Search Results (690)

Background/Objectives: Weight loss achieved through lifestyle interventions has been demonstrated to improve the clinical prognosis of female hyperandrogenism. However, the interplay between such interventions, androgens, and glucose–lipid metabolism remains heterogeneous. This study evaluated the effects of lifestyle-induced weight loss on glucose and lipid metabolism and androgen levels in Chinese women of reproductive age with hyperandrogenism and examined the association between the degree of weight loss and changes in androgen levels, glucose and lipid metabolism, exercise capacity, and dietary patterns. Methods: This observational study, based on real-world clinical settings, collected medical records of women of reproductive age with hyperandrogenism who underwent weight-loss interventions between July 2023 and September 2025. Correlation analysis employed Spearman’s rank correlation coefficient, whilst pre- and post-weight-loss comparisons utilised paired t-tests or Wilcoxon signed-rank tests. Results: After a follow-up of 6 to 7 months, a total of 66 participants achieved a mean weight loss of 5.67 ± 4.27 kg. Statistically significant reductions were observed in testosterone (0.40 ± 0.10 vs. 0.30 ± 0.10 ng/mL, p < 0.001), androstenedione (p < 0.001), and the free androgen index (p < 0.001). Glucose metabolism showed statistically significant improvement, with decreases in HOMA-IR (p = 0.040), fasting glucose (p = 0.001), and fasting/2 h postprandial insulin (p < 0.001). However, lipid profiles showed no statistically significant changes. Multiple linear regression revealed that change in testosterone was independently and inversely associated with change in apolipoprotein A1 (β = −0.496, p = 0.008), while change in dehydroepiandrosterone sulfate was inversely associated with change in fasting insulin (β = −0.357, p = 0.032). A non-linear, inverted U-shaped relationship was found between weight loss magnitude and change in sex hormone-binding globulin, with moderate weight loss (5–10%) yielding the greatest increase (p = 0.044). Marked weight loss (≥10%) was associated with the lowest follow-up fasting insulin levels (p = 0.039). Conclusions: Weight loss achieved through lifestyle interventions is associated with improvements in androgen levels and glucose metabolism, though its impact on lipid metabolism remains limited. The degree of improvement in insulin sensitivity correlates more strongly with the magnitude of weight reduction. Full article

Fulfilling corporate ESG responsibilities enhances a firm’s sustainable development capabilities but also comes at an economic cost. This study investigates whether firms should invest heavily in ESG or maintain moderate ESG practices to balance cost efficiency and resilience. Using a sample of A-share listed companies in China from 2012 to 2024, we employ OLS regression models to explore the impact of ESG responsibility fulfillment on cost stickiness and the factors that influence this relationship. The study finds that (1) there is an inverted U-shaped relationship between corporate ESG responsibility fulfillment and cost stickiness; (2) the turning point lies between the B and CCC Huazheng ESG rating levels. Below this level, ESG responsibility fulfillment reduces cost stickiness, while above it, excessive ESG fulfillment increases cost stickiness; (3) environmental sensitivity, managerial overconfidence, and state ownership amplify this non-linear effect, making the reduction or increase in cost stickiness more pronounced. This paper deepens the understanding of the drivers of cost stickiness from the perspective of ESG responsibility fulfillment, offering new insights for future research on cost behavior and providing valuable guidance for firms seeking to optimize cost management through ESG strategies. Full article

In the new development stage of China’s green and low-carbon transition, agricultural industry agglomeration serves as a key catalyst for sustainable agricultural practices. Its effects on agricultural carbon reduction and energy conservation urgently need investigation. This research uses panel data from 31 Chinese provinces spanning 2005 to 2021 to investigate the nonlinear effects of agricultural industry agglomeration on agricultural carbon emissions and energy consumption, employing econometric models such as the two-way fixed effects model, mediation model, and moderation model. The findings indicate that (1) there’s a clear inverted U-shaped pattern linking agricultural industry agglomeration to both carbon emissions and energy consumption in agriculture; (2) agricultural scale effects and socialized services are key mechanisms; (3) marketization and environmental regulation positively moderate this relationship; and (4) the carbon reduction and energy-saving effects are more pronounced in regions with higher agricultural modernization levels, higher urbanization rates, and plain areas. This finding contributes to optimizing the path of agricultural industry agglomeration and facilitates the synergy of carbon reduction and energy conservation in such agglomeration. Full article

