Search Results (1,259)

With the development of autonomous driving and intelligent connected vehicle technologies, the vehicle cabin is shifting from a simple transportation space to an intelligent mobile space integrating infotainment, interaction, and rest, and passenger comfort has gradually become an important factor affecting user experience, system trust, and perceived safety. Focusing on three categories of cabin environmental factors, namely the acoustic, optical, and thermal environments, this study develops an experimental design and comprehensive modeling method for passenger comfort evaluation. First, controlled single-factor experiments were conducted to establish quantitative mapping relationships between physical environmental parameters and subjective comfort ratings. The analytic hierarchy process (AHP) was then used to determine the weights of each indicator, and a penalty-based aggregation mechanism was introduced to construct a comprehensive comfort evaluation model. Finally, external validation was performed on an independent vehicle platform to examine the model’s applicability and consistency. The results show that acoustic comfort decreases as the sound pressure level increases, whereas optical and thermal comfort exhibit nonlinear behavior with optimal intervals. AHP weight results show that the thermal environment has the highest weight (0.4280), followed by the acoustic environment (0.3305) and the optical environment (0.2415). The external validation results indicate that the proposed model exhibits good predictive consistency across three steady-state operating conditions, with a mean absolute error of 0.122, a root-mean-square error of 0.150, and a Pearson correlation coefficient of 0.960. The findings show that the penalty-based aggregation model can effectively characterize the limiting-factor effect under the joint action of multiple environmental factors, providing a computable and interpretable evaluation framework for intelligent cockpit environmental control and automotive engineering experimental teaching. The conclusions of this study are mainly applicable to the current experimental platform and steady-state operating conditions, and further validation is still required with more vehicle models, dynamic road scenarios, and complex multi-environment factor disturbances. Full article

Existing research on the landscape patterns of urban parks and green spaces demonstrates a disproportionate focus across tiers within China’s urban hierarchy. Numerous studies have concentrated on economically developed first-tier cities, such as Beijing, Shanghai, and Guangzhou. In contrast, medium-to-large non-first-tier cities, especially provincial capitals and emerging cities within the first- and second tiers, have been relatively understudied, although they have received increasing attention in recent years. This bias extends regionally, with studies predominantly examining cities in the more developed central and eastern regions, while less-developed areas and lower-tier cities receive significantly less attention. This study tracks changes in park quantity, spatial concentration, patch structure and driver associations at three planning-related time points. Shenyang provides a distinct cold-region and old industrial city case, shaped by long winters, industrial renewal and outward urban growth. Furthermore, to inform park and green-space planning in Northeast China’s cold-climate cities, exemplified here by Shenyang, a major metropolis with a monsoon-influenced humid continental climate (Köppen Dwa), long cold winters, and relatively short warm summers, we document a shift in park distribution from the urban core to peripheral areas. Based on park vector layers reconstructed from planning documents, remote sensing interpretation and field verification, this study combined spatial analysis, landscape metric calculation and driver-association modeling. ArcGIS Pro was used to identify changes in distribution centers, directional extension and local clustering; FRAGSTATS 4.2 was used to calculate park landscape metrics; and SIMCA-P 14.1 was used to examine the statistical associations between selected landscape indicators and potential driving variables. The results show that the number and total area of parks in central Shenyang increased substantially from 2000 to 2024. Spatially, park distribution became less concentrated in the traditional inner city, while new clusters gradually appeared in peripheral districts and newly developed urban areas. The old urban core remained important, but its dominance weakened as park provision expanded outward. The landscape metric results further indicate that park expansion was accompanied by more irregular patch forms, stronger fragmentation and declining structural continuity. The driver association analysis suggests that climate conditions, population change, industrial restructuring, real estate investment, road construction and urban greening policies were related to different aspects of park landscape change. These associations should be interpreted as statistical relationships rather than direct causal effects. Overall, this study clarifies the spatial restructuring of park green spaces in a cold-region old industrial city and provides planning evidence for improving park connectivity, coordinating green space expansion with urban construction and supporting sustainable park system development in Northeast China. Full article

Within the trans-regional ecological governance framework of the Yangtze River Delta (YRD), Anhui Province acts as a critical ecological barrier. Yet, intra-provincial disparities in the fiscal pressure of ecological compensation remain underexplored. Drawing on panel data from 16 prefecture-level cities in Anhui (2018–2024), we develop a hierarchy–region dual-dimensional framework. This framework measures fiscal pressure by integrating cost–benefit and opportunity–cost methods. A two-way fixed-effects model exhibits a distinct spatial gradient: fiscal pressure decreases in the order of Southern (19.58%) > Northern (13.45%) > Central Anhui (5.24%). Mechanism tests support the “Triple Systemic Mismatch” as a coherent interpretive lens: fiscal pressure is positively associated with ecological contribution and negatively associated with fiscal capacity and industrial structure. Furthermore, regional integration policy significantly alleviates such fiscal pressure. Accordingly, this study puts forward a three-dimensional sharing mechanism that integrates government coordination, market empowerment, and social participation to support equitable cross-regional governance. Full article

