Search Results (3,000)

With the intensification of environmental degradation, it is crucial for environmental protection to monitor and evaluate the ecological environmental quality (EEQ) in a timely and accurate manner based on remote sensing technology. However, current remote sensing EEQ evaluation methods suffer from deficiencies with regard to the indicator system and the EEQ quantification, reducing the accuracy of EEQ evaluations. Therefore, a new EEQ evaluation method is proposed in this study. Remote sensing indicators used in the pressure–state–response (PSR) framework are selected based on the traditional EEQ evaluation system, and deep neural networks (DNNs) are used to quantify EEQ. The results show that the proposed method has a significantly higher EEQ estimation accuracy with NRMSE of 13.61% and R² of 0.75 than the commonly used remote sensing ecological index (RSEI) method with NRMSE of 19.13% and R² of 0.51. This study suggests that the proposed method is suitable for the estimation of EEQ in a city. Full article

Rational allocation and coordinated operation of water resources in arid inland river basins are crucial for sustaining irrigated agriculture, maintaining ecological baseflow and ensuring reservoir safety. To address this need, this study develops and evaluates joint-operation schemes for the Jingou River-Hongshan Reservoir irrigation system in Xinjiang, northwestern China, to improve coordination among irrigation water supply, ecological baseflow maintenance and reservoir safety. A monthly reservoir-canal-irrigation operation model is formulated with irrigation demands, ecological flow constraints and key engineering limits. Using this model, operating schemes are generated to explore trade-offs among three objectives: shortages, reliability and non-beneficial reservoir releases. The non-dominated schemes obtained from multi-objective optimization are then ranked using an entropy-weighted TOPSIS framework, from which representative solutions are selected for further interpretation. The results indicate that the top-ranked schemes deliver comparable and relatively well-balanced performance across the objectives. Under the preferred compromise scheme, annual irrigation shortages amount to about 39% of total demand, the mean satisfaction level of irrigation and ecological requirements reaches roughly 57%, and the combined index of spill losses and end-of-year storage deviation remains low. Schemes that push shortage reduction or reliability enhancement to extremes tend to increase spill losses, compromise storage security or both, thereby degrading overall performance. The proposed optimization-ranking framework offers a transparent basis for identifying robust operating strategies that reflect local management priorities and is transferable to other reservoir-supported irrigation systems in arid regions. Full article

Dissolved Gas Analysis (DGA) is a diagnostic strategy that monitors oil-immersed transformers by correlating their health status with various insulation degradation by-products, where the Health Index (HI) offers a unified metric for asset evaluation. Existing studies frequently emphasize classification accuracy or single-model regression, overlooking interpretability, feature reduction, and systematic benchmarking. This paper introduces a feature-enhanced multi-experimental methodology for HI prediction incorporating SHapley Additive exPlanations (SHAP) in a dual role—as both an interpretability and a feature selection tool. Models from four algorithmic families (linear, kernel/tree-based, boosting, and hybrid ensembles) were systematically benchmarked using a publicly available dataset. Results demonstrate that the proposed LightGBM–CatBoost hybrid ensemble, enhanced by SHAP-guided feature pruning, achieves superior predictive accuracy while reducing model complexity and improving transparency. Unlike prior works carried out using the same dataset, the proposed framework not only provides a balanced approach that combines interpretability and reduced complexity, but also surpasses previous regression-based approaches, reducing MAE and RMSE by 4.93% and 2.31%, respectively, and enhancing HI predictive accuracy by 1.45%. Full article

