Search Results (3,540)

Flax, an important oil and fiber crop, is widely cultivated in temperate and sub-frigid regions worldwide. China is one of the major producers of flax, with Gansu Province predominantly practicing cultivation in hilly areas. However, common issues such as feeding difficulties, stem entanglement, and low threshing efficiency significantly restrict the improvement of planting efficiency. This study addresses the key technical challenges in flax combine harvesting in hilly regions by developing a discrete element model of the flax plant and utilizing DEM-FEA co-simulation technology. The performance of two threshing drum models (T₁ and T₂) was analyzed, focusing on motion trajectory, stress distribution, and threshing effects. The simulation results show that the T₂ model, with its combination of rib and rod tooth design, significantly improves threshing and separation efficiency. The loss rate was reduced from 5.6% in the T₁ model to 1.78% in the T₂ model, while the maximum stress and deformation were significantly lower, indicating higher structural stability and durability. Field validation results revealed that the T₁ model had a total loss rate of 3.32%, an impurity rate of 3.57%, and an efficiency of 0.09 hm²/h. In contrast, the T₂ model achieved a total loss rate of 2.29%, an impurity rate of 3.39%, and an efficiency of 0.22 hm²/h, representing a 144.4% improvement in working efficiency. These findings indicate that the T₂ model has a higher potential for flax harvesting in hilly and mountainous regions, especially in improving threshing efficiency and operational stability, providing an important theoretical basis for optimizing threshing equipment design. Full article

To solve the problem of straw cleaning and drip irrigation belt restoration for no-till seeding in drip irrigation areas, a staggered straw cleaning device was developed for no-till seeding, which is mainly composed of a front two-sided tine discs group, a drip irrigation belt laying mechanism, a middle single inner tine discs group, a rear single outer tine discs group. Different tine disc groups are set in longitudinal, transverse, and radial directions to move and throw the straw on the surface of the seeding strip. The critical parameters of the tine disc were designed and calculated, and the radius was determined to be 160 mm, the number of teeth was 12, and the theoretical working width was obtained. The movement and straw scattering process were analyzed, and the main influencing factors and the maximum straw scattering distances in the horizontal and vertical directions were determined. The interaction model of staggered tine discs group–straw–soil is established using the discrete element method (DEM). The forwarding speed, rotating speed, disc rake angle, and lateral distance of the middle tine discs were used as influencing factors, and the straw cleaning rate and the mass of straw returned in the drip irrigation coverage area were selected as the text indexes to carry out quadratic orthogonal rotation experiments. The quadratic regression model of the three sensitive parameters on the cleaning rate and the mass of straw returned in the drip irrigation coverage area was constructed and optimized. The optimal solutions were obtained: the forwarding speed was 9 km/h, the disc rake angle was 33.7°, and the lateral distance of the middle tine discs was 529 mm. The field validation test was carried out, and the results showed that the straw cleaning was 89.13%, the straw cleaning width of the seed strip was 527.2 mm, and the straw coverage rate of the drip irrigation area was 80.74%. This achievement can provide a reference for straw cleaning of no-till seeding under drip irrigation. Full article

This paper established an accurate discrete element for ultrasonic vibration-cutter-soil interaction model to study the interaction mechanism between the soil-engaging component and the soil. In order to reduce the interaction between calibration parameters and improve the calibration accuracy, it is proposed that the soil constitutive, contact parameters, and bonding parameters be calibrated by combining the soil repose angle experiment and the soil resistance experiment of ultrasonic vibration cutting. The study adopts the Hertz-Mindlin (no slip) contact model used in EDEM, to explore soil particle interactions. The central composite design is used to achieve systematic investigation. 3-factor 3-level orthogonal design experiment was employed using the coefficient of restitution, the coefficient of static friction, and the coefficient of rolling friction as key test factors and soil’s repose angle as the response index. Based on the Hertz-Mindlin with bonding contact model, Design-Expert 13.0 software was used to design the Plackett-Burman experiment, the steepest ascent, and the Box-Behnken experiment. With the maximum soil cutting resistance in ultrasonic vibration cutting experiment used as the response value, the adhesion parameters were optimized, and the optimal solution combination was obtained as: Normal Stiffness = 4.635 × 10⁶ N/m, Shear Stiffness = 3.401 × 10⁶ N/m, and Bonded Disk Radius = 2.57 mm. The optimal parameter combinations obtained from the calibration experiments were verified in two ways: ultrasonic vibration cutting and non-ultrasonic vibration cutting. The results showed that the errors between the simulation values and the actual values of the two comparative experiments were less than 5%, and the model calibrated for the three parameters can be used to study the drag reduction mechanism of ultrasonic vibration cutting in soil. Full article