The pursuit of sustainable winter road maintenance has intensified the need for deicers that balance functional effectiveness, economic viability, and minimal environmental impact. However, the absence of a systematic, multi-dimensional evaluation framework has hindered informed product selection and green procurement. This study develops and validates the Comprehensive Deicer Multi-criteria Evaluation System (CDMES)—a structured assessment framework that integrates economic, functional, environmental, and infrastructural sustainability dimensions. The evaluation index system was constructed for deicers, consisting of 18 indicators including preparation cost, engineering maintenance cost, operability of agent preparation, application difficulty, asphalt binder adhesion loss, minimum application concentration, proportion of active ingredients, effective time, ambient temperature, freezing point, solid dissolution rate, relative snow/ice-melting capacity, seed damage rate, chlorophyll attenuation, soil pH, aqueous solution pH, steel–carbon corrosion rate, and pavement friction attenuation rate. Subsequently, the analytic hierarchy process (AHP) was employed to determine the weight of each indicator, and evaluation criteria were established in accordance with relevant standards and literature. Finally, this weight determination method, combined with the simple additive weighting (SAW) method for index aggregation, forms a quantitative evaluation model. These elements together constitute a comprehensive deicer evaluation system, designated as the Comprehensive Deicer Multi-criteria Evaluation System (CDMES). Validation using three representative deicers—sodium chloride, a composite chloride-based formulation, and an organic acetate-based product—demonstrated that the CDMES can effectively discriminate product performance across multiple sustainability dimensions and identify critical weaknesses that may be obscured by purely compensatory scoring. The framework offers a transparent and reproducible decision-support tool for winter maintenance managers seeking to align deicer selection with sustainability objectives. Full article

The seismic retrofit of existing reinforced concrete (RC) buildings equipped with dissipative bracing systems requires not only a global performance-based assessment, but also a rigorous verification of the local behavior of critical structural connections. In this context, the present study focuses on the numerical seismic performance of a beam–column connection extracted from a retrofitted RC hospital building located in Italy. The investigated joint represents a central node where two orthogonal steel bracing systems converge and transfer seismic forces to an RC column strengthened with heavy steel jacketing and anchorage devices. A detailed three-dimensional finite element model of the connection is developed using solid elements for concrete and steel components, explicit modeling of reinforcement bars, bolts, and anchor rods, and advanced nonlinear constitutive laws for both materials. Two modeling strategies are considered, including the explicit simulation of contact interfaces between steel components, in order to capture local stress redistribution and potential interaction effects. The connection is subject to seismic demand derived from the global structural analysis, corresponding to different values of the behavior factor, thus ensuring consistency between global design assumptions and local verification. The results highlight the progressive activation of nonlinear mechanisms within the steel components, the development of cracking and compression damage in the concrete core, and the preservation of a clear hierarchy of resistances under design-level seismic actions. The numerical outcomes allow a critical discussion on the role of local connection behavior in supporting the global dissipative strategy and provide quantitative insights into the evaluation of the behavior factor from a local-response perspective. The study emphasizes the importance of detailed connection-level analyses in the seismic retrofit of strategic facilities and supports a more consistent integration between global performance objectives and local structural design. Full article

High-latitude, cold-climate cities have long faced inherent climatic disadvantages due to prolonged frigid winters, historically limiting their attractiveness for population inflow. Global warming, particularly the polar amplification effect, offers potential for improving climate livability in such cities, creating new opportunities for population redistribution and urban development. Taking Harbin, a representative cold-climate city in Northeast China, as a case study, this research integrates meteorological data (2010–2023) with questionnaire responses from 1053 recent in-migrants. Using Analytic Hierarchy Process and Structural Equation Modeling, we systematically examine how climate livability is associated with migration decisions. The key findings are as follows. (1) Harbin’s climate livability improved significantly from 2010 to 2023. (2) In-migrants display a spatial pattern of “proximate dominance and distant diversity”, with pronounced heterogeneity in climate perception and satisfaction across origin regions. (3) Climate livability is associated with settlement intention through a partial mediation pathway: the indirect effect via deep adaptation (β = 0.330) accounts for 37.2% of the total effect, while a significant direct effect (β = 0.559) also exists, correcting an earlier inflated full-mediation estimate. (4) This perception–adaptation–decision pathway remains stable across subgroups and is not significantly moderated by origin climate contrast or occupational exposure, although boundary conditions apply. (5) Migration decisions involve trade-offs between climatic experience and socioeconomic rationality: climate livability reinforces long-term settlement intentions through psychological adaptation, while short-term migration is chiefly driven by socioeconomic factors. These findings provide empirical evidence and policy insights for cold-climate cities, such as Harbin, aiming to establish inclusive adaptation support systems and implement phased, context-sensitive population strategies. Full article

