Search Results (11,709)

As population aging accelerates, providing psychosocial support for adults in the retirement transition has become increasingly important. For this population, a central challenge is adapting to changes in social roles, daily routines, and social relationships, yet existing social robot research has paid insufficient attention to these companionship-related needs. From an embodied cognition perspective, this study developed a needs-driven design pathway for a social companion robot for this population in urban China. Sixteen key needs were identified through user interviews and prioritized through a Kano survey with 184 valid responses from urban community-dwelling adults in the retirement transition. Based on the classification and prioritization results, these needs were synthesized into four design strategies: emotional responsiveness and trust building, social connectedness and sustained engagement, low-burden interaction and daily life support, and safety, health, and privacy protection. Privacy and safety were treated as foundational conditions for product design and practical deployment. The strategies were subsequently mapped to technical features and hardware elements through quality function deployment (QFD), using an expert-panel evaluation procedure and sensitivity analysis to determine module-level configuration priorities. A single-session, laboratory-based concept evaluation was conducted with 50 participants using concept renderings and interaction-flow videos. Concept 3, whose overall configuration emphasized coordinated voice, screen-based visual, and expression/action feedback, received a significantly higher mean participant-level Behavioral Intention (BI) score than Concept 2, which placed greater emphasis on spatial mobility assistance through a mobile wheel module (8.94 ± 0.97 vs. 8.51 ± 1.21; adjusted p = 0.003). These evaluation findings informed the final concept configuration and provided preliminary support for its companionship-oriented multimodal interaction approach. Full article

Roofing systems strongly influence the energy performance and environmental footprint of buildings, particularly in hot–arid climates such as Saudi Arabia, where cooling dominates electricity demand; however, the comparative lifecycle environmental performance of alternative roofing strategies remains underexplored in this specific climatic and market context. This study therefore aims to evaluate and compare the environmental performance of four sustainable roofing strategies against a conventional flat roof (FR) baseline in order to provide evidence-based guidance for climate-specific roofing selection in Saudi Arabia. This study conducts a comparative cradle-to-grave lifecycle assessment (LCA) of four sustainable roofing strategies considering the hot–arid climate of Saudi Arabia. Green roof (GR), cool roof (CR), solar photovoltaic roof (SPV), and roof canopy (RC) were assessed using the ReCiPe 2016 method in the SimaPro software. The environmental impacts of these strategies were assessed across product, construction, use, and end-of-life stages relative to conventional flat roofs (FRs). The results indicate that the production stage consistently contributes the highest environmental impacts, with increases ranging from 30 to 3000% for GR, CR, and RC and exceeding 10,000% for SPV. On the other hand, the use stage offers the greatest reductions ranging from 10 to 200%, particularly for SPV and CR, due to operational energy savings and electricity generation. Overall, CR demonstrates the most balanced environmental performance, combining high impact reductions with minimal trade-offs, while SPV provides significant climate and fossil resource benefits but increases mineral resource use. These findings highlight the importance of climate-specific and resource-conscious selection of roofing strategies in Saudi Arabia and provide a transferable comparative LCA framework that can inform sustainable roofing decisions in other hot–arid and hot–humid regions, in support of the Kingdom’s Vision 2030 objectives for sustainable urban development. Full article

