Search Results (78)

Synergistic pollution reduction and carbon mitigation (SPRCM) is a critical pathway for advancing global climate governance and promoting green and low-carbon transitions. It also represents an important practice for strengthening ecological civilization and achieving regional sustainable development in China. Based on panel data from 31 Chinese provinces during 2010–2024, this study employs an improved entropy-weighted TOPSIS method to measure SPRCM levels and integrates a modified gravity model, social network analysis, and the CatBoost-SHAP explainable machine learning approach to examine its spatiotemporal evolution, spatial network structure, and nonlinear association characteristics. The main findings are as follows. First, China’s overall SPRCM level shows a gradual upward trend, while significant regional disparities remain. Second, the interprovincial spatial association network has gradually evolved toward a polycentric structure and exhibits clear hierarchical characteristics. Although network connectivity has continuously improved, linkages between core and peripheral provinces remain relatively weak. Third, individual network characteristics display distinct regional differentiation. Eastern coastal provinces consistently occupy core network positions, whereas northeastern and some western provinces remain relatively peripheral. Fourth, the block model analysis identifies four functional groups within the network: net beneficiaries, net spillovers, brokers, and two-way spillovers. These blocks play differentiated roles in spatial association and network interactions. Fifth, the CatBoost-SHAP analysis indicates that road density, freight volume, and human capital are the most important variables in explaining model predictions, with their combined mean absolute SHAP importance accounting for 54.59%. Moreover, these factors exhibit significant nonlinear association patterns with predicted SPRCM levels. Full article

Underground coal gasification (UCG) requires rigorous geological suitability evaluation to reduce project risks, and scientific site selection is critical for success. Taking the No. 15 coal seam in the Yushe–Wuxiang Block (Qinshui Basin) as the focus, this study evaluates the feasibility of deep UCG using a multi-criteria decision-making framework. A hierarchical evaluation model comprising four primary and 10 secondary geological indicators (e.g., coal thickness, parting coefficient, fault fractal dimension, roof lithology) was constructed. Subjective weights were derived from the Analytic Hierarchy Process (AHP) and combined with objective weights from the coefficient of variation method. The TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method was then applied to rank seven development units. Results indicate that the No. 15 coal seam has reasonable potential for UCG implementation. The most favorable areas (Blocks II and VII) are characterized by thick coal seams (>5 m), low parting coefficients (<8%), simple fault networks (fractal dimension ≤0.5–1.05), and competent mudstone roofs. Blocks III, V, and VI are moderately favorable, while Blocks I and IV are marginally favorable. These findings provide a prioritized roadmap for pilot-scale UCG testing in the Yushe–Wuxiang Block. Full article

Prefabricated mechanical, electrical, and plumbing (MEP) systems have been increasingly adopted in energy station projects; however, systematic evaluation frameworks capable of integrating construction performance, cost constraints, and uncertain multi-indicator assessments remain limited. To address this gap, this study constructs an Analytic Hierarchy Process (AHP)–Entropy–Fuzzy evaluation framework to assess the comprehensive benefits of BIM-enabled prefabricated MEP construction in energy stations. A hierarchical evaluation system was established based on five dimensions: schedule, quality, cost, safety, and environmental performance, and ten secondary indicators were defined. The Analytic Hierarchy Process was used to determine expert-based subjective weights, the entropy method was applied to capture objective data variability, and multiplicative normalization was employed to obtain combined weights. A fuzzy comprehensive evaluation model was then introduced to transform heterogeneous construction records into comparable benefit levels and scores. The prefabricated method scored 87.80 and was classified as “high”, whereas the conventional method scored 60.85 and was classified as “low”. A Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)-based sensitivity analysis further showed that, under 10%, 20%, and 50% criterion-weight perturbations, the prefabricated group consistently achieved higher closeness coefficients than the conventional group. The smallest margin occurred when the schedule weight was reduced by 50%, but the prefabricated group retained a positive advantage. The results demonstrate that Building Information Modeling (BIM)-enabled prefabricated MEP construction can achieve superior overall project performance through the coordinated optimization of schedule, cost, safety, quality, and environmental objectives, offering a practical evaluation framework and decision-support tool for the industrialized delivery of future energy infrastructure projects. Full article

