Search Results (201)

Crop row line detection is essential for precision agriculture, supporting autonomous navigation, field management, and growth monitoring. To address the low detection accuracy of rapeseed seedling rows under complex field conditions, this study proposes a detection framework that integrates an improved BiSeNetV2 with a dynamic sliding-window fitting strategy. The improved BiSeNetV2 incorporates the Efficient Channel Attention (ECA) mechanism to strengthen crop-specific feature representation, an Atrous Spatial Pyramid Pooling (ASPP) decoder to improve multi-scale perception, and Depthwise Separable Convolutions (DS Conv) in the Detail Branch to reduce model complexity while preserving accuracy. After semantic segmentation, a Gaussian-filtered vertical projection method is applied to identify crop-row regions by locating density peaks. A dynamic sliding-window algorithm is then used to extract row trajectories, with the window size adaptively determined by the row width and the sliding process incorporating both a lateral inertial-drift strategy and a dynamically adjusted longitudinal step size. Finally, variable-order polynomial fitting is performed within each crop-row region to achieve precise extraction of the crop-row lines. Experimental results indicate that the improved BiSeNetV2 model achieved a Mean Pixel Accuracy (mPA) of 87.73% and a Mean Intersection over Union (MIoU) of 79.40% on the rapeseed seedling dataset, marking improvements of 9.98% and 8.56%, respectively, compared to the original BiSeNetV2. The crop row detection performance for rapeseed seedlings under different environmental conditions demonstrated that the Curve Fitting Coefficient (CFC), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE) were 0.85, 1.57, and 1.27 pixels on sunny days; 0.86, 2.05 and 1.63 pixels on cloudy days; 0.74, 2.89, and 2.22 pixels on foggy days; and 0.76, 1.38, and 1.11 pixels during the evening, respectively. The results reveal that the improved BiSeNetV2 can effectively identify rapeseed seedlings, and the detection algorithm can identify crop row lines in various complex environments. This research provides methodological support for crop row line detection in precision agriculture. Full article

Background: The periodontal pathogen Tannerella forsythia is auxotrophic for muramic acid (MurNAc), a key component of bacterial peptidoglycan, and dependent on an external supply of MurNAc to maintain pure laboratory cultures. The focus of this study was to find a source of muramic acid and peptidoglycan fragments from a Staphylococcus aureus strain. This would facilitate the isolation of T. forsythia by incorporating peptidoglycan into conventional anaerobic media. Methods: The S. aureus strain ATCC 29213 was chosen as the source. The standardization and quantification of the method included verifying concentrations via spectrophotometry and developing a linear regression model with standard curves for muramic acid and lactic acid. The resulting lysate was used to seed Fastidious Anaerobe Agar (FAA) plates, which were inoculated with strain T. forsythia (ATCC 43037) and incubated in an anaerobic chamber for seven days. Results: The resulting lysate had an optical density ranging from 0.061 to 0.083, which corresponds to a muramic acid concentration of approximately 12 µg/mL. Pure cultures of T. forsythia could then be obtained on FAA plates supplemented with muramic acid (MurNAc) (FAA-Mur). The viability of the axenic T. forsythia culture was confirmed using muramic acid/peptidoglycan fragments of microbial origin. Conclusions: The method presented improves the growth of T. forsythia. Consequently, T. forsythia is available for further investigation into the regular performance of sensitivity tests in periodontics and the routine generation of growth curves for quantitative polymerase chain reaction (qPCR) analysis. Full article

In deep coal mining, fault slip-type rockbursts occur frequently. Understanding the shear mechanical properties of bedded coal seams and their intrinsic mechanisms is crucial. This study used PFC^2D7.0 numerical simulation to systematically investigate the shear mechanical behavior and micro-mechanisms of bedded coal under different normal stresses (1, 2, 3, 4 MPa). The research results show that: (1) The shear stress-displacement curves of bedded coal show three stages: elastic rise, strain softening, and residual stability. Both peak and residual shear strengths increase with the rise in normal stress. The peak strength shows nonlinear growth, while the residual strength exhibits a good linear relationship. Higher normal stress significantly reduces the strength reduction rate and effectively inhibits the brittleness of coal. (2) The failure mode consistently manifests as shear failure along the preset weak bedding plane, forming a distinct shear zone. Crack evolution analysis shows that shear cracks within the bedding are the primary form of damage, with minimal contribution from tensile cracks. (3) Force chain analysis shows that an increase in normal stress significantly enhances the density and connectivity of compressive force chains within the shear zone. It also effectively inhibits tensile force chains, with the bedding plane consistently serving as the primary area for stress concentration and transfer. This study provides important theoretical references for understanding the shear instability mechanism of bedded coal, predicting its mechanical response, and preventing fault slip-type rockbursts in deep coal mines. Full article

