Search Results (83)

This paper proposes finite-time (FT) and fixed-time (FXT) neurodynamic models with time-varying coefficients for solving inverse quasi-variational inequality problems (IQVIPs). Two projected models with time-dependent gains are developed to enhance convergence speed and transient performance. A nominal model establishes the equivalence between equilibrium points and IQVIP solutions. Under Lipschitz continuity and strong monotonicity assumptions, the existence, uniqueness, and global convergence of the proposed models are ensured. By employing Lyapunov stability theory, finite-time and fixed-time convergence of the continuous-time models are rigorously established, where explicit settling-time bounds independent of initial conditions are derived for the FXT case. Furthermore, the robustness of the proposed models under bounded disturbances is analyzed. To validate the theoretical findings, a discrete-time implementation based on the forward Euler method is developed. Numerical experiments demonstrate that all trajectories converge within a uniform upper bound, showing convergence behavior consistent with the fixed-time characteristics of the continuous-time model. Although the convergence time varies with initial conditions, it remains uniformly bounded, which is consistent with the fixed-time stability characteristics of the continuous-time model. The proposed framework provides a computationally efficient and scalable approach for solving IQVIPs, with potential applications in traffic equilibrium, communication networks, distributed control systems, and multi-agent coordination. Its adaptive structure and fixed-time convergence properties make it particularly suitable for real-time optimization in dynamic and uncertain environments. Full article

Rapid urbanization has intensified inequalities in the distribution of urban green resources, making green equity a critical concern within the framework of the United Nations Sustainable Development Goals. This study examines Zhangdian District in Zibo City, China, a representative “Whole-Area Park City” pilot area. This study integrates 1 km population density grid data with GIS network analysis, space syntax, population-weighted service pressure assessment, and a location–allocation model. Using these methods, it evaluates four categories of urban parks from the perspectives of spatial distribution, road connectivity, and social equity. The results reveal that vehicle and cycling modes achieved nearly complete 15 min coverage, whereas pedestrian accessibility remained insufficient. Walking accessibility for comprehensive parks reached 77.69%, whereas that of community parks and petty street gardens was below 33%. Population-weighted analysis further suggests that more than 78% of residents, concentrated in dense central–western neighborhoods, are served by only 21% of total park area. The Gini coefficient of per capita park area reached 0.4765, indicating substantial inequality in park green space allocation. After optimization through the addition of 76 new parks, improvements in road connectivity, and construction of a slow-traffic system, the Gini coefficient decreased to 0.4053, representing a 14.9% reduction. Meanwhile, the population below the national standard declined from 78.09% to 40.64%. These findings reflect spatial accessibility and area-based equity, while actual park service value also depends on park quality, facilities, and user behavior. This study provides quantitative evidence for equity-oriented park planning and a replicable framework for sustainable urban green space planning. Full article

Unmanned Aerial Vehicle Ad Hoc Networks (UAVANETs) are characterized by highly dynamic topology changes and unstable link conditions, which necessitate deep collaboration between transport-layer congestion control and network-layer routing decisions to ensure service quality. However, the existing layered architecture of Software-Defined Networking (SDN) results in a significant separation between routing information and congestion control mechanisms, rendering traditional protocols ineffective in handling severe performance fluctuations caused by highly dynamic route switching. The significant disconnect between network-layer route planning and transport-layer congestion control strategies in Software-Defined Unmanned Aerial Vehicle Ad Hoc Networks (SD-UAVANETs) leads to degraded transmission performance of BBR (Bottleneck Bandwidth and Round-trip propagation time) under high-dynamic route switching scenarios. As such, this paper proposes an in-band network telemetry (INT)-based cross-layer optimization scheme for BBR, named SDN-BBR. Firstly, a lightweight real-time route switching detection mechanism based on INT is designed. Secondly, a QoS inequality model before and after path switching is established, deriving the critical bandwidth of the new path and integrating it into the BBR algorithm to accelerate convergence and avoid congestion. Finally, the BBR state machine is redesigned to achieve cross-layer information fusion and coordinated control, thereby optimizing transmission performance. Experimental results show that the proposed scheme reduces convergence time by 69.8% and increases throughput by 73.9% in low-bandwidth to high-bandwidth switching scenarios; decreases packet loss rate by 86.8% and reduces delay by 8.3% in high-bandwidth to low-bandwidth switching scenarios; and improves throughput by 12.3%, lowers packet loss rate by 21%, and reduces delay by 7.9% in multi-traffic flow concurrent scenarios. The scheme significantly enhances the transmission performance of BBR in highly dynamic routing environments of SD-UAVANET. Full article

