Search Results (671)

Understanding the anisotropy in the physical and mechanical properties of layered rocks is essential for predicting and preventing instability in layered rock masses. However, in-situ sampling is often hindered by the difficulty of obtaining specimens with controlled bedding orientations. Cement-based 3D printing (3DP) offers an efficient approach for fabricating rock analogues, yet the inherent anisotropy induced by the layer-by-layer deposition process has not been well characterized, hindering its broader application. The objectives of this study are (i) to systematically evaluate the intrinsic anisotropy of cement-based 3DP rocks and (ii) to compare the mechanical anisotropy and failure modes of 3DP layered rocks with those of natural layered sandstone. The key findings are as follows: (1) The uniaxial compressive strength (UCS), P-wave velocity, and computed tomography (CT) number of the 3DP rock vary by less than 6% among the X-, Y-, and Z-directions, indicating lower intrinsic anisotropy compared to typical sandstones and several other natural rocks. (2) The UCS, elastic modulus, and secant modulus of the 3DP layered rocks all decrease initially and then increase with bedding dip angle, reaching a minimum at 60°. (3) The main fracture characteristics of the 3DP layered rocks are similar to those of layered sandstone; notably, the 3DP layered soft rock exhibits the most pronounced shear failure features. This study quantifies the low intrinsic anisotropy of cement-based 3DP rocks and validates their similarity to natural layered sandstone in both mechanical anisotropy and failure modes. It thereby provides a reliable, reproducible basis for physical modeling of layered rock masses using 3DP, offering a new approach for laboratory-scale investigations of layered rocks. Full article

A large number of reservoirs (or hydropower plants) have been constructed for flood control and energy production in the past several decades in the Yangtze River basin in China. The conventional scheduling rule curves (Scheme A) were designed in the reservoir construction period and did not consider river flow alternation, which needs to be modified to increase comprehensive benefits in the reservoir operation period. In this study, six large-scale cascade reservoirs or mega hydropower systems constructed and operated by the China Yangtze Three Gorges Corporation were selected for this case study. The current joint scheduling plans of cascade reservoirs (Scheme B) were introduced, and a joint scheduling and multi-objective coordinating operation model (Scheme C) was proposed for this mega hydropower system. The Gaussian radial basis functions (GRBFs) were used to fit operation policies of each reservoir, and the Borg multi-objective evolutionary algorithm was selected to optimize three-objective functions for Scheme C. The observed daily flow data series at main hydrometric stations from 2003 to 2025 were used to simulate and compare different operation scheduling schemes. The results show that the performance of joint scheduling of cascade reservoirs (both Schemes B and C) is much better than the single-reservoir scheduling (Schemes A) with overall benefit; Scheme C-best achieves a comprehensive target of decreasing average annual spillway wastewater by 12.82 billion m³ (or a decrease of 28.5%), increasing average annual power generation by 31.02 billion kWh (or an increase of 10.7%), and improving average annual impoundment efficiency rate by 5.0%. The GRBFs can fit reservoir operation policies well, while the Borg multi-objective evolutionary algorithm can quickly converge with high-precision non-dominated solution sets. The proposed joint scheduling and multi-objective coordinating operation model will provide a scientific basis for achieving maximum benefits in flood protection and hydropower generation for the mega hydropower system. Full article

Cover crop in orchards is recognized as a sustainable practice that enhances multiple ecosystem services, yet systematic evaluations of different cover crop management models in citrus orchards remain limited. This study investigated the effects of cover crop management models (natural cover crop: T1, Lolium perenne L.: T2, Trifolium repens L.: T3, Vicia villosa Roth: T4, and mixed cover crops: T5) on soil properties, soil CO₂ flux, leaf physiological traits, fruit quality, and yield in a citrus orchard, using clean tillage as a control. Results showed that cover crop management models significantly influenced soil water content, available nitrogen (AN), available phosphorus (AP), and available potassium (AK). The V. villosa model (T4) reduced AN and AP but enhanced leaf chlorophyll (Cl) and nitrogen (N) content. Soil CO₂ flux was significantly higher under T4, and it showed the lowest soil moisture. The results of mantel tests revealed that AP and soil moisture were key drivers of leaf traits, though no significant treatment effects on fruit quality or yield were detected within the two-year experimental period. These findings indicate that cover crop management models rapidly alter soil properties and CO₂ emissions, but longer-term observations are needed to evaluate cascading effects on fruit. This study offers evidence-based soil management solutions and a framework for enhancing multiple ecosystem services in orchards worldwide. Full article

