Search Results (4,302)

Globally, the rise in car ownership and usage has intensified parking challenges, particularly within central business districts (CBDs) of many developed cities. Scarce parking infrastructure and escalating land values have further exacerbated these issues, leading to heightened competition among business owners, residents, shoppers, and clients for the limited available paid and free on-street parking spaces. Against this backdrop, the present study sought to model the determinants of motorists’ parking challenges using a recursive structural equation model (RSEM), drawing on empirical evidence from Greater Kumasi, Ghana. Primary data were collected through a structured survey involving 1000 drivers within the designated catchment area, employing cluster and systematic sampling techniques to ensure representativeness. The findings reveal that four out of five structural paths of the constructs exerted significant influences on the structural model components. Both time-related indices and parking costs demonstrated direct and indirect effects on parking challenges, with vehicle type serving as a mediating variable. Furthermore, most of the measurement models significantly impacted the latent factors, either positively or negatively, highlighting the complex interrelationships between parking behavior and underlying determinants. Overall, this study makes several contributions: it provides localized empirical evidence from a developing-country context, offers theoretical refinements to existing models, demonstrates methodological rigor through the application of RSEM, and proposes practical policy insights to address urban parking challenges in rapidly growing African cities such as Kumasi. Full article

As a key indicator for measuring urban green visibility, the Green View Index (GVI) reflects actual visible greenery from a human perspective, playing a vital role in assessing urban greening levels and optimizing green space layouts. Existing studies predominantly rely on single-source remote sensing image analysis or traditional statistical regression methods such as Ordinary Least Squares and Geographically Weighted Regression. These approaches struggle to capture spatial variations in human-perceived greenery at the street level and fail to identify the non-stationary effects of different drivers within localized areas. This study focuses on the Luolong District in the central urban area of Luoyang City, China. Utilizing Baidu Street View imagery and semantic segmentation technology, an automated GVI extraction model was developed to reveal its spatial differentiation characteristics. Spearman correlation analysis and Multiscale Geographically Weighted Regression were employed to identify the dominant drivers of GVI across four dimensions: landscape pattern, vegetation cover, built environment, and accessibility. Field surveys were conducted to validate the findings. The Multiscale Geographically Weighted Regression method allows different variables to have distinct spatial scales of influence in parameter estimation. This approach overcomes the limitations of traditional models in revealing spatial non-stationarity, thereby more accurately characterizing the spatial response mechanism of the Global Vulnerability Index (GVI). Results indicate the following: (1) The study area’s average GVI is 15.24%, reflecting a low overall level with significant spatial variation, exhibiting a “polar core” distribution pattern. (2) Fractal dimension, normalized vegetation index (NDVI), enclosure index, road density, population density, and green space accessibility positively influence GVI, while connectivity index, Euclidean nearest neighbor distance, building density, residential density, and water body accessibility negatively affect it. Among these, NDVI and enclosure index are the most critical factors. (3) Spatial influence scales vary significantly across factors. Euclidean nearest neighbor distance, building density, population density, green space accessibility, and water body accessibility exert global effects on GVI, while fractal dimension, connectivity index, normalized vegetation index, enclosure index, road density, and residential density demonstrate regional dependence. Field survey results confirm that the analytical conclusions align closely with actual greening conditions and socioeconomic characteristics. This study provides data support and decision-making references for green space planning and human habitat optimization in Luoyang City while also offering methodological insights for evaluating urban street green view index and researching ecological spatial equity. Full article

