Search Results (2,399)

Against the backdrop of global agricultural sustainability transition, this study examines the mechanism through which peer effects influence the intention–behaviour paradox in farmers’ adoption of organic fertilisers as a substitute for chemical fertilisers, from the perspective of ecological rationality. Using survey data from 505 rice farmers in Hunan Province, this research integrates peer effects and ecological rationality into a unified analytical framework and employs a Probit model to test the mediating role of ecological rationality in the relationship between peer effects and the intention–behaviour gap in chemical fertiliser reduction for sustainable farmland management. The results show that support from family members and people in one’s immediate social environment can effectively alleviate the intention–behaviour paradox among farmers in the process of substituting chemical fertilisers with organic fertilisers, whereas support from friends is positively correlated with this degree of discrepancy. Ecological rationality serves as a mediating variable that strengthens the positive effect of peer influence on the consistency between farmers’ behavioural intentions and actual practices in sustainable agricultural production. These findings provide a new theoretical perspective for understanding farmers’ pro-environmental behaviour, and offer actionable policy implications for advancing agricultural sustainability by enhancing family and community support and improving farmers’ ecological rationality. Full article

The Fuzzy Cognitive Map (FCM) framework provides a useful tool for representing the complex interdependencies involved in wastewater treatment selection, particularly when social, ecological, climatic, and economic criteria are considered simultaneously. In this study, the FCM approach was applied to compare two wastewater treatment approaches in Ahvaz, Iran: constructed wetlands (CWs) as a nature-based solution and energy-based wastewater treatment plants. The developed model included 30 components and 127 causal links, and was used to examine four scenarios representing CWs, energy-based treatment, a hybrid approach, and direct wastewater discharge. The results showed that both CWs and energy-based solutions had similar effects on public health, while the hybrid scenario produced the greatest improvement. CWs had a positive effect on ecosystem restoration and showed better performance in heavy metal removal, whereas energy-based solutions had a greater negative influence on environmental conditions and climate-related components. In addition, the economic results indicated that CWs were more favorable in terms of capital cost, energy consumption, and operational cost. Sensitivity analysis using ±10% variations in causal weights showed that the main scenario-response patterns remained generally unchanged. Overall, the findings suggest that CWs and energy-based systems each have specific advantages and limitations, while the hybrid approach offers the most balanced performance across the evaluated criteria. This study demonstrates the usefulness of the FCM approach for supporting wastewater management decisions and for identifying trade-offs among treatment alternatives in sustainable water resource planning. Full article

As China’s urbanization shifts toward quality-oriented development, urban regeneration increasingly prioritizes the perceived quality of public spaces to enhance urban vitality and advance sustainable urban living. This study takes Zhengzhou’s Dongfeng Canal, a revitalized urban core waterfront, as a case to develop a human–machine collaborative analytical framework for exploring nonlinear relationships between visual environmental features and human spatial quality perception. By integrating 779 geolocated panoramic images with volunteers’ subjective rating data, this study adopts deep learning-based semantic segmentation to quantify eight objective visual indicators (e.g., greenness, color diversity, spatial structure). A random forest (RF) model links these indicators to three perceptual dimensions: scenic beauty, safety, and recreational value. Adopting explainable artificial intelligence (SHAP and PDPs), the results indicate that: (1) greenness is positively associated with positive perceptions but exhibits a significant threshold effect; (2) color diversity and waterfront accessibility substantially improve user experience, while excessive uniformity and extreme openness negatively affect perceived spatial quality. These findings challenge the simplistic linear “more-is-better” assumption in urban design and highlight the value of balanced, context-sensitive spatial interventions. This study provides evidence-based, segment-specific strategies for urban waterfront regeneration, advancing people-centered planning that integrates ecological functionality, social inclusivity, and long-term sustainability via Geospatial Artificial Intelligence (GeoAI) and geospatial analytics. Full article

