Search Results (732)

Unbalanced regional development is a long-standing spatial feature of China. Most extant studies are restricted to a single economic dimension and lack long-run comprehensive analysis that couples the economic, social and ecological dimensions. Drawing on China’s provincial panel data from 1990 to 2023, this paper constructs a comprehensive indicator system across three dimensions, measures comprehensive development levels with the entropy-weight TOPSIS method, and decomposes the overall imbalance into within-region disparity, between-region net disparity and the intensity of transvariation with the Dagum Gini coefficient, revealing the spatiotemporal evolution of imbalance across the four major zones of Southeast, Central, Western and Northeast China. The results show that the three types of imbalance are not synchronized: economic imbalance first rose and then declined, social imbalance fluctuated more strongly, and ecological imbalance changed mildly. The distribution of intra-provincial social and ecological disparities across zones is markedly crossed, whereas the cross-zone overlap of economic disparities has continuously weakened since 2000, and the gradient has become clear again. Accordingly, this paper proposes policy recommendations including three-dimensional assessment, classified governance, industrial collaboration and ecological compensation. This study enriches the multidimensional measurement paradigm of regional imbalance and provides quantitative support for coordinating innovation resources and promoting coordinated regional development. Full article

Reliable tactile object shape recognition on robotic hands is often achieved using dense sensor arrays or vision-based tactile skins, which increase fabrication complexity and computational cost. This work demonstrates that high-recognition performance can instead be achieved through principled sparse sensing. A minimal multimodal tactile system is developed by fusing soft capacitive stretch sensors at the proximal interphalangeal and metacarpophalangeal joints of the fingers with a sparse six-element palmar pressure array, integrated into a human-like hand mechanically constrained to emulate robotic grasping under a controlled and repeatable protocol. Using an ANOVA-based channel selection, low-informative metacarpophalangeal signals are identified and removed, reducing the number of sensors at the finger joints while improving classification accuracy. A lightweight multi-layer perceptron operating on this low-dimensional input achieves 95.4% size-invariant recognition accuracy across 12 rigid objects representing four geometric primitives—cuboid, sphere, cylinder, and cone—outperforming the denser baseline. Ablation studies confirm the complementary roles of finger-joint deformation, which encodes curvature cues, and palmar force distribution, which captures contact topology; neither modality alone achieves comparable performance. Beyond accuracy, the proposed design reduces sensor count, wiring, and computational requirements, enabling embedded-ready deployment. The results show that data-driven sensor placement, rather than sensors at all finger joints, can yield sufficient grasp-based shape recognition, offering practical guidance for tactile perception in resource-constrained robotic hands. Full article

To efficiently utilize oil sands resources, enhance their strategic position among traditional energy sources, and deeply reveal the essence of the pyrolysis reaction of oil sands bitumen (OSB), this study integrates experimental characterization with molecular simulation techniques. This paper innovatively adopts the “ring-bridge archipelago” method to construct two-dimensional molecular structure models of OSB from Karamay, Xinjiang (KXC), China, and Buton Island (DBI), Indonesia, with chemical formulas of C₂₅₀H₃₄₉N₃O₅ and C₂₅₀H₃₆₉NO₁₀S₉ respectively. The results showed that although DBI and KXC differ in elemental composition, their molecular structural characteristics are highly similar. Notably, the carbon–sulfur bonds in sulfoxide groups, the carbon–carbon bonds in alicyclic rings, and the carbon–oxygen bonds in aliphatic ethers exhibit high pyrolytic activity. Based on multidimensional analysis results, a novel simplified pyrolysis reaction mechanism model for OSB chemical structures is proposed. This model clarifies the selective bond cleavage characteristics in the pyrolysis system and identifies differences in bond order and recombination reactions during pyrolysis as key factors driving selective bond cleavage. Full article

