms are spatially distributed, and identify the prevailing trends in firm location choice. By defining a “Region Index” metric, we show how industries have concentrated in or diffused from the regions-of-interest over time. We apply this metric to the Central Area (CA) of Singapore and the London Region to decipher the relative tendency of industries to locate at CA as well as London. To analyze the spatial co-location of industries, we constructed a community network, which reveals subtle spatial relationships between firms. Extending this approach temporally to create a co-change network, we deduce the occurrences of industries in Singapore and London that move into or out of a spatial region synchronously. Based on this approach, we elucidate firm types that not only co-change but also co-occur in space and remain within a region-of-interest. Overall, we observe certain common and contrasting patterns of industry movements in the context of Singapore and London through the analysis. “Other Activities Auxiliary to Financial Services” is found to have the consistent tendency of diffusing out of CA and London throughout the period of study. Conversely, opposite movement patterns are observed where we see the proclivity of IT and digital service firms to locate in London but relocate out of CA, while the Media, Financial Services, and Life Insurance subsectors tend to diffuse out of London but concentrate in the CA of Singapore.

Assessing Spatial Heterogeneity in Urban Park Vitality for a Sustainable Built Environment: A Case Study of Changsha

In the realm of sustainable city development, evaluating the spatial vitality of urban green spaces (UGS) has become increasingly pivotal for assessing public space quality. This study delves into the spatial heterogeneity of park vitality across diverse urban landscapes at a city scale, addressing limitations inherent in conventional approaches to understanding the dynamics of park vitality. Leveraging geotagged check-in data from 65 parks in the study case of Changsha City, a quantitative analysis was undertaken to assess spatial vitality. The investigation incorporated data concerning internal and external factors influencing park vitality, employing the Multi-scale Geographically Weighted Regression (MGWR) model to dissect nuanced spatial heterogeneity. The research uncovers notable spatial discrepancies in factors influencing park vitality across diverse urban areas, emphasizing the reliance on adjacent residential communities and internal commercial amenities provision. These dependencies correspond with economic development differences among urban locales, revealing distinct geographic trends. This study has a novel perspective and methodology for investigating urban park vitality, providing significant insights for urban green space planning and management. It emphasizes the necessity of acknowledging spatial diversity in urban park planning and design by incorporating the distinct socio-economic characteristics of each urban zone, which is crucial for both urban planners and policymakers.

A Novel Modeling Approach to Quantify the Flood Resilience of Cities

In recent years, large-scale flood events have occurred more frequently, and the concept of resilience has become a prevalent approach to managing flood risk in many regions. This has led to an increased interest in how to effectively measure a city’s flood resilience levels. This study proposes a novel modeling approach to quantify urban flood resilience by developing D-number theory and analytical hierarchy process (AHP) models, which are applied to three cities in China using the VIse Kriterijumski Optimizacioni Racun (VIKOR) method. The findings reveal that Hefei City has the most effective level of flood resilience, Hangzhou City was ranked second, while Zhengzhou City has the least effective level of flood resilience. This study provides a new scientific basis on how to quantify flood resilience at the city scale and provides a useful reference for these three specific cities. The methods and approaches developed in this study have the potential to be applied to other cities and in the related aspects of disaster prevention, recovery, and reconstruction.

The Spatiotemporal Variation Characteristics and Influencing Factors of Green Vegetation in China

Green vegetation is one of the main objects of ecological environment restoration and protection, objectively reflecting the quality of regional ecological environments. Studying its spatial distribution characteristics is of great significance to the formulation of ecological environment restoration policies. Based on data on urban green vegetation in China from 2000 to 2022, this study attempts to analyze the destruction and protection patterns of urban green vegetation in China from the perspectives of total changes in green vegetation contraction and growth and spatial evolution characteristics and trends, and it explores the driving factors affecting the change in green vegetation area. The results show the following: (1) Green vegetation growth and contraction occurred alternately in China from 2000 to 2022. Vegetation contraction showed a “point–line–plane” evolution pattern, forming a contraction stage of point-like aggregation, linear series, and planar spread. Vegetation growth has always presented a frontal pattern. (2) The growth and contraction of green vegetation in China showed a north–south differentiation phenomenon. The vegetation contraction phenomenon spread in the Central Plains urban agglomeration and its surrounding areas and showed an expanding trend. The growth trend is obviously moving northward, mainly concentrated in Inner Mongolia, Ningxia, Gansu, Xinjiang, and other northern provinces, which also coincides with the key ecological restoration policies in northern China in recent years. (3) City scale, economic level, population scale, agro-industrial structure, and water resources content have significant effects on the spatial distribution of green vegetation.