This study investigated the interventional effects of dietary itaconic acid (ITA) on high-fat diet (HFD)-induced lipid deposition in largemouth bass (Micropterus salmoides) and the underlying mechanisms. Results showed that ITA supplementation significantly alleviated HFD-induced growth performance inhibition, as indicated by increased weight gain rate, increased specific growth rate, and reduced feed conversion ratio. ITA supplementation effectively reversed the HFD-induced increase in the hepatosomatic index, intraperitoneal fat ratio, serum triglycerides, total cholesterol, low-density lipoprotein/high-density lipoprotein ratio, hepatic lipid droplet accumulation, and hepatocyte vacuolation. Importantly, ITA ameliorated HFD-induced impairment of antioxidant capacity and reduced liver alanine aminotransferase and aspartate aminotransferase activities. Liver metabolomics revealed that ITA reduced levels of 20 fatty acids, 14 acylcarnitines, and 13 glycerides, suggesting enhanced fatty acid oxidation and reduced lipid esterification. Transcriptome sequencing and q-PCR validation demonstrated that ITA activated the AMPK/mTOR pathway, upregulating autophagy-related genes (prkaa1, ulk2, map1lc3a, sqstm1) and lysosomal biogenesis-related genes (ap3s2, igf2r, lgmn, ctso), thereby enhancing autophagic-lysosomal flux and promoting lipid degradation. In conclusion, ITA reduces hepatic lipid accumulation by synergistically activating autophagy and lysosomal biogenesis, thereby facilitating the oxidative degradation of fatty acids within lysosomes. This study provides a theoretical basis for the application of ITA as a functional feed additive in aquaculture. Full article

The molecular weight distribution (MWD) of cellulose and its degree of polymerization (DP) have a significant influence on the strength properties of wood. The most widely used method for analyzing MWD and DP is size exclusion chromatography (SEC). In this study, we monitored changes in the MWD and DP of cellulose in spruce wood after thermal treatment at temperatures of up to 280 °C. We employed the two most prevalent SEC methods: after direct dissolution of cellulose in a solution of dimethylacetamide and lithium chloride, and after its derivatization to tricarbanilates (CTCs). Both methods yield comparable results that correlate well with each other, although CTCs yield approximately 15% higher absolute values of DP. Our results show that a drop in DP begins at 100 °C, particularly above 220 °C, where significant cellulose degradation occurs. Both methods are appropriate for analyzing cellulose in thermally degraded wood. CTCs have the advantage of greater sensitivity and are suitable for small sample quantities. Direct dissolution can also provide information on the aromatic compounds formed during the thermal treatment of wood when used in conjunction with a refractive index (RI) detector and an ultraviolet (UV) detector. There is a strong linear relationship between DP and the modulus of rupture (MOR), as well as between the modulus of elasticity (MOE) and DP. Full article

The increasing demand for sustainable food requires the development of raw materials and products that provide not only high-quality proteins but also valuable lipids. The aim of this study was to compare the lipid quality of insect powders with that of selected cereal flours (millet, oat, and rice) during four months of storage at room temperature. To simulate increased oxidative conditions, the packages were filled only halfway, thereby increasing oxygen availability. Lipids were extracted using the Bligh–Dyer method, and their oxidation status was assessed based on peroxide value (PV), p-anisidine value (p-AsV), and the total oxidation (Totox) index. Fatty acid composition, antioxidant activity, and oxidative stability were determined using differential scanning calorimetry (DSC). Directly after purchase, none of the analyzed flours or insect powders exceeded a PV of 10 meq O₂/kg lipids or a p-AsV of 20. After four months of storage, lipid oxidation increased in all samples, with changes ranging from 4.6% to 30%, depending on the parameter analyzed. Lipids extracted from insect powders consistently showed significantly higher oxidation levels than those from cereal flours. The proportion of PUFAs in the lipids of the flours ranged from 36.40% to 64.21%, whereas in insect powders it ranged from 30.01% to 37.29%. After storage, only minor changes in PUFA content were observed, and these did not indicate advanced destructive oxidative degradation. Overall, the lipids present in the analyzed flours demonstrated favorable nutritional quality indices, including AI (0.10–0.48), h/H (2.23–10.47), and TI (0.22–1.14). The results indicate that insect powders can serve as a valuable source of fatty acids; however, their susceptibility to lipid oxidation necessitates careful consideration during processing and storage. Full article

Urban lakes are essential for ecological balance and urban development. This study developed a comprehensive framework to evaluate the ecosystem health of urban lakes in China. Nineteen representative lakes from four lake zones were examined using three decades of remote-sensing data combined with hydrological, water-quality, and aquatic–biological investigations. An extended DPSIR model guided the selection of 52 indicators, and a hierarchical weighting scheme was used: the analytic hierarchy process determined criterion-level weights, while principal component analysis with Softmax normalization was used for indicator-level weights. The established index system was applied to Xuanwu Lake and Erhai Lake, and an obstacle-degree model was used to identify key ecological constraints from 2010 to 2020. Results showed that urban lakes in the Yunnan–Guizhou Plateau and Eastern Plain zones were mainly constrained by eutrophication and intensive urbanization, with state- and impact-related indicators contributing most to the health index. The framework captured the decline of Xuanwu Lake, driven by poor water exchange and external nutrient loading, and its subsequent improvement following governance interventions, as well as the post-2014 degradation of Erhai Lake driven by climate-induced hydrological stress and non-point source pollution, providing a practical tool for diagnosing constraints and supporting adaptive, region-specific lake management. Full article

