Search Results (236)

Objective: To explore the relationship between type of grocery store used (chain vs. independent), transportation access, food insecurity, and fruit and vegetable intake in Detroit, Michigan, USA, during the COVID-19 pandemic. Design: A cross-sectional online survey was conducted from December 2021 to May 2022. Setting: Detroit, Michigan. Participants: 656 Detroit residents aged 18 and older. Results: Bivariate analyses showed that chain grocery store shoppers reported significantly greater fruit and vegetable intake (2.42 vs. 2.14 times/day for independent grocery store shoppers, p < 0.001) and lower rates of food insecurity compared to independent store shoppers (45.9% vs. 65.3% for independent grocery store shoppers, p < 0.001). Fewer independent store shoppers used their own vehicle (52.9% vs. 76.2% for chain store shoppers, p < 0.001). After adjusting for socioeconomic and demographic variables transportation access was strongly associated with increased odds of shopping at chain stores (OR = 1.89, 95% CI [1.21,2.95], p = 0.005) but food insecurity was no longer associated with grocery store type. Shopping at chain grocery stores was associated with higher fruit and vegetable intake after adjusting for covariates (1.18 times more per day, p = 0.042). Qualitative responses highlighted systemic barriers, including poor food quality, high costs, and limited transportation options, exacerbating food access inequities. Conclusions: These disparities underscore the need for targeted interventions to improve transportation options and support food security in vulnerable populations, particularly in urban areas like Detroit. Addressing these structural challenges is essential for reducing food insecurity and promoting equitable access to nutritious foods. Full article

The establishment and management of nature reserves play a crucial role in protecting biodiversity and supporting sustainable agriculture. This study focuses on 2538 nature reserves in 22 provinces, 5 autonomous regions and 4 municipalities directly under the central government in mainland China. Integrating GIS spatial statistics, imbalance index, and geodetector models, we reveal critical insights: (1) Pronounced spatial inequity is observed, where a small number of eastern provinces dominate the total reserve count, highlighting significant regional disparities in ecological resource allocation. The sparse kernel density in western regions, indicating sparse reserve coverage. The Standard Deviation Ellipse highlights directional dispersion and human-ecological conflicts in high-density zones. (2) Key sustainability indicators driving reserve distribution include: total water resources, water resources per capita, forest area. (3) The spatial distribution of China’s nature reserves, along with factors such as altitude, river distribution, and transportation infrastructure, plays a crucial role in their development. This research provides theoretical support for the scientific planning and policy-making of nature reserves in China and offers practical guidance for optimizing and adjusting sustainable agricultural development. The study emphasizes the vital functions of nature reserves in maintaining ecosystem balance, enhancing regional climate resilience, and serving as biodiversity reservoirs. This research offers strategic insights for integrating nature reserve spatial planning with sustainable agricultural development policies, providing a scientific basis for optimizing the eco-agricultural interface in China. Full article

Transportation infrastructure is a fundamental driver of economic growth and regional connectivity; and the supply of this infrastructure is often assumed to reduce spatial disparities. This study investigates the impact of transportation accessibility on regional disparities in land prices across South Korea from 2010 to 2019. Using spatial econometric models and geographically weighted regression (GWR), this study evaluates how variations in transportation networks influence land price differentials between regions. The results confirm that transportation accessibility positively affects land prices; but GWR coefficients reveal substantial regional variations in the extent to which accessibility improvements drive land price growth. Furthermore, while the overall distribution of transportation accessibility remained relatively stable, its influence on land price appreciation varied significantly, contributing to a widening gap in land values between regions. These findings underscore the critical role of transportation infrastructure in shaping regional inequalities and highlight the need for more equitable transportation policies to mitigate spatial disparities and promote balanced regional development Full article

This study explores the spatial and social implications of urban food systems in Quito, Ecuador, focusing on how food access inequalities reflect and reinforce broader urban disparities. The research addresses a critical problem in contemporary urbanization: the disconnection between food provisioning and spatial equity in rapidly growing cities. The objective is to assess and map disparities in food accessibility using a mixed-methods approach that includes field observation, participatory mapping, value chain analysis, and statistical modeling. Five traditional and emerging food markets were studied in diverse districts across the city. A synthetic accessibility function F(x) was constructed to model food access levels, integrating variables such as income, infrastructure, transport availability, and travel time. These variables were subjected to Principal Component Analysis (PCA) and hierarchical clustering to generate three typologies of territorial vulnerability. The results reveal that peripheral areas exhibit lower F(x) values and weaker integration with the formal food system, leading to higher consumer costs and limited fresh food options. In contrast, central districts benefit from multimodal infrastructure and greater diversity of supply. This study concludes that food systems should be treated as critical urban infrastructure. Integrating food equity into land use and mobility planning is essential to promote inclusive, sustainable, and resilient urban development. Full article