The core predicament of energy transition lies not in the availability of clean technologies, but in whether an economy possesses the institutional capacity and social foundation to systematically regulate its carbon-energy metabolic processes. Drawing upon co-evolutionary theory from evolutionary economics, this paper constructs a composite indicator of Low-Carbon Green Energy Eco-Co-evolution (LCEE) encompassing three functional dimensions: efficiency advancement, kinetic energy replacement, and boundary adherence. Concurrently, by integrating innovation ecosystem theory with inclusive development theory, we propose the concept of “Inclusive Potential of Regional Innovation Ecosystems” (IEP), characterizing the systemic potential for transforming innovation outcomes into social welfare across four dimensions: Knowledge Matrix Abundance (KMF), Cultural Capillary Permeation (CCP), Technological Community Succession (TCS), and Social Root Nourishment (SRN). Taking China’s 2016 intellectual property (IP) powerhouse construction pilot as the institutional prototype of Industrial Intellectual Property Upgrading Reform (IPR), we incorporate IPR, IEP, and LCEE into a unified causal analytical framework, proposing a testable transmission logic of ‘institutional supply → ecological development → co-evolutionary synergy. Using panel data from 30 Chinese provincial-level administrative regions over 2010–2022, we employ a Spatial Durbin Difference-in-Differences (SDM-DID) model to identify the direct and spatial spillover effects of IPR on LCEE, and embed a Double Machine Learning (DML) framework to test the mediating mechanism of IEP while controlling for high-dimensional nonlinear interference. The findings reveal that IPR exerts a significant and robust direct promoting effect on LCEE, generating positive spatial spillovers to neighboring regions through the public disclosure of patent information. IEP significantly promotes local LCEE, yet its spatial spillover lacks statistical support due to structural conflicts in inter-dimensional transmission attributes. IEP plays a significant partial mediating role between IPR and LCEE, with the indirect effect accounting for over one-third of the total effect, a finding robust to alternative machine learning algorithms, sample split adjustments, and exclusion of contemporaneous competing policies. Sub-path tests reveal that KMF bears the strongest mediating efficacy, serving as the primary transmission channel, while CCP exhibits full mediation—the institutional effect on LCEE in the cultural dimension depends almost entirely on the mediating transformation through the public cultural service system. Heterogeneity analysis further demonstrates full mediation in the Low-Carbon Green Energy Eco-Kinetic Replacement (KER) dimension, indicating that the institutional catalytic effect on clean energy substitution must be realized through IEP transformation. This paper provides empirical evidence for the proposed causal pathway through which institutional public goods indirectly enhance the synergistic quality of carbon-energy transition via the inclusive potential of innovation ecosystems, providing theoretical foundations and policy implications that, while grounded in China’s institutional context, may offer valuable reference points for emerging market economies facing similar dual pressures of technological constraints and green transition. Full article

Urban agglomerations are increasingly exposed to shocks that extend across administrative boundaries through infrastructure systems, industrial chains, population mobility, and shared ecological spaces. Existing urban resilience research has predominantly assessed city-level capacity, while comparatively less attention has been paid to the relational structures associated with differences in resilience capacity and geographic proximity. This study examines the model-implied spatial correlation network of urban resilience across 41 cities in the Yangtze River Delta from 2013 to 2022. A multidimensional resilience index covering economic, infrastructure, social, and ecological dimensions was constructed using the entropy weight method and directed intercity interaction potentials were estimated using a modified gravity model and analyzed through social network analysis. The results show that overall resilience improved during the study period, although substantial cross-city disparities persisted. Under the baseline row-specific mean threshold, network density remained broadly stable, fluctuating between 0.2476 and 0.2506 and decreasing slightly from 0.2506 in 2013 to 0.2482 in 2022. The model-implied network remained fully reachable but relatively sparse, with persistent positional differentiation. Nanjing and Hangzhou consistently occupied leading total-degree positions, while Hefei, Nanjing, Hangzhou, Huangshan, and Chuzhou repeatedly exhibited relatively high betweenness. The block-model structure was also comparatively stable, with only three cities changing block membership between 2013 and 2022. Robustness analyses further showed that broad positional differentiation was more stable than exact density levels, outward-oriented rankings, and brokerage positions. Overall, improvements in city-level resilience did not translate into substantial densification or reorganization of the regional network, highlighting the need to distinguish internal resilience capacity from model-implied network position when designing differentiated regional coordination strategies. Full article