Street ballet in the context of population contraction: A case study of Dongda Street in Rugao City

Most existing studies on shrinking cities focus on identifying and characterizing population contraction at the city scale and lack an in-depth exploration of the mechanisms of population contraction and daily life scenarios at the street scale. To fill this gap, this study employed semi-structured interviews and participant observation to analyze the street vitality and mechanisms of operation of Dongda Street in Rugao County of Jiangsu Province in China. The study found the following. First, the interspersed urban renewal has allowed residents to retain their original lifestyles and time-space routines, and they continue to enact an endogenous street ballet. Second, new residents gradually develop new lifestyles and time-space routines in the streets, showcasing an exogenous street ballet. Third, both groups jointly perform hybrid street ballets in their daily lives through close public interactions. These findings suggest that while Dongda Street is an aging neighborhood, the survival of the original street pattern and old buildings has allowed the neighborhood to retain its historical flavor. Additionally, the moving in of creative industries and merchants injects new vitality into the neighborhood. These findings examine daily street life in the context of population contraction and help break the stereotypes of population contraction.

Analysis of the causes of spatial differences in urban hotel location satisfaction: the case of Wuhan, China

ABSTRACT Customers' hotel location evaluations are critical to hotel location decisions, future investment, visitor experience and urban tourism development. In this paper, spatial autocorrelation analysis, GeoDetection and geographically weighted models are used to explore the characteristics of the location satisfaction pattern of 1126 hotels in Wuhan and its causes.The findings suggest that there are obvious spatial clustering distribution characteristics of hotel location satisfaction in Wuhan. Distance from highway entrances/exit, scenic spot accessibility, and free parking services have the strongest positive influence on the spatial differentiation pattern of hotel location satisfaction, while hotel transportation services, the percentage of water area, and the number of universities have significant spatial differentiation characteristics on the influence of hotel location satisfaction. This study contributes to a better understanding of hotel location satisfaction pattern and its causes through multi-source data and spatial analysis techniques. The results of the study are of practical significance to the planning and development of urban hotels in Wuhan, as well as to other cities similar to Wuhan in terms of city scale, spatial layout of hotels, and tourism development.

Water sensitive urban design approach for flood prone area (Study case: Kauman Riverfront Area, Semarang)

Kauman Semarang Riverfront Area is the center of the trade and services area in Semarang, especially for traditional trade. This area is located between three ethnic villages and is adjacent to Kali Semarang, a river that has an important meaning and historical value for the city’s development. Kauman Area is located in Central Semarang District, Semarang City, and is within a 1 km radius of the Semarang Old Town, a tourist attraction in the cultural heritage field, which is known as the priority of socio-cultural development on the city and province scale. However, with this type of potential, Kauman Riverfront Area has a medium-high flooding threat. In 2021, the number of flood incidents was the highest within five years (88 incidents). This study aims to examine the WSUD approach for the study area that focuses on the urban water system to decrease flooding risk and its correlation with urban design elements. The chosen method for this research is a fragmental method that consists of four steps, which begin with collecting data until producing the WSUD component approach, which is likely to be implied. The results show that the WSUD components and water system for Kauman Riverfront Area to increase the stormwater infiltration and storage.

Tipologi Aplikasi Infrastruktur Hijau Skala Komunitas pada Kampung Kota di Indonesia

This paper addresses one of the knowledge gaps that exists in green infrastructure (GI) discourses, that is the lack of understanding on the application of GI at community scale. GI was first introduced as an alternative to address problems caused by rapid urbanisation. Recently, GI has become a crucial part of strategies to achieve sustainable development and therefore has been widely advocated for its environmental, social, and economic benefits. Although the concepts and benefits of green infrastructure have been widely discussed and recognized in the literature, much of the discussions on GI tend to revolve around its applications at the city and regional scales, while the application of small scale GI at the community level has not been much explored, despite the importance of multiscale principle in the application of GI. To address that issue, this study focuses on the application of small-scale GI at the community level. It employed a systematic review to analyse publications, including articles published in scientific journals and news on reliable mass media on the internet, regarding the application of small-scale GI in 23 Indonesian urban kampung. The study shows that in dense settlements like urban kampung, community scale GI emerges as an alternative solution to the lack of space for GI development. From the 23 cases analysed, GI is mostly intended to function as a mean for environmental conservation and to promote food security.