Background: Timely prehospital management is critical for survival after traumatic injury. In rapidly growing metropolises, emergency medical service (EMS) systems often struggle to provide equitable care amid urban sprawl and traffic congestion. This study investigated spatiotemporal inequalities in trauma-related EMS response in a rapidly expanding capital city (Astana, Kazakhstan) to inform healthcare optimization and urban health equity. Methods: We analyzed a five-year population-based dataset of 26,073 trauma-related EMS calls recorded between 2020 and 2024. Spatial patterns were examined using Kernel Density Estimation (KDE) and Getis–Ord Gi* hotspot analysis. Road-network modeling assessed accessibility at 3, 5, and 10 min thresholds using a GIS-based network analyst framework. Results: Males accounted for 60.1% of utilization and had higher clinical severity (hospitalization rate: 45.5% vs. 40.3%, p < 0.001). Demand peaked at 20:00, coinciding with peak traffic. The mean total response time was 21.63 min, and only 16.9% of calls met the 10 min benchmark. Significant accessibility gaps were found in the Baikonur district (61.4% delay rate). Conclusions: The findings demonstrate that while the EMS system provides broad geographic coverage, it suffers from systemic spatiotemporal bottlenecks. Targeted infrastructure expansion in underserved peripheral districts and the implementation of dynamic deployment models are necessary to enhance urban health equity and reduce preventable mortality in expanding metropolitan areas. Full article

Sustainable urban development increasingly depends on understanding how digital activity is distributed across space and time, yet the spatiotemporal dynamics of the urban digital landscape remain poorly mapped by conventional data sources. This study uses Beijing as an empirical testbed, applying a multi-dimensional analytical framework to massive mobile network traffic data to decode the metabolic rhythms, distributional laws, and functional organization of the urban digital landscape. The results reveal three findings. First, the urban digital landscape exhibits a sleepless trapezoidal temporal rhythm characterized by continuous saturation without a midday trough and a quantifiable weekend activation lag, indicating that digital metabolism is structurally decoupled from physical mobility patterns. Second, digital traffic follows a skew-normal distribution consistent with a 20/70 rule of spatial polarization, in which the top 20% of super-connector nodes sustain approximately 70% of total urban digital flow, yielding a Gini coefficient of 0.68 as a measurable indicator of infrastructure inequality and systemic vulnerability. Third, four distinct functional prototypes are identified—ranging from continuously active metropolitan cores to inverse-tidal ecological peripheries—empirically validating Beijing’s polycentric transformation through the lens of digital flows. These findings demonstrate that large-scale mobile network traffic data offers a replicable and structurally distinct lens for sustainable urban digital governance, supporting resilient network planning, equitable allocation of digital resources, and evidence-based monitoring of urban functional transformation in rapidly growing megacities. Full article

In traditional wind turbine (WT) operation and maintenance, fault diagnosis and repair have long been relied on, yet the demand for continuous operation under faults persists. To address this, this study proposes a triggered fault-tolerant control framework for wind turbines with zonotope-based interval estimation. The method enhances safety from point to range estimation of FDI, reduces network traffic load via a WT load region-based adaptive event-triggered mechanism, and enables fast, robust fault diagnosis/isolation using interval residuals. A damage equivalent load (DEL)-sensitive cost term balances structural fatigue suppression while ensuring power tracking and safety constraints. Theoretically, Linear Matrix Inequality (LMI) conditions based on common quadratic Lyapunov ensure closed-loop stability and bounded observation errors, with proven interval residual fault sensitivity and triggering reliability. Numerically, on the standard NREL 5-MW WT model under multi-conditions (turbulence, faulty communication), it achieves an average power tracking accuracy of 95.56%, 28.68% fatigue suppression, and 67.40% bandwidth saving. Overall, it synergistically optimizes robust estimation, economical communication, and fatigue-aware control, providing a theoretically rigorous and experimentally validated technical framework for engineering-scale WT reliability improvement and lifespan extension. Full article