The economic downturns in South Africa present a significant threat, with the potential to disrupt the nation’s notable advances in addressing the persistent challenges of high unemployment, widespread poverty and stark inequality. In the absence of substantial and extensive structural transformation, South Africa’s aspirations to achieve its ambitious development goals may remain unattainable. Building on the precedent of a blend of literature review, comprehensive ex post analysis, and applied general equilibrium modelling tailored for ex ante assessments, this paper assesses options and impacts of alternative ambitious developmental interventions. The results indicate that, despite implementing a variety of strategies, there remains a disheartening underperformance in economic indicators. However, ex ante evaluations indicate that with targeted interventions and supportive government policies, the country can achieve economic growth and job creation. Simulation results identify sectors of personal and social service activities, transport, finance, and insurance as having the most formidable potential to significantly reduce unemployment while simultaneously catalysing robust economic growth. These pivotal sectors, nestled within the broader services and industries, are uniquely poised to bolster overall productivity and diminish unemployment, while adeptly absorbing a considerable influx of highly educated and skilled labour. This suggests that South Africa can decisively accelerate its economic progress by embracing a dual-pronged approach: fostering structural shifts towards manufacturing and services, while steadfastly advancing the upskilling of its dynamic workforce. Full article

The Yangtze River Economic Belt (YEB), serving as a pivotal transportation corridor connecting eastern and western China and a national strategic development hub, plays a central role in driving high-quality economic development (HQAED) across the country. Based on the new development paradigm with emphasis on green transformation and transportation integration, this study proposes a comprehensive evaluation framework for an HQAED index (HQAED) across five core dimensions. Employing the entropy-weighted CRITIC method to quantify provincial HQAED values, combined with Dagum–Gini coefficient analysis to examine regional inequality patterns and determinants, and complemented by kernel density estimation (KDE) for temporal dynamics analysis, this research reveals four key findings: (1) There are significant disparities in HQEDI levels across the YEB, with a clear east–west gradient: the lower reaches > middle reaches > upper reaches. (2) While the dimensions of green development and shared development have shown steady growth despite initial disadvantages, the openness dimension faces structural challenges that require particular attention. (3) The overall Gini coefficient fluctuates between 0.068 and 0.094, indicating moderate regional disparities with relatively limited inequality. (4) The rightward shift in the HQEDI kernel density curves confirms overall progress, but also highlights widening disparities in the upstream regions and growth stagnation in the midstream areas. Practically, the entropy–CRITIC fusion methodology offers a transferable framework for emerging economies measuring sustainability-transition progress, while the quantified “green transportation empowerment” effects provide actionable levers for policymakers to optimize ecological compensation mechanisms and cross-regional infrastructure investments. Full article

The increasing disparity in global food distribution has amplified the urgency of addressing food waste and food insecurity, both of which exacerbate economic, environmental, and social inequalities. Traditional food bank models often struggle with logistical inefficiencies, limited accessibility, and a lack of transparency in food distribution, hindering their effectiveness in mitigating these challenges. This study proposes a novel Food Bank Network Redesign (FBNR) that leverages the Quito Metro system to create a decentralized food bank network, enhancing efficiency and equity in food redistribution by introducing strategically positioned donation lockers at metro stations for convenient drop-offs, with donations transported using spare metro capacity to designated stations for collection by charities, reducing reliance on dedicated transportation. To ensure transparency and operational efficiency, we integrate a blockchain-based traceability system with smart contracts, enabling secure, real-time tracking of donations to enhance stakeholder trust, prevent food loss, and ensure regulatory compliance. We develop a multi-objective optimization framework that balances food waste reduction, transportation cost minimization, and social impact maximization, supported by a mixed-integer linear programming (MIP) model to optimize donation allocation based on urban demand patterns. By combining decentralized logistics, blockchain-enhanced traceability, and advanced optimization techniques, this study offers a scalable and adaptable framework for urban food redistribution, improving food security in Quito while providing a replicable blueprint for cities worldwide seeking to implement circular and climate-resilient food supply chains. Full article