The Impact of Financing Constraints on the Efficiency of Investment and Construction: Evidence from Municipal Infrastructure in China

Imperfect external capital market and internal soft budget constraints are important reasons for the issue of enterprise financing constraints. This paper studies the impact of financing constraints and influencing factors of financing constraints in municipal infrastructure investment and construction for local governments by using the panel data from 2003 to 2018 in China. The results show that, first, there are great financing constraints in municipal infrastructure investment and construction for local government in China. Second, the increase of self-financing capacity and external financing capacity can reduce the level and uncertainty of financing constraints, thus improving the efficiency of municipal infrastructure investment and construction. Third, the expansion of the city scale may reduce the uncertainty of financing constraints, but improve the level of financing constraints thus reducing the efficiency of municipal infrastructure investment and construction.

Effects of autonomous driving on residential location choice behavior: A travel-based multitasking perspective

Fully autonomous vehicles (AVs) allow users to engage in multitasking behavior while traveling, potentially inducing longer travel because multitasking in AVs would generate a positive utility. Eventually, this may further induce residential relocation, as positive utility virtually reduces the value of time. Such influence may vary depending on whether the AV is used individually or with others (i.e., ride-sharing), as well as the type and amount of multitasking activities carried out in the vehicle. This study examines the influence of the type of AV (ride-sharing or individually used) and the type and amount of in-vehicle multitasking activities on residential location choice behavior through a pivoted stated preference survey. Residential location choice behavior is represented by a panel binary mixed logit model. The model estimation results indicate that the willingness to pay for monthly rent to shorten commuting time is significantly lower when individually used AVs are introduced, compared to non-AVs (i.e., existing automobiles) and ride-shared AVs. Hence, further urban sprawl could occur if individually used AVs become prevalent. Such negative impacts on urban form, however, would be substantially small when AV is introduced under the ride-sharing scheme. It was also found that individuals who can engage in more multitasking behavior in an AV will accept longer travel regardless of the type of AV (ride-sharing or individually used), while individuals who can hardly perform in-car activities tend to resist additional commuting travel time. Moreover, the impact of automated driving at the city scale was examined by running simulations of residential choice in Hiroshima City as a case study. The results suggest that multitasking behaviors in AVs would have modest impacts on urban structure.

Stochastic Models of Electricity Consumption

The article considers a stochastic model of electricity consumption based on the convolution theory. It is assumed that the processes of switching on and off energy consumption on a city scale depend on a large number of independent random factors and have the form of a normal probability distribution. The functions of switching on and off the load are presented, graphs are plotted. The comparison of the intelligent power supply system with the existing power supply system in the Russian Federation is carried out. The reasons for the slow introduction of smart grids in the Russian Federation are revealed. At the moment, smart grids are not very popular in the Russian Federation, while in the countries of the European Union, the USA and China, projects related to the development, production of components and the widespread introduction of smart grids are actively receiving state financial support. Thus, the European Union allocates more than a billion dollars annually for projects in the field of electric power and smart grids. These funds are allocated according to the European Green Deal strategy. At the same time, the State Grid Corporation of China has introduced the concept of the "Global Energy Internet", which, in accordance with the government's expectation, will stimulate the smart grid market in the country. As in other countries of the world, the US electric power industry is also facing problems related to rising utility prices, fluctuations in peak load and the need to reduce carbon dioxide emissions. The consequence of this was the adoption at the end of 2021 of an "infrastructure" law providing for large-scale investments in green energy projects.

