Search Results (15,742)

Aligning urban morphology with carbon emission intensity categories is essential for advancing sustainable urban development and achieving dual carbon objectives. This study utilizes data from 336 Chinese cities across 2010, 2015, and 2020 to construct multi-dimensional morphological indicators. Spectral clustering categorizes cities into four distinct classes: high-emission intensity, medium-emission ecological, medium-emission developmental, and low-emission. An integrated gradient boosting framework, combined with SHAP and PDP interpretability tools, identifies key morphological drivers and their nonlinear contributions to class assignments. Results demonstrate that morphological features exert nonlinear and threshold-dependent effects on carbon emission intensity category assignments, exhibiting substantial spatial heterogeneity across urban clusters. Core drivers, such as economic density and the landscape shape index, follow distinctly different decision pathways in each category. Furthermore, morphological factors produce non-additive interactive effects that generate region-specific shifts in classification probability. Through this classification-oriented approach, the study provides policymakers with a systematic and readily interpretable reference to inform the formulation of context-specific low-carbon spatial planning strategies. Full article

As a key component of ecosystems, the synergistic relationship between wetland carbon storage and habitat quality is vital for maintaining ecological functions, and its evolution is profoundly influence by changes in wetlands. This study focuses on wetlands in western Jilin Province. Based on four sets of land use data from 2010 to 2023 and utilizing the InVEST model, combined with methods such as spatial autocorrelation, the Coupled Coordination Degree Model, and the GeoDetector, the study analyzed the co-variation of carbon storage and habitat quality, as well as their response to landscape patterns. The study found that between 2010 and 2023, the wetland area increased by a net 858.13 km², and landscape fragmentation was generally alleviated, although local connectivity continued to degrade. Regional carbon storage increased by 68.1%, totaling 7.43 × 10⁶ Mg, while the habitat quality index exhibited high spatiotemporal stability, fluctuating marginally between 0.609 and 0.621. Spatially, high-value areas remained primarily concentrated within nature reserves. Results of bivariate spatial autocorrelation analysis revealed a strengthening of spatial positive autocorrelation between carbon storage and habitat quality, with Moran’s I increasing from 0.410 to 0.501. The coupled coordination degree model further confirmed that the level of synergy between the two services exhibited a pattern of higher values in the north and lower values in the south, and that areas of high coordination expanded significantly outward following restoration projects. GeoDetector analysis indicates that the largest patch index is the core factor driving the synergistic development of ecosystem services. The results also suggest that the integrity of core wetland patches and a heterogeneous landscape pattern can promote the synergistic improvement of carbon storage and habitat quality through boundary effects and habitat complementarity. Full article

Traditional leaf area index (LAI) measurement methods are destructive, time-consuming, and labor-intensive. In this study, 282 four-year-old central-leader apple trees were used as research subjects. Canopy reflectance spectra in the range of 4000−10,000 cm⁻¹ were collected, and the corresponding true LAI values were measured destructively by harvesting all leaves from a representative branch of each tree using a leaf area meter. The dataset was randomly divided into training (70%) and testing (30%) sets. Eight spectral pretreatment methods were compared. The Competitive Adaptive Reweighted Sampling (CARS) algorithm was employed to extract characteristic wavelengths. Subsequently, both a BP neural network and a Support Vector Machine (SVM) model for LAI prediction were constructed. The optimal model was selected based on evaluation metrics including the coefficient of determination (R²), mean absolute error (MAE), mean bias error (MBE), and mean absolute percentage error (MAPE). The combined preprocessing of MSC and SD yielded the optimal results, screening out 26 characteristic wavelengths. The SVM linear kernel model (c = 5, g = 0.3) constructed based on MSC + SD preprocessing performed best, achieving a validation set R² of 0.90, MAE of 0.2117, MBE of −0.1214, and MAPE of 16.09%. The performance on the training set and validation set was comparable, with no overfitting observed. The MSC + SD preprocessing combined with CARS feature screening and SVM linear kernel modeling enables rapid, non-destructive estimation of apple canopy LAI, providing an effective technical tool for precision orchard management. Full article