Xinjiang grasslands are major ecological barriers and pastoral bases exposed to climate variability, grazing, land-use change, and socioeconomic pressures. This study assessed the vulnerability of grassland social–ecological systems in 81 counties from 2001 to 2020. A driver–pressure–state–impact–response (DPSIR) framework was integrated with CRITIC weighting and the TOPSIS model. Sen’s slope estimator and the Mann–Kendall test were used to detect temporal trends, and the obstacle degree model identified key constraints. The mean vulnerability index declined from 55.82 to 50.27, accompanied by a marked increase in counties with low or relatively low vulnerability. Vulnerability was highest in southern Xinjiang, where highly vulnerable counties were concentrated in densely populated oasis agricultural areas. Significant declines occurred in 80 of the 81 counties. The response, state, and pressure dimensions showed the highest obstacle degrees. Fiscal self-sufficiency, agricultural machinery power, the grassland–cropland ratio, economic density, and the remote sensing ecological index were the main obstacles. Declining vulnerability was associated with lower grazing intensity, a smaller bare land proportion, and increases in economic density, rural disposable income, and total agricultural machinery power, whereas the comparatively high vulnerability in southern Xinjiang was associated with limited fiscal capacity, lower ecological quality, and arid conditions. These findings support region-specific grassland conservation and differentiated county-level governance. Full article

Background: Pakistan is one of only two countries where wild poliovirus type 1 (WPV1) continues to persist. Vaccine refusals challenge efforts to end the virus, especially in high-risk communities. Methods: A qualitative exploratory study took place from September to November 2025 in three High-Risk Union Councils (HRUCs) of Karachi, Pakistan. The study examined reasons for refusing the polio vaccine and identified specific communication and operational strategies to improve vaccine acceptance. A total of 23 in-depth interviews and 10 focus group discussions were conducted with 71 participants, including parents who refuse the vaccine, polio program staff, physicians, and government stakeholders. Data were analyzed using a sequential inductive and deductive thematic approach, mapping findings onto the Socio-Ecological Model (SEM) with NVivo 15 (Lumivero, Denver, CO, USA). Results: Factors influencing polio vaccine refusals were interconnected and spanned multiple levels. At the intrapersonal level, campaign fatigue, a lack of knowledge about poliomyelitis, concerns about side effects, and rumors about infertility were common. Community-level factors included household gatekeepers, local influencers, and digital misinformation. Institutional barriers included weak communication from the frontline, inadequate supervision, workforce shortages, poor tracking of refusals, and limited involvement of physicians. At the policy level, refusals were linked to distrust in governance, poor municipal services, and dissatisfaction with vertical campaign methods. Recommended strategies included integrating polio services with routine immunization and primary healthcare, strengthening counseling by physicians, engaging trusted local influencers and community leaders, expanding targeted social media campaigns to counter misinformation, implementing quick responses to rumors, enhancing workforce capacity, and using data-driven microplanning, including targeted SNIDs and focused interventions in areas with chronic refusals. Conclusions: Polio vaccine refusals are shaped by social, communication, operational, and structural factors. Improving communication and operational guidelines by reducing the number of campaigns, increasing active engagement at the frontline, integrating polio activities into routine health services, and addressing misinformation with a dynamic communication strategy may enhance vaccine acceptance and support polio eradication efforts. Full article