New energy power systems with high penetration rates feature complex spatiotemporal coupling relationships among generation, transmission, load, and storage. The random fluctuations in wind and solar power output, combined with load uncertainty, exacerbate system operational risks. Traditional static modeling, single-metric evaluation, and centralized analysis methods struggle to adapt to the dynamic, highly uncertain, and multi-constrained operational scenarios of new power systems. To address this, this paper proposes an Artificial Intelligence-based Comprehensive Evaluation Method for Power System Flexibility and Sustainability (AI-FSEA) under privacy and security constraints. This method first establishes an intelligent fusion module for multi-source, heterogeneous power data, which accurately extracts the system’s multidimensional dynamic features through adaptive wavelet denoising and a temporal self-attention mechanism. Second, it establishes a five-objective coupled evaluation model that balances technical, economic, low-carbon, and reliability considerations, with regulation margin loss, response delay, operating costs, carbon emissions, and power supply instability rate as the core optimization objectives, thereby achieving multi-objective trade-off optimization within the system’s feasible domain; furthermore, a Hierarchical Deep Q-Network-Assisted Multi-Objective Evolutionary Algorithm (HDQN-MOEA) is designed, which leverages the value iteration, composite reward mechanism, and feedback clustering screening mechanism of the deep Q-network to enhance the model’s solution accuracy and convergence efficiency. Results from multiple sets of comparative experiments, ablation studies, and uncertainty generalization experiments conducted using the IEEE standard node system and real-world power grid data from East China indicate that, compared with mainstream optimization algorithms such as NSGA-III and TS-NSGA-II, the proposed HDQN-MOEA algorithm achieves an average improvement of 10.2% in the hypervolume metric and an average reduction of 35.6% in the span metric; the results of the ablation experiments confirm that the absence of the multi-source data fusion module, the hierarchical strategy module, or the feedback clustering screening module would result in a 15.3% and 12.1% decrease in the model’s hypervolume metric, respectively, as well as a slight deterioration in population diversity; under three types of highly uncertain operating conditions—random fluctuations in renewable energy, sudden load spikes, and extreme weather—the algorithm proposed in this paper consistently maintains stable optimization performance, meeting convergence accuracy requirements in as few as 5000 iterations. Without increasing the complexity of existing algorithms, it achieves the synergistic optimization of data privacy and security, evaluation accuracy, and operational efficiency. The proposed method can accurately quantify the dynamic flexibility and long-term sustainability of the new power system, providing reliable intelligent technical support for the planning and dispatch of the new power system, the optimal allocation of resources, and low-carbon, sustainable operation. Full article

Older adults commonly face challenges such as insufficient spatial accessibility and a lack of safety facilities in their home environments. This paper proposes a multi-criteria decision-making (MCDM) model integrating the Analytic Hierarchy Process (AHP) and Particle Swarm Optimization (PSO) to enhance the scientific rigor and practicality of age-friendly renovation solutions. Based on 543 valid questionnaires and interview data, an evaluation system was constructed, covering four key dimensions: safety assurance, spatial accessibility, independent living capability, and environmental comfort. The weight allocation incorporates dual-source fusion of expert judgment and sample-aggregated resident preferences to improve model rationality and stability. Results demonstrate that the AHP-PSO model outperforms comparative models in prediction accuracy (MAE = 0.121), functional reasonableness (FDR = 0.136), dimensional balance (DBR = 0.912), and robustness (FSR = 94.8%). Comprehensive adaptation analysis reveals that while most residences satisfactorily meet the needs of the elderly, emergency response facilities, kitchen convenience, and furniture adaptability remain critical shortcomings constraining overall performance. The findings validate the effectiveness of the AHP-PSO model for age-friendly home modifications, providing methodological support for resource allocation optimization and aging-in-place policy formulation. Full article