Freshwater aquaculture in China has expanded rapidly in recent decades, raising growing concerns about its environmental sustainability. However, the relationship between industrial agglomeration and environmental efficiency in freshwater aquaculture remains insufficiently understood. Using panel data from 18 major freshwater aquaculture provinces in China from 2009 to 2023, this study investigates the nonlinear effects of industrial agglomeration on environmental efficiency. Environmental efficiency is evaluated using a Global Super-SBM model incorporating undesirable outputs, while industrial agglomeration is measured by the location quotient index. A two-way fixed-effects model is employed for empirical estimation. The results reveal a significant inverted U-shaped relationship between industrial agglomeration and environmental efficiency, with a turning point at an agglomeration level of 2.519. Moderate agglomeration improves environmental efficiency through economies of scale and technology diffusion, whereas excessive agglomeration generates crowding effects that reduce efficiency. Further mechanism analysis shows that technology diffusion, proxied by the number of trained fishermen, plays a significant mediating role in this relationship. This study provides new empirical evidence on the nonlinear environmental effects of industrial agglomeration in freshwater aquaculture and offers policy implications for optimizing industrial spatial layout and developing differentiated environmental regulations to support the green and sustainable development of the sector. Full article

Monitoring the activity of the autonomic nervous system, including the sympathetic and parasympathetic divisions, plays a crucial role in studying emotional processing. However, few methods allow the dynamic tracking of parasympathetic activity. Here, we propose a testable hypothesis that ear thermography may serve as a dynamic index of sympathetic and parasympathetic activity, with a time resolution of seconds. Anatomical and physiological evidence suggests that the vascular structures of the ear may be innervated in a region-specific manner by the autonomic nervous system, with the posterior regions (e.g., the helix) predominantly influenced by sympathetic activity and the anterior regions (e.g., the tragus) potentially affected by parasympathetic mechanisms. Recent thermographic studies during emotional film viewing have demonstrated distinct spatial and functional patterns: posterior regions showed a linear negative association between temperature and emotional arousal, consistent with sympathetic vasoconstriction, whereas anterior regions exhibited a non-linear (inverted-U-shaped) relationship, resembling the known non-monotonic characteristics of parasympathetic activity. These findings suggest that ear thermography may be used to assess sympathetic- and parasympathetic-related dynamic processes, although direct evidence remains to be established. Full article

From the perspective of interactions between energy firm behavior and government intervention strategies, this study develops a contagion control model for energy firm debt default risk utilizing cellular automata and complex network theory. This research investigates the spatio-temporal evolution of risk transmission and evaluates the efficacy of various mitigation protocols through computational simulation. The research results indicate that: (1) An escalation in both the transmission likelihood and the rate of immunity decay significantly amplifies the propagation strength of debt default risks. Conversely, the stability of the energy firm network is bolstered as the probabilities of immunity and recovery increase. (2) The contagion intensity for debt default risk is positively correlated with market noise, the risk appetite of energy firms, and their corporate influence. It is negatively correlated with risk awareness, creditworthiness, regulatory intensity, and policy subsidies. Furthermore, it exhibits an inverted U-shaped relationship with investor sentiment. (3) Within the interconnected network of energy firms, risk contagion can be effectively mitigated not only by enhancing risk perception and credit standing but also by guiding risk preference and managing firm influence. Furthermore, the integration and adjustment of government intervention strategies, such as regulatory intensity and policy subsidies, can more efficiently accelerate the eradication of debt default risk among energy firms. Full article