Brazil presents a distinctive convergence of continental-scale climatic diversity, extensive urbanization, large-scale biomass burning, rapid land-use change, persistent air-quality monitoring gaps, and deep social inequalities, producing highly heterogeneous and compound environmental health risks. In this context, treating air pollution and climate change as parallel environmental crises obscures their structural interconnections through shared emission sources, mutually reinforcing exposure pathways, and overlapping health and social consequences. In this narrative review, we critically synthesize scientific and institutional lines of evidence and argue that air pollution and climate risks can be more effectively addressed in Brazil through a single strategic agenda for science, public health, and governance. We first discuss why these challenges cannot be managed in isolation, emphasizing the effects of heat, drought, stagnation events, biomass burning, and extreme weather on pollutant formation, dispersion, and health burden. We then examine Brazil as a critical case where recent regulatory advances coexist with structural limitations in monitoring, data integration, and territorial coverage. Based on this diagnosis, we propose an integrated national agenda organized around five mutually reinforcing priorities: monitoring through hybrid networks; predictive science through climate-informed modeling and early warning; public health through the convergence of epidemiology, toxicology, and mechanistic research; equity-oriented research and action through the explicit incorporation of vulnerability, inequality, and climate justice; and policy appraisal through the assessment of disease burden, economic costs, mitigation co-benefits, and trade-offs. We further discuss the governance mechanisms needed to connect these priorities and translate evidence into coordinated action and adaptive public policies. We also argue that the Amazon should be approached not as an isolated ecological exception but as a central component of a broader Brazilian and Global South discussion on environmental health, land-use change, and climate justice. In this scenario, Brazil has the scientific capacity and regulatory momentum to become a reference in the integrated management of air pollution and climate risks, but this will depend on replacing fragmented approaches with a coordinated framework capable of linking exposure, mechanism, burden, inequality, and action. Full article

The central challenge of the energy transition lies in whether an economy possesses the institutional capacity to systematically regulate its own energy inputs and carbon emissions. Drawing upon social metabolism theory, this study constructs an indicator of carbon–energy metabolic control capacity (CMCC). Building on business ecosystem theory, it conceptualizes the intelligent economic ecosystem (IEE) and incorporates industrial chain intellectual property empowerment (IP) into a causal framework of institutional provision → ecosystem development → enhancement of metabolic control capacity. Using panel data from 30 provincial-level administrative regions in China covering the period 2010–2022, this study employs a spatial Durbin difference-in-differences (SDID) model and a double machine learning (DML) framework for empirical analysis. The results indicate that industrial chain intellectual property empowerment significantly enhances carbon–energy metabolic control capacity and generates positive spatial spillover effects on neighboring regions through the public diffusion of patent information. Furthermore, intelligent economic ecological development serves as a significant partial mediator between intellectual property empowerment and carbon–energy metabolic control capacity, with the indirect effect accounting for more than one-third of the total effect. This mediating mechanism remains robust after replacing machine learning algorithms, altering sample-splitting ratios, controlling for concurrent innovation policies, and excluding the impact of the COVID-19 pandemic. Path-specific mediation analysis further reveals that computing power acquisition and value transformation together with digital substrate robustness constitute the dominant transmission channels, whereas innovation metabolic flux contributes a relatively smaller mediating effect due to the long gestation period required for translating fundamental research into practical applications. Heterogeneity analysis further demonstrates that the transmission mechanism exhibits full mediation in the dimension of metabolic structure, indicating that the contribution of industrial chain intellectual property empowerment to the clean substitution of energy structures depends almost entirely on the mediating role of the intelligent economic ecosystem. These findings provide clear actionable guidelines for three specific policy-making domains to advance low-carbon transitions. First, intellectual property authorities should transition from quantity-driven patent creation to establishing cross-regional patent navigation and industrial chain IP pooling. Second, digital economy and industry regulators need to prioritize computing power value conversion (CCV) over raw infrastructure expansion to mitigate energy rebound effects. Third, energy and environmental agencies ought to integrate real-time algorithmic dispatching with green finance incentives. Ultimately, this study demonstrates that achieving deep low-carbon transformation requires leveraging institutional public goods to catalyze digital ecosystems, which in turn enable precise, dynamic carbon–energy metabolic control. Full article