To address the challenges of labor-intensive, inefficient, and inconsistent manual hole sowing and transplanting of Angelica sinensis in rain-fed hilly regions of Northwest China, a pneumatic hole-sowing device was designed based on the principle of electromagnetically controlled, high-speed reciprocating cylinder motion. Considering the agronomic requirements for transplanting mulched Angelica sinensis, the device’s structure and operational parameters were optimized. The key mechanisms involved in hole sowing and seedling placement were analyzed. A pneumatic circuit system, controlled by a relay circuit, was established, and a hole-sowing mechanism with a delayed closure effect was designed. Using the Discrete Element Method (DEM) and Multi-Body Dynamics (MBD) coupling technology, a simulation of the hole-sowing process was conducted to evaluate the device’s performance and its impact on soil disturbance and hole reformation in the seedbed. Prototype device performance tests were conducted, using qualified seeding depth under mulch and hole spacing as indicators. When the theoretical hole spacing was 30 cm and the hole-sowing frequency was 60 plants/(min·row), the soil bin test results indicated a seeding depth qualification rate of 93%, a misalignment rate of 3%, and a spacing qualification rate of 83%; the field test results showed a qualified seeding depth rate under mulch of 96%, the hole misalignment rate was 5%, and the spacing qualified rate was 86%. The pneumatic hole-sowing device’s performance meets the agronomic requirements for vertical transplanting of Angelica sinensis seedlings. This research can serve as a reference for designing planting machinery for rhizomatous medicinal plants. Full article

The understanding of the characteristics and metabolite changes in waxy and normal maize kernels after cooking is rather limited. This study was designed to meticulously analyze the differences in characteristics and metabolites of these kernels before and after steaming. To cut environmental impacts, samples were obtained by pollinating one ear with mixed pollen. Non-targeted metabolomics was used to analyze metabolites comprehensively. The results demonstrated that a total of 4043 annotated metabolites were identified. Principal component analysis (PCA) indicated distinct variances between kernels before and after steaming and between the two maize types. Steaming led to an increase in differential metabolites (DEMs) for both maize varieties, noticeably in waxy maize. In waxy maize, the down-regulated DEMs were associated with lipid metabolism, while the up-regulated ones were related to amino acid, phenylpropanoid, and flavone metabolism. Compared to steamed normal maize kernels, waxy maize had more DEMs in purine and steroid pathways, fewer in fatty acid, α-linolenic acid, and phenylpropanoid ones, with marked differences in secondary metabolites like those in amino acid metabolism. This study offers a vital foundation and direction for future research on metabolic pathways regarding maize quality improvement and flavor regulation. Full article

Rainfall infiltration is the primary triggering factor for the instability of unsaturated slopes. At present, rainfall-induced landslides are mainly considered to be influenced by the overall infiltration conditions, while few investigations have been conducted on the influence of infiltration boundaries on slope instability. This study proposes a rainfall infiltration method using a discrete element model (DEM), which is based on saturated–unsaturated seepage theory. The influence of three infiltration boundaries on the instability of homogeneous unsaturated soil slopes was studied. The results showed that the infiltration rate of a rainfall-covered slope crest was faster than that of rainfall-covered slope surfaces. A transient saturated zone was formed on the slope surface after a certain duration of rainfall. Rain infiltration boundary conditions significantly impact the saturation distribution, seepage field, failure mode, and failure period. The safety and stability factors for the rainfall-covered slope crest and full area decreased monotonically with the increase in rainfall duration, while there was a brief increase at the initial stage of rainfall before a quick decline for rainfall-covered slope surfaces. This research provides a preliminary exploration of the impact of rainfall boundary conditions on the instability of slopes, offering a reference basis for DEM simulations that consider slope stability under the influence of rainfall infiltration. Full article