Transportation hub cities serve as pivotal nodes within integrated transport systems. This study reveals the corridor-oriented characteristics of comprehensive transportation system, confirms the progress of its transportation hub city development, and identifies future improvement directions based on diagnostic evaluation, taking Gansu Province, China as the research subject. To address hierarchical differentiation and structural constraints in the development of integrated transportation hubs, this study develops an evaluation framework integrating the entropy-weighted TOPSIS method, a coupling coordination model, and indicator-based diagnostic analysis. This framework was applied to 14 prefecture-level cities and autonomous prefectures in Gansu, classifying them into four hub tiers according to the comprehensive evaluation index. The results reveal a pronounced hierarchical and corridor-oriented spatial structure: Lanzhou is identified as the only Tier 1 core hub, five cities are classified as Tier 2 backbone hubs, seven cities and prefectures as Tier 3 general hubs, and Pingliang as Tier 4 terminal hub. Lanzhou exhibits the highest development level, with a comprehensive evaluation index of 0.9640, which is substantially higher than the provincial mean of 0.3867, but its radiation-driving capacity still needs to be strengthened. In terms of subsystem coordination, Lanzhou reaches the primary coordination stage with a coupling coordination degree of 0.532, while Jiuquan, Jiayuguan, and Tianshui are classified into the near-coordination stage with D values of 0.353, 0.351, and 0.321, respectively; the remaining ten units are classified as uncoordinated relatively. Based on the combined perspectives of development level and subsystem coordination, the study identifies future development directions for hub operational organization, multimodal transport integration, feeder connectivity, and industry-logistics coupling. The findings reveal the corridor-oriented characteristics and development progress of Gansu’s transportation hub system, highlight the analytical value of distinguishing hub development level from subsystem coordination, and provide empirical evidence for understanding hierarchical and functional differentiation in corridor-oriented inland regions. Full article

The rapid adoption of artificial intelligence (AI) in healthcare is reshaping service delivery and enabling more personalized, data-driven care. However, cross-country differences in AI implementation and perceived strategic importance remain insufficiently understood. This study proposes a dual-dimensional framework to assess AI maturity across 50 countries in the WHO European Region, distinguishing between actual AI applications and perceived opportunities. Using data from the WHO 2024–2025 Artificial Intelligence for Health survey, the AI Applications Index (AIA) is constructed using an intuitionistic fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method that accounts for uncertainty in implementation. In parallel, the AI Opportunities Index (AIO) is developed using a belief-structure TOPSIS approach to capture perceptions of AI’s strategic relevance. To better understand underlying patterns, Multiple Correspondence Analysis and Ward hierarchical clustering are applied to identify latent structures, homogeneous groups, and transitional development pathways. An Index of Alignment (IA) is introduced to measure coherence between AI applications and perceived opportunity. Countries are grouped into four development trajectories based on the mean values of the AI Applications and AI Opportunities indexes: AI leaders, implementation-driven systems, opportunity-driven systems, and lagging systems. These results are further compared with Ward clustering, revealing hybrid and transitional profiles not fully captured by aggregate classifications. The findings indicate that AI maturity is shaped not only by implementation levels but also by the alignment between technological capacity and strategic perception. The results highlight the multi-speed and institutionally differentiated nature of AI transformation in European healthcare systems. Full article

Runway incursions (RIs) have emerged as a major threat to airport surface safety, driven by the coupled influence of human, equipment, environmental, and management factors. Conventional assessment methods struggle to simultaneously capture the fuzziness of expert linguistic judgment and the randomness of operational conditions. This study proposes an integrated DEMATEL–Cloud–TOPSIS framework for runway incursion risk assessment and validates it at Chengdu Tianfu International Airport. A hierarchical indicator system comprising 24 indicators across four dimensions—Human (H), Equipment (M), Environment (E), and Management (G)—was constructed from 90 RI cases collected between 2018 and 2023. DEMATEL quantified inter-indicator causal dependencies and DEMATEL-derived weights; the Cloud model translated linguistic expert judgments into digital characteristics (Ex, En, He); and TOPSIS produced relative closeness coefficients for risk ranking. Human, equipment, and environmental risks are all at a medium-risk, while management risk is at a low-risk, but significant differences still exist. Management achieved the highest closeness ($C_i$ = 0.6322) and Environment the lowest ($C_i$ = 0.5096). At the indicator level, ATC Instruction Accuracy (H1) exhibited the greatest operational maturity ($C_i$ = 0.9119), whereas Unclear Crew Coordination (H6) showed the lowest relative closeness ($C_i$ = 0.0156), followed by Aircraft Equipment (M5) ($C_i$ = 0.0195). Meanwhile, Runway Configuration Complexity (E2) remained a weak structural factor within the Environmental dimension ($C_i$ = 0.1502). The framework provides an interpretable, quantitative basis for targeted safety management at complex hub airports. Full article