This paper develops a theoretical model to analyze the protective effect and nonlinear mechanism of preferential rules of origin (ROOs) on regional supply chains amid global value chain restructuring and rising regional supply chain security demands. Supported by numerical simulations and a triple difference-in-differences (DDD) empirical approach based on the China–ASEAN Free Trade Agreement (CAFTA), the findings reveal a nonlinear, inverted U-shaped relationship between ROO stringency and supply chain stability—exhibiting a typical Laffer curve characteristic. Moderate restrictions significantly promote intra-regional intermediate goods procurement and stabilize regional supply chain layout, while excessively stringent rules raise enterprise compliance costs and restrain integration. These findings carry important implications for regional economic resilience and sustainable development. While our empirical analysis focuses on economic resilience (measured through regional procurement stability), we discuss how well-designed ROO may also support broader sustainability goals, including contributions to SDG 8 (Decent Work and Economic Growth) and SDG 17 (Partnerships for the Goals) through more stable and inclusive regional production networks. The study highlights the need for careful calibration of ROO stringency to balance protective effects with compliance costs in pursuit of both resilient and sustainable regional trade governance. Full article

Industrial robots are an important strategic resource for manufacturing firms to achieve automation and intelligent development, and their role in corporate risk management has become increasingly prominent. Using data on Chinese A-share-listed manufacturing firms from 2012 to 2023, this paper examines the impact of industrial robot adoption on firms’ risk-taking levels. The results show that for every one-unit increase in industrial robot application, the firm’s risk-taking level increases by 0.206 and 0.384 units, respectively. Mechanism analyses indicate that the use of industrial robots can reduce agency costs and enhance innovation capability, thereby promoting higher levels of corporate risk-taking. Further analysis reveals that the positive effect of industrial robot adoption on firms’ risk-taking is significant only for privately owned firms, firms facing high financing constraints, firms with a higher proportion of technical employees, and firms located in regions with high innovation network density. Meanwhile, the relationship between corporate risk-taking and firm value exhibits an inverted U-shaped pattern, indicating that firms should adhere to the principle of moderation when introducing industrial robots, so as to avoid potential damage to firm value caused by excessive or blind investment. This study extends the literature on industrial robots and corporate risk-taking and provides important implications for Chinese manufacturing firms seeking to enhance their risk-taking capacity through the adoption of intelligent technologies. Full article

Climate change represents a major threat to environmental sustainability by accelerating ecological degradation and undermining long-term economic resilience, particularly in emerging economies. Motivated by the growing policy need to understand how energy structure and socioeconomic conditions shape environmental outcomes, this study examines the impact of energy consumption, structural change, human capital, financial development, and political risk on the ecological footprint of Mexico, Indonesia, Nigeria, and Türkiye (MINT economies). Guided by an extended Environmental Kuznets Curve (EKC) framework, the study examines whether environmental degradation follows a nonlinear trajectory in response to energy consumption, rising at the initial stages of energy expansion due to dominant scale effects, but declining beyond a critical threshold as efficiency gains, technological progress, and structural adjustments begin to offset environmental pressures. Energy consumption is disaggregated into oil-based energy, natural gas, and renewable energy to capture their distinct environmental effects. The empirical analysis employs the Panel-Corrected Standard Errors estimator as the baseline approach, complemented by Feasible Generalized Least Squares and Generalized Method of Moments estimators to ensure robustness and to address potential endogeneity and cross-sectional dependence. The results show that renewable energy and oil consumption exhibit inverted U-shaped relationships with environmental degradation, indicating nonlinear threshold effects consistent with EKC-type adjustments. In contrast, natural gas consumption demonstrates a predominantly linear and environmentally deteriorating effect, with no statistically significant turning point. Economic growth consistently intensifies environmental pressure, confirming the dominance of scale effects in rapidly industrializing economies. Structural change and human capital contribute to environmental improvement under certain specifications, while political risk exacerbates environmental degradation. Meanwhile, financial development shows an insignificant negative impact on environmental degradation. The results emphasize the importance of accelerating renewable energy expansion beyond critical penetration thresholds while progressively reducing fossil fuel dependence and strengthening institutional frameworks to ensure that economic growth translates into sustained environmental improvement. Full article