The heritagisation of cultural landscapes is often understood as a state-led administrative process. At the same time, the discursive origins and adaptive mechanisms that precede formal designation remain underexplored, especially in relation to cultural sustainability. This study examines the pre-heritagisation of Suzhou’s classical gardens during China’s modern transformation by analysing periodical discourse published between 1870 and 1948. Using a mixed-methods approach that combines quantitative content analysis and Critical Discourse Analysis (CDA), it investigates 699 historical texts from the Index to Chinese Newspapers & Periodicals database. The findings reveal a dual discursive process. On the one hand, reports portrayed the gardens as accessible, multifunctional civic spaces through narratives of public use. On the other hand, literati discourse reinforced their classical value through historical memory and aesthetic preservation. Together, these tendencies show how the gardens were materially refunctioned and symbolically re-anchored under modern conditions. Rather than directly producing later heritage designation, this process helped create the socio-cultural conditions through which the gardens acquired broader public intelligibility, cultural legitimacy, and heritage-like meanings before formal institutional recognition. Full article

This paper presents an absolute distance measurement system based on three-wavelength synchronous phase-shifting interferometry. A synthetic wavelength chain is established using three semiconductor lasers in an all-fiber Fizeau interferometer. By integrating a piezoelectric transducer (PZT)-driven sinusoidal phase modulation with multi-channel synchronous sampling for phase demodulation, and further combining it with a fractional multiplication method, the proposed system achieves high-precision absolute distance measurement over an extended range. Experimental results demonstrate an unambiguous measurement range of 240 μm, a static measurement precision better than 0.6 nm, and a dynamic displacement measurement accuracy superior to 2 nm in comparison with the reference device. The main error sources of the system, including synthetic wavelength uncertainty, phase measurement uncertainty, and air refractive index uncertainty, are systematically modeled and analyzed. In addition, the influence of dynamic factors, such as PZT nonlinearity, is discussed and compensated. The proposed method provides a robust and high-precision solution for absolute ranging and shows strong potential for applications in industrial precision inspection and optical sensing. Full article

Introduction: Low back pain (LBP) is the leading cause of disability worldwide, with substantial variation in prevalence across regions. It is associated with a wide range of biophysical, psychological, social, and lifestyle factors, as well as comorbid conditions. Given its high impact, identifying population-level correlations of LBP is essential for informing prevention strategies. This study aimed to assess demographic, socioeconomic, lifestyle, and health-related factors associated with LBP in Hungary. Methods: A repeated cross-sectional analysis was conducted using secondary data from three waves of the European Health Interview Survey (EHIS) carried out in Hungary in 2009, 2014, and 2019. Results: The prevalence of LBP increased over the study period. Female sex, higher educational attainment, normal body mass index, non-smoking status, abstaining from alcohol, and good self-perceived health were associated with lower odds of LBP. In contrast, older age (≥65 years), unfavorable financial status, residence in socioeconomically disadvantaged regions, use of over-the-counter medications, and several chronic conditions were associated with higher odds. Conclusions: Reducing the impact of low back pain requires its integration into comprehensive public health frameworks that combine chronic disease management with consideration of socioeconomic inequalities at the population level. Full article

Background/Objectives: Clear cell renal cell carcinoma (ccRCC) involves complex interactions between immune evasion and metabolic reprogramming. This study aimed to characterize ccRCC through integrated immunometabolic profiling, develop a prognostic signature, and investigate the functional role of the key driver gene UCN using in vitro and in vivo approaches. Methods: Integrated immunometabolic profiling was performed to identify molecular subtypes and establish a prognostic gene signature. Two distinct molecular subtypes were identified, and a 9-gene Immune Metabolic Index (IMI) was constructed. The functional role of the key driver gene UCN was investigated through in vitro functional assays and in vivo xenograft models in BALB/c mice, including combination with PD-1 blockade. Results: Two molecular subtypes with significant survival differences (p < 0.001) were identified. The established IMI demonstrated high prognostic accuracy, with Area Under the Curve (AUC) values of 0.813, 0.751, and 0.779 at 1-, 3-, and 5-year intervals, respectively. UCN was identified as the highest-risk gene in the signature. Functional assays showed that UCN silencing significantly inhibited cell proliferation and migration (p < 0.05). In BALB/c mouse xenograft models, UCN silencing remodeled the tumor microenvironment by increasing CD8+ T cell infiltration and reducing regulatory T cells (p < 0.01). Furthermore, UCN knockdown significantly suppressed tumor growth and synergized with PD-1 blockade to enhance antitumor efficacy (p < 0.001). Conclusions: The IMI is a robust tool for risk stratification in ccRCC. Targeting the UCN-driven immunometabolic axis represents a promising therapeutic strategy to overcome immune resistance in ccRCC. Full article