Due to the destruction of natural aquatic ecosystems, developing comprehensive biological index evaluation methods is critical for river restoration and regeneration. However, research on spatial multiple-scale biological assessments remains lacking. This study used the biological integrity index methodology to examine the effectiveness of fish and macrobenthos in ecological assessments, as well as to analyze environmental factors impacting aquatic ecosystem health assessments. The Daning River basin in Chongqing was selected as the study area, and aquatic ecosystem health assessments were conducted at both regional and local scales. The results indicated that benthos were more abundant than fish, but there were no significant differences in species richness between sub-basins (p > 0.05). The assessment results for F-IBI and B-IBI showed partial discrepancies at the local fine-scale level but were nearly consistent at the regional broad-scale sub-basin level, with only small differences between the F-IBI and B-IBI ratings in one sub-basin. This discrepancy may be due to the diverse water environment. Woodland areas have significant negative relationships with F-IBI, while water areas have significant positive relationships with it. Comprehensively, the assessment findings of F-IBI beat those of B-IBI, implying that F-IBI may be better suited for regional assessments. However, the impact of local water quality issues remains unclear. To enhance ecological restoration, it is vital to conduct additional research into the degree of interference caused by water quality variables. Full article

Groundwater level prediction is essential for sustainable water resource management. Although machine learning models are widely applied, input variable selection critically affects predictive performance, and existing studies rarely evaluate model performance comprehensively, considering accuracy, stability, physical interpretability, and computational efficiency. To address this issue, this study develops a hybrid framework integrating grid search-optimized long short-term memory (GS-LSTM) with the technique for order preference by similarity to ideal solution (TOPSIS). Using the Houston area as a case study, the framework evaluates 30 input combinations derived from precipitation (P), air temperature (T), relative humidity (H), wind speed (W), and reference evapotranspiration (E) across 22 monitoring wells to identify optimal and minimal input variable combinations sets. Key findings include: (1) optimal input combinations vary substantially among wells, highlighting spatial heterogeneity; (2) P and E are dominant drivers; (3) compared to daily input data, monthly averaged data increases the prediction success rate (proportion of successful runs across 27 hyperparameter configurations) by >40% and improves R² by >0.3; (4) the minimal set comprises eight representative combinations that collectively cover the top-three ranked variable combinations for all 22 wells, maintaining high accuracy (e.g., Well 12# daily data: MAE = 0.13 m, RMSE = 0.16 m, R² = 0.92) while reducing computational cost by 92.1% relative to testing all 30 combinations. The proposed optimal and minimal input sets offer a stable, accurate, and computationally efficient solution for groundwater resource management that accounts for spatial heterogeneity. Full article

Pathological cardiac hypertrophy is an important risk factor for cardiovascular disease. Ganoderic acid A (GAA), the primary bioactive constituent of Ganoderma lucidum (G. lucidum), is known for its stable chemical properties and diverse biological activities. It has been shown to confer protection against myocardial ischemia–reperfusion injury in rat models, potentially through modulating inflammatory responses and inhibiting protein expression linked to both NF-κB and apoptosis pathways. Nevertheless, the role of GAA in cardiac hypertrophy has not yet been fully elucidated. Using transverse aortic constriction (TAC)-induced cardiac hypertrophy in mice, we analyzed the degree of hypertrophy using echocardiography and at the pathology and molecular levels. Our results demonstrate that GAA effectively attenuates Ang II-induced cardiomyocyte hypertrophy in vitro and reduces pressure overload-induced cardiac hypertrophy in vivo. Further investigation revealed that GAA exerts its anti-hypertrophic effects by downregulating the mRNA expression of hypertrophic and fibrotic markers and attenuating inflammatory responses, and that the protective effects of GAA may involve NF-κB signaling. This study provides valuable theoretical support for the potential therapeutic application of GAA in treating pathological myocardial hypertrophy and heart failure. Full article