To address challenges in seed feeding stability and seeding uniformity in agricultural practices, this study aimed to introduce a cylindrical air-assisted drill sowing device (CADSD) designed for rapeseed, wheat, and rice (RWR). The device features a prototype hill-feeding mechanism that addresses problems related to seed feeding, airflow disruptions, and seed–wall collisions. Comprehensive bench tests, Discrete Element Method (DEM) simulations, and preliminary field experiments were conducted to evaluate the seed-feeding stability characteristics and optimize the structural parameters of the air-assisted drill sowing system, enhancing seeding uniformity and operational efficiency. The optimal operating speed range is between 4 and 5 km/h. When the seed feeding speed is 30 to 38 r/min, the coefficient of variation of the seed supply rate stability is less than 0.55%, and the relative error between the theoretical and the experimental actual values of the RWR supply rate regression model is less than 2%, further supporting the effectiveness of the device. A preliminary field test revealed a seeding uniformity coefficient of variation (CV) of 3.44% and an emergence rate of 88%, closely aligning with the desired metrics. The CADSD effectively sows multiple crop types with improved precision and uniformity, handling diverse seed types and sizes without requiring equipment modifications, highlighting its innovative impact on agricultural technology in the precise seeding of RWR. Full article

Previous research showed that a tsunami similar to the 1755 event would inundate Caxias’ low-ground areas in Oeiras municipality, Portugal. However, the streets of downtown Caxias were not well reproduced, which is a limitation of the area’s mitigation strategies and evacuation plan. For these reasons, new Lidar data were used for the first time in Portugal. The new local topography data allowed the construction of a more accurate DEM, which was used in the tsunami numerical model to update and improve the inundation results. As a complement, a field survey was conducted in several locations to assess coastal features and protection. The numerical model results show that low-ground areas up to 6 m in height were inundated by the tsunami, including the residential area, the road, and the railway. To stop the tsunami waves from inundating these areas, it is proposed that the construction of more sea walls up to 7 m in height and a third bridge over the Barcarena Stream, only for pedestrians, ranging from 5 to 7 m in height, which will serve as a gate for the incoming tsunami waves. These coastal protections should be part of the strategy to mitigate coastal overtopping (winter storm surges and tsunamis) not only in Caxias but also in other coastal zones. Full article

The objective of our research is to produce a digital elevation model (DEM) in a real-time domain. For this purpose, GNSS measurements are obtained from a kinematic trajectory in a clear location in New Aswan City, Egypt. Different real-time processing solutions are employed, including real-time precise point positioning (RT-PPP) and real-time kinematics (RTK); additionally, the widely used post-processed precise point positioning (PPP) processing scenario is used. Thereafter, the acquired positioning estimates are compared with the traditional kinematic differential GNSS solution counterparts. To achieve the RT-PPP mode, the instantaneous products from the Centre National d’Etudes Spatiales (CNES) are utilized. Our proposed models are validated for both kinematic positioning and DEM accuracies. For kinematic positioning accuracy validation, the findings indicate that the three-dimensional position is about 0.480 m, 0.101 m, and 0.628 for RT-PPP, RTK, and PPP solutions, respectively. Furthermore, the DEM accuracy investigation shows that the produced DEMs have accuracies within 0.249 m, 0.005 m, and 0.264 m for RT-PPP, RTK, and PPP solutions, respectively. Full article

Marine and underwater structures, such as seawalls, piers, breakwaters, and pipelines, are particularly susceptible to seismic events. These events can directly damage the structures or destabilize their supporting soil through phenomena like liquefaction. This review examines advanced numerical modeling approaches, including CFD, FEM, DEM, FVM, and BEM, to assess the impacts of earthquakes on these structures. These methods provide cost-effective and reliable simulations, demonstrating strong alignment with experimental and theoretical data. However, challenges persist in areas such as computational efficiency and algorithmic limitations. Key findings highlight the ability of these models to accurately simulate primary forces during seismic events and secondary effects, such as wave-induced loads. Nonetheless, discrepancies remain, particularly in capturing energy dissipation processes in existing models. Future advancements in computational capabilities and techniques, such as high-resolution DNS for wave–structure interactions and improved near-field seismoacoustic modeling show potential for enhancing simulation accuracy. Furthermore, integrating laboratory and field data into unified frameworks will significantly improve the precision and practicality of these models, offering robust tools for predicting earthquake and wave impacts on marine environments. Full article

