Search Results (362)

The Shizhuyuan polymetallic deposit in Hunan Province, China, is a world-class ore field rich in tungsten (W), tin (Sn), molybdenum (Mo), and bismuth (Bi), now facing resource depletion due to prolonged exploitation. This study addresses the limitations of traditional geological prediction methods in complex terrain by integrating multi-source datasets—including γ-ray spectrometry, high-precision magnetometry, induced polarization (IP), and soil radon measurements—across 5049 samples. Unsupervised factor analysis was employed to extract five key ore-indicating factors, explaining 82.78% of data variance. Based on these geological features, predictive models including Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) were constructed and compared. SHAP values were employed to quantify the contribution of each geological feature to the prediction outcomes, thereby transforming the machine learning “black-box models” into an interpretable geological decision-making basis. The results demonstrate that machine learning, particularly when integrated with multi-source data, provides a powerful and interpretable approach for deep mineral prospectivity mapping in concealed terrains. Full article

Accurate prediction of soil–structure interface shear strength (τ_max) is critical for reliable geotechnical design. This study combines experimental testing with interpretable machine learning to overcome the limitations of traditional empirical models and black-box approaches. Ninety large-displacement ring shear tests were performed on five sands and three interface materials (steel, PVC, and stone) under normal stresses of 25–100 kPa. The results showed that particle morphology, quantified by the regularity index (RI), and surface roughness (R_t) are dominant factors. Irregular grains and rougher interfaces mobilised higher τ_max through enhanced interlocking, while smoother particles reduced this benefit. Harder surfaces resisted asperity crushing and maintained higher shear strength, whereas softer materials such as PVC showed localised deformation and lower resistance. These experimental findings formed the basis for a hybrid symbolic regression framework integrating Genetic Programming (GP) with Shapley Additive Explanations (SHAP), Fourier feature augmentation, and physics-informed constraints. Compared with multiple linear regression and other hybrid GP variants, the Physics-Informed Neural Fourier GP (PIN-FGP) model achieved the best performance (R² = 0.9866, RMSE = 2.0 kPa). The outcome is a set of five interpretable and physics-consistent formulas linking measurable soil and interface properties to τ_max. The study provides both new experimental insights and transparent predictive tools, supporting safer and more defensible geotechnical design and analysis. Full article

Due to the complexity of impurity removal from the residual film, there is currently no better impurity removal equipment. To improve the screening performance of the residual film mixture, the vibrating screen was designed. In this paper, the key factors A, B, C, and D were identified through mechanical analysis of the mixture (where they represented the screen aperture diameter, vibration amplitude, vibration frequency, and screen mesh inclination angle, respectively). The soil screen rate (Y₁) and screening loss rate (Y₂) were evaluated. And the optimal ranges for these factors were determined by single-factor experiments. Based on the EDEM, the discrete element model was established to simulate the interaction between residual film and soil. And the motion characteristics of the residual film mixture were analyzed within the screen body through a combination of simulation and bench tests. The vibrating screen’s structural parameters were optimized using Box-Behnken experiments. The most suitable combination of settings was as shown below: A = 6.5 mm, B = 25 mm, C = 3.8 Hz, and D = 4°. Following the optimization of these parameters, the screening performance was optimized. Results of bench tests showed that the soil screening rate was 80.33% and the screening loss rate was 19.31%. This study was expected to offer theoretical and simulation-based methods for optimizing the parameters of residual film-soil vibrating screening devices. Full article

The pile–soil composite foundation system, highly acclaimed for its remarkable load-bearing capacity and limited deformation characteristics, has emerged as a fundamental element in geotechnical engineering practices. In the applications of adjacent slope engineering, such composite foundations are influenced by intricate loading scenarios. These scenarios involve both active vertical–horizontal combined load and passive soil-displacement forces generated due to the alteration of soil constraints. In this study, a self-designed movable retaining wall model box was employed. By applying different vertical and horizontal loads and controlling the rotation of the retaining wall around its base, a systematic investigation was conducted on the horizontal bearing mechanisms of single-pile and four-pile composite. The experimental data indicate that for every increment of 15 kPa in the vertical load, the horizontal bearing capacity experiences an average growth of approximately 18.9%, and the extreme value of the bending moment shows an average increase of 19.6. The analysis reveals coupled effects in internal force distribution and deformation patterns within load-bearing pile segments under concurrent active–passive loading conditions, while the embedded sections remain unaffected. Among four-pile composite foundations, the horizontal bearing mechanism of the front-row piles is consistent with that of a single-pile system. However, the maximum bending moments of the front-row and rear-row piles, compared to the single-pile system, have reached 0.68 times and 1.74 times, respectively. Notably, the bending moment of the front-row piles under the translational mode of the retaining wall is approximately 2.9 times that under the rotational mode, posing a potential risk of damage to the retaining structure, and necessary intervention is required. The results of this study provide a scientific basis for the force and deformation mechanism of piles at different positions in the composite foundation near foundation pit engineering, as well as their design for bending and shear resistance. Full article

