Search Results (1,226)

Gully erosion refers to the landform formed by soil and water loss through gully development, which is a critical manifestation of soil degradation. However, research on the spatio-temporal variations in erosion gullies at the county scale remains insufficient, particularly regarding changes in gully aggregation and their driving factors. This study utilized high-resolution remote sensing imagery, gully interpretation information, topographic data, meteorological records, vegetation coverage, soil texture, and land use datasets to analyze the spatio-temporal patterns and influencing factors of erosion gully evolution in Bin County, Heilongjiang Province of China, from 2012 to 2022. Kernel density evaluation (KDE) analysis was also employed to explore these dynamics. The results indicate that the gully number in Bin County has significantly increased over the past decade. Gully development involves not only headward erosion of gully heads but also lateral expansion of gully channels. Gully evolution is most pronounced in slope intervals. While gentle slopes and slope intervals host the highest density of gullies, the aspect does not significantly influence gully development. Vegetation coverage exhibits a clear threshold effect of 0.6 in inhibiting erosion gully formation. Additionally, cultivated areas contain the largest number of gullies and experience the most intense changes; gully aggregation in forested and grassland regions shows an upward trend; the central part of the black soil region has witnessed a marked decrease in gully aggregation; and meadow soil areas exhibit relatively stable spatio-temporal variations in gully distribution. These findings provide valuable data and decision-making support for soil erosion control and transformation efforts. Full article

Background: CCAAT/enhancer-binding protein alpha–basic leucine zipper in-frame (CEBPA^bZIP-inf) mutations are associated with favorable outcomes in acute myeloid leukemia (AML). So far, there are limited data on integrating clinical and genomic features impacting the outcomes. Methods: Clinical and genomic data from consecutive patients with CEBPA^bZIP-inf were reviewed. A Cox proportional hazards regression was used to identify the variables associated with event-free survival (EFS), relapse-free survival (RFS) and survival. Results: 224 CEBPA^bZIP-inf patients were included in this study. In the 201 patients, except for the 19 receiving the transplant in the first complete remission with no events (the transplant cohort), multivariate analyses showed that IKZF1 mutations/deletions were significantly associated with poor EFS (p = 0.001) and RFS (p < 0.001); FLT3-ITD mutations, poor RFS (p = 0.048). In addition, increasing WBC count, lower hemoglobin concentration, non-intensive induction, and MRD positivity after first consolidation predicted poor outcomes. On the basis of the number of adverse prognostic covariates for RFS, the 201 patients were classified into low-, intermediate- or high-risk subgroups, and there were significant differences in the 3-year EFS, RFS and survival rates (all p < 0.001); however, except for survival in the low-risk group, these metrics were lower than those in the transplant cohort. Conclusions: We identified a potential high-risk population with adverse prognostic factors in CEBPA^bZIP-inf AML patients for which transplantation should be considered. Full article

Asia minor bluegrass (Polypogon fugax), a widespread Poaceae weed, exhibits broad tolerance to abiotic stresses. Validated reference genes (RGs) for reliable RT-qPCR normalization in this ecologically and agriculturally significant species remain unidentified. This study identified eight candidate RGs using transcriptome data from seedling tissues. We assessed the expression stability of these eight RGs across various abiotic stresses and developmental stages using Delta Ct, BestKeeper, geNorm, and NormFinder algorithms. A comprehensive stability ranking was generated using RefFinder, with validation performed using the target genes COR413 and P5CS. Results identified EIF4A and TUB as the optimal RG combination for normalizing gene expression during heat stress, cold stress, and growth stages. EIF4A and ACT were most stable under drought stress, EIF4A and 28S under salt stress, and EIF4A and EF-1 under cadmium (Cd) stress. Furthermore, EIF4A and UBQ demonstrated optimal stability under herbicide stress. Additionally, application of validated RGs revealed higher acetyl-CoA carboxylase gene (ACCase) expression in one herbicide-resistant population, suggesting target-site gene overexpression contributes to resistance. This work presents the first systematic evaluation of RGs in P. fugax. The identified stable RGs provide essential tools for future gene expression studies on growth and abiotic stress responses in this species, facilitating deeper insights into the molecular basis of its weediness and adaptability. Full article