A unified dataset for the city-scale traffic assignment model in 20 U.S. cities

City-scale traffic data, such as traffic flow, speed, and density on every road segment, are the foundation of modern urban research. However, accessing such data on a city scale is challenging due to the limited number of sensors and privacy concerns. Consequently, most of the existing traffic datasets are typically limited to small, specific urban areas with incomplete data types, hindering the research in urban studies, such as transportation, environment, and energy fields. It still lacks a city-scale traffic dataset with comprehensive data types and satisfactory quality that can be publicly available across cities. To address this issue, we propose a unified approach for producing city-scale traffic data using the classic traffic assignment model in transportation studies. Specifically, the inputs of our approach are sourced from open public databases, including road networks, traffic demand, and travel time. Then the approach outputs comprehensive and validated citywide traffic data on the entire road network. In this study, we apply the proposed approach to 20 cities in the United States, achieving an average correlation coefficient of 0.79 in average travel time and an average relative error of 5.16% and 10.47% in average travel speed when compared with the real-world data.

Achieving Carbon Mitigation with Economic Benefits through High-Resolution Analysis of Renewable Resource Integration in Global Coastal Cities.

Coastal regions, home to more than half of the global population and contributing over 50% to the global economy, possess vast renewable resources, such as seawater and solar energy. The effective utilization of these resources, through the seawater-cooled district cooling system (SWDCS), seawater toilet flushing (SWTF), and rooftop solar photovoltaic system (RTPV), has the potential to significantly reduce carbon emissions. However, implementing these technologies in different geographic contexts to achieve the desired carbon and economic outcomes at the city level lacks a clear roadmap. To address this challenge, we comprehensively analyzed 12 coastal megacities worldwide by integrating geospatial building data. Our study evaluated the potential energy savings, carbon mitigation, and levelized carbon abatement costs (LCACs) from a life cycle perspective. The results revealed that using seawater and solar energy within urban boundaries can reduce electricity consumption from 1 to 24% across these cities. The spatial distribution of the LCAC for seawater-based systems exhibited more variation compared to the RTPV. By applying specific LCAC thresholds ranging from 0 to 225 USD/tCO2e, all cities could achieve both carbon reductions and economic benefits. These thresholds resulted in up to 80 million tonnes of carbon emission reductions and 5 billion USD of economic benefits, respectively. Our study provides valuable insights into integrating renewable resource systems, enabling coastal cities to achieve carbon and economic advantages at the city scale simultaneously.

The seismic resilience-based methodology of regional building function recovery assessment

Regional assessment of the functional recovery time of urban buildings is critical for decision-making after an earthquake, both as a key indicator of seismic disaster risk and for evaluating urban resilience. However, existing studies are insufficient for assessing the functional recovery time of buildings at the city scale. To address this issue, this study proposes a new methodology for predicting the functional recovery time of an area. This approach comprehensively considers performance-based repair objectives, various damage states, and the affected building area. It offers two improvements over traditional methods based on the assumption of unlimited restoration resources within the disaster area. First, the method establishes a standard for categorizing damaged buildings into repairable and reconstructive buildings using the building damage level parameter. The existing moderate damage states are considered rough and are further divided into three detailed damage states. The distribution functions of the three new states relative to the existing moderate damage are derived from actual earthquake cases. Second, a new parameter, the reconstruction rate, which characterizes the rate of reconstruction time per unit area of a building, is proposed. The repair time per unit area of a house in a repairable state, i.e., the repair rate, is discounted based on this new parameter using the damage state as an indicator. To illustrate the methodology in more detail, we constructed an earthquake scenario for the northeastern margin of the Tibetan Plateau and then provided a detailed assessment of the postearthquake recovery time of Zhangye under the earthquake scenario. This study aims to provide valuable insights for the government to formulate appropriate predisaster prevention policies and rational postdisaster recovery and reconstruction.

Effects of the interplay between topology and function of an integrated urban development on patterns of user movement

With the advent of distributed multi-sensory networks of devices, vast troves of real-time data can be gathered about our interactions with the built environment. These rich data sets can be mined to achieve improved and informed data-driven designs of buildings, neighborhoods, and potentially entire cities. Among those, integrated developments have the peculiarity of combining multiple functions within a compact space and, as such, behave as microcosms of a city that can help address the problem of urban sprawl and density. However, a general lack of data and framework about integrated developments hinders our ability to test design hypotheses about the complex interplay between heterogeneity in both space and function. Here, we apply a data-driven approach to analyze the joint influence of topology and function on user movement within a state-of-the-art integrated development in Singapore. Specifically, we leverage the network representation of the building and use movement data collected from 51 individuals over a month. We show evidence of correlation (40%) between the spatial network features and human movement at the building level. We are also able to quantify the relationship between the functional and spatial components of the integrated development through user movement. Previous studies have shown a 60% or higher correlation between the topology and human movement at the city or country scales. Our moderate correlation, therefore, implies that more factors influencing user movement are at play. The heterogeneity in the spatial function introduced trips with diverse origins and destinations. A further data-driven analysis integrating origins and destinations reveals both qualitative and quantitative means of studying the relationship between the built environment and the processes that take place in them.