This study proposed a methodology for obtaining a valid database of food retail establishments and characterized the community food environment, understood as the distribution and type of food outlets, in a Brazilian medium-sized municipality after the collapse of a mining tailings dam. An ecological study was conducted with establishments selling food for home consumption (butcher shops, fish markets; fruit and vegetable specialty markets; large- and small-chain supermarkets; bakeries and local markets) and immediate consumption (bars, snack bars, and restaurants). For home-consumption establishments, data were requested from governments and completed with website/app searches, virtual audits (Google Street View), and on-site audits. For immediate-consumption establishments, only on-site audit was used due to the low quality of the secondary databases. Agreement between databases was assessed with the Kappa statistic. Density (d) was calculated by the area (in km²) of the sampling stratum. Public databases presented low validity (23.0%; Kappa −0.388; p = 1.000), even after virtual auditing (31.4%; Kappa 0.37; p < 0.001). 96 establishments for home consumption and 261 for immediate consumption were identified, with predominance of local markets (35.4%), bars (35.2%), and snack bars (29.1%). The region with the highest density of establishments was the “Other Areas” stratum (d = 4.7 for home-consumption establishments and d = 13.2 for immediate-consumption establishments). Audit proved most effective, especially for small establishments. The lack of governmental databases and the identified food environment should inform municipal policies to promote food and nutrition security and reduce inequalities after the disaster. Full article

The quality of the soundscape in historical districts is receiving increasing attention from urban governments due to its significant potential to highlight historical characteristics and enhance the acoustic environment of urban areas. However, there is still a lack of research on the relationship between natural and cultural soundscapes as they interact in historic areas. Using the historical area of Wuhou Shrine Museum in Chengdu as a case study, this study analyzed the differences in sound levels, sound source recognition, and subjective perception between two distinct spatial types: the historical street and adjacent urban forest. Additionally, structural equation modeling (SEM) was employed to explore the impact of sound source recognition and sound levels on subjective perception. The results reveal the following: (1) The soundscape interaction between the historical street and the adjacent urban forest exhibits a conflicting relationship, with cultural and natural soundscapes struggling to coexist harmoniously. (2) Within the historical region, L₁₀ has the strongest effect on subjective evaluation, while L₉₀ has the weakest. (3) Quietness is not always positively correlated with comfort and pleasure, indicating that a tranquil environment does not necessarily enhance pleasantness. These findings provide differentiated soundscape optimization strategies tailored to historical areas. Full article

Recognizing the negative consequences of auto-oriented urban transportation, Chinese cities began developing Urban Street Design Guidelines (USDGs) in 2016. The literature on urban transportation design from a decision-making perspective is very limited. As the first systematic evaluation of the pioneering effort by cities in China, this study analyzes local USDG documents and interviews key practitioner stakeholders from ten large cities by adapting a leading policy evaluation tool of urban street design for sustainable transportation based on the Complete Streets Policy Framework. A total of 11 USDGs adopted between 2016 and 2020 were evaluated to represent the wide range of urban contexts in China. The evaluation revealed an average performance of only 30.9% of the total possible score. Despite strong aspirations, local USDGs face significant implementation challenges, lack consideration of disadvantaged communities, and need clarify modal priorities in diverse contexts. Targeted improvements could contribute to more effective and sustainable urban street building and management in China’s cities. As an ex-ante assessment, this study provides a key reference for the future analyses of the outcomes of local USDGs. Full article

Among wireless communication technologies underlying Internet of Things (IoT)-based smart buildings, IQRF (Intelligent Connectivity Using Radio Frequency) technology is a promising candidate due to its low power consumption, cost-effectiveness, and wide coverage. However, effectively modeling the propagation characteristics of IQRF in complex indoor environments for simple and accurate network deployment remains challenging, as architectural elements like walls and corners cause substantial signal attenuation and unpredictable propagation behavior. This study investigates the applicability of a site-specific modeling approach, originally developed for urban street canyons, to characterize peer-to-peer (P2P) IQRF links operating at 868 MHz in typical indoor scenarios, including line-of-sight (LoS), one-turn, and two-turn non-line-of-sight (NLoS) configurations. The received signal powers are compared with well-known empirical models, including international telecommunication union radio communication sector (ITU-R) P.1238-9 and WINNER II, and ray-tracing simulations. The results show that while ITU-R P.1238-9 achieves lower prediction error under LoS conditions with a root mean square error (RMSE) of 5.694 dB, the site-specific approach achieves substantially higher accuracy in NLoS scenarios, maintaining RMSE values below 3.9 dB for one- and two-turn links. Furthermore, ray-tracing simulations exhibited notably larger deviations, with RMSE values ranging from 7.522 dB to 16.267 dB and lower correlation with measurements. These results demonstrate the potential of site-specific modeling to provide practical, computationally efficient, and accurate insights for IQRF network deployment planning in smart building environments. Full article