Forests are crucial for biodiversity, climate regulation, and hydrological cycles, requiring sustainable management due to threats like deforestation and climate change. Traditional forest monitoring methods are labor-intensive and limited, whereas UAV LiDAR offers detailed three-dimensional data on forest structure and extensive coverage. This study primarily assesses individual tree segmentation algorithms in two forest ecosystems with different levels of complexity using high-density LiDAR data captured by the Zenmuse L1 sensor on a DJI Matrice 300RTK platform. The processing methodology for LiDAR data includes preliminary preprocessing steps to create Digital Elevation Models, Digital Surface Models, and Canopy Height Models. A comprehensive evaluation of the most effective techniques for classifying ground points in the LiDAR point cloud and deriving accurate models was performed, concluding that the Triangular Irregular Network method is a suitable choice. Subsequently, the segmentation step is applied to enable the analysis of forests at the individual tree level. Segmentation is crucial for monitoring forest health, estimating biomass, and understanding species composition and diversity. However, the selection of the most appropriate segmentation technique remains a hot research topic with a lack of consensus on the optimal approach and metrics to be employed. Therefore, after the review of the state of the art, a comparative assessment of four common segmentation algorithms (Dalponte2016, Silva2016, Watershed, and Li2012) was conducted. Results demonstrated that the Li2012 algorithm, applied to the normalized 3D point cloud, achieved the best performance with an F1-score of 91% and an IoU of 83%. Full article

Gully erosion is one of the significant environmental issues facing the black soil regions in Northeast China, and its formation is closely related to various environmental factors. This study employs multiple machine learning models to assess gully erosion susceptibility in this region. The primary objective is to evaluate and optimize the top-performing model under high-resolution UAV data conditions, utilize the optimized best model to identify key factors influencing the occurrence of gully erosion from 11 variables, and generate a local gully erosion susceptibility map. Using 0.2 m resolution DEM and DOM data obtained from high-resolution UAVs, 2,554,138 pixels from 64 gully and 64 non-gully plots were analyzed and compiled into the research dataset. Twelve models, including Logistic Regression, K-Nearest Neighbors, Classification and Regression Trees, Random Forest, Boosted Regression Trees, Adaptive Boosting, Extreme Gradient Boosting, an Artificial Neural Network, a Convolutional Neural Network, as well as optimized XGBOOST, a CNN with a Multi-Head Attention mechanism, and an ANN with a Multi-Head Attention Mechanism, were utilized to evaluate gully erosion susceptibility in the Dahewan area. The performance of each model was evaluated using ROC curves, and the model fitting performance and robustness were validated through Accuracy and Cohen’s Kappa statistics, as well as RMSE and MAE indicators. The optimized XGBOOST model achieved the highest performance with an AUC-ROC of 0.9909, and through SHAP analysis, we identified roughness as the most significant factor affecting local gully erosion, with a relative importance of 0.277195. Additionally, the Gully Erosion Susceptibility Map generated by the optimized XGBOOST model illustrated the distribution of local gully erosion risks. Full article

Snow avalanche is one of the major natural hazards in the mountain region, yet it has received less attention compared to other mountain hazards, such as landslides, floods, and droughts. After a comprehensive overview of snow avalanche hazards in Tibet area, the spatial distribution and main driving factors of snow avalanche hazards in the high mountain region in Tibet were presented in the study first. Snow avalanche-prone areas in Tibet were then mapped based on the snow cover distribution and DEM data and were validated against in situ observations. Results show that there are the highest frequencies of avalanche occurrences in the southeastern Nyainqentanglha Mountains and the southern slope of the Himalayas. In the interior of plateau, avalanche development is constrained due to less precipitation and much flatter terrain. The perennially snow avalanche-prone areas in Tibet account for 1.6% of the total area of the plateau, while it reaches 2.9% and 4.9% of the total area of Tibet in winter and spring, respectively. Snow avalanche hazards and fatalities appear to be increasing trends under global climate warming due to more human activities at higher altitudes. In addition to the continuous implementation of engineering prevention and control measures in pivotal regions in southeastern Tibet, such as in the Sichuan–Tibet highway and railway sections, enhancing monitoring, early warning, and forecasting services are crucial to prevent and mitigate avalanche hazards in the Tibetan high mountain regions, which has significant implications for other global high mountain areas. Full article