To address the insufficient adaptability of imported peanut harvesting equipment’s soil-engaging components to the specific soil conditions in Xinjiang, this study conducted Discrete Element Method (DEM)-based calibration of soil mechanical parameters using field soil samples with 1–20% moisture content from typical peanut cultivation areas in southern Xinjiang. Through the EDEM simulation platform, a comprehensive approach integrating the Hertz–Mindlin with the JKR adhesion model and Hertz–Mindlin with the Bonding model was employed to systematically calibrate nine key parameters: coefficient of restitution, static friction coefficient, rolling friction coefficient, JKR surface energy, normal/tangential stiffness per unit area, critical normal/tangential force, and soil bonding disk radius. Adopting static angle of repose (SAOR) and unconfined compressive force (UCF) as dual-response indicators, a hybrid experimental design strategy combining Central Composite Design (CCD), Plackett–Burman (PB) screening, and Box–Behnken Design (BBD) optimization was implemented. Regression models for SAOR and UCS were established, yielding six sets of soil parameters optimized for different moisture conditions through parameter optimization. Field validation demonstrated the following: ≤3.27% error in SAOR, ≤1.46% error in UCF, and ≤5.05% error in drawbar resistance validation for field digging shanks. Experimental results confirm that the model demonstrates strong prediction accuracy for soils in typical peanut harvesting regions of southern Xinjiang, thereby providing key parameter references for the future self-developed, highly adaptive soil-engaging components with drag reduction optimization in peanut harvesters for the Xinjiang region. Full article

Improving sowing quality is crucial for ensuring wheat emergence and healthy growth. To address issues of poor wheat sowing quality, such as uneven sowing depth and inadequate soil coverage, in the Yangtze River Delta region of China, this study systematically analyzed the effects of the implement’s structural and operational parameters on sowing quality. Based on this analysis, a double-shaft rotary tillage and double-press seeder was designed. Protrusions on the grooving press roller are used to form seed furrows, rotary tiller blades cover the seeds with soil, and the rear press roller compacts the soil. DEM-MBD (discrete element method–multibody dynamics) coupled simulations, combined with single-factor and central composite design (CCD) experiments, were conducted with seeding depth as the evaluation index and four experimental factors: the protrusion height on the press grooving roller, forward speed, seed mass in the seed box, and straw mulching amount. The optimal protrusion height was 29 mm. The effects of rotary tiller blade working depth, rotational speed, and forward speed on soil-covering mass and its coefficient of variation were evaluated through discrete element method (DEM) simulations. The optimal working depth and rotational speed were found to be 55 mm and 350 r·min⁻¹, respectively, based on single-factor and Box–Behnken Design experiments. Field experiments based on optimized parameters showed results consistent with the simulations. The qualified rate of seeding depth decreased as forward speed increased. The optimal forward speed was 4.5 km·h⁻¹, at which the average seeding depth was 25.7 mm, the qualified seeding depth rate was 90%, the soil-covering mass within a 50 cm² area was 143.2 g, and the coefficient of variation was 13.21%, meeting the requirements for wheat sowing operations. Full article