This study addresses the issue of low utilization rates of kitchen waste recycling facilities in urban communities in China, caused by insufficient resident willingness to participate and sustain use, which impacts the efficiency of urban sustainability. A system design model based on Affordance Theory (BIATM) is proposed to connect behavioral insights with design and decision-making tools to improve sustainability outcomes at the local level. This model includes three components: demand classification identification based on Affordance Theory and the Best-Worst Method (BWM), hierarchical relationship analysis of demand based on Interpretive Structural Modeling (ISM), and design transformation based on Affordance Theory. Unlike prior approaches that apply affordance theory as a post hoc interpretive lens, this study operationalizes it as a generative design tool integrated with quantitative demand analysis. The results indicate that “Incentive Feedback” is a key factor directly influencing sustained participation behavior, while factors related to hygiene anxiety and operational burden are fundamental constraints to residents’ use of community kitchen waste recycling facilities. This suggests that the explicit needs expressed by residents may not always be the primary drivers of behavior initiation and continuity. To promote sustained participation, design should prioritize meeting deeper behavioral prerequisites and maintain participation through superficial feedback and incentive mechanisms. Based on this analysis, three design proposals for community kitchen waste management facilities are presented, evaluated, and optimized using the TOPSIS method. The study concludes that combining demand weight identification, hierarchical relationship analysis, and Affordance Theory translation effectively supports the identification, design generation, and optimization of community kitchen waste management facilities, providing a methodological reference for the sustainable design of public service facilities and practical pathways for promoting resident participation in community resource recycling. Full article

During drilling in stress-sensitive fractured formations, fracture aperture dynamically evolves with wellbore pressure fluctuations. The sealing layer often undergoes repeated cycles of sealing, destabilization, and re-sealing. Formulation selection based on a single metric or empirical selection cannot simultaneously satisfy multiple objectives, including pressure-bearing capacity, loss control, and dynamic adaptability. This study proposes an entropy-weighted TOPSIS and grey relational analysis method to optimize lost circulation formulations for stress-sensitive fractured formations. A hierarchical evaluation system is established with four criteria layers and eight indicator metrics. A baseline formulation framework is determined through static fracture sealing tests. Experimental data for different elastic-material systems are obtained using a self-developed DTDL dynamic fracture plugging apparatus. Indicator weights are objectively determined using the entropy weight method. A Grey–TOPSIS model is applied to compute grey relational closeness to the positive and negative ideal solutions, enabling formulation ranking and optimal scheme identification. A case study shows that the ternary elastic formulation with Rubber:Graphite:Net = 3:2:1 achieves the highest grey relational closeness and delivers the best overall sealing performance. The ranking remains unchanged when the distinguishing coefficient ρ varies from 0.1 to 0.9, confirming the robustness and feasibility of the proposed method. Compared with entropy-weighted TOPSIS and classical TOPSIS, the proposed method provides a more integrated treatment of the multi-metric data and better aligns the evaluation with the underlying sealing behavior in stress-sensitive fractures. Therefore, it leads to more reliable and comprehensive evaluation results for formulation selection. The results demonstrate that the proposed model provides reliable support and a methodological basis for formulation optimization in dynamic fracture loss control. Full article