High-precision urban vegetation mapping is essential for assessing carbon sink capacities, mitigating the urban heat island effect, and supporting sustainable development. Although deep learning and high-resolution remote sensing have advanced automated vegetation monitoring, existing models still face challenges when a common segmentation architecture is evaluated under different imaging geometries. In this study, Cityscapes and ISPRS Vaihingen are treated as two independent benchmarks representing perspective street-level imagery and orthographic aerial imagery, rather than as simultaneous cross-view inputs. “Background dominance” caused by perspective distortion and the “gridding artifacts” inherent in orthographic textures severely constrain segmentation accuracy across varying vegetation scales, particularly for small targets. To address these limitations, we propose a Scale-Aware Mixture of Experts (SA-MoE) architecture for fine-grained vegetation segmentation under two distinct imaging views, together with a scene-specific optimization strategy. The core SA-MoE framework consists of two main components. First, the spatial gating network uses a temperature polarization mechanism with τ = 0.5 to adjust the initial logit maps, sharpening expert-weight differences while preserving stable gradient propagation. Second, we use a heterogeneous expert group with five parallel branches: a pixel-level expert, three spatial experts with different dilation rates, and a global average-pooling expert. A dynamic pixel-level weighted fusion mechanism is then applied, decoupling feature extraction from receptive-field allocation. Furthermore, to address the heterogeneity of “hard samples” and “label noise” across the two benchmark settings, we introduce a scene-specific optimization strategy. Our findings show that the Focal-Dice (FD) loss is more suitable for perspective scenes with severe target imbalance and hard-to-classify vegetation targets, whereas the Cross-Entropy (CE) loss is more robust to boundary jitter in orthographic imagery. Comparative experiments on the Cityscapes (perspective view) and ISPRS Vaihingen (orthographic view) datasets reveal that SA-MoE achieves a highly competitive balance between computational efficiency and fine-grained segmentation, particularly in micro-target recall. Notably, the recall for extra-small (XS) scale targets in the aerial dataset improved by 3.21 percentage points compared to the second-best model. For the street-level dataset, our model achieved competitive global performance in terms of Overall Accuracy (OA), Precision, and F1-Score. However, we also observed a performance trade-off, where Transformer-based models maintained an advantage in preserving fine boundary details for these extra-small targets. In the routing analysis, we observed a pattern that we refer to as “receptive field inversion”, in which the model assigns lower weights to large-dilation experts for large canopy regions in orthophotos. We interpret this pattern as a plausible routing hypothesis. Overall, SA-MoE offers an efficient and adaptive solution for urban vegetation mapping under two imaging views. Full article

Port-related maritime emissions constitute a significant source of urban air pollution and greenhouse gas emissions, particularly in rapidly developing coastal cities. Within this context, the present study quantifies ship-related emissions at the Port of Casablanca, Morocco’s largest and most strategically important port, and evaluates their associated environmental and socio-economic impacts. A bottom-up methodology was applied to estimate emissions from vessel operations between 2017 and 2021. The inventory integrates vessel characteristics, engine specifications, operational load factors, emission factors, and the duration of maneuvering and hotelling phases to estimate emissions of CO₂, SO₂, NO_x, CO, NMVOCs, PM, PM₁₀, and PM_2.5. The emission inventory was subsequently coupled with damage cost factors to assess the external costs associated with shipping emissions. The obtained results demonstrate that CO₂ was the dominant emitted pollutant, representing approximately 97% of total emissions, whereas NO_x and SO₂ accounted for 2% and 1%, respectively. Bulk carriers emerged as the principal emission source (44%), followed by container vessels (36%), with the highest emission levels observed during 2018–2019, coinciding with increased port operations. Furthermore, the integration of emission inventories with damage cost factors demonstrated that NO_x, although emitted in much smaller quantities than CO₂, exerts a disproportionately higher environmental and societal burden due to its impacts on public health and ecosystem quality. This study provides one of the first integrated bottom-up emission inventories and external cost assessments for a Moroccan port. The proposed framework supports evidence-based decision-making for sustainable port management and demonstrates the need for emission reduction strategies that simultaneously address climate change and air quality objectives. Full article

In this paper, a route- and environment-aware rule-based energy management system (EMS) strategy for EVs equipped with HESSs consisting of a lithium-ion battery and a supercapacitor is proposed. The proposed rule-based EMS integrates driving mode classification, traffic conditions, road gradient, wind resistance, ambient temperature, and the supercapacitor (SOC) to determine the optimal power-sharing strategy between the battery and the supercapacitor under various driving conditions, including city, highway, and stop-and-go traffic. A mathematical model of the EV powertrain, battery, and supercapacitor is developed. The performance of the proposed rule-based EMS strategy is validated in MATLAB/SIMULINK under three representative driving cycles: the Urban Dynamometer Driving Schedule (UDDS), Artemis Motorway 130, and a Central Business District (CBD) driving cycle. It is shown that the proposed rule-based EMS strategy significantly reduces the battery current stress while increasing supercapacitor usage. Full article