Global climate change is intensifying, and green technology innovation (GTI) is widely regarded as a core driver of low-carbon economic transition. However, its actual emission reduction effects remain debated. Based on panel data from 30 Chinese provinces (2009–2023), this study constructs a nonlinear econometric model to empirically analyze the impact of GTI on carbon emissions and carbon performance, while also examining the mediating roles of energy consumption structure and industrial structure, and regional heterogeneity. The results show (1) a significant inverted-U relationship between GTI and carbon emissions, and a U-shaped relationship between GTI and carbon performance; (2) GTI indirectly promotes low-carbon transition by reducing the share of coal in energy consumption (energy structure optimization) and increasing the share of the tertiary industry (industrial upgrading); (3) significant regional heterogeneity exists—resource-based cities show weaker emission reduction effects due to traditional energy dependence, while non-resource-based cities exhibit stronger carbon reduction outcomes. Based on these findings, we propose policy recommendations including strengthening GTI financial support, accelerating clean energy adoption, promoting industrial upgrading, implementing region-differentiated policies, and improving GTI evaluation systems to achieve the win-win goal of economic development and environmental protection. Full article

Agricultural mechanization’s carbon consequences remain contested. Using provincial panel data from 30 Chinese provinces (2000–2023), we combine benchmark regression, mediation, threshold, and spatial models to examine how mechanization affects agricultural carbon emission intensity. We find a robust inverted U-shaped relationship, with an inflection point at 0.428; approximately 61% of province-year observations have entered the emission-reduction phase, while provinces with lower mechanization levels (e.g., Yunnan and Guizhou) remain on the upward slope. Mechanization operates through two opposing pathways; higher fertilizer application intensity increases emissions, while greater fertilizer use efficiency reduces them, with the intensity pathway accounting for the larger share of the observed mediated association (68% of the total mediated effect). The emission-reduction effect only materializes once fertilizer use efficiency crosses a critical threshold (−0.626 in log terms); provinces below this level face the risk of carbon lock-in as mechanization expands. A grain-oriented shift in cropping structure and spatial spillovers constitute additional channels, with the latter accounting for over half of the total effect. These findings call for regionally differentiated policies; provinces with persistently low fertilizer use efficiency should build precision fertilization capacity before scaling up mechanization, while more advanced regions can draw on cross-regional machinery networks to spread low-carbon agricultural practices. Full article

The governance of land use carbon emissions is pivotal to achieving the goals of carbon peak and carbon neutrality. Rural revitalization significantly shapes the spatiotemporal patterns and evolutionary dynamics of land use carbon emissions, yet this relationship has received inadequate attention in existing literature. This study employs a combination of decoupling models, the Boston Matrix, spatial analysis, and interpretable machine learning models to conduct an empirical analysis of 124 regions in western China. The findings reveal diversified spatiotemporal evolution trends in rural revitalization land use carbon emissions. The decoupling relationship between rural revitalization and carbon emissions demonstrates a polarized nature, with over half of the assessed regions experiencing negative decoupling effects. The role of impact factors in decoupling relationships is characterized by a mixed nature, hierarchical intensity, nonlinear pathways, spatial heterogeneity and autocorrelation. The pathways of factor effects display nonlinear forms such as wave-like, inverted U-shaped, and U-shaped patterns, with the nature and intensity of effects dynamically shifting between “threshold mutations” and “inflection reversals” as factors evolve. The spatiotemporal evolution patterns, decoupling relationships, and SHAP values all exhibit significant spatial autocorrelation and form “spatial clusters” of various shapes. The decoupling of rural revitalization and carbon emissions in western China constitutes a complex systemic endeavor, necessitating comprehensive analysis from multiple dimensions—encompassing spatiotemporal evolution patterns, decoupling relationship, nonlinear mechanisms, and spatial effects—followed by the formulation of differentiated and precision-targeted governance strategies. Full article

