Search Results (68)

Territorial tourism has brought new development opportunities for historic and cultural neighborhoods. However, an insufficient understanding of the spatial distribution and influencing mechanisms of neighborhood vitality continues to constrain effective revitalization strategies. This study takes the Shuitingmen Historical and Cultural Neighborhood in Quzhou, China, as a case study and develops a multi-dimensional vitality evaluation framework incorporating point-of-interest (POI) data, location-based service (LBS) heatmaps, street network data, historical resources, and environmental perception indicators. The Analytic Hierarchy Process (AHP) is applied to assign indicator weights and calculate composite vitality scores across 19 streets. The results reveal that (1) comprehensive evaluation corrects the bias of single indicators and highlights the value of integrated assessment; (2) vitality is higher on rest days than on weekdays, with clear temporal patterns and two types of daily fluctuation trends—similar and differential; and (3) vitality levels are spatially uneven, with higher vitality in central and western areas and lower performance in the southeast, often related to low accessibility and functional monotony. This study confirms a strong positive correlation between street vitality and objective spatial factors, offering strategic insights for the micro-scale renewal and sustainable revitalization of historic neighborhoods. Full article

Unmanned aerial vehicles (UAVs), owing to their flexible coverage expansion and dynamic adjustment capabilities, hold significant application potential across various fields. With the emergence of urban low-altitude air traffic dominated by UAVs, the integrated aviation information network combining UAVs and manned aircraft has evolved into a complex space–air–ground integrated Internet of Things (IoT) system. The application of 5G/6G network technologies, such as cloud computing, network function virtualization (NFV), and edge computing, has enhanced the flexibility of air traffic services based on service function chains (SFCs), while simultaneously expanding the network attack surface. Compared to traditional networks, the aviation information network integrating UAVs exhibits greater heterogeneity and demands higher service reliability. To address the failure issues of SFCs under attack, this study proposes an efficient SFC recovery method for recovery rate optimization (ERRRO) based on virtual network functions (VNFs) migration technology. The method first determines the recovery order of failed SFCs according to their recovery costs, prioritizing the restoration of SFCs with the lowest costs. Next, the migration priorities of the failed VNFs are ranked based on their neighborhood certainty, with the VNFs exhibiting the highest neighborhood certainty being migrated first. Finally, the destination nodes for migrating the failed VNFs are determined by comprehensively considering attributes such as the instantiated SFC paths, delay of physical platforms, and residual resources. Experiments demonstrate that the ERRRO performs well under networks with varying resource redundancy and different types of attacks. Compared to methods reported in the literature, the ERRRO achieves superior performance in terms of the SFC recovery rate and delay. Full article

Urban parks are essential public resources that contribute significantly to residents’ well-being. However, disparities in the spatial distribution and social benefits of urban parks remain a pressing issue. This study focuses on the central urban area of Shanghai, a representative high-density megacity, and its findings hold significant reference value for similar cities, systematically evaluating urban park services from the perspectives of accessibility, spatial equity, and social equity. Leveraging multi-source big data and enhanced analytical methods, this study examines disparities and spatial mismatches in park services. By incorporating dynamic data, such as actual visitor attendance and residents’ travel preferences, and improving analytical models, such as an enhanced Gaussian two-step floating catchment area method and spatial lag regression models, this research significantly improves the accuracy and reliability of its findings. Key findings include (1) significant variations in accessibility exist across different types of parks, with regional and city parks offering better accessibility compared to pocket parks and community parks. (2) Park resources are unevenly distributed, with neighborhoods within the inner ring exhibiting relatively low overall accessibility. (3) A spatial mismatch is observed between park accessibility and housing prices, highlighting equity concerns. The dual spatial-social imbalance phenomenon reveals the prevalent contradiction in rapidly urbanizing areas where public service provision lags behind land development. Based on these results, this study proposes targeted recommendations for optimizing urban park layouts, including increasing the supply of small parks in inner-ring areas, enhancing the multifunctionality of parks, and strengthening policy support for disadvantaged communities. These findings contribute new theoretical insights into urban park equity and fine-grained governance while offering valuable references for urban planning and policymaking. Full article