Digital infrastructure (DI) and agricultural socialized services (ASSs) are key drivers of agricultural value chain efficiency (AVCE), yet their causal effects remain confounded by endogeneity bias. This study constructs an integrated SFA-Tobit-DML framework using 31-province Chinese panel data (2011–2023). SFA estimates provincial technical efficiency; Tobit provides associational benchmarks; and Double Machine Learning (DML) with K = 5 cross-fitting identifies causal average treatment effects (ATEs). The DML results validate the Tobit benchmark for DI (LassoCV ATE: 0.810, 95% CI [0.656, 0.963]; Tobit: 0.826), while revealing Tobit overestimates ASSs by approximately 37% (LassoCV: 0.850 [0.599, 1.101]; Tobit: 1.347). Bootstrap mediation tests confirm that agricultural R&D investment mediates 61.58% and 47.45% of DI and ASS effects. Heterogeneity analysis shows that urbanization amplifies DI marginal returns (ATE: 1.401 in low-urban vs. 0.711 in high-urban regions), while government intervention exhibits conditional crowding-out effects. These findings imply that policies should shift from uniform investment toward regionally differentiated strategies that account for local absorptive capacity. Full article

Most studies have explored the impact of different types of local climate zones (LCZs) on energy consumption, but few have examined climate differences within intra-local climate zones (intra-LCZs) and the impact of cold waves (CW) on energy consumption. This study conducted a 150-day long-term observation of air temperature (Ta) and relative humidity (RH) in six LCZs in Shenyang, a severe cold region, to examine climate differences within intra-LCZs and the influence of CW and the urban heat island (UHI) on energy consumption. The results show that the temperatures and heating energy consumption in 5 LCZ4s exhibited a clear gradient from the urban core to the suburbs. During CW, the differences increased, and the nighttime differences were more pronounced. CW significantly increased residential heating energy consumption, whereas the urban heat island (UHI) reduced it in urban areas. Additionally, there was a clear positive correlation between UHI and the urban-suburban energy consumption difference. Under the combined effects of CW and UHI, the average daily cumulative heating energy consumption in urban areas (CW) was much higher than in suburban areas during non-cold-wave (NCW) periods, increasing by 69.2–85.9%. This study provides empirical evidence for energy conservation and strategies for responding to extreme weather events. Full article

This study examines how spatial design, particularly lightscape interventions, operates as a behavioral nudge associated with collaborative participation intention in urban environments. Drawing on nudge theory, place attachment, and cultural heritage literature, we analyze data from a questionnaire survey of 720 urban residents across major metropolitan regions in Japan using structural equation modeling (SEM). The results indicate that urban development and cultural heritage assets are positively associated with lightscape interventions, which in turn show a strong positive relationship with collaborative participation intention. While urban development exhibits both direct and indirect relationships with participation intention, the influence of cultural heritage assets operates primarily through lightscape interventions as a mediating mechanism. These findings suggest that cultural heritage alone does not automatically stimulate civic participation; rather, its social value is activated when heritage resources are translated into meaningful spatial and visual experiences. Lightscape interventions thus serve as an effective non-coercive mechanism linking spatial and cultural resources to civic engagement intentions. This research offers valuable insights for urban planners and policymakers seeking design-based, non-coercive strategies to enhance citizens’ place attachment and willingness to contribute to community activities. Full article

Industrial heritage-based cultural and creative parks (IHCCPs) have become an important approach to adaptive reuse and sustainable urban regeneration in post-industrial cities. As the primary interface between the city and the park, entrance spaces play a critical role in shaping visitors’ first impressions, place identity, and cultural perception. Drawing on Cultural Perception Theory, this study investigates the entrance spaces of four representative IHCCPs in China using field surveys, questionnaire surveys, and a modified Importance–Performance Analysis (IPA) framework, in which the conventional importance–performance dimensions are reconceptualized as perception and satisfaction. The results indicate that the case study parks perform well in barrier-free accessibility, entrance image, and material application. Based on the perception–satisfaction analysis, the entrance-space attributes were systematically classified according to their relative strengths and improvement priorities, providing the basis for identifying key optimization directions. Accordingly, a perceptual experience-oriented optimization framework is proposed, comprising four complementary strategies: functional coordination, environmental layering, landmark organization, and cultural translation. By integrating Cultural Perception Theory into an adapted IPA framework for entrance-space evaluation, this study extends existing research and provides a practical framework for the adaptive reuse of industrial heritage and the regeneration of public spaces in comparable post-industrial contexts. Its broader applicability to different geographical and cultural settings warrants further validation through future research. Full article