Environmental DNA (eDNA) metabarcoding has emerged as a powerful tool for biodiversity monitoring, yet its accuracy is fundamentally constrained by the completeness and taxonomic reliability of reference sequence databases. For the Three Gorges Reservoir (TGR), no integrated multi-marker eDNA reference library exists, hampering standardized fish conservation monitoring under the Yangtze River Ten-Year Fishing Ban. Here, we constructed a comprehensive, multi-marker eDNA reference database for the fish fauna of the TGR, encompassing mitochondrial 12S rRNA, 16S rRNA, and cytochrome c oxidase subunit I (COI) gene sequences from 173 specimens (120 species) collected between 2021 and 2024. After integrating publicly available sequences, the final database comprised 161 species. Then, we quantitatively compared species annotation performance between this local database and public repositories. Results showed that while public databases achieved higher nominal species coverage (94.67%), they exhibited critical deficiencies in annotation accuracy, correctly annotating only 77.97% (12S rRNA), 75.00% (16S rRNA), and 38.14% (COI) of sequences from shared species under controlled conditions. In contrast, the local database exhibited 92.37%, 93.10% and 100% annotation accuracy for the respective markers. Optimal interspecific Kimura 2-parameter (K2P) thresholds for species delimitation were 0.00448 (12S rRNA), 0.00531 (16S rRNA), and 0.00734 (COI). In addition, 15, 0, and 4 species pairs exhibited zero interspecific distance for 12S rRNA, 16S rRNA, and COI, respectively. These limitations reinforce the need for cautious interpretation of eDNA metabarcoding results and the integration of multiple markers or complementary nuclear loci. This study provides preliminary evidence that regionally curated, multi-marker reference libraries could improve taxonomic assignment reliability in eDNA metabarcoding compared to uncurated public repositories, providing a foundational resource for biodiversity conservation. Full article

Landslides are one of the most common natural hazards in China, and the efficient screening of important factors is crucial for landslide susceptibility mapping. Taking the Zigui–Badong section of the Three Gorges Reservoir Area (TGRA) as the study area, this research initially selected 25 evaluation factors based on topography, geology, hydrology, remote sensing images, and previous studies. Thirteen key factors were obtained through analysis. Three machine learning models—RF, DT, and XGBoost—were then used for landslide susceptibility mapping, with SHAP and LIME employed to interpret the models. Finally, a scoring method was used to rank the six sets of results and compare them with those from the traditional AUC-based Recursive Feature Elimination (AUC-RFE) method. The results showed that the core factor sets screened by interpretable methods outperformed those from AUC-RFE. To further obtain accurate core factor sets, two additional interpretable methods—PI and Explainable Boosting Machine (EBM)—were integrated, ultimately identifying a core factor set consisting of eight factors including Elevation, Slope Height, and Aspect. This set achieved an AUC value of 0.931, only 0.003 lower than that of the 13 filtered factors. The screening method proposed in this paper can significantly improve the efficiency of factor acquisition, reduce the difficulty of factor acquisition, and provide a new approach for the selection of key factors in landslide susceptibility assessment. Full article

At around 8:40 a.m. on 17 July 2024, the Wanshuitian landslide in the Three Gorges Reservoir Area (TGRA) experienced a deformation failure characterized by thrust load-caused deformations and high-speed sliding. Using geological surveys and unmanned aerial vehicle (UAV) photography, this study divided the Wanshuitian landslide area into five zones: sliding initiation (A1), secondary disintegration (A2), main accumulation (B1), right falling (B2), and left falling (B3) zones. Through monitoring data analysis and GeoStudio-based numerical simulations, this study revealed the mechanisms behind the landslide failure mode characterized by slope sliding approximately along the strike of the rock formation under the coupling effect of hydrological and geological conditions. The results indicate that factors inducing the landslide failure include the geomorphic feature of alternating grooves and ridges, the lithologic assemblage characterized by interbeds of soft and hard rocks, the slope structure with well-developed joints, and the sustained heavy rains in the preceding period. In the Wanshuitian landslide area, mudstone valleys are prone to accumulate rainwater, which can infiltrate directly into the weak interlayers of rock masses and soften the rock masses. Multi-peak rain events with a short time interval serve as a critical factor in groundwater recharge. Within 17 days preceding its failure, the Wanshuitian landslide experienced a superimposed process of heavy and secondary rain events with a short interval (four days). Rainwater from the first heavy rain event failed to completely discharge during the short interval, while the secondary rain event also caused rainwater accumulation. These led to a continuous rise in the groundwater table, a constant decrease in the shear strength of the slope, and ultimately the landslide instability. Since the landslide sliding in the dip direction of the rock formation was impeded, the main sliding direction of the landslide formed an angle of 88° with this direction. This led to a unique failure mode characterized by slope sliding approximately along the strike of the rock formation. Based on these findings, this study proposed characteristics for the early identification of the failure of similar landslides, aiming to provide a robust scientific basis for the monitoring, early warning, and prevention and control of the failure of similar landslides. Full article