The effective delineation of fire station response zones is critical for urban public safety planning, yet traditional methods often fail to account for dynamic traffic conditions, leading to suboptimal resource allocation. This study proposes a novel block-unit-based method that incorporates real-time traffic data to delineate fire station response zones, improving the scientificity of response time estimation. The method was validated using data from Daxiang District, China, a typical urban–rural mixed region, encompassing 2230 block units, 4 fire stations, and 13,097 demand points. Analysis of 1,225,047 data samples revealed an average travel time of 960.7 s, highlighting significant accessibility challenges. The re-delineated response zones cover areas ranging from 1.07 to 156.24 km², with significant variations. It is attributed to the concentration of fire stations in urban areas, insufficient coverage of vast rural regions, and the proximity of one station to a river and regional boundary. These findings underscore the spatial inequities in fire service provision and the need for a more balanced resource allocation strategy. Recommendations include establishing rural fire stations, improving urban traffic conditions, and relocating certain fire stations. This approach can enhance regional accessibility and provides a scientific basis for fire service planning. Full article

This study develops a Smart Mobility Index (SMI) tailored to the 17 Local Government Units (LGUs) of Metro Manila to evaluate their readiness to adopt integrated, efficient, and technology-enabled mobility systems. While global smart mobility indices are often ill-suited to the realities of developing countries, this research proposes a context-specific framework built around four thematically grounded dimensions: public transportation service, active mobility, unified cashless fare systems, and smart traffic management. The SMI was constructed through a mixed-method approach combining expert interviews with metropolitan transport specialists and co-occurrence network analysis. The results reveal substantial disparities across LGUs, with central jurisdictions such as Makati, Manila, and Pasay demonstrating significantly higher smart mobility readiness than peripheral LGUs. Clustering identifies three distinct mobility profiles, underscoring persistent structural inequalities in infrastructure, institutional capacity, and digital integration. Forecasts incorporating the completion of six major railway projects by 2035 indicate moderate improvements in overall SMI scores and limited changes in relative rankings, suggesting that infrastructural expansion alone will not reduce regional disparities. Expert insights further highlight both the potential and the constraints of leapfrogging, with interviewees expressing optimism regarding advanced ICT-enabled mobility solutions while acknowledging challenges related to governance fragmentation, limited funding, and uneven technical capabilities. Full article

Climate change intensifies natural disasters, requiring enhanced understanding of urban resilience mechanisms. While green infrastructure’s disaster mitigation role has been established through engineering studies, empirical evidence linking green infrastructure quality to post-disaster economic adaptation remains limited. This study examines whether community-level green infrastructure quality correlates with post-disaster economic adaptation following Hurricane Laura’s August 2020 landfall. [Methods] Using a natural experiment design, we analyzed 247 Census Block Groups in two coastal Texas communities (Galveston and Port Arthur) experiencing differential disaster severity. We employed ordinary least squares regression with SafeGraph foot traffic data to measure economic recovery and satellite-derived Normalized Difference Vegetation Index (NDVI) to measure green infrastructure quality. Results demonstrate that green infrastructure quality significantly correlates with post-disaster adaptation (β = 1.27, p < 0.001), independent of socioeconomic characteristics. The NDVI–severity interaction proved non-significant, indicating consistent associations across impact contexts. These findings suggest that green infrastructure supports resilience universally rather than only in moderate-risk areas. From an environmental justice perspective, equitable distribution may reduce disaster-related inequalities, supporting “bouncing forward” adaptation trajectories. Full article