The Internet of Vehicles (IoV) operates in an environment characterized by asymmetric security threats, where centralized vulnerabilities create a critical imbalance that can be disproportionately exploited by attackers. This study addresses this imbalance by proposing a symmetrical security framework that integrates Blockchain and Federated Learning (FL) to restore equilibrium in the Vehicle–Road–Cloud ecosystem. The evolution toward sixth-generation (6G) technologies amplifies both the potential of vehicle-to-everything (V2X) communications and its inherent security risks. The proposed framework achieves a delicate balance between robust security and operational efficiency. By leveraging blockchain’s symmetrical and decentralized distribution of trust, the framework ensures data and model integrity. Concurrently, the privacy-preserving approach of FL balances the need for collaborative intelligence with the imperative of safeguarding sensitive vehicle data. A novel Cloud Proxy Re-Encryption Offloading (CPRE-IoV) algorithm is introduced to facilitate efficient model updates. The architecture employs a partitioned blockchain and a smart contract-driven FL pipeline to symmetrically neutralize threats from malicious nodes. Finally, extensive simulations validate the framework’s effectiveness in establishing a resilient and symmetrically secure foundation for next-generation IoV networks. Full article

The use of Auxenochlorella pyrenoidosa (formerly Chlorella pyrenoidosa) and its intracellular substances (ISs) to promote biofloc development has been extensively studied. To identify the key components of the ISs of A. pyrenoidosa that drive biofloc formation, algal-extracted polysaccharides (AEPSs) and algal-extracted proteins (AEPTs) were isolated from the ISs. In this study, we established four groups: ISs, AEPSs, AEPTs, and tap water (TW, control), to investigate the effects of AEPSs and AEPTs on biofloc formation dynamics, water quality parameters, and microbial community composition. The results indicated no significant differences were observed between the ISs and AEPSs groups during the cultivation period. AEPSs significantly enhanced flocculation efficiency, achieving a final floc volume of 60 mL/L. This enhancement was attributed to the selective promotion of floc-forming microbial taxa, such as Comamonas, which can secrete procoagulants like EPS, and Pseudomonas and Enterobacter, which have denitrification capabilities. Water quality monitoring revealed that both AEPSs and AEPTs achieved nitrogen removal efficiencies exceeding 50% in the biofloc system, with AEPSs outperforming AEPTs. This is closely related to the fact that the microorganisms with increased flocculation contain numerous nitrifying and denitrifying bacteria. So, the intracellular polysaccharides were the key component of the ISs of A. pyrenoidosa that drive biofloc formation. These findings provide critical insights into the functional roles of algal-derived macromolecules in biofloc dynamics and their potential applications in wastewater treatment. Full article

Multibeam echosounder systems (MBESs) are widely used in unmanned surface vehicle swarms (USVs) to perform various marine bathymetry surveys because of their excellent performance. To address the challenges of systematic error superposition and edge beam error propagation in multibeam bathymetry surveying, this study proposes a novel error adjustment method integrating crossover error density clustering and beam incident angle (BIA) compensation. Firstly, a bathymetry error detection model was developed based on adaptive Density-Based Spatial Clustering of Applications with Noise (DBSCAN). By optimizing the neighborhood radius and minimum sample threshold through analyzing sliding-window curvature, the method achieved the automatic identification of outliers, reducing crossover discrepancies from ±150 m to ±50 m in the deep sea at a depth of approximately 5000 m. Secondly, an asymmetric quadratic surface correction model was established by incorporating the BIA as a key parameter. A dynamic weight matrix ω = 1/(1 + 0.5θ²) was introduced to suppress edge beam errors, combined with Tikhonov regularization to resolve ill-posed matrix issues. Experimental validation in the Western Pacific demonstrated that the RMSE of crossover points decreased by about 30.4% and the MAE was reduced by 57.3%. The proposed method effectively corrects residual systematic errors while maintaining topographic authenticity, providing a reference for improving the quality of multibeam bathymetric data obtained via USVs and enhancing measurement efficiency. Full article