Volatile halogenated hydrocarbons (VHHs) are critical air toxic pollutants, with some ozone-depleting substances (ODSs) strictly regulated by the Montreal Protocol. However, current understanding of the pollution characteristics, sources, and health risks of atmospheric VHHs in Southwest China remains insufficient. This study performed field observations of atmospheric VHHs in summer in Mianyang, a medium-sized industrial city in the Sichuan Basin. Freon-12 (563 ± 20 ppt) and Freon-11 (264 ± 15 ppt) were the most abundant chlorofluorocarbons (CFCs); chloromethane (785 ± 261 ppt) and methylene chloride (563 ± 505 ppt) dominated among VSLSs. The mean concentration of regulated ODSs (1037 ± 33 pptv) was notably lower than unregulated very short-lived chlorinated substances (1887 ± 745 pptv), reflecting effective ODSs phase-out locally, yet enhancements relative to Northern Hemisphere background implied potential leakage from residual tanks. Methylene chloride and trichloroethylene concentrations exceeded global background levels by over 10 times, indicating strong anthropogenic industrial influences. Phased-out CFCs displayed negligible diurnal variation due to stringent emission controls, whereas unregulated VSLSs exhibited a distinct U-shaped diurnal cycle, with peaks driven by morning boundary layer dynamics and evening accumulation. Positive matrix factorization revealed that industrial sources, including electronic solvents (28.6%), industrial processes (27.8%), and solvent usage (23.7%), accounted for 80.1% of total VHHs. The total carcinogenic risk (2.3 × 10⁻⁵) surpassed the acceptable threshold (1 × 10⁻⁶), dominated by 1,2-dichloroethane, chloroform, carbon tetrachloride, and 1,2-dichloropropane. All individual compounds exhibited mean hazard quotients (HQs) below the non-carcinogenic risk threshold. The cumulative hazard index reached 1.5, suggesting combined non-carcinogenic risks to the local population. These results support VHHs health risk management and ODSs control in Southwest Chinese industrial cities. Full article

To support low-cost, non-destructive crop growth monitoring, this study systematically compared different vegetation indices, voxel sizes, and camera angles using a point cloud voxelization approach combined with a vegetation index weighted canopy volume index (CVM_VI) to assess aboveground biomass (AGB) in winter oilseed rape (Brassica napus L.). Field experiments were conducted from 2021 to 2024 at the Yangma Experimental Base of the Chengdu Academy of Agricultural and Forestry Sciences. Red, green, blue (RGB) imagery of oilseed rape was acquired using an unmanned aerial vehicle (UAV) during the following five key growth stages: seedling, bolting, flowering, podding, and maturity. Collected images were processed to generate point clouds, which were subsequently voxelized at four resolutions (0.03, 0.05, 0.07, and 0.1 m). CVM_VI was constructed by integrating vegetation indices (VIs) derived from the RGB data and the voxelized canopy structural information. Regression models were established between the CVM_VI values and field-measured AGB to estimate biomass. Model performance was evaluated using the coefficient of determination (R²), root mean square error (RMSE), and relative error (RE). There were strong correlations (r > 0.80) between the estimated and measured AGB across all voxelization treatments throughout the growth period. Among the 20 VIs tested, regression methods based on the blue green ratio index (BGI), color intensity index, blue red ratio index, vegetative index, and green red ratio index consistently showed superior estimation performance across three consecutive years, demonstrating their good applicability for estimating AGB in oilseed rape under varying agronomic conditions (different varieties, densities, and sowing dates). The cubic regression model CVM_BGI performed best under a 45° UAV camera angle, with the highest R² and lowest RMSE and RE (2021–2022: R² = 0.864, RMSE = 2414.18 kg/ha, RE = 14.8%; 2022–2023: R² = 0.754, RMSE = 2550.53 kg/ha, RE = 14.9%; 2023–2024: R² = 0.863, RMSE = 1953.61 kg/ha, RE = 22.9%). Since the estimation performance showed negligible differences among voxel sizes, and the 0.1–m voxel offered the smallest data volume and shortest analysis time, the CVM_BGI model with a 0.1–m voxel was selected as the preferred approach, providing a practical balance between estimation performance and processing demand. These findings highlight the application potential of point cloud voxelization technology for crop biomass estimation. This study proposes a novel, non-destructive, and efficient framework for estimating field crop AGB using low-cost UAV RGB imagery, facilitating the wider adoption of UAV technology in practical agricultural production. Full article