Variational inequality problems (VIPs) provide a versatile framework for modeling a wide range of real-world applications, including those in economics, engineering, transportation, and image processing. In this paper, we propose a novel iterative algorithm for solving VIPs in real Hilbert spaces. The method integrates a double-inertial mechanism with the two-subgradient extragradient scheme, leading to improved convergence speed and computational efficiency. A distinguishing feature of the algorithm is its self-adaptive step size strategy, which generates a non-monotonic sequence of step sizes without requiring prior knowledge of the Lipschitz constant. Under the assumption of monotonicity for the underlying operator, we establish strong convergence results. Numerical experiments under various initial conditions demonstrate the method’s effectiveness and robustness, confirming its practical advantages and its natural extension of existing techniques for solving VIPs. Full article

Transit deserts, defined by insufficient public transit provision relative to demand, aggravate socio-economic inequalities by restricting access to employment, education, and healthcare. With increasing urbanization and growing disparities in public transport accessibility, identifying transit deserts is critical for equitable mobility planning. As urban populations expand, addressing transit accessibility requires advanced data-driven approaches. This study applies machine learning (ML) models, decision trees (DTs), logistic regression (LR), and random forest (RF), within an Intelligent Transport System (ITS) framework to detect transit deserts in Lucknow, India. Employing a 100 × 100 m spatial grid data, the models classify transit accessibility based on economic status, trip frequency, population density, and service access. The results indicate that RF achieves superior classification accuracy, while DT offers interpretability with slightly lower recall. LR underperforms due to its linear assumptions. The findings reveal the spatial clustering of transit deserts in socio-economically disadvantaged areas, highlighting the need for targeted interventions. This study advances ML-driven ITS analytics, offering a novel approach for classifying transit accessibility patterns at a granular level, thereby aiding policy interventions for improved urban mobility. Full article

Limited access to education in rural areas of Senegal is a structural barrier to human development and equal opportunities. The Bicycles for Education project, promoted by the Utopia Foundation—Bicycles Without Borders (BSF), aims to improve the educational participation of young people aged 12 to 21 by providing bicycles to facilitate their travel to school. In this study, the GRITS research group from the University of Barcelona externally evaluates the impact of the project on improving access to education, reducing gender inequalities, and the associated socioeconomic as well as community benefits. A qualitative approach based on individual interviews (n = 23), focus groups (n = 6) and group interviews (n = 8) was used, with a total of 80 participants, including students, families, teachers, project coordinators, and institutional managers. The analysis was carried out through thematic coding and content analysis, identifying four main axes: educational impact, gender equity, economic effects, and community transformation. The results show that the provision of bicycles throughout the school year led to increased school attendance and punctuality, improvements in academic performance, a reduction in social inequalities, gender inequalities in access to education, and a decrease in household costs associated with transport and food. In addition, there has been a cultural transformation in the perception of cycling as a viable means of mobility and a change in those communities where the project has been running for more than a decade. Full article

Urban regeneration is pivotal to sustainable development, requiring innovative strategies that align social dynamics with spatial configurations. Traditional paradigms increasingly fail to tackle systemic challenges—neighborhood alienation, social fragmentation, and resource inequality—due to their inability to integrate human-centered spatial governance. This study addresses these shortcomings with a novel multidimensional framework that merges social perception (life satisfaction) analytics with spatial quality (GIS-based) assessment. At its core, we utilize geospatial and machine learning models, deploying an ensemble of Gradient Boosted Decision Trees (GBDT), Random Forest (RF), and multiscale geographically weighted regression (MGWR) to decode nonlinear socio-spatial interactions within Suzhou’s community environmental matrix. Our findings reveal critical intersections where residential density thresholds interact with commercial accessibility patterns and transport network configurations. Notably, we highlight the scale-dependent influence of educational proximity and healthcare distribution on community satisfaction, challenging conventional planning doctrines that rely on static buffer-zone models. Through rigorous spatial econometric modeling, this research uncovers three transformative insights: (1) Urban environment exerts a dominant influence on life satisfaction, accounting for 52.61% of the variance. Air quality emerges as a critical determinant, while factors such as proximity to educational institutions, healthcare facilities, and public landmarks exhibit nonlinear effects across spatial scales. (2) Housing price growth in Suzhou displays significant spatial clustering, with a Moran’s I of 0.130. Green space coverage positively correlates with price appreciation (β = 21.6919 ***), whereas floor area ratio exerts a negative impact (β = −4.1197 ***), highlighting the trade-offs between density and property value. (3) The MGWR model outperforms OLS in explaining housing price dynamics, achieving an R² of 0.5564 and an AICc of 11,601.1674. This suggests that MGWR captures 55.64% of pre- and post-pandemic price variations while better reflecting spatial heterogeneity. By merging community-expressed sentiment mapping with morphometric urban analysis, this interdisciplinary research pioneers a protocol for socio-spatial integrated urban transitions—one where algorithmic urbanism meets human-scale needs, not technological determinism. These findings recalibrate urban regeneration paradigms, demonstrating that data-driven socio-spatial integration is not a theoretical aspiration but an achievable governance reality. Full article