The offshore implementation of vertical-axis wind turbines (VAWTs) presents a promising new paradigm for advancing marine wind energy utilization, owing to their omnidirectional wind acceptance, compact structural design, and potential for lower maintenance costs. However, VAWTs still face major aerodynamic challenges, particularly due to the pitching motion, where the angle of attack varies cyclically with the blade azimuth. This leads to strong unsteady effects and susceptibility to dynamic stalls, which significantly degrade aerodynamic performance. To address these unresolved issues, this study conducts a comprehensive investigation into the dynamic stall behavior and wake vortex evolution induced by Darrieus-type pitching motion (DPM). Quasi-three-dimensional CFD simulations are performed to explore how variations in blade geometry influence aerodynamic responses under unsteady DPM conditions. To efficiently analyze geometric sensitivity, a surrogate model based on a radial basis function neural network is constructed, enabling fast aerodynamic predictions. Sensitivity analysis identifies the curvature near the maximum thickness and the deflection angle of the trailing edge as the most influential geometric parameters affecting lift and stall behavior, while the blade thickness is shown to strongly impact the moment coefficient. These insights emphasize the pivotal role of blade shape optimization in enhancing aerodynamic performance under inherently unsteady VAWT operating conditions. Full article

Subsurface drainage and biochar application are conventional measures for improving saline–alkali soils. However, their combined effects on the fate of nitrogen (N) fertilizers remain unclear. This study investigated the combined effects of subsurface drainage and biochar amendment on the fate of nitrogen (N) in coastal saline–alkali soils, where these conventional remediation measures’ combined impacts on fertilizer N dynamics remain seldom studied. Using ¹⁵N-labeled urea tracing in an alfalfa–soil system, we examined how different drainage spacings (0, 6, 12, and 18 m) and biochar application rates (5, 10, and 15 t/ha) influenced N distribution patterns. Results demonstrated decreasing in drainage spacing and increasing in biochar application; these treatments enhanced ¹⁵N use efficiency on three harvested crops. Drainage showed more sustained effects than biochar. Notably, the combination of 6 m drainage spacing with 15 t/ha biochar application achieved optimal performance of ¹⁵N use, showing N utilization efficiency of 46.0% that significantly compared with most other treatments (p < 0.05). ¹⁵N mass balance analysis revealed that the plant absorption, the soil residual and the loss of applied N accounted for 21.6–46.0%, 38.6–67.5% and 8.5–18.1%, respectively. These findings provide important insights for optimizing nitrogen management in coastal saline–alkali agriculture, demonstrating that strategic integration of subsurface drainage (6 m spacing) with biochar amendment (15 t/ha) can maximize N use efficiency, although potential N losses warrant consideration in field applications. Full article

Cu-Ni-Si is a prominent example of a high-end lead frame copper alloy. The enhancement of strength without compromising electrical conductivity has emerged as a prominent research focus. The evolution of the precipitates exerts a significant influence on the strength and electrical conductivity of Cu-Ni-Si-Co-Mg alloys. In this paper, the effects of aging treatment and Mg addition on the properties and precipitates of cold-rolled Cu-Ni-Si-Co alloys were studied. The precipitate was (Ni, Co)₂Si and was in a strip shape. During aging, precipitation and coarsening of the (Ni, Co)₂Si precipitates were observed. In the early stage of aging, a significant number of fine (Ni, Co)₂Si precipitates were formed. These fine precipitates could not only have a better effect of precipitation strengthening, but also impeded the dislocation movement, thus increasing the dislocation density and improving the dislocation strengthening effect. However, the coarsening of the precipitates became dominant with increasing aging times. Therefore, the strengthening effect was weakened. The addition of 0.12% Mg promoted finer and more diffuse precipitates, which not only improving the tensile strength by 100–200 MPa, but also exhibiting a smaller effect on the electrical conductivity. However, further increases in Mg contents resulted in a significant decrease in electrical conductivity, with little change in the tensile strength. The optimum amount of added Mg was 0.12%, and the aging parameters were 300 °C and 20 min. Full article

It is vital to stabilize pillar dams in underground reservoirs in coal mine goafs to protect groundwater resources and quarry safety, practice green mining, and protect the ecological environment. Considering the actual occurrence of coal pillar dams in underground reservoirs, acoustic emission (AE) mechanical tests were performed on dry, naturally absorbed, and soaked coal samples. According to the mechanical analysis, Quantitative analysis revealed that dry samples exhibited the highest mechanical parameters (peak strength: 12.3 ± 0.8 MPa; elastic modulus: 1.45 ± 0.12 GPa), followed by natural absorption (peak strength: 9.7 ± 0.6 MPa; elastic modulus: 1.02 ± 0.09 GPa), and soaked absorption showed the lowest values (peak strength: 7.2 ± 0.5 MPa; elastic modulus: 0.78 ± 0.07 GPa). The rate of mechanical deterioration increased by ~25% per 1% increase in moisture content. It was identified that the internal crack development presented a macrofracture surface initiating at the sample center and expanding radially outward, and gradually expanding to the edges by adopting AE seismic source localization and the K-means clustering algorithm. Soaked absorption was easier to produce shear cracks than natural absorption, and a higher water content increased the likelihood. The b-value of the AE damage evaluation index based on crack development was negatively correlated with the rock damage state, and the S-value was positively correlated, and both effectively characterized it. The research results can offer reference and guidance for the support design, monitoring, and warning of coal pillar dams in underground reservoirs. (The samples were tested under two moisture conditions: (1) ‘Soaked absorption’—samples fully saturated by immersion in water for 24 h, and (2) ‘Natural absorption’—samples equilibrated at 50% relative humidity and 25 °C for 7 days). Full article