Vehicular emissions are a major contributor to air pollution and respiratory morbidity in Ecuador’s urban centers. Despite increasing evidence of traffic-related health impacts, national research remains fragmented and unevenly distributed. This narrative review synthesizes 26 peer-reviewed studies published between 2000 and 2024 to characterize vehicular air pollution sources, pollutants, and respiratory health effects in Ecuador. The evidence shows a strong geographic concentration, with more than half of the studies conducted in Quito, followed by Guayaquil and Cuenca. National inventories indicate that the transport sector accounts for approximately 41.7% of Ecuador’s CO₂ emissions. Across cities, PM_2.5, PM₁₀, NO₂, CO, and SO₂ were the most frequently assessed pollutants and were repeatedly reported to approach or exceed international guideline values, particularly during traffic peaks and under low-dispersion conditions. Health-related studies documented substantial impacts, including up to 19,966 respiratory hospitalizations in Quito, with short-term PM_2.5 exposure associated with increased hospitalization risk in children. Among schoolchildren attending high-traffic schools, carboxyhemoglobin levels above 2.5% were linked to a threefold increase in the risk of acute respiratory infections. Occupationally exposed adults, such as drivers, traffic police officers, and outdoor workers with regular exposure to traffic-related air pollution, also showed a higher prevalence of chronic respiratory symptoms. Environmental evidence further highlighted the accumulation of traffic-related heavy metals (Zn, Cu, Pb, Cr) and pronounced spatial inequalities affecting low-income neighborhoods. Overall, the review identifies aging vehicle fleets and diesel-based transport as dominant contributors to observed pollution and health patterns, while underscoring methodological limitations such as the scarcity of longitudinal studies and uneven monitoring coverage. These findings provide integrated and policy-relevant evidence to support sustainable urban planning, cleaner transport strategies, and targeted respiratory health policies in Ecuador. Full article

In this paper, we investigate optimization problems for a Hermitian quadratic matrix-valued function involving two variable matrices. We derive algebraic formulas for the maximal and minimal ranks and partial inertias of this function based on a linearization method and specific block matrix rank and inertia transformations. Further, we establish necessary and sufficient conditions for the existence of solutions satisfying the associated matrix equation and various Hermitian inequalities. As applications, we obtain extremal ranks and inertias for the Hermitian generalized Schur complement with respect to Hermitian reflexive generalized inverses, and provide conditions for Hermitian reflexive generalized inverses to satisfy specific Hermitian properties. In addition, we apply these results to analyze optimization, stability, and congestion in a traffic flow network modeled by this quadratic function. Full article

Urban ecosystems are increasingly shaped by multiple environmental stressors, which may threaten both biodiversity and human well-being. We summarised the current knowledge on the ecological and social consequences of seven major urban pressures: air pollution, freshwater degradation, biological invasions, noise pollution, habitat fragmentation, soil pollution and climate crisis. Air and soil pollution, largely driven by traffic and industrial activities, compromises vegetation functions, reduces ecosystem services, and affects human health. Urban freshwater systems face contamination from stormwater runoff, wastewater, and microplastics, leading to biodiversity loss, altered ecosystem processes, and reduced water availability. Biological invasions, facilitated by human activities and habitat disturbances, reshape ecological communities, outcompete native species, and impose socio-economic costs, while management requires integrated monitoring and citizen engagement. Noise pollution disrupts animal communication, alters species distributions, and poses significant risks to human physical and mental health. Simultaneously, habitat fragmentation and loss reduce ecological connectivity, impair pollination and dispersal processes, and heighten extinction risks for both plants and animals. Collectively, these stressors interact synergistically, amplifying ecological degradation and exacerbating health and social inequalities in urban populations. The cumulative impacts highlight the need for systemic and adaptive approaches to urban planning that integrate biodiversity conservation, public health, and social equity. Nature-based solutions, ecological restoration, technological innovation, and participatory governance emerge as promising strategies to enhance urban resilience. Furthermore, fostering citizen science initiatives can strengthen monitoring capacity and create community ownership of sustainable urban environments. Addressing the combined pressures of urban environmental stressors is thus pivotal for building cities that are ecologically robust, socially inclusive, and capable of coping with the challenges of the climate crisis and global urbanization. Full article