Aiming at key issues in harvesting film-covered potatoes in hilly and mountainous areas—incomplete residual film collection, poor potato–soil separation, and high damage from potato-collecting devices—this study developed a crawler self-propelled potato harvester suitable for these regions. This study first expounds the overall structure and working principle of the potato harvester and then conducts principal analysis and structural design for key components (film-collecting device, digging device, primary conveying and separating device, secondary conveying and separating device, and intelligent potato-collecting device) from the perspectives of material force and movement. Finally, field performance tests were carried out in Huangzhong County, Xining City, Qinghai Province. The test results show that the machine can achieve an operation effect with a potato harvest loss rate of 2.4%, a potato damage rate of 1.4%, an impurity content rate of 2.8%, a skin-breaking rate of 2.7%, and a residual film cleaning rate of 89.6%, meeting the potato harvesting needs of this region. The lightweight self-propelled crawler potato harvester designed in this paper can realize functions such as residual film collection, potato–soil vibration separation, manual auxiliary sorting, and intelligent potato boxing, providing technical and equipment references for the harvesting of film-covered potatoes in complex terrain areas. Full article

Lycium barbarum is a traditional medicinal and edible plant species in China, exhibiting notable salt tolerance that enables cultivation in salt-affected soils. However, intensifying soil salinization has rendered severe salt stress a critical limiting factor for its fruit yield and quality. Universal stress proteins (USPs) serve as crucial regulators for plant abiotic stress responses through developmental process modulation. Nevertheless, the characteristics and functional divergence of USP gene family members remain unexplored in L. barbarum. Here, we performed genome-wide identification and characterization of the USP gene family in L. barbarum, revealing 52 members unevenly distributed across all 12 chromosomes. Phylogenetic analysis classified these LbUSP members into four distinct groups, demonstrating the integration of the conserved USP domain and diverse motifs within each group. Collinearity analysis indicated a stronger synteny of LbUSPs with orthologs in Solanum lycopersicum than with other species (Arabidopsis thaliana, Vitis vinifera, and Oryza sativa), demonstrating that gene duplication coupled with functional conservation represented the primary mechanism underlying USP family expansion in L. barbarum. In silico promoter screening detected abundant cis-acting elements associated with abiotic/biotic stress responses (MYB and MYC binding sites), phytohormone regulation (ABRE motif), and growth/development processes (Box-4 and G-box). Transcriptome sequencing and RT-qPCR validation revealed tissue-specific differential expression patterns of LbUSP8, LbUSP11, LbUSP12, LbUSP23, and LbUSP25 in roots and stems under salt stress, identifying them as prime candidates for mediating salt resistance in L. barbarum. Our findings establish a foundation for the functional characterization of LbUSPs and molecular breeding of salt-tolerant L. barbarum cultivars. Full article

To address compacted soils with high power consumption and waterlogging risks in rice–rapeseed rotation areas of the Yangtze River, this study designed a ditching machine combining a stepped cutter head and trapezoidal cleaning blade, where the mechanical synergy between components minimizes energy loss during soil-cutting and -throwing processes. We mathematically modeled soil cutting–throwing dynamics and blade traction forces, integrating soil rheological properties to refine parameter interactions. Discrete Element Method (DEM) simulations and single-factor experiments analyzed impacts of the inner/outer blade widths, blade group distance, and blade opening on power consumption. Results indicated that increasing the inner/outer blade widths (200–300 mm) by expanding the direct cutting area significantly reduced the cutter torque by 32% and traction resistance by 48.6% from reduced soil-blockage drag; larger blade group distance (0–300 mm) initially decreased but later increased power consumption due to soil backflow interference, with peak efficiency at 200 mm spacing; the optimal blade opening (586 mm) minimized the soil accumulation-induced power loss, validated by DEM trajectory analysis showing continuous soil flow. Box–Behnken experiments and genetic algorithm optimization determined the optimal parameters: inner blade width: 200 mm; outer blade width: 300 mm; blade group distance: 200 mm; and blade opening: 586 mm, yielding a simulated power consumption of 27.07 kW. Field tests under typical 18.7% soil moisture conditions confirmed a <10% error between simulated and actual power consumption (28.73 kW), with a 17.3 ± 0.5% reduction versus controls. Stability coefficients for the ditch depth, top/bottom widths exceeded 90%, and the backfill rate was 4.5 ± 0.3%, ensuring effective drainage for rapeseed cultivation. This provides practical theoretical and technical support for efficient ditching equipment in rice–rapeseed rotations, enabling resource-saving design for clay loam soils. Full article