Rapid urbanization and escalating demands for pollution and carbon reduction pose significant challenges to the cement industry in China, characterized by high energy consumption and emissions. However, a multidimensional framework to assess the synergies and trade-offs between environmental, carbon, and economic effects for various decarbonization technologies in cement production is still lacking. Here, six application scenarios of new suspension preheater dry process cement production were developed and evaluated using a life cycle assessment (LCA) framework to quantify environmental impacts, synergistic reduction of pollution and carbon emissions (SRPC), and economic performance. A multi-attribute decision-making model, Analytic Hierarchy Process–entropy–TOPSIS (AHP–entropy–TOPSIS), was applied to assess environmental–economic trade-offs. The results indicate that biomass fuel substitution and high grinding efficiency achieved the best SRPC and environmental–economic trade-off scores (S_norm: 0.17–0.22). Alternative raw materials moderately reduced carbon but increased pollutant emissions and economic uncertainty (S_norm: 0.14–0.20). Mono-ethanolamine absorption and calcium looping provided substantial carbon reduction but weaker overall performance due to environmental trade-offs and higher costs (S_norm: 0.12–0.16). These findings provide quantitative guidance for prioritizing and combining decarbonization strategies to support the green transition and sustainable development of the cement industry. Full article

Conventional structural design frameworks assess natural hazards as statistically independent phenomena, a practice that can lead to significant underestimation of risk for structures subjected to sequential or concurrent hazards. The generation of probabilistic fragility functions under such cascading loads, particularly for post-fire seismic events, presents a computational barrier for standard non-linear dynamic analysis. To address this barrier, this study introduces a comprehensive computational framework centered on a physics-constrained neural network (PCNN) to serve as a high-fidelity surrogate model. The framework first uses a non-linear 12-degree-of-freedom structural model to generate a baseline dataset of collapse times under post-fire, concurrent wind-earthquake loading via the computationally efficient endurance time (ET) method, confirming that wind effects are negligible under ambient conditions and that the framework correctly identifies this hazard hierarchy without prior labeling, while fire and seismic parameters dominate. This dataset is subsequently used to train the PCNN, which is validated to achieve exceptional predictive accuracy ($R^2=$ 0.991), performing on par with a state-of-the-art Random Forest model while enforcing physical constraints. A feature importance analysis confirmed that structural collapse is dominated by fire intensity (≈55%) and initial structural period (≈45%). The validated PCNN is then applied to demonstrate the framework’s capability, rapidly generating fragility curves that quantify the catastrophic effect of fire on seismic resilience. This analysis reveals that a severe 800 °C localized fire reduces the structure’s median collapse capacity by 94.7%, thereby establishing the proposed framework as a successful template for tackling complex, non-linear problems in multi-hazard engineering. Full article

Constructing age-friendly residential environments is essential for supporting aging in place among the growing population of urban empty-nest older adults in China. Grounded in person–environment fit theory, this study developed and validated a multidimensional Aging-Suitability Index (ASI) to examine how residential environmental factors shape housing suitability and perceived independence. In this study, “aging suitability” refers to the degree of fit between residential environments and older adults’ needs for safety, functionality, accessibility, social support, and technological support, with the central aim of enabling aging in place and independent living. Questionnaire data were collected from 753 urban empty-nest older adults across 19 provinces in China and analyzed using partial least squares structural equation modeling (PLS-SEM). The structural model showed strong explanatory power (R² = 0.754). The results revealed a clear hierarchy of environmental influences. Safety facilities and physical design were the strongest direct predictors of residential aging suitability, indicating that risk reduction and ergonomically appropriate spatial design constitute the foundation of age-friendly housing. Although accessibility showed a smaller direct effect, it exerted a significant indirect effect through perceived independence, with 67.35% of its total effect mediated through this pathway, highlighting the importance of barrier-free design in maintaining autonomy. Social support and smart technology also contributed positively as complementary resources that strengthened person–environment fit. These findings suggest that age-friendly housing interventions should move beyond fragmented modifications toward integrated residential renewal strategies that prioritize safety and physical design, improve accessibility to support independent living, and combine community support with age-friendly technologies. This study provides empirical evidence to inform built-environment decision-making in the design and renewal of housing for older adults in rapidly aging urban contexts. Full article