Analyzing the population’s access to ecosystem services offered by urban greening constitutes a measure of environmental justice, as it directly affects the quality of life and health of the population living in cities. This article is committed to proposing a geoenvironmental model in a geographic information system (GIS), envisaged to estimate the share of urban forests and green spaces in territorial planning units (TPUs), corresponding to neighborhoods of a pilot city, using high-spatial-resolution images of the China–Brazil Earth Resources Satellite (CBERS-4A) and the normalized difference vegetation index (NDVI). These data were combined by means of a Boolean analysis with social vulnerability indicators assessed from census data related to income, education, housing, and sanitation. This model ultimately aims to identify priority areas for urban afforestation in the context of environmental justice and is thus targeted to improve the inhabitants’ quality of life. The municipality of Goiânia, the capital of Goiás state, located in the Brazilian Central–West Region, was chosen as the study area for this experiment. Goiânia presents 19.5% of its urban territory (82.36 km²) covered by vegetation. The analyses indicate an inequity in the distribution of urban forest patches and green areas in this town, where 7.8% of the total TPUs have low priority, 28.2% have moderate to low priority, 42.2% have moderate to high priority, and 21.8% have high priority for urban afforestation. This urban greening imbalance is particularly observed in its most urbanized central nuclei, associated with a peripheralization of social vulnerability. These findings are meant to support initiatives towards sound territorial planning processes designed to promote more sustainable and equal development to ensure environmental justice and combat climate change. Full article

Urban green spaces are essential for public health and well-being, emphasizing the importance of their equitable distribution in urban development. Despite efforts to expand green spaces, however, significant disparities persist between their spatial and social allocation. This study classified urban green spaces into community parks, urban parks, and country parks, and examined the relationship of their green coverage and park accessibility to neighborhood property prices in Hangzhou. We then assessed the urban green space equity using Gini coefficients. We found that (1) urban green space inequities occurred in both green coverage and accessibility; (2) high-priced neighborhoods occupied more green resources, especially green coverage and community park accessibility, but exhibited less green equity; and (3) low-priced neighborhoods and urban villages had the lowest green resources but more equity for country parks. This study highlights the relationship between property price (as a proxy for income) and urban green space equity at the neighborhood scale. The results offer guidance for policymakers and planners aiming to promote green equity and sustainable development in cities. Full article

With the escalating environmental crisis, electric vehicles have emerged as a key solution for emission reductions in logistics due to their low-carbon attributes, prompting significant attention and extensive research on the electric vehicle routing problem (EVRP). However, existing studies often overlook charging infrastructure (CI) capacity constraints and fail to fully exploit the synergistic potential of heterogeneous energy replenishment infrastructures (HERIs). This paper addresses the EVRP with HERIs under various capacity constraints (EVRP-HERI-CC), proposing a mixed-integer programming (MIP) model and a hybrid ant colony optimization (HACO) algorithm integrated with a variable neighborhood search (VNS) mechanism. Extensive numerical experiments demonstrate HACO’s effective integration of problem-specific characteristics. The algorithm resolves charging conflicts via dynamic rescheduling while optimizing charging-battery swapping decisions under an on-demand energy replenishment strategy, achieving global cost minimization. Through small-scale instance experiments, we have verified the computational complexity of the problem and demonstrated HACO’s superior performance compared to the Gurobi solver. Furthermore, comparative studies with other advanced heuristic algorithms confirm HACO’s effectiveness in solving the EVRP-HERI-CC. Sensitivity analysis reveals that appropriate CI capacity configurations achieve economic efficiency while maximizing resource utilization, further validating the engineering value of HERI networks. Full article