The present research investigates the relationship between urban regeneration initiatives and residential real estate market dynamics by assessing market price appreciation associated with the factors most commonly considered in housing transactions. The study focuses on the Esquilino district in the city of Rome (Italy) with particular attention to the redevelopment of Piazza dei Cinquecento, the major public space located in front of Roma Termini railway station. The intervention aims to improve urban accessibility, reduce traffic congestion, and enhance public space quality through a new spatial configuration and the creation of a tree-lined area. The objective of the study is to verify whether, and to what extent, the ongoing regeneration project has influenced residential property values. To achieve this goal, an econometric analysis is implemented to quantify the contribution of different housing and locational attributes to residential asking prices and to identify the variables that significantly affect value formation within the local market. Given that the initiative is still in progress and approaching completion, the analysis adopts a diachronic perspective by comparing two distinct temporal stages: the ante project phase (second half of 2021) and the in itinere phase (first half of 2025). Building on the findings of a previous pre-intervention study, the research systematically examines changes in market behaviors over time, with the dual purpose of identifying variations in price determinants and analyzing the associations between the current urban transformations and the residential real estate market. The results indicate a substantial stability in the main determinants of residential property prices across the two periods, suggesting that the regeneration initiative has not yet been fully capitalized into market behaviors. However, variations in the contribution and functional relationships of some spatial variables highlight preliminary signs of market adjustment during the ongoing transformation process. The study highlights the importance of monitoring for assessing how urban regeneration processes are progressively incorporated into real estate market dynamics. The proposed framework provides a transferable tool for evaluating regeneration processes in different urban contexts, supporting evidence-based decision-making and the comparative assessment of urban transformation strategies. Full article

Nature-Based Solutions (NBS) have emerged as a key strategy to address complex and intensifying urban sustainability challenges, yet empirical assessments of regulatory frameworks that operationalize these strategies remain limited. This study addresses that gap through an empirical evaluation of the Green Area Ratio (GAR), a hybrid performance-based zoning regulation for sustainable landscapes in Washington, DC, using more than a decade of regulatory implementation data. Regulatory plan approval records from 1329 private properties subject to GAR between 2015 and 2025 were analyzed to examine trends in landscaping Best Management Practice (BMP) selection, relationships with parcel characteristics, and interactions with stormwater management requirements. Over this period, approximately 184 ha of multifunctional NBS were approved through GAR plans primarily consisting of landscaping areas, plantings, and tree planting and preservation, often combined through BMP stacking and amplified by a native plant bonus. BMP selection varied significantly according to zoning district, lot area, and GAR Score Requirement. Importantly, GAR requirements influenced BMP selection differently than stormwater requirements. The findings suggest that simplicity, flexibility, and adaptability of the GAR make the regulation a versatile policy instrument for DC and a useful model for cities seeking to expand NBS through performance-based zoning regulation. Full article

Rapid peri-urban sprawl is intensifying flood risk by replacing natural landscapes with dense, impervious residential developments. Thailand’s land use regulations require a 5% minimum green space allocation for new housing developments as a measure to promote livability and well-being. Green space also has the potential to sustainably manage stormwater runoff, but for Thailand’s peri-urban development, the question remains whether 5% green space is sufficient to reduce flood risk. As such, this study critically evaluates whether this 5% green space guideline is sufficient for peri-urban runoff and flood management in peri-urban Pathum Thani, particularly given the acceleration of Bangkok’s urban sprawl over the past 30 years. Using a multi-scalar framework, we integrated GIS spatial analysis of 164 gated communities (1995–2025) with site-specific PCSWMM hydrologic modeling to test baseline conditions and Nature-based Solution (NbS) interventions against 5-, 10-, 50-, and 100-year design storms. Findings reveal developers generally adhere to the 5% guideline, thereby addressing policy while maximizing salable land space. PCSWMM simulations show the 5% baseline alone does not adequately manage runoff, with localized residential flooding expected for a 5-year design storm under current baseline conditions. Scenario testing indicates a hybrid grey–green infrastructure approach would optimally manage flooding. Given economic barriers to expanding open space, converting roads to permeable pavements offers a possible optimization strategy. Ultimately, static area-based regulations remain insufficient; policies must transition to performance-based volumetric retention targets to mitigate downstream flooding and foster resilient communities. Full article