Urban transportation systems are facing increasingly severe threats from extreme weather events such as rainstorms, which can trigger cascading failures and lead to regional traffic paralysis. The strategic location of emergency facilities to enhance system resilience has emerged as a critical proactive prevention strategy. This study proposes a multi-objective hierarchical coverage location model that integrates point and flow demands to improve the resilience of urban road traffic systems under rainstorm conditions. First, the resilience risk levels of road nodes were quantified using an entropy-weighted TOPSIS method that combines topological attributes, traffic flow performance, and indirect propagation intensity. Second, a flow-capturing mechanism was introduced to address the dynamic rescue demands of stranded vehicles in motion, enabling the pre-positioning of “safe havens” along critical travel routes. The model balances two objectives: maximizing the resilience risk value of the covered demands and minimizing facility construction costs. A case study was conducted in Jianghan District, Wuhan, a flood-prone area, and the NSGA-II algorithm was employed to solve the multi-objective optimization problem. The results demonstrate that the proposed model significantly outperforms traditional single-demand location models in terms of coverage effectiveness and cost efficiency, achieving improvements in resilience risk coverage of up to 311.6% and cost reductions of up to 63.6%. This study provides a systems science perspective for pre-disaster emergency resource allocation, shifting the paradigm from infrastructure-centric protection to human-centered rescue. Full article

Runway incursions remain a major threat to airport surface safety, and effective prevention depends on the accurate identification of causal risk factors and their interaction mechanisms. However, existing studies have mainly focused on isolated risk factors or static causal relationships, offering limited insight into the hierarchical structure and dynamic propagation of runway incursion risk in complex operational environments. To address this gap, this study proposes a quantitative framework for runway incursion risk analysis by integrating grounded theory and complex network theory. Published runway incursion cases in the Chinese civil aviation system from 2022 to 2025 were systematically analyzed through open coding, axial coding, and selective coding, resulting in a hierarchical indicator system comprising five main categories, twelve subcategories, and 112 risk indicators. Based on this system, a runway incursion causal network was constructed to characterize the causal interdependencies among risk factors. Node importance was evaluated using a TOPSIS-based multi-criteria method integrating multiple network metrics, and a load-distribution-based propagation mechanism was introduced to quantify the risk propagation probability and risk propagation intensity of each node. The results indicate that insufficient night lighting (N99), taxi-route memory errors (N14), ambiguous controller instructions (N1), and excessive controller workload (N10) exhibit relatively high risk propagation probability and risk propagation intensity, indicating their critical roles in the evolution and cascading propagation of runway incursion risk. These findings demonstrate that the proposed framework can effectively capture both the structural importance and propagation characteristics of causal risk factors. Therefore, this study provides quantitative support for understanding runway incursion risk evolution and for developing targeted prevention strategies and post-incident response measures to improve runway safety management. Full article

Sustainable tourism is essential for preserving natural habitats and represents a vital component of sustainable development. This study addresses a business decision-making problem related to natural resource conservation and habitat protection through waste management and IT applications in the Serbian hotel sector. Tourism in Serbia and the Western Balkans represents a sensitive issue concerning the balance between economic development and environmental protection. Therefore, the multi-criteria optimization methods Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are applied to address this problem. To achieve this goal, a hierarchical model was developed that considers nine criteria and four alternatives. The alternatives considered are: service user satisfaction, service cost, waste minimization, and service quality. The developed model was analyzed using a hybrid AHP–TOPSIS approach to identify the optimal alternative. The results indicate that environmental waste prevention ranks highest among all considered alternatives and plays a significant role in the development of sustainable tourism in Serbia. Full article

Against the backdrop of global climate change and dual carbon goals, the logistics industry, which accounts for about 14% of global greenhouse gas emissions, needs green transformation. Yet, existing evaluation systems have fragmented dimensions, excessive subjectivity, and insufficient objectivity. This study aims to construct a scientific evaluation framework. It uses two rounds of the Delphi method to screen 13 core indicators, forming an environment–economy–society–technology four-dimensional system, and it improves the three-interval TOPSIS method with interval-type ideal solutions, supplemented by Spearman and Pearson dual verification. Taking 24 core cities in the Yangtze River Delta as samples, the results show hierarchical and regional differences: 3 cities (Shanghai, Suzhou, Hangzhou) are excellent, 12 are good, and 9 are qualified. The evaluation system unifies standards for cross-regional and industry comparisons, which works as a quantitative tool for government policy-making and enterprise green transformation, contributing to the development of the logistics industry’s low-carbon intelligent and the achievement of dual carbon goals. Full article