Floods increasingly threaten communities and infrastructure in Uganda due to climate variability and land use changes. This study assessed flood hazard, vulnerability, and risk in the Mpanga River Catchment using the Rainfall–Runoff–Inundation (RRI) model integrated with the Analytical Hierarchy Process (AHP). The RRI model showed good performance during calibration (NSE = 0.83) and validation (NSE = 0.71), enabling the generation of hazard maps for different return periods. Results revealed a clear escalation in flood extent with increasing return period, where inundation expanded from about 120.5 km² in the 5-year event to nearly 348.4 km² under the 100-year flood scenario. Vulnerability was evaluated through AHP using nine indicators (Land use, population density, distance to river, elevation, rainfall, slope, drainage density, Total Wetness Index, and soil type); however, only Land Use and population density were retained in the final mapping due to data relevance and weight dominance. Combining hazard and vulnerability produced risk maps that revealed most of the catchment falls under low to moderate risk, with high-risk areas concentrated in upstream urbanized zones. Validation with satellite-derived flood maps confirmed model reliability. Evaluation of mitigation strategies showed dams and channel improvements to be the most effective in reducing flood extent. The study provides a practical framework for flood risk management in data-scarce environments, supporting evidence-based planning and interventions. Full article

The rapid integration of UAVs (Unmanned Aerial Platforms) introduces new operational capabilities but also raises critical challenges. This paper presents a quantitative risk assessment approach for evaluating the risks related to drone-assisted systems. The methodology combines established standards with the principles of the multi-criteria hierarchy concept. First, a qualitative analysis is performed to identify and register the required risk elements. Following this, a hierarchical model is developed to model the dependencies between systems’ components, environmental factors, structural limitations, and operational uncertainties. An AHP-based (Analytic Hierarchy Process) process is applied to enable elements quantification. To demonstrate the applicability and feasibility of the proposed methodology, two different drone-assisted systems are examined, showcasing their effectiveness in evaluating critical risk elements and computing cumulative risk contribution to quantify and prioritize potential risk events. The results indicate the significance of the methodology in ranking the verified risk elements and identifying those that made the greatest contribution to system failure. As revealed, power- and weather-related elements are among the most significant contributors to performance deterioration. In addition, operator-related factors significantly contribute to the system’s overall functional performance, especially when it is manually controlled. Finally, a comparative analysis underscores the sensitivity of risk ranking to variations in AHP scoring. Full article

Background: Leadership in sustainability-oriented inter-organizational networks is increasingly enacted through governance-related practices rather than firm-centric or individualized constructs, reflecting distributed authority, shared accountability, and plural sustainability objectives. Yet scholarship remains conceptually fragmented across adjacent constructs such as orchestration, meta-governance, and brokerage. Objective: This systematic review synthesizes how leadership is conceptualized and enacted through governance mechanisms in inter-organizational networks pursuing sustainability goals. Methods: Peer-reviewed journal articles in English were included; non-peer-reviewed publication types and studies lacking substantive inter-organizational and leadership/governance relevance were excluded. Structured searches were conducted in Scopus and Web of Science Core Collection (last searched 11 February 2026). Results were synthesized through qualitative narrative synthesis using iterative thematic coding and narrative integration. Risk of bias was not formally assessed because the review aimed at conceptual mechanism integration rather than effect estimation; interpretive adequacy safeguards guided inclusion and synthesis. Results: Thirty-one peer-reviewed journal articles were included. Across the corpus, leadership is primarily theorized as (i) orchestration and meta-governance; (ii) governance mechanisms as the formal and informal infrastructure enabling and constraining network leadership; and (iii) brokerage and boundary-spanning practices that align actors and mediate institutional tensions. These dimensions operate as mutually reinforcing layers of coordination capacity, shaping how sustainability trade-offs become governable in the absence of hierarchy. Limitations: Evidence is limited by database-only searching, English-language restriction, and the absence of a formal risk-of-bias appraisal; findings are therefore interpretive and mechanism-oriented rather than effect-based. Conclusions: The review advances a conceptual reframing: leadership in sustainability-oriented inter-organizational networks is best understood not as an actor property but as a systemic coordination capacity embedded in governance architecture. By articulating meta-governance as a design layer, orchestration as a coordination layer, and brokerage as a translation and legitimacy layer, the study develops a multilevel analytical model integrating leadership and governance at the network level, with implications for innovation ecosystems, strategic collaboration, and sustainability transitions. Full article