This paper investigates a class of distributed fractional-order stochastic differential equations driven by fractional Brownian motion with a Hurst parameter $1/2<H<1$. By employing the Picard iteration method, we rigorously prove the existence and uniqueness of solutions with Lipschitz conditions. Furthermore, leveraging the Girsanov transformation argument within the $L^2$ metric framework, we derive quadratic transportation inequalities for the law of the strong solution to the considered equations. These results provide a deeper understanding of the regularity and probabilistic properties of the solutions in this framework. Full article

The Second Law of Thermodynamics states that entropy S increases in a spontaneous process in an ideal isothermal and isolated system. Real systems are influenced by external forces and fields, including the temperature field. In this case, only entropy is not enough, and we suggest using a new function, $L_s$, which is analogous to the Lagrangian in classical mechanics. It includes total potential energy but instead of mechanical kinetic energy, $L_s$ includes the product ST, and the system always evolves towards increasing this modified Lagrangian. It reaches an equilibrium when total potential force is balanced by both entropic and thermal forces. All forces have the same units, Newton/mol, and may be added or subtracted. For condensed systems with friction forces, it is a molecular transport velocity, and not acceleration, which is proportional to the acting force. Our approach has several advantages compared to Onsager’s non-equilibrium thermodynamics with its thermodynamic forces, which may have different units, including 1/T for energy transport. For isolated systems, the description is reduced to Second Law and Clausius inequality. It easily explains diffusion, Dufour effect, and Soret thermodiffusion. The combination of electric, thermal, and entropic forces explains thermoelectric phenomena, including Peltier–Seebeck and Thomson (Lord Kelvin) effects. Gravitational and entropic forces together inside a black hole may lead to a steady state or the black hole evaporation. They are also involved in and influenced by solar atmospheric processes. Full article

Educational achievement plays a significant role in the labour market, benefiting individuals and society. Graduating from high school is a key step towards better employment opportunities and a prerequisite for higher education attainment. In 2023, only 22.5% of the Romanian population graduated tertiary education, while 16.6% left education or training early. The Romanian public high school network comprises 1558 units, mostly located in urban areas. The high school enrolment rate is 83.5% in urban areas, and it drops to less than 60% in rural areas, with the country registering the highest out-of-school rate in the EU for the 15-year-old population. Spatial accessibility may influence enrolment in high schools, particularly for students living in rural or remote areas, who often face financial challenges fuelled by long distances and limited transportation options. Hence, travel distance may represent a potential barrier to completing the educational process or may determine inequalities in educational opportunities and outcomes. This paper aims to assess the spatial accessibility of the public high school network in Romania by using distance data provided by the Open Street Map API (Application Programming Interface). We examine variations in spatial accessibility based on the distribution of high school units and road network characteristics considering three variables: travel distance to the nearest high school, the average distance to three different categories of high schools, and the number of high schools located within a 20 km buffer zone. The results highlight a significant urban–rural divide in the availability of public high school facilities, with 84.1% (n = 1311) located in urban areas while 49.1% of the high school-aged population lives in rural areas. Many rural communities lack adequate educational facilities, often having limited options for high school education. The findings also show that 32% of the high school-aged population has to travel more than 10 km to the nearest high school, and 7% has no high school options within a 20 km buffer zone. This study provides insights into the educational landscape in Romania, pointing out areas with limited access to high schools, which contributes to further inequalities in educational attainment. The findings may serve as a basis for developing policies and practices to bridge the urban–rural divide in educational opportunities and foster a more equitable and inclusive education system. Full article

Inequitable access to parks persists in cities where race, income, and geography shape residents’ proximity to public green space. This study analyzes 20 parks in Salt Lake City—10 in the Eastside and 10 in the Westside—using demographic, housing, and transportation data drawn from GIS tools and spatial platforms. By assessing indicators such as household income, racial composition, rent burden, walkability, and transit access, the findings confirm that Westside parks—located in lower-income and more racially diverse neighborhoods—are significantly less accessible. Eastside parks, by contrast, tend to serve higher-income, majority-white areas with better infrastructure. This paper illustrates how spatial inequality in surrounding conditions limits park accessibility, and it proposes GIS as a tool for diagnosing and addressing environmental injustice in urban planning. Full article