To address the challenges in intuitive feature discrimination and precise quantitative evaluation of cable defects, this paper proposes a diagnostic methodology utilizing the Symmetrized Dot Pattern (SDP) transform and reflection coefficient spectra. The Dung Beetle Optimizer (DBO) is introduced to adaptively optimize the SDP transform parameters, employing the Structural Similarity Index Measure (SSIM) as a fitness function to maximize discriminability between deterioration states. Three quantitative features, including the number of effective pixels, the degree of red–blue aliasing, and radial dispersion, are extracted to characterize the physical degradation processes of signal energy accumulation, angular evolution, and path divergence. By incorporating a self-reference calibration mechanism for structural differences, features are fused into a Comprehensive Deterioration Index (CDI). Experimental results on coaxial cables simulating shielding damage and thermal aging demonstrate that SDP images reveal continuous evolution patterns corresponding to defect severity. A regression model based on these patterns effectively characterizes deterioration trends. Compared to complex models, this study achieves intuitive fault identification and preliminary quantitative description of degradation trends through image feature fusion. Although the current sample size is limited, the results validate the feasibility of this method in evaluating cable deterioration severity, offering an efficient new data-processing perspective for cable condition monitoring. Full article

Acute kidney injury (AKI) continues to pose a significant clinical challenge due to its high morbidity rates and limited therapeutic options. Recent evidence suggests that natural compounds may provide renoprotective benefits by modulating oxidative stress and inflammation. This study examines the protective effects of a novel polysaccharide peptide extracted from Ganoderma lucidum (GL-PPQ1) against renal ischemia–reperfusion (I/R) injury, with particular emphasis on the integrin β3/Fibronectin 1 (Fn1) signaling axis. A murine model of renal I/R injury was established, and GL-PPQ1 was administered orally for seven days before surgery. The assessment included renal function, histopathology, oxidative stress markers, and inflammatory cytokines. Additionally, transcriptomic profiling and protein expression analyses were conducted to elucidate the underlying mechanisms. The results revealed that GL-PPQ1 pretreatment significantly reduced renal tubular damage, lowered serum creatinine and blood urea nitrogen levels, and diminished oxidative stress and inflammatory responses. RNA sequencing revealed that GL-PPQ1 affected gene sets associated with extracellular matrix remodeling and cell adhesion. Western blot and immunohistochemistry further confirmed that GL-PPQ1 decreased the expression of integrin β3 and Fn1, suggesting a regulatory effect on their interaction during I/R injury. These findings demonstrate that GL-PPQ1 offers substantial kidney protection by mitigating oxidative stress, inflammation, and dysregulation of the integrin β3/Fn1 signaling pathway. Thus, this study supports that polysaccharide peptides derived from Ganoderma lucidum could have the potential to serve as both a dietary supplement and a therapeutic agent in the treatment of AKI. Full article