Background: In high-dimensional, small-sample omics studies such as metabolomics, feature selection not only determines the discriminative performance of classification models but also directly affects the reproducibility and translational value of candidate biomarkers. However, most existing methods primarily optimize classification accuracy and treat stability as a post hoc diagnostic, leading to considerable fluctuations in selected feature sets under different data splits or mild perturbations. Methods: To address this issue, this study proposes FRL-TSFS, a feature selection framework synergistically driven by filter-based Robust Rank Aggregation and L1-sparse modeling. Five complementary filter methods—variance thresholding, chi-square test, mutual information, ANOVA F test, and ReliefF—are first applied in parallel to score features, and Robust Rank Aggregation (RRA) is then used to obtain a consensus feature ranking that is less sensitive to the bias of any single scoring criterion. An L1-regularized logistic regression model is subsequently constructed on the candidate feature subset defined by the RRA ranking to achieve task-coupled sparse selection, thereby linking feature selection stability, feature compression, and classification performance. Results: FRL-TSFS was evaluated on six representative metabolomics and gene expression datasets under a mildly perturbed scenario induced by 10-fold cross-validation, and its performance was compared with multiple baselines using the Extended Kuncheva Index (EKI), Accuracy, and F1-score. The results show that RRA substantially improves ranking stability compared with conventional aggregation strategies without degrading classification performance, while the full FRL-TSFS framework consistently attains higher EKI values than the other feature selection schemes, markedly reduces the number of selected features to several tens of metabolites or genes, and maintains competitive classification performance. Conclusions: These findings indicate that FRL-TSFS can generate compact, reproducible, and interpretable biomarker panels, providing a practical analysis framework for stability-oriented feature selection and biomarker discovery in untargeted metabolomics. Full article

Healthy soil serves as the fundamental basis for sustainable Panax notoginseng (Burkill) F.H. Chen ex C.Y. Wu & K.M. Feng cultivation in understory systems. Current management practices have raised concerns about potential soil degradation and ecological imbalance. To comprehensively assess the soil health status, this study investigated typical understory P. notoginseng plantations in the subtropical mountain monsoon region of western Yunnan. By analyzing 29 soil physical, chemical, and biological indicators, we constructed a Minimum Data Set (MDS) using Principal Component Analysis to evaluate soil health and identify major constraints. The results showed that the MDS for soil health assessment consisted of 11 key indicators: acid phosphatase, fungal ACE index, organic matter, total nitrogen, sucrase, fungal Simpson index, fine sand, non-capillary porosity, silt content, bulk density, and microbial biomass nitrogen. Using both linear and non-linear scoring functions, the Soil Health Index (SHI) calculated based on the MDS showed a significant positive correlation with the SHI derived from the Total Data Set (TDS) (linear scoring: R² = 0.43, p < 0.001; non-linear scoring: R² = 0.305, p < 0.001). This indicates that the MDS captures a substantial and significant portion of the variation explained by the TDS and can serve as a practical and simplified alternative for soil health evaluation in this cultivation system. Based on the MDS, the SHI values obtained using linear and non-linear scoring functions ranged from 0.53 to 0.72 and 0.48–0.59, with mean values of 0.62 and 0.51, respectively, indicating moderate soil health status in the study area. Significant differences in SHI were observed across planting durations and seasons (p < 0.05), with two-year-old plantations showing notably better soil health indices than three-year-old plantations, particularly during the rainy season. The main constraints identified in understory P. notoginseng plantations included microbial community degradation, nutrient imbalance, and physical structural deterioration. Implementing scientific soil management strategies such as optimized rotation cycles, organic amendment applications, and microbial community regulation can effectively mitigate these soil constraints, enhance soil health, and promote the sustainable development of understory P. notoginseng cultivation. Full article