Building cycling-friendly street environments is crucial for promoting sustainable urban mobility. However, existing studies exploring the influence of the built environment on cycling have paid limited attention to the three-dimensional characteristics of street landscapes and have mostly relied on linear assumptions. To address these gaps, this study employs street view imagery and interpretable machine learning methods to investigate the nonlinear and interaction effects of street landscape elements on residents’ cycling preferences in Xiamen Island, China. The results reveal that the visual indices of buildings, sky, vegetation, and roads are the most influential variables affecting cycling preferences. These factors exhibit pronounced nonlinear relationships with cycling preference. For instance, buildings exhibit a threshold effect, with positive influences on cycling preference when the building index is below 0.12 and negative effects when it exceeds 0.12. A low sky index significantly suppresses cycling preference, whereas higher values offer only limited additional benefits, with an optimal range of 0.1–0.25. Vegetation contributes positively only at relatively high levels, suggesting that its index should ideally exceed 0.3. The road index shows a V-shaped relationship: values between 0.15 and 0.25 reduce cycling preference, whereas values below 0.15 or above 0.25 enhance it. Moreover, clear interaction effects among these variables are observed, suggesting that the combined visual composition of the streetscape plays an important role in shaping cycling preferences. These findings deepen the understanding of how street landscape characteristics influence cycling behavior and provide nuanced, practical insights for designing cycling-friendly streets and promoting sustainable travel in urban environments. Full article

Research efforts to explain urban vitality encompass accessibility studies, place-based qualitative studies, morphological analysis, and land use studies. While several of these isolated approaches have yielded promising results, integrating these explanatory frameworks into a single model remains underexplored—and this constitutes the core goal of the present research. For the empirical study on the vitality of a commercial district, 13 explanatory factors were identified, with measured pedestrian flow (as a proxy for street vitality) serving as the dependent variable, examined in the Chunxi Road area of central Chengdu. To account for temporal variations in street vitality, pedestrian flow was measured across different times of the day and days of the week. Bivariate analysis and principal components analysis were employed to develop a multivariate regression model, which was further refined into a predictive algorithm tool to quantify the relative contributions of the explanatory factors. The results indicate that accessibility and street image factors each independently explain a large proportion of the variance in pedestrian flow, while public transport topological distance exerts a negative effect. Notably, the combined model exhibits significantly stronger explanatory power than the individual contributions of various factors reported in existing literature. Beyond advancing theoretical understanding of urban vitality, the primary purpose of this study is to utilize street vitality (operationalized via pedestrian flow) as an optimization indicator for commercial street planning and design schemes. The developed predictive algorithm model serves as a practical tool for designers, providing actionable references during the design formulation process, enabling them to assess potential street vitality based on preliminary design parameters and make evidence-based adjustments to enhance the effectiveness of commercial street designs. Additionally, the study findings offer insights for the management of urban commercial areas to further promote urban vitality. Full article

This study investigates how the expansion of Warsaw’s metro system—specifically the opening of the second underground line (M2)—affects urban vibrancy, defined as the diversity and intensity of social, economic, and cultural activities. Using a spatial panel Difference-in-Differences (DiD) model with two-way fixed effects, the analysis examines changes in local vibrancy, proxied by the density of small catering businesses (SCB), across four years (2019–2023). Our results show that while built environment features such as building footprint, parking area, and street furniture positively correlate with vibrancy, the short-term effect of new metro stations is negative: areas within a 15 min walking distance of new stations experienced a relative decline in local activity compared to control areas. This pattern likely reflects a behavioral shift, as residents and consumers increasingly use the metro to access amenities in central, already vibrant districts. However, the effect attenuates over time, suggesting that neighborhoods gradually adapt to new mobility conditions. The findings highlight that large-scale transport investments may generate temporary disruptions before fostering long-term equilibrium and renewed urban vitality, underscoring the need for adaptive urban policies that mitigate transitional impacts and support local socio-economic resilience. Full article