Open Government Data (OGD) has the potential to support urban planning by increasing transparency, improving evidence-based decision-making, enhancing public participation, and monitoring progress toward sustainability goals. Despite this potential, the extent to which OGD supports planning and sustainability in practice remains unclear. This study evaluates the user-friendliness of OGD portals in 19 U.S. cities using four criteria identified in the literature: breadth of portal content, structure of governance, user-friendly support, and equitable user access. It also examines how cities incorporate OGD into OGD policies, general plans, and sustainability/climate action plans. This study was designed as an exploratory comparative case study of OGD practices, and the methods included portal assessment using four criteria, content analysis of OGD policies and plans, and semi-structured interviews with OGD and planning experts. The findings indicate that most OGD portals function primarily as data repositories, rather than as planning support tools, and vary considerably in portal content, governance, and user support, affecting their usefulness for planning and sustainability efforts. OGD policies are often absent or underdeveloped and typically emphasize transparency rather than planning applications or public engagement. Only nine cities identified a role for OGD in at least one planning-related document. Interviewees identified low public awareness, limited user capacity, and insufficient integration of data into decision-making as key barriers. The findings identify practical strategies that cities can adopt to better integrate OGD into urban planning and sustainability, including proactive identification of datasets and indicators that will be of interest to various stakeholders, improved stakeholder engagement, data standardization, use of graphics to highlight policy-relevant data trends, improved OGD management, and closer alignment between OGD initiatives and action-oriented planning processes. Full article

Extreme weather events increasingly threaten urban smart grids, where sudden power outages constitute not merely technical failures but socio-technical crises that test the very fabric of sustainable emergency governance. Drawing on framing theory, this study uses a 2 × 2 experiment with 1195 participants to examine how information content and timing affect public compliance. Results show action framing outperforms interpretive framing, with trust and safety mediating 46.9% and 34.7% of the effect. Timing moderates these pathways: action framing boosts compliance via trust and safety during crisis, while interpretive framing sustains compliance via safety and trust repair after restoration. This temporal asymmetry advances crisis communication theory and offers guidance for sustainable governance, turning crisis communication into a stage-matching process that bridges short-term recovery and long-term resilience. Full article

As urban housing becomes increasingly compact and companion animals become more deeply integrated into domestic life, human–cat cohabitation presents design challenges related to spatial efficiency, furniture wear, maintenance, and everyday coexistence. This study examines shared-interface conflicts in compact apartments and proposes an integrated SOR–Kano–FBS pathway for sustainable human–cat shared furniture design. In-home observations, semi-structured interviews, behavioral path recording, and Kano questionnaires were used to identify high-frequency activity contexts and prioritize user requirements. These requirements were translated through the FBS model into functional objectives, behavioral scripts, and structural strategies. The results indicate that ease of cleaning and maintenance, structural stability and user-perceived safety, and dedicated scratching guidance primarily represent must-be requirements. Movement-path separation, centralized storage, and aesthetic integration function as performance-enhancing requirements, whereas shared yet stratified zoning, elevated observation points, and moderate visual connection improve the cohabitation experience. Two conceptual designs—a human–cat shared living-room sofa system and a foldable work/study system—were developed. Their descriptive comprehensive acceptance indices were 0.802 and 0.794, respectively, while a combined conventional-furniture reference set scored 0.520. Because the reference set represented two conventional activity contexts, these values were used only as diagnostic, user-perception-based evidence and not as inferential proof or a direct ranking between the schemes. The findings suggest that the proposed pathway can support design-level sustainability in compact human–cat cohabitation; however, further validation through physical prototypes, long-term in-home testing, and life-cycle assessment is required. Full article