Digital services imports have become a key driver of service trade and globalization. However, their rapid expansion has raised economic and security concerns, leading to increased digital trade barriers. This research investigates how these barriers affect digital services imports. Based on the panel data from 87 countries (2014–2022), the research shows: an inverted U-shaped relationship exists between digital trade barriers and digital services imports, characterized by an initial increase followed by a subsequent decrease. This finding remains robust after addressing endogeneity concerns and conducting a range of sensitivity tests. This relationship is most evident in developed economies with large imports, particularly in telecommunications, and is primarily driven by electronic transaction barriers and other barriers. Mechanism analysis indicates that digital trade barriers affect digital service imports through economic freedom, with the observed inverted U-shaped effect being primarily driven by the government size dimension. The institutional context reinforces the inverted U-shaped effect, with government efficiency and regulatory quality having the strongest moderating influence. By clarifying the inverted U-shaped relationship between digital trade barriers and digital services imports, this research provides a theoretical foundation and empirical evidence to support the sustainable development of digital trade. Full article

Reconciling economic growth with environmental sustainability and energy security is a defining challenge for resource-constrained emerging economies. This study examines whether Jordan follows the Environmental Kuznets Curve (EKC) and the Energy Kuznets Curve (EnKC)—two hypotheses positing that as an economy grows, its environmental degradation and energy consumption follow an inverted U-shaped curve in relation to per capita GDP—as counterparts to the original Kuznets curve. While these relationships have been investigated in cross-country settings, little attention has been given to individual emerging economies such as Jordan, where energy and environmental issues are among the most pressing challenges of the new century. The existence of EKC and EnKC curves is tested using a “time-varying parametric (TVP) framework”—specifically, the unobserved components model (UCM), utilizing annual data from 1980 to 2024. Further tests are carried out to validate the nonlinearity hypothesis using the variable-addition test and non-nested model selection tests. Moreover, we augment the EKC and EnKC by incorporating trade openness and urbanization as control variables. For robustness, we support the UCM results with the Dynamic OLS (DOLS) long-run estimator. The results support the EnKC across the entire battery of tests, with a turning point of roughly USD 4000–4650 depending on specification. For the EKC, the OLS quadratic estimation does not exhibit a clear inverted-U; however, once a stochastic trend (UCM) or appropriate covariates (Trade, Urban) are introduced, the inverted-U re-emerges with a turning point near USD 4149–4874. This study contributes novel empirical evidence on the EKC and EnKC for Jordan using a TVP framework. Whereas prior studies have explored the EKC in Jordan, this study systematically validates both the energy and environmental variants of the Kuznets curve using robust econometric strategies. The results offer valuable policy insights for sustainable development in Jordan and other resource-constrained emerging economies facing analogous development–environment trade-offs within international climate transition frameworks. Full article

Grain production resilience forms a critical foundation for national food security, and the ongoing development of land transfer provides essential momentum for establishing a more resilient grain production system. Using panel data from 30 provincial-level regions from 2013 to 2024, this study constructs a multi-dimensional evaluation system for grain production resilience and calculates the comprehensive grain production resilience index using the entropy value method. This study applies two-way fixed effects and mediation models to empirically analyze the impact of land transfer on grain production resilience and its underlying mechanisms. The results show the following: (1) Land transfer significantly enhances grain production resilience: a 1 percentage point increase in the land transfer rate leads to a 0.0014-point increase in the resilience index, equivalent to 0.64% of the sample mean, and this finding remains robust after model replacement, extreme value trimming, and variable substitution. (2) Land transfer exerts its positive effect through three mediating pathways: agricultural insurance (scale dimension), specialized farmer cooperation, and agricultural mechanization. (3) Heterogeneity analysis reveals significant regional differences: the enhancing effect is more pronounced in non-major grain-producing regions and areas with underdeveloped agricultural service systems; while in major grain-producing regions and high-service-level regions, the relationship presents an inverted U-shape, with turning points at 66.794% and 71.921% of the land transfer rate respectively. Accordingly, this study proposes that China should further improve the institutional design of land transfer to systematically support the development of grain production resilience, optimize relevant policy pathways, and implement region-specific measures for targeted and effective intervention. Full article