Growth traits are the most important economic traits in red tilapia (Oreochromis spp.) production, and are the main targets for its genetic improvement. Increasing salinity levels in the environment are affecting the growth, development, and molecular processes of aquatic animals. Red tilapia tolerates saline water to some degree. However, few credible genetic markers or potential genes are available for choosing fast-growth traits in salt-tolerant red tilapia. This work used genome-wide association study (GWAS) and RNA-sequencing (RNA-seq) to discover genes related to four growth traits in red tilapia cultured in saline water. Through genotyping, it was determined that 22 chromosomes have 12,776,921 high-quality single-nucleotide polymorphisms (SNPs). One significant SNP and eight suggestive SNPs were obtained, explaining 0.0019% to 0.3873% of phenotypic variance. A significant SNP peak associated with red tilapia growth traits was located on chr7 (chr7-47464467), and plxnb2 was identified as the candidate gene in this region. A total of 501 differentially expressed genes (DEGs) were found in the muscle of fast-growing individuals compared to those of slow-growing ones, according to a transcriptome analysis. Combining the findings of the GWAS and RNA-seq analysis, 11 candidate genes were identified, namely galnt9, esrrg, map7, mtfr2, kcnj8, fhit, dnm1, cald1, plxnb2, nuak1, and bpgm. These genes were involved in ‘other types of O-glycan biosynthesis’, ‘glycine, serine and threonine metabolism’, ‘glycolysis/gluconeogenesis’, ‘mucin-type O-glycan biosynthesis’ and ‘purine metabolism signaling’ pathways. We have developed molecular markers to genetically breed red tilapia that grow quickly in salty water. Our study lays the foundation for the future marker-assisted selection of growth traits in salt-tolerant red tilapia. Full article

Chilling injury can limit the productivity of tomato (Solanum lycopersicum L.), especially in over-wintering greenhouse. We here explored the effect of the pre-application of chlorogenic acid (CGA) in mitigating the impact of chilling on tomato. Flowering plants subjected to either chilling (15 °C/5 °C, day/night) or pre-treatment with CGA followed by chilling for 6 days and then by a two-day control recovery period were compared to plants maintained at control conditions (25 °C/18 °C, day/night). Chilling significantly affected the expression of PSII CP43 Chlorophyll Apoprotein, NAD (P) H-Quinone Oxidoreductase Subunit 5 and ATP Synthase CF1 Beta Subunit, reduced leaf Fv/Fm and increased malondialdehyde (MDA) levels, suggesting elevated oxidative stress. These correlated with reduced shoot biomass. All these aspects were mitigated by pretreatment with CGA. Transcriptomic and metabolomic co-analysis indicated that CGA also suppressed the shikimate pathway, phenylpropanoid biosynthesis and phenylalanine accumulation but enhanced cinnamic acid and indole acetate synthesis. Hence, the pre-chilling CGA protected the tomato plant from chilling injury by maintaining light energy utilization and reprograming secondary metabolism. This study describes the mechanism through which CGA pre-treatment can be used to maintain tomato productivity under chilling conditions. Full article