Grouting to seal the recharge channels of water-bearing aquifers is an effective method for reducing mine water inflow. Evaluating effectiveness and establishing a hierarchical classification system are crucial for assessing project quality. Taking the grouting seal project of the Cambrian limestone aquifer recharge channels at Mine No.7 in the Pingdingshan Coalfield as a case study, this paper first comprehensively evaluates the grouting seal effectiveness based on the difference in dynamic water recharge to goaf before and after grouting, derived from long-term pumping test data. Further, six indicator factors—grout volume, grout volume per unit time, grout volume per unit thickness, final borehole pressure, penetration depth into Cambrian limestone, and variation in rock mechanical strength—were selected. Weights for these factors were determined by integrating the Analytic Hierarchy Process, entropy weight method, and composite weighting method. The TOPSIS model was applied to classify and rank the grouting seal effectiveness in six recharge channels. Results indicate that post-grouting water recharge from goaf decreased by 240.78 m³/h during dry season and 878.57 m³/h during wet season, confirming high-quality grouting seal. The grouting seal quality of the six recharge channels was ranked from highest to lowest as follows: NO.3 > NO.2 > NO.6 > NO.1 > NO.5 > NO.4. The evaluation results corresponded with the actual karst fissure development and distribution of goaf in the exposed recharge channels. Full article

Enhancing herders’ livelihoods is essential in balancing human–land interactions and promoting inclusive, sustainable development within protected area management. Using a household survey (N = 3539; March–June 2025) and a mixed-methods quantitative approach (weighted TOPSIS, obstacle degree, Spatial Durbin Model, and hierarchical regression), we assessed household livelihood resilience in the Lancang River source area of Sanjiangyuan National Park. Key findings included the following. Overall livelihood resilience was moderate, with a mean score of 0.411. This was characterized by a marked weakness in learning capacity (0.358) and relative strength in self-organization (0.431). Major barriers to resilience included cooperative participation (obstacle degree: 8.14%), education levels (7.58%), skills training (7.18%), household savings (6.40%), and information acquisition abilities (5.97%). The spatial analysis revealed a core-periphery pattern of resilience, evidenced by significant negative spatial autocorrelation (W×HLR coefficient = −0.787, p = 0.001), suggesting competitive interactions among villages. Within this pattern, cooperative participation induced significant positive spatial spillovers (W×X₈ coefficient = 0.147, p < 0.001), while benefits derived from information acquisition abilities remained localized (Direct Effect = 0.061, p < 0.001). The pathways to resilience were associated with household heterogeneity. Associations between key factors and resilience varied across demographic groups, with women and youth benefiting more from skills training and education. Livelihood strategies were linked to information utilization, with cordyceps-dependent households exhibiting greater sensitivity to information acquisition abilities (interaction coefficient = 0.009, p = 0.009). The institutional environment shaped organizational benefits; the positive association with cooperative participation diminished in the core protected zone (interaction coefficient = −0.011, p = 0.036). These findings highlight household heterogeneity as a key factor influencing diverse resilience pathways. They also emphasize the need for targeted, spatially specific, and group-oriented governance strategies. Full article

Symmetry in vehicle body morphology is a crucial factor for achieving visual sensory balance in users, and it also serves as an important method for enhancing the efficiency of vehicle body research and development. This study proposes an AHP-SD-TOPSIS-AIGC integrated morphological design method to address multi-factorial design complexities in new energy commercial vehicle body styling under emotion-driven frameworks. Through literature retrieval and survey analysis, a Kansei evaluation system was constructed, with hierarchical design indicators established via Analytic Hierarchy Process (AHP) and weights determined through consistency matrices. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) identified optimal style forms exhibiting high emotional intention coupling, while edge detection algorithms extracted symmetrical spline features for body contour modeling. Artificial Intelligence Generated Content (AIGC) tools subsequently generated innovative solutions, validated through truck design applications to confirm method rationality and effectiveness. The results of the study show that the styling elements are accurately matched to user preferences and can identify target improvement points, and that the method can effectively achieve the output of the proposal for the design of commercial vehicle body morphology and is also applicable to passenger car-type vehicles to achieve the adaptation of multi-intentional emotional design. Full article