This study investigates the roles gold and the US dollar play as safe-haven, hedging, or diversifier assets relating to six important financial stock market indices: the S&P 500, FTSE 100, Hang Seng, CAC 40 (Paris), Shanghai Composite Index, and Nikkei 225. This paper applies the bivariate dynamic copula technique and the DCC-GARCH econometric advanced methods from January 2013 to July 2024 by focusing on four serious market crashes: the Chinese stock market meltdown (2015–2016), the trade war between the US and China (2018–2020), the COVID-19 pandemic (2020–2022), and the conflict between Russia and Ukraine (2022–2024). The results show that the US dollar displays reliable hedging and safe-haven characteristics with strong evidence mainly for its role as a safe-haven asset against the FTSE 100, Hang Seng, and S&P 500. Our findings support the idea that the US dollar serves consistently as a safe-haven asset. In contrast, gold showcased a twofold function, serving as a hedge for the FTSE 100 and the S&P 500 during crisis times and acting as a diversifier for the CAC 40 and the Shanghai Composite Index in times of market stability. This dynamic was specifically noticeable in the COVID-19 period, when gold’s hedging properties were outstanding and its role as a diversifier became more pronounced in the Paris and Shanghai markets. Our results suggest that the consistent reliability of the US dollar as a safe-haven asset combined with gold’s dual role presents a compelling argument for including both in well-diversified portfolios. This strategy enables investors to mitigate risk and safeguard their wealth, especially during periods of financial market volatility. Full article

Functionally graded multi-material thermoplastic architectures provide a promising route for tailoring viscoelastic energy dissipation through controlled phase contrast and interfacial interactions. However, rational selection of optimal material compositions remains challenging due to competing requirements among stiffness, damping efficiency, thermal stability, and processability. The absence of a quantitative decision framework often limits systematic design of architected polymer systems. This study proposes an Analytic Hierarchy Process (AHP)-based multi-criteria decision model to identify the optimal rigid–elastic thermoplastic composition for enhanced damping performance. Nine performance criteria were considered, including storage modulus, loss factor, damping bandwidth, interfacial adhesion strength, elongation at break, impact resistance, glass transition temperature, thermal stability, and printability. Fourteen alternative material configurations combining different rigid phases, elastomeric interlayers, filler contents, and layer thickness ratios were evaluated. Pairwise comparison matrices were constructed based on experimentally measured thermomechanical data and literature-reported values, and consistency ratios were maintained below 0.1 to ensure decision reliability. Numerical results indicate that a graded PLA/soft-TPU/PLA architecture with optimized layer thickness ratio achieved the highest global priority weight (0.431), outperforming the baseline PLA/TPU system by approximately ~25–30% in overall performance index. Sensitivity analysis confirmed ranking robustness across variations in damping and stiffness weighting factors. The proposed framework establishes a systematic methodology for polymer material selection and multi-material architectural optimization, enabling data-driven design of thermoplastic systems with tunable viscoelastic performance. Full article

To improve solar irradiance simulation accuracy for precise photovoltaic power forecasting, we developed a hybrid framework combining WRF-Solar numerical simulation and random forest (RF) machine learning for a PV plant in Guangdong, China. Weather conditions were objectively classified into clear, intermittent cloudy, and overcast using the Daily Variability Index (DVI) and Daily Clear-sky Index (DCI). We calibrated the WRF-Solar model’s microphysics and radiative transfer schemes via sensitivity tests to optimize overcast-sky performance, then applied RF correction to the simulated irradiance. Results show that RF correction significantly reduces simulation errors for intermittent and overcast conditions, while the original WRF-Solar outperforms the corrected results under clear skies due to RF overfitting. Full article

The influence of rootstocks on mineral nutrient composition in the edible tissue of citrus fruits has not been explored so far. This study assessed leaf and juice mineral nutrients of sweet orange (Citrus sinensis (L.) Osbeck) cultivars (‘Pusa Sharad’ and ‘Pusa Round’) grafted onto different rootstocks (‘RLC-6’, ‘C-35’, ‘X-639’, ‘Yamma Mikan’, ‘Soh Sarkar’, ‘RLC-7’, and ‘Jatti Khatti’). Deviation from optimum percentage (DOP) index was employed as an integrative measure to assess leaf mineral nutrient balance for specific scion–rootstock combinations. The relative abundance of leaf mineral nutrients was ranked as follows: Ca > K > P > S > Mg > Na > Fe > Mn > Zn > Cu. Overall, rootstock ‘X-639’ demonstrated superior mineral nutrient uptake efficiency across grafted plants of both scion cultivars, as indicated by higher leaf mineral nutrient concentrations. Juice mineral nutrient concentrations followed the order K (930.87–1362.17 mg L⁻¹), Ca (346.40–651.33 mg L⁻¹), P (116.23–236.97 mg L⁻¹), Mg (64.60–102.50 mg L⁻¹), S (49.35–74.34 mg L⁻¹), Na (25.61–47.88 mg L⁻¹), Fe (4.76–7.92 mg L⁻¹), Zn (1.79–4.34 mg L⁻¹), Mn (0.73–1.62 mg L⁻¹), and Cu (0.41–0.71 mg L⁻¹), indicating distinct differences in the accumulation pattern of macro- and micro-mineral nutrients in the edible tissues across the studied scion–rootstock combinations. Multivariate analysis revealed that the rootstocks significantly influenced juice mineral nutrient levels, indicating rootstock-mediated agronomic biofortification. Rootstock ‘RLC-6’ enhanced juice K levels, and ‘Soh Sarkar’ improved juice Mg contents, while ‘X-639’ improved juice micronutrient (Zn, Mn, Cu) accumulation in both cultivars. This study constitutes the first comprehensive investigation that explicitly evaluates the influence of rootstocks on the enhancement of mineral nutrient content in the edible tissues of citrus fruits. It further elucidates how rootstock selection can indirectly affect dietary mineral intake, thereby highlighting its potential role for improved nutrition. Full article