In the context of sustainable development, the concept of active mobility plays a key role in modern urban areas. To evaluate active mobility in these areas, we formulate a framework for characterising active mobility by calculating street network indices using global, free, and open data. This framework comprises the download and processing of pedestrian, cycling, driving, and public transport street networks from OpenStreetMap, the selection of street network indices from the academic literature, and their implementation and calculation. A total of 50 indicators are reported for each urban area distributed in eight index types, including thematic variables, proximity to Points of Interest (POIs), proximity to public transport, intersection density, street density, street length, link–node ratio, circuity, slope, and orientation entropy. To test the framework, we calculate street network indices for pedestrian and cycling networks for the urban areas of 176 cities from around the world. The resulting dataset is published as open data. An analysis of the calculated indices indicates that cities in higher-income economies generally exhibit better conditions for active mobility, especially in Europe, attributed to better map completeness, and to more compact and connected urban areas where it is easier to access amenities and public transport. Full article

Energy efficiency is widely recognized as a critical strategy for reducing energy consumption in industrial systems. Improving energy efficiency has become a central point in industrial systems aiming to reduce energy consumption and operational costs. Industrial air compressors are among the most energy-intensive assets and often operate under static control policies that fail to adapt to real-time dynamics. This paper proposes a cognitive digital twin (CDT) framework that integrates reinforcement learning as, especially, a Proximal Policy Optimization (PPO) agent into the virtual replica of the air compressor system. CDT learns continuous from multidimensional telemetry which includes power, outlet pressure, air flow, and intake temperature, enabling autonomous decision-making, fault adaptation, and dynamic energy optimization. Simulation results demonstrate that PPO strategy reduces average SEC by 12.4%, yielding annual energy savings of approximately 70,800 kWh and a projected payback period of one year. These findings highlight the CDT potential to transform industrial asset management by bridging intelligent control. Full article

Symbiosis and synergy among urban uses are key determinants of spatial quality, liveability, and resilience. While symbiosis denotes the coexistence of users and functions within specific places, synergy refers to the collective benefits emerging from their interaction. These dynamics are especially relevant in city centres and main streets, which serve as structural and social backbones of urban life. This article applies the SyM_SyN Method to Zwycięstwa Street in Gliwice, Poland, to assess the intensity and distribution of symbiotic and synergistic relations. The analysis identified significant spatial deficiencies that weaken the coherence and attractiveness of the street. The results demonstrate how a systematic, data-driven evaluation can expose hidden weaknesses in urban structures. Importantly, from the perspective of the smart city paradigm, liveability and responsiveness of urban spaces cannot be reduced to technology-driven systems of sensors and devices. They must also be understood in terms of human-scale interactions and the ability of urban form to support them. Beyond its methodological contribution, the study emphasises the practical implications for urban renewal: reinforcing positive interactions between adjacent uses enhances street vitality, improves social inclusiveness, and supports more sustainable development strategies. The SyM_SyN Method thus provides both an analytical framework and a decision-support tool for designing user-oriented, high-quality urban spaces within the broader smart and sustainable city paradigm. Full article