The SDG 15.3.1 framework provides a standardized approach using land use/land cover (LULC) change, land productivity, and soil organic carbon (SOC) dynamics to assess land degradation. However, SDG 15.3.1. faces limitations like coarse resolutions of Landsat-8 and Sentinel-2, particularly for fine-scale studies. Accordingly, this paper integrates Very Deep Super-Resolution (VDSR) for downscaling Landsat-8 imagery to 1 m resolution and the Vegetation Health Index (VHI) into SDG 15.3.1 to enhance detection in the heterogeneous Loiret region, France—a temperate agricultural hub featuring mixed croplands and peri-urban interfaces—using 2017 as baseline and 2024 as target. Results demonstrated that 1 m resolution detected more degraded LULC areas than coarser scales. SOC degradation was minimal (0.15%), concentrated in transitioned zones. VHI reduced overestimation of productivity declines compared to the Normalized Difference Vegetation Index by identifying more stable areas and 2.69 times less degradation in integrated assessments. The “One Out, All Out” rule classified 2.6% (using VHI) and 7.1% (using NDVI) of the region as degraded, mainly in peri-urban and cropland hotspots. This approach enables metre-scale land degradation mapping that remains effective in heterogeneous landscapes where fine-scale LULC changes drive degradation and would be missed at lower resolutions. However, future ground validation and longer timelines are essential to enhance the presented methodology. Full article

Enhancing the carbon sequestration (CS) capacity of urban green spaces is crucial for mitigating global warming, environmental degradation, and urbanisation-induced issues. This study focuses on the urban community unit to establish a system of determining factors for the CS capacity of green space, considering the built-up spatial pattern and green space morphology. An interpretable machine learning approach (Random Forest + Shapley Additive exPlanations) is employed to systematically analyse the non-linear relationship of built-up spatial pattern and green space morphology factors. Results demonstrate significant urban zonal heterogeneity in green space CS, whereas southern suburban area communities exhibited higher capacity. In terms of green space morphology factors, higher fractional vegetation cover (FVC) and cohesion were positively correlated with green space CS capacity. Leaf area index (LAI), canopy density (CD), and the evergreen-broadleaf forest ratio additionally further enhanced the positive effect of two-dimensional green space factors on CS. For built-up spatial pattern factors, communities with a high green space ratio and low development intensity exhibited higher CS capacity. And the optimal ranges of FVC, LAI and CD for effective facilitation of community green space CS were identified as 0.6–0.75, 4.85–5.5 and 0.68–0.7, respectively. Moreover, cohesion, LAI and CD bolstered the CS capacity in communities with a high building density and plot ratio. This study provides a rational basis for planning and layout of green space patterns to enhance CS efficiency at the urban community scale. Full article

Excessive nitrogen fertilization can degrade soil quality by inducing nutrient leaching, disrupting the microbial balance, and impairing plant reproductive growth, ultimately reducing crop yields. Optimizing nitrogen application rates and integrating humic acid fertilizers are promising strategies for enhancing soil fertility and improving agricultural productivity. The experimental design included four nitrogen application rates (N0:0 kg ha⁻¹, N1:120 kg ha⁻¹, N2:150 kg ha⁻¹, and N3:180 kg ha⁻¹) with and without humic acid (H: 1500 kg ha⁻¹). Key findings revealed that: (1) The combined application of humic acid (1500 kg ha⁻¹) and medium nitrogen (150 kg ha⁻¹) significantly increased the contents of soil organic carbon (SOC), total nitrogen (TN), available phosphorus (AP), and available potassium (AK) by an average of 21.7% (p < 0.05), 90.5% (p < 0.01), 59.4% (p < 0.05), and 11.3% (p < 0.05), respectively (two-year mean), with significant interactive effects between nitrogen and humic acid on nutrient accumulation; (2) humic acid supplementation significantly increased soil bacterial abundance and diversity: under the combined treatment of medium nitrogen (150 kg ha⁻¹) and humic acid, the bacterial Ace index (indicating species richness) and Shannon index (indicating community diversity) increased by an average of 0.76% and 0.30%, respectively, compared with the single medium nitrogen treatment (p < 0.05), promoting a more balanced microbial community; and (3) quinoa yields improved by 24.62–66.83% with humic acid application, with the highest yield increase observed under the moderate nitrogen rate (150 kg ha⁻¹) in combination with humic acid. These results demonstrate that integrating humic acid with optimized nitrogen fertilization (150 kg ha⁻¹ N + 1500 kg ha⁻¹ HA) can effectively improve soil nutrients and enhance quinoa productivity. The increases in soil total nitrogen (TN, p < 0.01), available phosphorus (AP, p < 0.05), bacterial Shannon index (p < 0.05), and quinoa yield (p < 0.01) under this combined treatment were all significantly higher than those under single nitrogen fertilization or humic acid application, confirming the synergistic effect of the two fertilizers. Full article