Artificial intelligence (AI) is reshaping the hospitality industry at an unprecedented pace. However, existing hospitality research has overwhelmingly concentrated on customer-facing applications, including service robots, chatbots, personalization, and revenue management, while largely overlooking the internal operational systems that sustain hotel performance. As a result, the concept of AI maturity within back-of-house hotel operations remains theoretically undefined, fragmented across functional domains, and lacks an integrated framework for assessment. This study addresses this critical gap by asking a fundamental research question: What does AI maturity actually mean for hotel back-of-house operations? Drawing upon a systematic literature review following the PRISMA protocol, this study synthesizes evidence from 18 studies spanning the interdisciplinary fields of hospitality management, operations management, information systems, and artificial intelligence to examine how AI is transforming core internal hotel functions. The review identifies current applications, implementation patterns, organizational enablers, barriers to adoption, and emerging trends across human resource management, procurement, finance and accounting, inventory management, housekeeping planning, maintenance, energy management, and managerial decision support. Building on these findings, the study develops the Artificial Intelligence Maturity in Back-of-House Operations (AIM-BoH) Framework, a domain-specific conceptual framework designed to conceptualize AI maturity across hotel back-of-house functions. The framework conceptualizes AI maturity as a multidimensional organizational capability encompassing technological adoption, process automation, decision intelligence, data readiness, human–AI collaboration, governance and ethical preparedness, and measurable operational outcomes. By moving beyond technology-centric perspectives, the framework provides a comprehensive model for understanding how AI creates organizational value through the integration of internal hotel processes. The proposed framework advances hospitality literature by establishing a common theoretical foundation for understanding AI maturity in internal hotel operations while offering hotel executives a structured conceptual lens for considering organizational capability development in the planning of digital transformation initiatives. The article concludes by proposing a research agenda for the empirical validation, refinement, and cross-cultural application of the AIM-BoH Framework, positioning it as a reference model for future hospitality AI research and practice. Full article

Against a backdrop of growing rural differentiation and ongoing rural revitalization efforts, understanding how farmers develop intentions to relinquish their rural homesteads is essential for improving context-sensitive policy design. Drawing on survey data from 407 farmers in the pilot areas of homestead system reform in Shenyang City, this study proposes a “household capital endowment-value cognition/perceived risk-coping capacity-homestead withdrawal intention” framework. A structural equation model (SEM) is used to estimate both the direct effects of multidimensional household capital endowment and its indirect effects through the two mediating variables. Multi-group analyses are further conducted across generations, farm household pluriactivity, and village types. The results indicate that human and economic capital are positively associated with homestead withdrawal intention, whereas natural and social capital are negatively associated with it. Value cognition and perceived risk-coping capacity mediate several pathways: the former weakens withdrawal intention, whereas the latter strengthens it. The multi-group analyses further suggest variation in within-group significance patterns and coefficient estimates across generations, farm household pluriactivity, and village types. These findings highlight the need for differentiated homestead withdrawal policies that are responsive to farmers’ capital endowments and value–risk perceptions, thereby promoting the productive use of rural land resources while safeguarding farmers’ livelihood security. Full article

Synergistic pollution–carbon mitigation is critical for China’s dual carbon targets. Taking coal-resource Shanxi Province as the case, this study developed an integrated Long-range Energy Alternatives Planning (LEAP)–Community Multiscale Air Quality (CMAQ) coupled framework combined with a three-dimensional vector model to simulate energy consumption, CO₂, and major air pollutant emissions (CO₂, CO, SO₂, NO₂, PM_2.5, and PM₁₀) under Baseline and Policy scenarios (2026–2050). The core novelty of this study lies in methodological innovation: the multi-model linkage realizes full-chain energy-emission-atmosphere simulation, remedying the isolation flaw of single models in prior research. The results indicated that low-carbon levels would rise steadily in both scenarios from 2026 to 2050. The Policy scenario achieved superior long-term low-carbon performance compared with the Baseline scenario and narrowed gaps in underdeveloped social subsystems, despite short-term transition costs. This scenario optimized the overall energy structure yet failed to fully reduce emission loads from residential and transport sectors. It drastically cut carbon and pollutant emissions, optimized spatial emission patterns, and decoupled most air pollutants from carbon emissions. However, this scenario still had prominent limitations: phased delays in emission abatement, strong coupling of CO, NO₂ and carbon emissions, and rising residential carbon emissions. Further pollution–carbon synergy assessment revealed worsening multi-dimensional imbalances under the Baseline scenario. While the Policy scenario experienced temporary systemic imbalance, its long-term coordination level improved steadily. This finding verified that systematic, long-term low-carbon governance constituted the core driver of Shanxi’s green transition. Targeted phased, classified collaborative governance strategies were proposed to resolve structural transformation risks for resource-based regions. Full article