The relationship between coronary heart disease (CHD) and complex urban built environments remains a subject of considerable uncertainty. The development of predictive models via machine learning to explore the underlying mechanisms of this association, as well as the formulation of intervention policies and planning strategies, has emerged as a pivotal area of research. A cross-sectional dataset of hospital admissions for CHD over the course of a year from a hospital in Dalian City, China, was assembled and matched with multi-source built environment data via residential addresses. This study evaluates five machine learning models, including decision tree (DT), random forest (RF), eXtreme gradient boosting (XGBoost), multi-layer perceptron (MLP), and support vector machine (SVM), and compares them with multiple linear regression models. The results show that DT, RF, and XGBoost exhibit superior predictive capabilities, with all R² values exceeding 0.70. The DT model performed the best, with an R² value of 0.818, and the best performance was based on metrics such as MAE and MSE. Additionally, using explainable AI techniques, this study reveals the contribution of different built environment factors to CHD and identifies the significant factors influencing CHD in cold regions, ranked as age, Digital Elevation Model (DEM), house price (HP), sky view factor (SVF), and interaction factors. Stratified analyses by age and gender show variations in the influencing factors for different groups: for those under 60 years old, Road Density is the most influential factor; for the 61–70 age group, house price is the top factor; for the 71–80 age group, age is the most significant factor; for those over 81 years old, building height is the leading factor; in males, GDP is the most influential factor; and in females, age is the most influential factor. This study explores the feasibility and performance of machine learning in predicting CHD risk in the built environment of cold regions and provides a comprehensive methodology and workflow for predicting cardiovascular disease risk based on refined neighborhood-level built environment factors, offering scientific support for the construction of sustainable healthy cities. Full article

Background: Seminal plasma is an important component of semen and has a significant effect on sperm function. However, the relationship between seminal plasma and sperm freezing capacity has not been fully studied. Purpose: Exploring metabolites and proteins related to the boar sperm freezing capacity in seminal plasma, by metabolomic and proteomic approaches, and directly verifying the protective effect of seminal plasma on the cryopreservation of boar sperm using high and low freezability seminal plasma as base freezing extender. Methods: Semen samples were collected from 30 different boars, 11 high and 11 low freezing-resistant boars were selected after freezing 2~4 times, and seminal plasma was selected at the same time. Sperm motility and movement parameters were analyzed using a CASA system. Reproductive hormones (Testosterone, progesterone, estradiol, prolactin, prostaglandin F2α, luteinoid hormone) in seminal plasma were detected by ELISA. Analysis of proteins and metabolites in high and low freezing-resistant seminal plasma by proteomics and metabolomics techniques. Results: The six reproductive hormones tested were not significantly associated with sperm freezing resistance. A total of 13 differentially expressed metabolites (DEMs) and 38 differentially expressed proteins (DEPs) were identified, while a total of 348 metabolites and 1000 proteins were identified. These DEMs were related to energy metabolism, drugs, or environmental pollutants, while the DEPs were mainly involved in the cytoskeletal dynamics and cell adhesion processes. There were 33 metabolites and 70 proteins significantly associated with mean progress motility (PM) at 10 min and 2 h after thawing. The 70 related proteins were associated with cell division and cycle regulation in gene ontology (GO) terms, as well as KEGG pathways, thermogeneration, and pyruvate metabolism. Using highly freezable boar SP as a base freezing extender made no difference from using lowly freezable boar SP, and both were not as good as the commercial control. Conclusion: There were significant differences in seminal plasma with different freezability, but the similarity was much greater than the difference. The protection effect of seminal plasma is not remarkable, and it does not exhibit superior cryoprotective properties compared to commercial semen cryoelongators. Significance: This study provides a deeper understanding of how seminal plasma composition affects sperm freezabilty. It provides potential biomarkers and targets for improving sperm cryopreservation techniques. Full article