Concern over the presence of pharmaceutical waste in the environment has prompted research into the management of emerging organic micropollutants (EOMs). In response, sustainable technologies have been applied as alternatives to reduce the effects of these contaminants. This study investigated the capacity of filamentous fungi isolated from iron mine soil in the Amazon region to biodegrade the drug chloroquine diphosphate. An initial screening assessed the growth of four fungal strains on solid media containing chloroquine diphosphate: Trichoderma pseudoasperelloides CBMAI 2752, Penicillium rolfsii CBMAI 2753, Talaromyces verruculosus CBMAI 2754, and Penicillium sp. cf. guaibinense CBMAI 2758. Among them, Penicillium sp. cf. guaibinense CBMAI 2758 was selected for further testing in liquid media. A Box–Behnken factorial design was applied with three variables, pH (5, 7, and 9), incubation time (5, 10, and 15 days), and chloroquine diphosphate concentration (50, 75, and 100 mg·L⁻¹), totaling 15 experiments. The samples were analyzed by gas chromatography–mass spectrometry (GC-MS). The most effective conditions for chloroquine biodegradation were pH 7, 100 mg·L⁻¹ concentration, and 10 days of incubation. Four metabolites were identified: one resulting from N-deethylation M1 (N4-(7-chloroquinolin-4-yl)-N1-ethylpentane-1,4-diamine), two from carbon–carbon bond cleavage M2 (7-chloro-N-ethylquinolin-4-amine) and M3 (N1,N1-diethylpentane-1,4-diamine), and one from aromatic deamination M4 (N1-ethylbutane-1,4-diamine) by enzymatic reactions. The toxicity analysis showed that the products obtained from the biodegradation of chloroquine were less toxic than the commercial formulation of this compound. These findings highlight the biotechnological potential of Amazonian fungi for drug biodegradation and decontamination. Full article

The identification of unmarked graves is important in archaeology, forensics, and cemetery management, but invasive methods are often restricted due to ethical or cultural concerns. This necessitates the use of non-invasive geophysical techniques. Our study demonstrates the potential of induced polarization (IP) imaging as a non-invasive remote sensing technique specifically suited for detecting and characterizing unmarked graves. IP leverages changes in the electrical properties of soil and pore water, influenced by the accumulation of organic matter from decomposition processes. Measurements were conducted at an inactive cemetery using non-invasive textile electrodes to map a documented grave from the early 1990s, with a survey design optimized for high spatial resolution. The results reveal a distinct polarizable anomaly at a 0.75–1.0 m depth with phase shifts exceeding 12 mrad, attributed to organic carbon from wooden burial boxes, and a plume-shaped conductive anomaly indicating the migration of dissolved organic matter. While electrical conductivity alone yielded diffuse grave boundaries, the polarization response sharply delineated the grave, aligning with photographic documentation. These findings underscore the value of IP imaging as a non-invasive, data-driven approach for the accurate localization and characterization of graves. The methodology presented here offers a promising new tool for archaeological prospection and forensic search operations, expanding the geophysical toolkit available for remote sensing in culturally and legally sensitive contexts. Full article

In high-slope substrates, special requirements are imposed on sprayed ecological soil, which needs to exhibit high rheological properties before spraying and rapid curing after spraying. Traditional stabilizers are often unable to meet these demands. This study developed a thermo-responsive hydrogel stabilizer (HSZ) and applied it to ecological soil. The effects of HSZ on the rheological, mechanical, and vegetation performance of ecological soil were investigated, and the mechanism of the responsive carrier in the stabilizer was explored. The experimental results show that the ecological soil containing HSZ has high flowability before response, but its flowability rapidly decreases and consistency sharply increases after response. After the addition of HSZ, the 7 d unconfined compressive strength of the ecological soil reaches 1.55 MPa. The pH value of the ecological soil generally ranges from 6.5 to 8.0, and plant growth in a simulated vegetation box is favorable. Conductivity and viscosity tests demonstrate that the core–shell microcarriers, upon thermal response, release crosslinking components from the carrier, which rapidly react with the precursor solution components to form a curing system. This study provides a novel method for regulating ecological soil using a responsive stabilizer, further expanding its capacity to adapt to various complex scenarios. Full article