Public Fire Emergency Literacy (PFEL) is a critical determinant that fundamentally shapes individual survivability and the efficacy of societal safety governance—particularly amid intensifying fire risks characterized by growing complexity and destructive potential. Traditional single-perspective or linear analytical frameworks fail to capture PFEL’s multi-causal and configurational nature. To address this gap, this study integrates the Emergency Management Life Cycle Theory with the WSR system approach to measure PFEL across 36 major Chinese cities using 3872 survey responses and explores its multidimensional attributes and generative mechanisms via multiple methods (Delphi technique, entropy weighting, GIS spatial analysis, multiple regression, fsQCA). Key findings: (1) PFEL exhibits a pronounced cognition precedes capability gap with marked demographic heterogeneity; (2) PFEL displays a distinct “Central > Northeast > East > West” hierarchical gradient and notable spatial disequilibrium—core cities in the Central region (e.g., Wuhan and Zhengzhou) outperform traditional first-tier metropolises in the East; (3) physical infrastructure, organizational management, and individual cognition jointly shape PFEL with significant regional heterogeneity—participation in emergency training emerges as the most potent driver; (4) configurational path analysis indicates that PFEL is determined by a complex conjunctive causal mechanism formed by the combined effects of physical facilities, organizational management and individual initiative. Policy implications cover strengthened public emergency response capacity, differentiated policies, and multi-factor collaborative governance. The findings offer theoretical references and practical guidance for improving public resilience systems and emergency resource allocation. Full article

The building sector faces an urgent challenge in balancing carbon neutrality goals with natural resource conservation. This study constructs a three-dimensional dynamic coupling model integrating Life Cycle Assessment, carbon footprint, and emergy analysis to evaluate the sustainability of a hydrogen–solar–geothermal hybrid energy system for an ecological office building in China’s hot summer and cold winter climate zone over a twenty-year horizon. The model incorporates dynamic factors including grid decarbonization, equipment efficiency degradation, and replacement cycles to overcome the systematic bias inherent in static LCA. Results reveal a significant trade-off: the hybrid system achieves a 29.8% reduction in global warming potential with a seven-year carbon payback period, yet non-renewable resource consumption doubles and resource scarcity damage increases by 173%. The carbon payback trajectory exhibits non-monotonic fluctuation, with electrolyzer replacement in year ten generating 360 tonnes of additional emissions that nearly reset the cumulative net value to zero. Multi-objective optimization identifies photovoltaic capacity as the system baseline (170–210 kW) and electrolyzer capacity as the primary regulating variable (35–62 kW), with the TOPSIS-recommended compromise solution of 200 kW photovoltaic, 50 kW electrolyzer, 30 kW fuel cell, and 32 m³ hydrogen storage achieving annual carbon emissions of 280 tonnes and a 33.3% reduction. Carbon pricing exhibits a nonlinear leverage effect with an incentive threshold of 200 RMB per tonne, substantially above China’s current 60–80 RMB per tonne level. This study concludes that while hydrogen–solar–geothermal hybrid systems offer substantial climate benefits, their comprehensive sustainability depends on proactive management of material scarcity costs, precise planning of equipment replacement cycles, and coordinated multi-level policy instruments. The findings provide methodological foundations for transitioning building carbon neutrality assessment from static LCA to dynamic coupling frameworks and from single carbon metrics to integrated carbon-resource-cost evaluations. All quantitative results presented herein are derived from this specific case study under the stated assumptions and parameter values; generalization to other building types or climate zones requires recalibration. Full article