Peripheral vestibulopathy (PV) is a common disorder that causes dizziness and balance impairment, substantially affecting patients’ quality of life. When symptoms persist, they frequently lead to anxiety, depression, and an increased risk of social isolation. Although central vestibular compensation (CVC) often promotes functional recovery, current pharmacological options remain limited and are primarily aimed at symptom control. Consequently, they should be considered adjuncts rather than alternatives to rehabilitation-based strategies. Vestibular rehabilitation (VR) remains the cornerstone of treatment for promoting functional recovery in patients with PV. Based on the complementary mechanisms of adaptation, substitution, and habituation, VR enhances the central nervous system’s ability to compensate for vestibular deficits by optimizing the integration of visual, proprioceptive, and residual vestibular inputs. Robust evidence from both clinical and preclinical studies has demonstrated its efficacy in improving postural stability, dynamic balance, gaze stabilization, and overall functional performance. Experimental studies using animal models have further highlighted the critical role of active sensorimotor training in ecologically relevant environments for enhancing vestibular compensation. Pharmacological interventions may further facilitate these adaptive processes by modulating the neurobiological mechanisms underlying vestibular compensation, thereby improving responsiveness to rehabilitation. Likewise, emerging neuromodulation approaches, including galvanic vestibular stimulation, have shown promising potential to enhance neural plasticity and augment the effects of rehabilitation. Consequently, combining VR with targeted pharmacological therapies and/or vestibular stimulation techniques may provide synergistic benefits and maximize functional recovery. In conclusion, vestibular rehabilitation should remain the foundation of PV management and be integrated with pharmacological and neuromodulatory approaches within a multidisciplinary therapeutic framework. Further research is needed to optimize rehabilitation protocols, identify the biological determinants of successful vestibular compensation, and develop personalized therapeutic strategies aimed at maximizing functional recovery and improving patients’ quality of life. Full article

A growing demand for resources that exceeds the capacity of the biophysical system to regenerate puts environmental resources under stress, and society faces uncertainties about their scarcity and climate change. In this context, understanding how interactions among environmental, social, and economic systems shape behavioural responses becomes essential for explaining the emergence of sustainable socio-ecological dynamics. Therefore, this research explores how interactions among environmental, social, and economic systems influence sustainability outcomes, where emergent behaviours, including cooperation, reveal the interaction mechanisms connecting environmental, social and economic subsystems. A simulation model is built using the agent-based model method for this goal. The simulations suggest that scarcity may reinforce non-cooperative behaviours and generate lock-in dynamics that hinder transitions toward more sustainable system states. Additionally, cooperative behaviours emerge from the interactions among heterogeneous agents embedded within environmental, social, and economic subsystems, highlighting cooperation as a key mechanism connecting these subsystems and supporting more sustainable socio-ecological dynamics. Full article

Rapid urbanization in China has intensified ecological degradation, loss of architectural and cultural heritage, and declining well-being in traditional villages. Existing conservation approaches often address ecological, economic, or physical heritage issues in isolation, while insufficiently incorporating residents’ quality of life (QoL) as a central criterion of sustainability. This study develops a human-centred traditional village preservation framework grounded in the ecovillage concept and a QoL-oriented sustainability paradigm, using Langde Miao Village in Guizhou Province as a representative ethnic heritage settlement. A mixed-methods approach combining systematic literature review, Delphi expert consultation, household surveys, and partial least squares structural equation modelling (PLS-SEM) was employed to examine the interrelationships among ecological, cultural, social, and economic dimensions of sustainable built heritage. Based on valid responses, the empirical results indicate that the ecological dimension exerts the strongest direct effect on residents’ quality of life, followed by the cultural and economic dimensions, while the social dimension shows a comparatively weaker effect. The proposed framework provides a community-centred model for sustainable architectural heritage conservation and rural revitalization in traditional villages. Full article