Soil Health (SH) is a key concept in discussions on sustainable land use, with implications that extend beyond agriculture. To address the need for integrated assessments, this study developed a Sustainable Agricultural Development Index (SADI) by combining the Soil Health Index (SHI) with socioeconomic and management indicators. The analysis was conducted across Germany using 3300 soil analysis sites and environmental covariates, including climate, topography, vegetation indices, and bare soil reflectance. From this foundation, SADI was designed to evaluate agricultural sustainability across German states based on three dimensions: Management (Bare Soil Frequency), Environment (SHI Maps), and Economy (Profit per Hectare). Results revealed that SHI correlated significantly with land surface temperature (R = −0.47), bare soil frequency (R = −0.40), and vegetation indices (R = 0.43). Soil organic carbon also played a key role in explaining degradation patterns. While economically stronger states tended to achieve higher SH scores, environmentally sound and well-managed regions also performed well despite lower economic returns. These findings emphasize that sustainable agriculture depends on balancing economic growth, environmental integrity, and management efficiency. The SADI provides a comprehensive framework for policymakers and land managers to evaluate and guide sustainable agricultural development. Full article

Rheumatoid arthritis (RA) and osteoarthritis (OA) are significant global health challenges, fueling the need for innovative therapeutic strategies. Natural polyphenolic compounds, such as green tea catechins, exhibit promising anti-inflammatory, antioxidant, and immunomodulatory properties, making them potential adjuncts to rheumatic disease therapy. This review examines the effects of catechins, particularly epigallocatechin-3-gallate (EGCG), on key pathophysiological processes associated with RA and OA, such as pro-inflammatory cytokine production, oxidative stress, cartilage degradation, angiogenesis, and immune cell activation and proliferation. This study contains experimental data contained in full-text articles published in open-access indexed journals published only in English. The most important conclusions drawn from the in vitro and in vivo studies available so far, as well as studies on patients, show that green tea catechins modulate pro-inflammatory pathways, reduce the level of pro-inflammatory cytokines and improve the condition of the intercellular matrix in joint tissues, limiting the destruction of joint tissues in animals and patients and reducing pain. Although these studies suggest potential benefits, such as reduced inflammation and improved clinical parameters, the number and scale of studies are insufficient to confirm the clinical efficacy in a broad patient population. Therefore, claims of adjunctive therapy to conventional therapies should be interpreted with caution, and further well-designed and more powerful clinical trials are needed to verify the translation of the promising molecular mechanisms of green tea catechins into clinical practice. Full article

The exacerbation of Aluminum (Al) toxicity is a leading cause of forest degradation. However, the effects of Al on clone bamboo are not well-characterized. This study examined the influence of Al on bamboo growth using one-year-old Phyllostachys edulis seedlings subjected to control Al treatments, which aim to provide theoretical support for improving the soil quality of bamboo forests. The results indicated that the Al content in the seedlings increased by 86.42% to 162.79% compared to the control. However, it remained within a relatively stable range, with the root being the primary site of accumulation. Among the treatments, the 0.3 mM Al group (Al³⁺) exhibited the highest values in biomass indexes (LB, RB and AGB). In contrast, the 2.0 mM Al treatment led to a significantly higher root-to-shoot ratio (RSR) than other groups. Physiological analyses revealed coordinated responses in key antioxidant enzymes (POD, SOD, CAT) and osmotic adjustment substances (Pro, SP, Bet). These findings demonstrate that P. edulis possesses considerable tolerance to Al, with a significant phenotypic inhibitory effect that was not observed with 2.0 mM Al treatment. Bamboo responds to Al stress through controlling Al absorption, optimizing resource reallocation, and enhancing adaptability physiology capacity, illustrating a comprehensive collaboration adaptive mechanism. Full article