Economic growth and the effectiveness of official development assistance (ODA) have long been a topic of debate, with the current concern being that there are high levels of aid dependency in Sub-Saharan Africa, despite low levels of structural transformation. The study analyses the growth impacts of multidimensional ODA dependency, the moderating effect of institutional quality and the possible thresholds of aid dependency in an unbalanced panel of 48 Sub-Saharan African countries over the period 2000–2025. Two-way fixed effects, System Generalized Method of Moments, Difference Generalized Method of Moments, and Common Correlated Effects Pooled are used to analyze a principal component-based ODA Dependency Index, and least-squares threshold regression is used to investigate multiple thresholds. These results show that there is a strong negative correlation between aid dependency and economic growth, while institutional quality is consistently positive to growth, but does not significantly moderate the aid–growth relationship. There are no stable thresholds for aid dependency as a function of the specification of the index. The findings highlight the need to improve domestic resource mobilization, productive investment and institutional capacity to decrease reliance on structural aid and ensure sustainable economic growth in the long term. Full article

Climate change poses significant challenges to agricultural production, water availability, and food and nutrition security, particularly in semi-arid regions where rural livelihoods depend heavily on rain-fed agriculture. In Eswatini, increasing temperatures, erratic rainfall, and recurrent droughts have intensified pressures on smallholder farming systems; however, limited empirical research has examined how climate variability simultaneously affects agriculture, water resources, and household food security within an integrated food–water–nutrition nexus framework. Therefore, this study assessed the impacts of climate change on agricultural production, water availability, food security, and access to nutritious food among smallholder households in the Lubombo Region of Eswatini. A concurrent triangulated mixed-methods approach was employed, combining quantitative data from 880 households with qualitative insights from open-ended responses. Descriptive statistics, Spearman’s correlation, binary logistic regression, and thematic analysis were used to analyse the data. The findings reveal that climate change significantly affects both agricultural and water systems, which in turn directly influence household food security outcomes. The majority of households reported declining crop yields (56.5%), widespread food shortages (79.5%), meal skipping (69.0%), and high levels of food-related anxiety (87.6%). Water insecurity is also prevalent, with over 83% of households experiencing water shortages and nearly all respondents indicating that climate change has affected water access. Correlation and regression analyses demonstrate that drought frequency and reduced rainfall are the strongest predictors of both water insecurity and food insecurity, highlighting the central role of climate variability. Water scarcity emerged as a critical pathway linking climate change to food insecurity, with strong associations between water shortages and reduced crop yields, food shortages, and coping strategies such as skipping meals. Qualitative findings further highlighted declining agricultural productivity, loss of traditional foods, reduced dietary diversity, and increased psychological stress associated with food insecurity. The study concludes that food insecurity in the Lubombo region is multidimensional, driven by the interconnected effects of climate variability, water scarcity, and socio-economic constraints. The findings emphasise the need for integrated, climate-resilient strategies that simultaneously address agricultural production, water resource management, and household adaptive capacity to enhance food and nutrition security. Future research should evaluate the effectiveness of nexus-based adaptation strategies and climate-smart interventions in enhancing long-term food, water, and nutrition security in vulnerable smallholder farming systems. Full article