Tuberculosis (TB) remains one of the most burdensome infectious diseases in Indonesia. One contributing factor is the environment, particularly issues related to household ventilation and lighting. TB control efforts do not solely rely on medical interventions but also require a community-based approach that emphasizes active community involvement in preventing and controlling environmental risks to TB transmission. This study aims to analyze risk factors, distribution patterns, and their implications for environmentally based TB transmission risk control strategies. A mixed-methods design was conducted in two stages: first, risk factor analysis (with a case–control approach) and disease distribution pattern determination on environmental variables were performed, followed by a multidimensional scaling model (by using the Rapid Appraisal for Fisheries (RAPFISH) method) according to sustainability dimensions (ecological, economic, social, institutional, and technological) based on the resulting significant variables/indicators. This research was conducted in 2024, in four villages/nagari in West Sumatra of Indonesia. For quantitative analysis, data were collected through interviews, physical measurements of the environment, and determination of the coordinates of the residences of people with TB. Data were analyzed using bivariate and multivariate analyses. For the distribution pattern, Nearest Neighbor Analysis (NNA) in the ArcView program version 3.1 was used. Meanwhile, for qualitative data collection, focus group discussion (FGD) was performed. This study found that poor ventilation, minimal lighting, and a lack of stigma competency significantly increased the risk of TB transmission. Varied distribution patterns between regions demand adaptive and locally based strategies. The community-triggering approach is key to building community awareness and participation in creating a healthy and TB-free home environment. Full article

The transmission of trauma across generations has traditionally been explained through genetic, epigenetic, familial, and attachment-based mechanisms. While these approaches have generated valuable insights, they remain insufficient for explaining the persistence of psychological vulnerability in contexts where the original traumatic event has disappeared but maladaptive patterns continue to emerge across generations. This paper introduces the Contextual Resonance Theory of Psychopathology (CRTP), a novel cognitive–systemic framework proposing that transgenerational trauma is maintained through the recursive reproduction of trauma-shaped environments rather than exclusively through biological inheritance. According to this model, traumatic experiences generate adaptive cognitive, emotional, and behavioral responses that become embedded within family narratives, relational structures, institutional practices, and cultural expectations. Over time, these adaptations evolve into self-maintaining contextual systems that continuously communicate threat, unpredictability, and hypervigilance to subsequent generations. The theory introduces the concepts of contextual traumatic inertia, distributed psychopathology, and recursive contextual resonance to explain how vulnerability becomes socially reproduced even in the absence of direct trauma exposure. Drawing on predictive processing, ecological psychology, systems theory, and contemporary trauma research, the paper proposes that psychopathology emerges from persistent interactions between individuals and pathogenic environments rather than solely from intrapsychic dysfunction. Furthermore, a complementary mechanism termed corrective recontextualization is proposed as a pathway for reversing transgenerational vulnerability through repeated exposure to safe, predictable, and psychologically restorative contexts. The framework offers an integrative perspective capable of bridging cognitive neuroscience, developmental psychopathology, trauma studies, and mental health intervention research. Clinical, educational, organizational, and societal implications are discussed, alongside future directions for empirical validation and neurocognitive investigation. Full article

Understanding land-use carbon emissions (LUCE) requires accounting for both spatial heterogeneity and intercity linkages, yet most studies treat cities as isolated units, overlooking network-level interactions and their implications for regional ecological support and functional zoning. Using the Beijing–Tianjin–Hebei urban agglomeration as a case study, we estimated LUCE from 2005 to 2020 via the carbon emission coefficient method, constructed potential intercity association networks using a gravity model and social network analysis (SNA), and integrated ecological support capacity (ESC) with network structural roles to develop a two-dimensional carbon balance zoning framework. Results indicate that LUCE exhibited an overall increasing trend with a stable south-high and north-low spatial pattern. The association network remained connected and exhibited a persistent core–periphery structure, with Beijing and Tianjin occupying core positions and the network showing increasing concentration after 2010. ESC displayed an opposite spatial gradient to LUCE, indicating stronger ecological support in northern and northwestern cities and weaker support in central-southern areas. Integrating ESC and network structural roles identified four carbon balance functional zones. The integrated framework provides a basis for differentiated low-carbon land-use management and collaborative carbon governance in urban agglomerations. Full article