Spacecraft catering to the Lunar Gateway or other “permanent” stations in the lunar vicinity would require frequent travel between periodic orbits around the Earth–Moon $L_1$ and $L_2$ Lagrange points. The transition through the Hill sphere is often characterized by close passages of our nearest neighbor—rendering the optimization problem numerically challenging due to the increased local sensitivities. Depending on the mission requirements and resource constraints, transfer architectures must be studied, and trade-offs between flight time and fuel consumption quantified. While direct low-thrust transfers between the circular restricted three-body problem periodic orbit families have been studied, the asymptotic flow in the neighborhood of the periodic orbits could be leveraged for expansion and densification of the solution space. This paper presents an approach to achieve a dense mapping of manifold-assisted, low-thrust transfers based on initial and terminal coast segments. Continuation schemes are utilized to attain the powered intermediate time-optimal segment through a multi-shooting approach. Interesting insights regarding the linear correlation between $\Delta$V and change in reduced two-body osculating elements associated with the initial-terminal conditions are discussed. These insights could inform the subsequent filtering of the osculating selenocentric periapsis map and provide additional interesting and efficient solutions. The described approach is anticipated to be extremely useful for future crewed and robotic cis-lunar operations. Full article

We examined neighborhood-level demographic, economic, and social characteristics and food and health-services access to gauge the vulnerability of older-adult neighborhoods in New York State (NYS), which is understudied and is significant given the rapid aging of populations worldwide. We conducted descriptive ecological analyses using data from the American Community Survey, historical redlining maps, Social Capital Instruments, U.S. Department of Agriculture food access atlas, ESRI businesses, and Social Determinants of Health. We compared census tracts classified as having high and low levels of older-adult population; among those identified as high-older-adult neighborhoods, we then examined tracts with high and low levels of adult population living alone and in poverty. Our results showed that NYS neighborhoods with large shares of the older adult population are generally faring well in terms of their socioeconomic status, social capital, lack of social isolation, and health services access. However, the older-adult neighborhoods with larger shares of the population living alone and in poverty fare worse, living in areas with poorer socioeconomic status, lower social capital, and considered medically underserved. NYS older adult communities are projected to increase by 2030. Resources should be invested in such areas with vulnerable groups so populations may age in equitable and accessible communities. Full article

Community members seeking alternatives to policing have played a substantive role in promoting safety and responding to harm for decades. The Survival Line was formed as a volunteer-run hotline to respond to community members’ concerns about neighborhood crime or police misconduct. It was established in the summer of 1970 as a mechanism for gathering data while also referring callers to community resources like pro bono attorneys and low-cost social services. It ran as a 24/7 hotline staffed entirely by volunteers from the Action for Survival coalition, a group of community-based organizations, which included the Chicago Urban League. Using historical analytic methods, this study asks the following: what function did this citizen-run hotline serve in 1970s Chicago? This study mobilizes archival research methods to analyze call records, meeting minutes, publicity materials, and internal memos from the Chicago Urban League and its Survival Line archives. This archival analysis found that the Survival Line served multiple functions; it was a non-state response to urban crises, a vehicle for Black solidarity, and a mechanism for gathering data on crime and police misconduct in the city. By functioning as an alternative to policing and state responses to crime, a vehicle for Black neighborhood solidarity, and a data collection mechanism, the Survival Line was at the core of an impactful micropolitical intervention upon urban crises in 1970s Chicago. As a historical example of community-driven violence and crisis response, this hotline has implications for contemporary social work—specifically for direct practice, community organizing, program design and evaluation, and community-based participatory research. Full article