Nature on our doorstep: How do residents perceive urban parks vs. biodiverse areas?

The role of nature in enhancing urban well-being is well-established, but perceived naturalness may not always align with scientific definitions. Our study aimed to investigate whether areas selected for nature-related activities demonstrate increased biodiversity, offer diverse experiences, and integrate both social and ecological perspectives. We aimed to bridge the gap between perceived naturalness and objective ecological richness. Integrating social and environmental parameters, we considered both objective indicators, such as the presence of rare species, and subjective perspectives. Extensive geotagged surveys among 401 working-age Warsaw residents, coupled with field analyses, and biodiversity data collected for the scale of the whole city, allowed to juxtapose human perception with tangible ecological indicators. Our results revealed that only 14% of the locations identified by respondents as natural were associated with high biological diversity. In contrast, over 30% were in areas with low biological diversity, lacking rare species. Factors like presence of natural and semi-natural vegetation types, distance from buildings, population density, presence of water, noise, and extreme temperatures were found to be significant. We distinguished four types of natural areas: close to home, open grassland, high naturalness, and forested, reflecting different preferences and alternative choices when high-quality natural areas are not nearby. Most notably, urban parks emerged as key locations for nature contact, even though objective measures of biodiversity were often low. This underscores the need for a comprehensive understanding of how urban residents interact with and value natural spaces, bridging the gap between subjective experiences and objective ecological richness within the city's green areas. Our study highlights the complex interplay between the physical properties of urban green spaces, individual perceptions, and the ecological aesthetics influencing these interactions. In particular, the concept of perceived naturalness emerges as a critical factor, often contrasting with objective, quantifiable naturalness, and necessitating a nuanced approach in urban planning and public health contexts to cater to diverse needs and preferences of city dwellers.

Evaluating the Impact of Urban Digital Infrastructure on Land Use Efficiency Based on 279 Cities in China

The development and application of urban digital infrastructure can alter land use patterns and facilitate the aggregation of factors such as labor and capital, thereby influencing the land use efficiency in cities. Based on statistical data from 279 cities in China spanning from 2004 to 2019, this study employs fixed-effects and mediation models to analyze the impact of urban digital infrastructure on land use efficiency. The findings reveal that the construction of urban digital infrastructure significantly promotes the enhancement of land use efficiency, with technological innovation levels and industrial structural transformation serving as mediators between urban digital infrastructure and land use efficiency. The impact of urban digital infrastructure on land use efficiency exhibits heterogeneity across different city scales, urban tiers, geographic locations, and policy implementation batches. Its effects are more pronounced in larger-scale cities, higher-tier cities, those located in the central and western regions, and the first two batches of pilot cities. The research findings contribute to providing theoretical references and a decision-making basis for enhancing land use efficiency, advocating for increased investment in urban digital infrastructure construction, encouraging technological innovation levels, and facilitating the upgrading of industrial structural transformation.

Wilding cities for biodiversity and people: a transdisciplinary framework.