Strawberry planting requires different amounts of soil water-holding capacity and fertilizer at different growth stages. Determining the stages of strawberry growth has important guiding significance for irrigation, fertilization, and picking. Quick and accurate identification of strawberry plants at different stages can provide important information for automated strawberry planting management. We propose an improved multistage identification model for strawberry based on the YOLOv9 algorithm—the ASHM-YOLOv9 model. The original YOLOv9 showed limitations in detecting strawberries at different growth stages, particularly lower precision in identifying occluded fruits and immature stages. We enhanced the YOLOv9 model by introducing the Alterable Kernel Convolution (AKConv) to improve the recognition efficiency while ensuring precision. The squeeze-and-excitation (SE) network was added to increase the network’s capacity for characteristic derivation and its ability to fuse features. Haar wavelet downsampling (HWD) was applied to optimize the Adaptive Downsampling module (Adown) of the initial model, thereby increasing the precision of object detection. Finally, the CIoU function was replaced by the Minimum Point Distance based IoU (MPDIoU) loss function to effectively solve the problem of low precision in identifying bounding boxes. The experimental results demonstrate that, under identical conditions, the improved model achieves a precision of 97.7%, a recall of 97.2%, mAP50 of 99.1%, and mAP50-95 of 90.7%, which are 0.6%, 3.0%, 0.7%, and 7.4% greater than those of the original model, respectively. The parameters, model size, and floating-point calculations were reduced by 3.7%, 5.6% and 3.8%, respectively, which significantly boosted the performance of the original model and outperformed that of the other models. Experiments revealed that the model could provide technical support for the multistage identification of strawberry planting. Full article

A multi-parameter optimization-based design method for soil-mixing blades was proposed to address the issue of excessive straw residue in the seeding layer after maize straw incorporation. A discrete element model simulating the interaction between the soil-mixing blades, soil, and corn straw was established. The key structural parameters included the bending line angle (α), bending angle (β), side angle (δ), tangential edge height (h), and bending radius (r); the straw burial rate (Y₁) and straw percentage in the seeding layer (Y₂) were selected as evaluation indicators. Single-factor experiments determined the significance level (p < 0.05) and the parameter range. A Box–Behnken response surface design, combined with analysis of variance (ANOVA), was employed to elucidate the influence patterns of the structural parameters and their interactions regarding straw burial performance. Multi-objective optimization yielded an optimal parameter combination: α = 55°, β = 100.01°, δ = 130°, h = 40.05 mm, and r = 28.67 mm. The simulation results demonstrated that this configuration achieved a Y₁ of 96.04% and reduced Y₂ to 35.25%. Field validation tests recorded Y₁ and Y₂ values of 96.54% and 34.13%, respectively. This study quantitatively elucidated the relationship between soil-mixing blade parameters and straw spatial distribution, providing a theoretical foundation for optimizing straw incorporation equipment. Full article

Accurate quantification of soil organic matter (SOM) is crucial for improving soil fertility and maintaining ecosystem health. The content of SOM affects soil nutrient availability and is closely linked to the global carbon cycle. The use of an electronic nose to detect SOM contents has the advantages of rapidity, accuracy, and low pollution to the environment. This study proposes a method for obtaining SOM contents via pyrolysis coupled with an artificial olfaction system. To improve the accuracy of SOM content determination, the effects of three parameters (pyrolysis temperature, pyrolysis time, and soil sample mass) related to the pyrolysis process on the distinguishability of pyrolysis gases were investigated. Firstly, single-factor experiments were conducted to determine the optimal values of three parameters that can improve the differentiation of pyrolysis gases. Secondly, a regression model based on the Box–Behnken experiment was established to analyze the interrelationships between the three parameters and the discrete ratio. The experimental results showed that the three parameters exerted significant influences on the discrete ratio, with pyrolysis time having the greatest impact, followed by soil sample mass and pyrolysis temperature. The optimal discrimination and minimal dispersion ratio of the pyrolysis gases were achieved at a pyrolysis temperature of 384 °C, with a pyrolysis time of 2 min 41 s and a soil sample mass of 1.68 g. Finally, the Back-Propagation Neural Network (BPNN) and Partial Least-Squares Regression (PLSR) algorithms were used to establish an SOM prediction model after obtaining soil pyrolysis gases under the optimal combination of pyrolysis parameters. The experimental results demonstrated that the SOM prediction model based on PLSR achieved the best accuracy and the highest generalization capability, with R² > 0.85 and RMSE < 7.21. This study could provide a theoretical basis for the prediction of SOM contents via pyrolysis coupled with an artificial olfaction system. Full article