The aim of this study is to conduct a comprehensive assessment of the water quality of the Sidi Mohammed Ben Taiba (SMBT), one of the largest drinking water reservoirs in northwestern Algeria, by integrating chemical and biological indicators. The assessment combines the Drinking Water Quality Index (DWQI), the Irrigation Water Quality Index (IWQI), the Organic Pollution Index (OPI) and zooplankton-based biological indicators (Zoo-IQ). A total of 23 physicochemical parameters were analyzed and interpreted using multivariate statistical approaches. This study fills an important knowledge gap by evaluating long-term temporal variability (January 2018–May 2025) and recent spatial heterogeneity (June 2023–May 2025), aiming to support sustainable water management. The results indicate that the reservoir water quality is generally suitable for drinking purposes (22.3 < DWQI < 54.0), is deemed excellent for agricultural irrigation (65 < IWQI < 69) and that the reservoir surface waters are slightly polluted to unpolluted (0.3 < OPI < 1.1). However, a deterioration in water quality has been detected in recent years, linked to increasing nutrient concentrations, as confirmed by the TSI–SD index. Despite the early signs of nutrient enrichment, the Zoo-IQ index remained within the moderate to good range, suggesting a certain degree of resilience in the zooplankton community. However, pronounced seasonal fluctuations observed in the Zoo-IQ and species diversity (H′) during periods of environmental stress serve as an early warning signal of emerging problems that may negatively affect water quality indices (WQI, IWQI, OPI). Station S4, located at the confluence of Wadi Belhassen and Wadi Farhat, descending from the Dahra mountain range in Algeria, has been identified as the most sensitive area and a potential hotspot for future pollution. The study provides robust data on the quality of reservoir water, offering a valuable decision-making tool for artificial reservoir managers and contributing to sustainable water management by identifying risk areas and supporting the implementation of preventive measures. Full article

The intensive use of agricultural inputs and the increasing incorporation of nano-materials into crop management practices raise concerns about their ecotoxicological interactions in plant systems. This study evaluated phytotoxicity, cytotoxicity, and genotoxicity in Allium cepa L. under experimental nano-agrochemical exposure scenarios combining two conventional nitrogen fertilizers—ammonium sulfate (AS) and urea—with silver nanoparticles (AgNPs). Biological responses were assessed across fertilizer concentrations (0.03–0.5 g/L), applied individually, simultaneously, and sequentially, to identify modulatory effects of AgNPs on plant proliferative activity and genomic stability. Results showed the relative stability of morphophysiological indicators associated with root growth, whereas cytogenetic biomarkers exhibited selective alterations under specific conditions. Significant increases in genetic damage markers were detected at intermediate ammonium sulfate concentrations, suggesting sublethal phytotoxicity windows not reflected by macroscopic growth parameters. In addition, modulation of the mitotic index and absence of generalized genotoxic effects in most combined or sequential treatments indicate that AgNPs primarily acted as modulators of proliferative responses rather than direct cytotoxic agents. Overall, these findings highlight the dynamic and non-linear nature of nano-agrochemical interactions in plant systems and underscore the importance of multibiomarker approaches for the early detection of genomic instability. The results provide experimental evidence relevant to the environmental risk assessment of nano-enabled fertilization strategies under realistic mixed-exposure scenarios. This study contributes to advancing the ecotoxicological understanding of emerging agricultural technologies and supports the need for further mechanistic research and field-based evaluations to guide the safe and sustainable use of nanomaterials in crop production. Full article