This study addresses the research gap concerning how rural cultural–tourism integration contributes to regional economic resilience, a relationship that remains underexplored despite growing policy interest in rural revitalization. Using cross-sectional data for 285 Chinese prefecture-level cities in 2020, the study constructs a multidimensional ACT (agriculture–culture–tourism) indicator system and employs XGBoost regression with SHAP (SHapley Additive exPlanations) analysis to examine the nonlinear associations between ACT factors and economic resilience. Spatial analysis reveals significant positive spatial autocorrelation (Moran’s I = 0.412) and pronounced regional disparities. Machine learning results indicate that traditional village numbers and primary industry value-addedness are the most important predictors, with SHAP dependence analysis revealing threshold effects and diminishing marginal returns. An illustrative micro-level case study of 140 social media posts from Guangzhou provides interpretive evidence on how low-intensity, leisure-oriented tourism experiences mediate the translation of ACT resources into economic outcomes. The findings suggest that ACT integration is associated with stability-oriented resilience buffering rather than transformative growth, highlighting the importance of functional integration, product diversification, and institutional capacity for enhancing regional economic resilience. Full article

Amid accelerating climate change, natural resource depletion, and rising consumer demand for sustainable, health-promoting products, circular agriculture has emerged as a strategic pathway for reconciling agricultural productivity with environmental and social sustainability; however, empirical evidence on how circular production, health-product innovation, and experiential tourism can be jointly evaluated within a single model remains limited. This study aims to propose a multidimensional value assessment framework for circular agriculture through a case study of the Tam Dao Mushroom Cooperative (TDMC) in Phu Tho Province, Vietnam, centered on the cooperative’s Cordyceps militaris-based production system, nanotechnology-enabled health-product processing, most notably the Nano Cordy Milk functional beverage and Science, Technology, Engineering, and Mathematics (STEM)-oriented experiential tourism activities, comprising guided production tours, hands-on cultivation and processing demonstrations, and on-site product tastings offered to school and university groups, domestic and international tourists, and visiting farmers and cooperatives. The research integrates a case study approach with the Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) to determine the priority weights of value dimensions based on the evaluations of seven experts. The findings identify five key dimensions of value generated by the circular agricultural model: economic value, environmental value, social value, educational value, and tourism value. The Fuzzy-AHP results indicate that economic value has the highest priority weight (Best Non-fuzzy Performance, BNP = 0.4050), followed by environmental value (0.2715), social value (0.1307), educational value (0.1313), and tourism value (0.0621). The study demonstrates that the circular agriculture model not only generates economic benefits but also simultaneously creates significant environmental, social, educational, and tourism values. These findings contribute to the theoretical foundation for assessing the multidimensional value of circular agriculture while providing practical references and policy implications for the sustainable development of circular agricultural models. Full article

Water resource conservation and intensive utilization is an important pathway for promoting sustainable regional water resource management and high-quality development. Against the backdrop of increasing constraints on water resources, existing studies have paid insufficient attention to the multidimensional comprehensive assessment of water resource conservation and intensive utilization capacity and its underlying evolutionary mechanisms. Therefore, Heilongjiang Province was selected as the study area, and an evaluation system comprising 15 indicators was established. The game-theoretic combination weighting method, TOPSIS model, obstacle degree model, and GM(1,1) grey forecasting model were employed to comprehensively evaluate, diagnose obstacle factors, and predict the trend of water resource conservation and intensive utilization capacity in Heilongjiang Province from 2004 to 2023. The results showed that the overall capacity exhibited a fluctuating upward trend, with the comprehensive evaluation value increasing from 0.44 to 0.62. The industrial water reuse rate, effective utilization coefficient of farmland irrigation water, comprehensive water consumption rate, per capita water consumption, and ecological water use rate were the indicators with relatively high obstacle contributions. The obstacle factors exhibited distinct stage-specific characteristics: the constraining effects of efficiency-related indicators gradually weakened, whereas those of the comprehensive water consumption rate and per capita water consumption generally intensified, indicating that the factors constraining water resource conservation and intensive utilization in Heilongjiang Province underwent distinct stage-specific changes. The prediction results indicated that the capacity for water resource conservation and intensive utilization in Heilongjiang Province would continue to increase steadily in the future. However, balancing ecological water use requirements with growing water demand remains an important factor affecting sustainable water resource utilization. The evaluation–diagnosis–prediction framework developed in this study can provide a reference for the assessment and optimized management of regional water resource conservation and intensive utilization. Full article