Differences in exposures and resources to manage personal health contribute to persistent inequities in air pollution burden despite vast air quality improvements over the past 2–3 decades in the United States. These factors are, partly, linked to historic racist practices, such as redlining, a discriminatory housing policy that was practiced legally between 1935 and 1968. Using 100 m × 100 m resolution land-use regression predicted surfaces of PM_2.5 constituents (black carbon, nickel, vanadium, and copper) as pollution source indicators, we fit Bayesian generalized linear mixed-effects models to examine differences in source exposures over two study periods, 2008–2015 and 2016–2019, comparing (1) redlined to not redlined and (2) high-asthma to low-asthma neighborhoods. We examine redlining as an indicator of historical, and structural racism and asthma rates as an indicator of present-day community burden. Redlined areas saw near elimination of disparities in exposure to residual oil boilers and marine residual oil but persistent disparities in traffic. High-asthma neighborhoods continue to have disproportionately high exposures to both residual oil boilers and traffic, with no discernable disparities related to marine residual oil emissions. Overall exposure disparities are small, with PM_2.5 disparities by both asthma morbidity and redlining amounting to less than 1 µg/m³ and NO₂ disparities by asthma and redlining amounting to less than 2 ppb in the post-2016 period. For context, 2019 NYC average PM_2.5 and NO₂ were 8.5 µg/m³ and 20 ppb, respectively. Our findings suggest that local pollution policy should focus on reducing traffic and building boiler emissions in high-asthma neighborhoods to reduce exacerbations. Full article

Background: Health inequities begin before birth and are influenced by pregnancy conditions, race/ethnicity, social class, and environment. Research indicates that, in the United States, Black women are significantly more likely to have low-birth-weight babies compared to White women. Interestingly, Hispanic women in the United States do not experience this birth weight inequity. The reasons for this disparity remain unclear. Both Hispanic and Black women face discrimination, and this is often cited as a primary reason for the higher prevalence of low-birth-weight babies among Black women. One type of discrimination that is less examined is neighborhood deprivation. Method: This study systematically examined the impact of various sociodemographic and pregnancy predictors among 9607 women in Phoenix, Arizona. Using multilevel modeling, we analyzed whether neighborhood deprivation (using the Area Deprivation Index) influenced the association between demographic and pregnancy risk and protective factors on birth weight outcomes. Results: Consistent with prior research, we found that Black and Asian women had lower-birth-weight babies than White women, while Hispanic women did not show a significant difference from non-Hispanic women. Additionally, multilevel modeling suggested that increased neighborhood deprivation tends to exacerbate the impact of some risk factors (e.g., race) and reduce the impact of specific protective factors (e.g., gestational age) on birth weight. Conclusion: These findings suggest that both place and individual factors synergistically influence birth weight outcomes. Moreover, the results underscore the importance of targeting interventions to enhance resources among those who live in the most deprived neighborhoods. Full article

The rapid increase in urban population density driven by urban development has intensified inequity in urban green space distribution. Identifying the causes of changes in green equity and developing strategies to improve urban greening are crucial for optimizing resource allocation and alleviating social inequalities. However, the long-term spatio-temporal evolution of green visibility and equity remains underexplored. This study utilized the “Time Machine” feature to capture street view images from 2014, 2017, and 2021, analyzing changes in green visibility and its equity across residential communities in Wuhan. Deep learning techniques and statistical methods, including the Gini coefficient and location quotient (LQ), were employed to assess the distribution and spatial equity of street-level greenery. The results showed that overall green visibility in Wuhan increased by 4.18% between 2014 and 2021. However, this improvement did not translate into better spatial equity, as the Gini coefficient consistently ranged between 0.4 and 0.5. Among the seven municipal districts, only the Jiang’an District demonstrated relatively equitable green visibility in 2017 and 2021. Despite a gradual reduction in disparities in green visibility, a spatial mismatch persisted between UGS growth and population distribution, leading to uneven patterns in UGS equity. This study explores the factors driving inequities in green visibility and proposes strategies to enhance urban greening. Key recommendations include integrating the green visibility equity evaluation framework into urban planning to guide fair green space allocation, prioritizing greenery in low-income neighborhoods, and reducing hardscapes to support the planting and maintenance of tall canopy trees. These measures aim to enhance accessible and visible green resources and promote equitable access across communities. Full article