The Tibetan Plateau (TP) atmospheric heat source crucially modulates East Asian summer monsoon precipitation, yet its synergy with upstream oceanic signals remains elusive. Using observations (1971–2020) and CMIP6 simulations, we investigate mechanisms coupling the summer TP heating and precipitation over the Middle and Lower Yangtze River (MLYR). SVD analysis reveals a robust positive coupling between them. Mechanistically, TP heating triggers a quasi-stationary Rossby wave train, inducing a “saddle-like” circulation that drives intense MLYR moisture convergence (contributing >90% to precipitation changes). Crucially, we re-examine the upstream oceanic precursor to propose a “dual-pathway superposition” framework. Contrary to the assumed linear causal chain, four-quadrant analysis reveals the spring Indian Ocean Basin Warming (IOBW) and summer TP heating are largely independent drivers (R = 0.24). While IOBW thermodynamically excites an Anomalous Anticyclone supplying abundant MLYR moisture, it lacks robust control over TP heating, which is dominated by internal atmospheric dynamics. However, our findings reveal a critical non-linear synergy: extreme MLYR rainfall strictly requires the coincidental phase overlap of these independent pathways (strong dynamic lifting coupled with oceanic moisture). CMIP6 simulations corroborate this independence, further emphasizing that extreme MLYR rainfall results from phase superposition rather than a single causal chain. Full article

Deep reinforcement learning (DRL) has been increasingly used in reservoir operation, but several key challenges and limitations need further study. This paper developed a novel and optimal reservoir operation model incorporating inflow forecasts based on DRL and the deterministic policy gradient algorithm. A multi-dimensional reward function was derived from the objective functions and constraints, and an optimal scheduling scheme was established with dynamically weighted reward functions. The observed daily flow data and 5-day inflow forecasts of the Three Gorges Reservoir (TGR) during flood seasons (from 10 June to 31 October) from 2010 to 2025 were used to evaluate the model performance and compared with the actual operation results. The results show that, compared with the actual operation, Scheme-1 with dynamic weights increases annual average flood prevention storage capacity by approximately 36.8%, enhances power generation by about 2.86 billion kW·h (≈5.49%), and reduces spillway waste water volume by around 3.33 billion m³. This study demonstrates that the optimal scheduling model can substantially improve the overall efficiency of reservoir operation, and the improvement is even more pronounced when the reward function weights are set dynamically. Full article

Caladium bicolor is an important ornamental foliage plant; however, its tropical origin makes it highly sensitive to environmental stresses such as drought and low temperature, which limits its cultivation and industrial development. Basic helix–loop–helix (bHLH) transcription factors play key roles in plant responses to abiotic stresses, but their functions in C. bicolor remain largely unknown. Here, a bHLH transcription factor gene, CbbHLH35, was cloned from C. bicolor, and its sequence characteristics, subcellular localization, expression patterns, and potential roles in stress responses were analyzed. The results showed that CbbHLH35 contains a conserved bHLH domain and is localized in the nucleus. qRT-PCR analysis revealed that CbbHLH35 is expressed in different tissues, with the highest expression in tubers, and is significantly induced by methyl jasmonate (MeJA), abscisic acid (ABA), drought, and low-temperature treatments. Transgenic C. bicolor plants overexpressing CbbHLH35 were generated and subjected to drought and cold stress. Compared with control plants, the overexpression lines showed higher chlorophyll content and POD activity but lower electrolyte leakage and MDA content, indicating enhanced drought and cold tolerance. These results suggest that CbbHLH35 plays a positive role in regulating drought and cold tolerance in C. bicolor and represents a promising candidate gene for the molecular breeding of stress-resistant cultivars. Full article

To study the creep mechanical behavior of surrounding rock under the coupled effect of confining pressure unloading and deviatoric stress increase during the excavation of deep underground engineering, triaxial creep tests under stepwise unloading of confining pressure and loading of deviatoric stress were conducted using marble as the research object. The influences of different initial confining pressures, unloading amounts, and stress levels on the axial and circumferential creep deformation, creep rate, and failure characteristics of marble were systematically analyzed. The results indicate the following: (1) As the amount of confining pressure unloading increases, the creep failure stress of marble decreases significantly, and the test duration is markedly shortened. (2) Under conditions of small unloading amounts, the creep rate initially decreases and then increases with increasing stress levels, while under large unloading amounts, the creep rate monotonically increases with stress levels, indicating that confining pressure unloading significantly weakens the stability of the rock mass during creep. (3) Based on the test results, a three-dimensional non-stationary Nishihara creep model suitable for the stress path of stepwise confining pressure unloading and deviatoric stress loading was established. The model calculations agree well with the experimental data, effectively describing the entire creep process of marble under unloading conditions. The research findings can provide a reference for the long-term stability analysis of the surrounding rock after excavation in deep underground engineering. Full article