In recent years, the rapid expansion of urban rail transit has significantly improved travel efficiency, yet it has also exacerbated spatial inequality in service coverage. Accessibility, as a fundamental metric for evaluating the equity of service distribution, remains limited by three major shortcomings in current assessment methods: the neglect of actual road network characteristics, reliance on a single static scale, and the absence of quantitative mechanisms to assess accessibility equity. These deficiencies hinder a comprehensive understanding of how equity evolves with the spatiotemporal dynamics of rail systems. To address the aforementioned issues, this study proposes an innovative spatiotemporally dynamic and multi-scale analytical framework for evaluating urban rail accessibility and its equity implications. Specifically, we develop a network-based buffer decay model to refine service population estimation by incorporating realistic walking paths, capturing both distance decay and road network constraints. The framework integrates multiple spatial analytical techniques, including the Gini coefficient, Lorenz curve, global and local spatial autocorrelation, center-of-gravity shift, and standard deviation ellipse, to quantitatively assess the equity and evolutionary patterns of accessibility across multiple spatial scales. Taking the central urban area of Hangzhou as a case study, this research investigates the spatiotemporal patterns and equity changes in metro station accessibility in 2019 and 2023. The results indicate that the expansion of the metro network has partially improved overall accessibility equity: the Gini coefficient at the TAZ (Traffic Analysis Zone) scale decreased from 0.56 to 0.425. Nevertheless, significant inequality remains at finer spatial resolutions (grid-level Gini coefficient = 0.404). In terms of spatial pattern, the core area (e.g., Wulin Square) forms a ‘high-high’ accessibility agglomeration area, while the urban fringe area (e.g., northern Yuhang) presents a ‘low-low’ agglomeration, and the problem of local ‘accessibility depression’ still exists. Additionally, the accessibility centroid has consistently shifted northwestward, and the long axis of the standard deviation ellipse has rotated from an east–west to a northwest-southeast orientation, indicating a growing spatial polarization between core and peripheral zones. The findings suggest that improving equity in urban rail accessibility cannot rely solely on expanding network size; rather, it requires coordinated strategies involving network structure optimization, branch line development, multimodal integration, and the construction of efficient transfer systems to promote more balanced and equitable spatial distribution of rail transit resources citywide. Full article

Autonomous public transport (APT) is revolutionizing urban mobility by integrating advanced technologies, including electric autonomous buses and shared autonomous vehicles (SAVs). This paper examines the historical evolution of APT, from early automation efforts in the 1920s to the deployment of autonomous shuttles in contemporary cities. It highlights technological milestones, legislative developments, and shifts in public perception that have influenced the adoption of APT. The research identifies key benefits of APT, including enhanced road safety, reduced greenhouse gas emissions, and improved cost-efficiency in public transport operations. Additionally, the environmental potential of SAVs to reduce traffic congestion and emissions is explored, particularly when integrated with renewable energy sources and sustainable urban planning. However, the study also addresses significant challenges, such as handling emergencies without human intervention, rising cybersecurity threats, and employment displacement in the transportation sector. Social equity concerns are also discussed, especially regarding access and the risk of increasing urban inequality. This paper contributes to the broader discourse on sustainable mobility, transportation innovation, and the future of smart cities by providing a comprehensive analysis of both opportunities and obstacles. Effective policy frameworks and inclusive planning are essential for the successful implementation of APT systems worldwide. Full article

This study examines the extended dissipativity analysis for newly designed mixed traffic systems (MTSs) utilizing the coupling memory sampled-data control (CMSDC) approach. The traffic flow creates a platoon, and the behavior of human-driven vehicles (HDVs) is presumed to adhere to the optimal velocity model, with the acceleration of a single-linked automated vehicle regulated directly by a suggested CMSDC. The ultimate objective of this work is to present a CMSDC approach for optimizing traffic flow amidst disruptions. The primary emphasis is on the proper design of the CMSDC to ensure that the closed-loop MTS is extended dissipative and quadratically stable. A more generalized CMSDC methodology incorporating a time delay effect is created using a Bernoulli-distributed sequence. The existing Lyapunov–Krasovskii functional (LKF) and enhanced integral inequality methods offer sufficient conditions for the suggested system to achieve an extended dissipative performance index. The suggested criteria provide a comprehensive dissipative study, evaluating $L_2-L_{\infty }$, $H_{\infty }$, passivity, and dissipativity performance. A simulation example illustrates the accuracy and superiority of the proposed controller architecture for the MTS. Full article