Most of the affordable housing communities are built in disadvantaged locations (e.g., the suburbs of Chinese cities) and are generally considered to be the main space for middle- and low-income groups to live in. After decades of development, with the relocation of residents, housing sales and the implementation of mixed housing policies in some countries, there is a common phenomenon of mixed living among different groups in many affordable housing communities. Existing studies have explored the differences and social inequities between affordable housing communities and other types of neighborhoods, but little attention has been paid to the differentiation of residents’ daily activities and the unfair access to resources within affordable housing communities. Understanding this difference is crucial to sustainable community development and the delicate management of cities. From a personal-based perspective, this study examines the sociospatial differentiation of different income groups in the community from two aspects: the multidimensional characteristics of the individual activity space and the availability of different types of urban space. The results highlight significant differences in the activity spaces of different income groups across four dimensions: extensity, intensity, diversity, and exclusivity. Low-income suburban residents have fewer opportunities to access inner-city and inner-suburban areas compared to their non-low-income counterparts. They are more constrained to the outer suburbs. Regression models show that income is a key factor influencing how outer-suburb residents use urban spaces. Other factors, such as one’s employment status, family structure, education level, and the built environment, also play an important role in shaping access to different urban resources. This study highlights the impact of income on social isolation within Chinese urban affordable housing communities. It provides nuanced insights that can inform future policy recommendations in a broader urban context. Full article

To achieve economic resilience and green, low-carbon development are two goals of China’s high-quality economic development. This paper uses the entropy weight method and coupling coordination degree model to estimate the coupling coordination level of economic resilience and green, low-carbon development. Kernel density estimation, Moran index, Dagum Gini coefficient, Markov chain, and obstacle degree model are used to explore the spatiotemporal evolution characteristics and obstacle factors. The results are as follows. (1) The coupling coordination degree between China’s economic resilience and green, low-carbon development has increased overall. However, the eastern region has the highest, and the central region has the fastest growth. (2) The coupling coordination degree shows positive spatial autocorrelation, with most provinces exhibiting high–high or low–low aggregation characteristics. (3) The contribution of imbalance mainly comes from inter-regional differences, but the contribution of intra-regional differences to imbalance is increasing. (4) The spatio-temporal evolution pattern is generally better, and the probability of the coupling coordination degree maintaining the initial state is the largest. The neighborhood’s state affects the transition probability but does not affect that of high-level provinces. (5) Innovation capacity is the main obstacle to improving economic resilience, and per capita water resources are the main obstacle to green and low-carbon development. Finally, this paper puts forward suggestions for creating a good innovation environment, increasing R&D investment, promoting green technology progress, optimizing regional cooperation and resource allocation, and promoting industrial green transformation. Full article

With the wide application of computer-aided manufacturing (CAM) software, manufacturing enterprises have accumulated a wealth of numerical control (NC) programming data, providing valuable knowledge resources for new products’ development. Efficiently acquiring and reusing existing NC knowledge is essential for enhancing programming efficiency, improving product quality, and shortening manufacturing cycles. This study proposes an intelligent NC programming method based on knowledge graph. Firstly, the relevant knowledge in the NC programming domain is analyzed, and CAM knowledge elements are constructed to reduce the granularity of knowledge. Then, the ontology layer and data layer are constructed to achieve the development of the knowledge graph. Next, knowledge reasoning is performed on the knowledge graph through entity alignment and semantic rule-based reasoning. Furthermore, to address the issues of low reliability, limited applicability and need for frequent manual modifications in NC programming templates guided by the CAM knowledge graph, a CAM knowledge graph completion method based on neighborhood aggregation and semantic enhancement is proposed. Finally, an intelligent NC programming system based on knowledge graph is developed, and comparative experiments with mainstream algorithms on public datasets for few-shot knowledge graph completion are conducted, validating the effectiveness of the proposed method by experimenting with the key components of marine diesel engines. Full article