Accelerating urbanisation and associated lifestyle changes result in loss of biodiversity and diminished wellbeing of people through fewer direct interactions and experiences with nature. In this review, we propose the notion of urban wilding (the promotion of autonomous ecological processes that are independent of historical land-use conditions, with minimal direct human maintenance and planting interventions) and investigate its propensity to improve biodiversity and people-nature connections in cities. Through a large interdisciplinary synthesis, we explore the ecological mechanisms through which urban wilding can promote biodiversity in cities, investigate the attitudes and relations of city dwellers towards urban wild spaces, and discuss the integration of urban wilding into the fabric of cities and its governance. We show that favouring assembly spontaneity by reducing planting interventions, and functional spontaneity by limiting maintenance practices, can promote plant diversity and provide ecological resources for numerous organisms at habitat and city scales. These processes could reverse biotic homogenisation, but further studies are needed to understand the effects of wilding on invasive species and their consequences. From a socio-ecological perspective, the attitudes of city dwellers towards spontaneous vegetation are modulated by successional stages, with grassland and woodland stages preferred, but dense shrubby vegetation stages disliked. Wild spaces can diversify physical interactions with nature, and enrich multi-sensory, affective and cognitive experiences of nature in cities. However, some aspects of wild spaces can cause anxiety, feeling unsafe, and the perception of abandonment. These negative attitudes could be mitigated by subtle design and maintenance interventions. While nature has long been thought of as ornamental and instrumental in cities, urban wilding could help to develop relational and intrinsic values of nature in the fabric of cities. Wildness and its singular aesthetics should be combined with cultural norms, resident uses and urban functions to plan and design urban spatial configurations promoting human-non-human cohabitation. For urban wilding to be socially just and adapted to the needs of residents, its implementation should be backed by inclusive governance opening up discussion forums to residents and urban workers. Scientists can support these changes by collaborating with urban actors to design and experiment with new wild spaces promoting biodiversity and wellbeing of people in cities.

High spatial-resolved source-specific exposure and risk in the city scale: Influence of spatial interrelationship between PM2.5 sources and population on exposure

Research on High Spatial-Resolved Source-Specific Exposure and Risk (HSRSSER) was conducted based on multiple-year, multiple-site synchronous measurement of PM2.5-bound (particulate matter with aerodynamic diameter<2.5 μm) toxic components in a Chinese megacity. The developed HSRSSER model combined the Positive Matrix Factorization (PMF) and Land Use Regression (LUR) to predict high spatial-resolved source contributions, and estimated the source-specific exposure and risk by personal activity time- and population-weighting. A total of 287 PM2.5 samples were collected at ten sites in 2018–2020, and toxic species including heavy metals (HMs), polycyclic aromatic hydrocarbons (PAHs) and organophosphate esters (OPEs) were analyzed. The percentage non-cancer risk were in the order of traffic emission (48 %) > industrial emission (22 %) > coal combustion (12 %) > waste incineration (11 %) > resuspend dust (7 %) > OPE-related products (0 %) ≈ secondary particles (0 %). Similar orders were observed in cancer risk. For traffic emission, due to its higher source contributions and large population in central area, non-cancer and cancer risk fraction increased from 23 % to 48 % and 20 % to 46 % after exposure estimation; while for industrial emission, higher source contributions but small population in suburb area decreased the percentage non-cancer and cancer risk from 38 % to 22 % and 39 % to 24 %, respectively.

Measuring acceptance of tradable credit scheme and its effect on behavioral intention through theory of planned behavior

Public support is crucial for the successful implementation of congestion charging schemes. The Tradable Credits Scheme (TCS), a novel concept built upon the cap-and-trade principle, is believed to possess qualities of effectiveness and fairness that should lead to greater public approval. This study investigates the level of acceptance of TCS among the public and its impact on the propensity to shift travel modes in the TCS framework. In this study, we used the Theory of Planned Behavior, encompassing components such as attitudes toward TCS, subjective norms and perceived behavioral control and assessed the perceived effectiveness and equity of TCS. Data were acquired through an online survey involving 544 participants in China. The findings indicate that public acceptance of TCS is significantly influenced by subjective norms and attitudes toward TCS. In turn, behavioral intention is indirectly shaped by these factors, with acceptance serving as a mediator. Perceived behavioral control exerts a direct influence on behavioral intention, while perceived effectiveness and equity positively impact both the acceptance of TCS and behavioral intention. Moreover, latent profile analysis was used to determine the influence of various factors on TCS acceptance, following which we categorized the participants into four distinct groups. The results show that age, city scale, income, holding a driving license or not, car ownership, necessity through congested areas, main transportation modes, and the frequency of using different travel modes all affect the distribution of individuals in support or rejection groups Notably, over one-third of participants express TCS acceptance, with most holding a neutral stance, indicative of TCS's potential for public acceptance with effective guidance and comprehensive explanation. In summary, this research provides novel insights into the multifaceted factors that influence individuals' acceptance of TCS and offers valuable assistance in promoting an innovative traffic demand management policy.