Packet delivery in vehicular ad hoc networks degrades under realistic road dynamics, where mobility and local density vary over time and across road layouts. This study revisits route lifetime control in AODV and introduces Vehicular Traffic Condition-Based AODV, which adjusts the Active Route Timeout and the Delete Period Constant online at each HELLO reception using locally observable cues on neighbor density and short-term speed variation. The design is empirically informed by OpenStreetMap and SUMO mobility with OMNeT++/Veins/INET co-simulation. The analysis highlights two recurrent patterns that guide the method: (i) an intermediate neighbor-density range—roughly from the mid-teens to about twenty neighbors—where average speed tends to vary more rapidly; and (ii) a distribution of short-term speed-change magnitudes, sampled at the instants of HELLO reception, that is concentrated within a narrow interval with a light upper tail. Accordingly, the proposed method increases or decreases route-entry lifetimes with heightened responsiveness inside this density range, while applying conservative updates elsewhere to mitigate oscillations. Evaluation across multiple vehicular-traffic conditions spanning three fleet sizes (200, 300, 400 vehicles) and three speed-limit settings (10, 20, 30 km/h) demonstrates consistent packet delivery ratio gains over conventional AODV and close tracking of the best static lifetime configurations identified per condition. The gains are attributable to timely pruning of unstable paths and sustained retention of stable paths, which increases valid forwarding opportunities without centralized coordination. Full article

Background: Antibiotic drug resistance is a serious global health problem that threatens therapeutics against infectious diseases. As antibiotics become less effective every year, our objective was to evaluate the adjuvant activity of methanolic extracts of Moringa oleifera seed combined with antibiotics of clinical use against multidrug-resistant Escherichia coli isolated from street food samples searching for a new alternative to treat infectious diseases commonly treated with antibiotics. Methods: Secondary metabolites of M. oleifera seeds were obtained through maceration (methanol 80%) and detected following qualitative phytochemical assays. MIC, MBC and tolerance level were determined using microdilution tests. Antimicrobial activity was tested by sensitivity analysis, and the adjuvant activity was explored in combination with twelve antibiotics against the E. coli samples. Results: Alkaloids, phenolic compounds, flavonoids, and polyphenols were detected. MIC and MBC values ranged from 31.3 to 62 mg/mL and 62–125 mg/mL, respectively. The extract showed low antimicrobial activity against the multidrug-resistant E. coli, but the inhibitory capacity of ampicillin, cephalexin, and amoxicillin/clavulanic acid was significantly increased when combined with the plant extract. In contrast, the activity of ciprofloxacin, levofloxacin, tetracycline, polymyxin, and nalidixic acid decreased with the extract. Conclusion: Methanolic extracts of M. oleifera seeds represent a potential adjuvant for beta-lactams in the face of the growing problem of global antimicrobial resistance. This study represents the first steps in exploring the adjuvant capacity of plants against resistant environmental pathogens in Mexico. Full article

Hydropower is the primary source of electricity in several countries in Latin America. Hydropower provides approximately 80% of Ecuador’s electricity; however, it remains highly vulnerable to climate change, resulting in uncertainties in power generation due to altered precipitation patterns, runoff, and systematic failures. Consequently, Ecuadorians are becoming increasingly reliant on diesel generators during crises, resulting in public health, safety, and economic impacts, as well as social and political disruptions. This study evaluated noise pollution in the central urban area of the city of Loja for the first time during the 2024–2025 electricity crisis in Ecuador. A Type 1 integrating sound-level meter was used to monitor noise pollution (LAeq, 10min) at 20 locations during periods of generator operation and non-operation. At each location, the number of generators, the density of commercial activities along the streets, as well as traffic and other urban characteristics, were recorded. Results revealed that the presence of generators, street width, and the number of generators significantly increased the LAeq, 10min, often exceeding the limits set by the World Health Organization and Ecuador’s environmental regulations. Frequency spectrum analysis revealed that medium frequencies increased with A-weighting, while low frequencies rose with C-weighting, suggesting potential health risks to the local population. The thematic noise map during generator inactivity showed lower noise levels, averaging around 71.5 dBA. Conversely, when the generators were operational, noise levels exceeded 79.6 dBA, indicating a significant increase in environmental noise exposure associated with their use. This highlights an urgent need to implement and expand renewable energy sources, as existing options like wind power, photovoltaic energy, and biomass are insufficient to meet community demands. Full article