To address the power quality deterioration caused by the large-scale integration of grid-following (GFL) electric vehicle charging stations, this paper proposes a comprehensive assessment method based on relative entropy distance fusion weighting and a dynamic ideal solution VIKOR algorithm. First, a multi-dimensional power quality evaluation system is constructed, focusing on key indicators such as voltage deviation, frequency deviation, three-phase imbalance, and harmonic distortion, to accommodate the operational characteristics of vehicle-to-grid (V2G) under grid-following and grid-forming (GFM) interaction scenarios. Building on this, the three-scale analytic hierarchy process (AHP) is employed to determine subjective weights, while the divergence-maximized entropy weight method is used to derive objective weights. The relative entropy distance model is then applied to achieve adaptive fusion of subjective and objective weights, resulting in an optimal combined weighting. Subsequently, a dynamic ideal solution mechanism is introduced into the VIKOR algorithm, where the range of the ideal solution is adjusted based on the indicator weights to enhance the discrimination of key indicators. By comprehensively calculating the group utility value, individual regret value, and compromise evaluation index, accurate ranking and performance assessment of different mitigation schemes are achieved. Using measured data from a vehicle-grid interaction demonstration base for analysis, the results demonstrate that the proposed method can effectively quantify the actual effects of various mitigation schemes, providing decision-making support for power grid safety and stability under high penetration of renewable energy and converter-interfaced generation. Full article

Achieving sustainable urban development and optimizing the urban scale structure are central priorities in global governance. However, the relentless population agglomeration in Chinese megacities, despite astronomical living costs, presents a prominent “China Paradox” that seemingly defies classical spatial equilibrium theories. This study decodes this paradox by endogenizing the strategic land supply behaviors of local governments. Utilizing a comprehensive panel dataset of 287 Chinese prefecture-level cities from 2006 to 2020, we construct a multi-dimensional mediation framework and a panel threshold model to investigate how the structural misallocation of land—specifically, the pro-industrial and anti-residential bias—reshapes urban migration dynamics. Empirical results reveal that this land allocation bias acts as the fundamental institutional engine driving urban polarization. Analysis of the transmission pathways reveals a complex push–pull dynamic at the core of this paradox. The artificial restriction of residential land drives up housing prices, generating a profound centrifugal “push” force. However, this dispersion effect is entirely neutralized by two formidable centripetal “pull” forces: industrial co-agglomeration fueled by subsidized manufacturing land, and premium public service capitalization financed through lucrative land revenues. Furthermore, this demographic pull effect exhibits a pronounced inverted U-shaped dynamic, peaking during the rapid growth phase but diminishing precipitously once cities cross the threshold into highly developed megacities (LnGDP > 11.525). These findings highlight the ultimate unsustainability of the land-driven urbanization model. We propose a paradigm shift towards sustainable urban governance, advocating for stage-specific land supply reforms and the transition from monopolistic land finance to a sustainable property tax system to foster a spatially just and resilient urban hierarchy. Full article

To address the challenge of efficiently and cost-effectively generating images of intangible cultural heritage (ICH) furniture that can adapt to diverse modern spatial contexts for visual communication, this paper proposes and constructs an Generative Artificial Intelligence (AIGC) virtual studio system based on ComfyUI. The system is designed for ICH furniture designers, cultural communicators, and digital preservation practitioners, aiming to overcome the bottlenecks of scene switching encountered in traditional photography and 3D modeling. First, furniture images and user scene descriptions are collected, and a dual lexicon consisting of AI prompts and user prompts is constructed. The analytic hierarchy process (AHP) is then applied to weight and filter prompt combinations, forming a quantifiable and integrated prompt system. Second, a visual workflow incorporating ControlNet and IPAdapter nodes is built in ComfyUI to enable the transfer of ICH furniture images to various preset spatial scenes. Finally, a Likert-scale comparison is conducted between the experimental group (using AHP-weighted prompts) and the control group (using unweighted prompts). The results show that the experimental group achieves significant improvements in image realism, style consistency, and cultural communication effectiveness. The images generated by this system can be directly used for digital display, e-commerce product pages, design proposals, and cultural archives of ICH furniture. The method is applicable to the context-aware AIGC generation of traditional furniture and home products, provided that a certain amount of image data and a ComfyUI environment are available. This study provides a reusable technical pathway for the modern visual presentation of ICH furniture and offers methodological support and empirical evidence for the integration of AIGC into environmental design. Full article