This study investigates the impact of circumferential angle (φ) and interaction angle (θ) between hydrogen jets and diesel sprays in a co-axial hydrogen–diesel injector on combustion and emissions in a hydrogen–diesel dual-fuel engine using 3D CFD simulations. The results demonstrate that a co-axial dual-layer nozzle design significantly enhances combustion performance by leveraging hydrogen jet kinetic energy to accelerate fuel–air mixing. Specifically, a co-axial alignment (φ = 0°) between hydrogen and diesel sprays achieves optimal combustion characteristics, including the highest in-cylinder pressure (20.92 MPa), the earliest ignition timing (−0.3° CA ATDC), and the maximum indicated power of the high-pressure cycle (47.26 kW). However, this configuration also results in elevated emissions, with 29.6% higher NOx and 34.5% higher soot levels compared to a φ = 15° arrangement. To balance efficiency and emissions, an interaction angle of θ = 7.5° proves most effective, further improving combustion efficiency and increasing indicated power to 47.69 kW while reducing residual fuel mass. For applications prioritizing power output, the φ = 0° and θ = 7.5° configuration is recommended, whereas a φ = 15° alignment with a moderate θ (5–7.5°) offers a viable compromise, maintaining over 90% of peak power while substantially lowering NOx and soot emissions. Full article

The mechanism of low- to middle-rank coal seam gas accumulation in the Baode block on the eastern edge of the Ordos Basin is well understood. However, exploration efforts in the Shizuishan area on the western edge started later, and the current understanding of enrichment and accumulation rules is unclear. It is important to systematically study enrichment and accumulation, which guide the precise exploration and development of coal seam gas resources in the western wing of the basin. The coal seam collected from the Shizuishan area of Ningxia was taken as the target. Based on drilling, logging, seismic, and CBM (coalbed methane) test data, geological conditions were studied, and factors and reservoir formation modes of CBM enrichment were summarized. The results are as follows. The principal coal-bearing seams in the study area are coal seams No. 2 and No. 3 of the Shanxi Formation and No. 5 and No. 6 of the Taiyuan Formation, with thicknesses exceeding 10 m in the southwest and generally stable thickness across the region, providing favorable conditions for CBM enrichment. Spatial variations in burial depth show stability in the east and south, but notable fluctuations are observed near fault F1 in the west and north. These burial depth patterns are closely linked to coal rank, which increases with depth. Although the southeastern region exhibits a lower coal rank than the northwest, its variation is minimal, reflecting a more uniform thermal evolution. Lithologically, the roof of coal seam No. 6 is mainly composed of dense sandstone in the central and southern areas, indicating a strong sealing capacity conducive to gas preservation. This study employs a system that fuses multi-source geological data for analysis, integrating multi-dimensional data such as drilling, logging, seismic, and CBM testing data. It systematically reveals the gas control mechanism of “tectonic–sedimentary–fluid” trinity coupling in low-gentle slope structural belts, providing a new research paradigm for coalbed methane exploration in complex structural areas. It creatively proposes a three-type CBM accumulation model that includes the following: ① a steep flank tectonic fault escape type (tectonics-dominated); ② an axial tectonic hydrodynamic sealing type (water–tectonics composite); and ③ a gentle flank lithology–hydrodynamic sealing type (lithology–water synergy). This classification system breaks through the traditional binary framework, systematically explaining the spatiotemporal matching relationships of the accumulated elements in different structural positions and establishing quantitative criteria for target area selection. It systematically reveals the key controlling roles of low-gentle slope structural belts and slope belts in coalbed methane enrichment, innovatively proposing a new gentle slope accumulation model defined as “slope control storage, low-structure gas reservoir”. These integrated results highlight the mutual control of structural, thermal, and lithological factors on CBM enrichment and provide critical guidance for future exploration in the Ningxia Autonomous Region. Full article

Location-based services have important economic and social values. The positioning accuracy and cost have a crucial impact on the quality, promotion, and market competitiveness of location services. Dead reckoning can provide accurate location information in a short time. However, it suffers from motion pattern diversity and cumulative error. To address these issues, we propose a PCA-GWO-KELM optimization gait recognition indoor fusion localization method. In this method, 30-dimensional motion features for different motion patterns are extracted from inertial measurement units. Then, constructing PCA-GWO-KELM optimization gait recognition algorithms to obtain important features, the model parameters of the kernel-limit learning machine are optimized by the gray wolf optimization algorithm. Meanwhile, adaptive upper thresholds and adaptive dynamic time thresholds are constructed to void pseudo peaks and valleys. Finally, fusion localization is achieved by combining with acoustic localization. Comprehensive experiments have been conducted using different devices in two different scenarios. Experimental results demonstrated that the proposed method can effectively recognize motion patterns and mitigate cumulative error. It achieves higher localization performance and universality than state-of-the-art methods. Full article