Accurate plant phenotyping is crucial for gaining a deeper understanding of plant growth patterns and improving yield. However, the segmentation and measurement of 3D phenotypic data in maize remains challenging due to factors such as complex canopy structure, occlusion, and uneven point distribution. To address this, we propose a deep learning network, DUFA-Net, based on dual uncertainty-driven feature aggregation. This method employs a dual uncertainty-driven farthest point sampling (DU-FPS) strategy to mitigate errors caused by uneven point cloud density. Furthermore, for local feature encoding, we designed a Dynamic Feature Aggregation (DFA) module to model neighborhood structures and capture fine-grained geometric features, thereby effectively handling complex canopy structures. Experiments on a self-constructed maize dataset demonstrate that DUFA-Net achieves 95.82% segmentation accuracy and a mean IoU of 92.52%. Based on the segmentation results, six key phenotypic features were accurately extracted, showing high R² values ranging from 0.92 to 0.99. Further evaluation on the Syau Single Maize dataset confirms the generalization capability of the proposed method, achieving 92.52% accuracy and 91.23% mIoU, outperforming five state-of-the-art baselines, including PointNet++, PointMLP, and CurveNet. These results highlight the effectiveness and robustness of DUFA-Net for high-precision organ segmentation and phenotypic trait extraction in complex plant architectures. Full article

This study introduces Cylindrical Scan Context (CSC), a novel LiDAR descriptor designed to improve robustness and efficiency in GPS-denied or degraded outdoor environments. Unlike the conventional Scan Context (SC), which relies on azimuth–range projection, CSC employs an azimuth–height representation that preserves vertical structural information and incorporates multiple physical channels—range, point density, and reflectance intensity—to capture both geometric and radiometric characteristics of the environment. This multi-channel cylindrical formulation enhances descriptor distinctiveness and robustness against viewpoint, elevation, and trajectory variations. To validate the effectiveness of CSC, real-world experiments were conducted using both self-collected coastal–forest datasets and the public MulRan–KAIST dataset. Mapping was performed using LIO-SAM with LiDAR, IMU, and GPS measurements, after which LiDAR-only localization was evaluated independently. A total of approximately 700 query scenes (1 m ground-truth threshold) were used in the self-collected experiments, and about 1200 scenes (3 m threshold) were evaluated in the MulRan–KAIST experiments. Comparative analyses between SC and CSC were performed using Precision–Recall (PR) curves, Detection Recall (DR) curves, Root Mean Square Error (RMSE), and Top-K retrieval accuracy. The results show that CSC consistently yields lower RMSE—particularly in the vertical and lateral directions—and demonstrates faster recall growth and higher stability in global retrieval. Across datasets, CSC maintains superior DR performance in high-confidence regions and achieves up to 45% reduction in distance RMSE in large-scale campus environments. These findings confirm that the cylindrical multi-channel formulation of CSC significantly improves geometric consistency and localization reliability, offering a practical and robust LiDAR-only localization framework for challenging unstructured outdoor environments. Full article

This study investigates the differences in photosynthetic characteristics of Paphiopedilum parishii (Rchb.f.) Stein during its reproductive and nutrient growth periods. Using plants from the same individual, we compared light response curves, chlorophyll content, leaf epidermal structure, and leaf anatomical structure between these two growth stages. The results show the following: (1) The overall shape of the light response curves was similar across both periods, but plants in the nutrient growth period exhibited higher net photosynthetic rates (P_n) at all light intensities compared to those in the reproductive growth period. (2) During the nutrient growth period, apparent quantum efficiency (AQY), maximum net photosynthetic rate (P_max), and light saturation point (LSP) were all significantly higher than in the reproductive growth period, while the light compensation point (LCP) and dark respiration rate (Rd) showed no significant differences. (3) Structurally, during the nutrient growth period, stomatal density significantly increased, while stomatal area decreased. Additionally, leaf thickness and mesophyll tissue thickness both markedly increased, indicating enhanced carbon assimilation efficiency through improved CO₂ uptake capacity and expanded photosynthetic area. (4) Significant differences in leaf anatomical structure between the two periods were primarily observed in leaf thickness and mesophyll tissue thickness, providing more space for energy accumulation during the post-flowering recovery phase. This study systematically reveals the dynamic changes in photosynthetic physiology and structural characteristics of P. parishii across different phenological stages, offering a theoretical foundation for its reintroduction and cultivation management. Full article

Photodynamic inactivation (PDI) represents a promising strategy to overcome bacterial resistance by combining light, oxygen, and a photosensitizer (PS) to generate reactive oxygen species (ROS) that damage essential cellular components. Combining PDI with conventional antibiotics (ATBs) may further enhance bacterial eradication through complementary mechanisms. In this study, the tetracationic 5,10,15,20-tetra(4-N,N,N-trimethylammoniophenyl)porphyrin (TMAP⁴⁺) was evaluated in combination with ATBs: ampicillin (AMP) and rifampicin (RIF) against Staphylococcus aureus and cephalexin (CFX) against Escherichia coli. The photostability of all agents was assessed under the experimental irradiation conditions, and no evidence of physical interaction between TMAP⁴⁺ and the ATBs was detected. AMP and CFX remained photostable, while RIF exhibited only minimal photodegradation under white light, confirming its stability during PDI treatments. The antimicrobial assays revealed that irradiation significantly enhanced the bactericidal activity of TMAP⁴⁺. When combined with ATBs, photoactivated TMAP⁴⁺ led to a pronounced reduction in the minimum inhibitory concentration (MIC) values of AMP and RIF for S. aureus and of CFX for E. coli, indicating additive effects. Growth curve analyses corroborated these results, showing delayed bacterial growth and decreased maximal optical densities in the combined treatments compared to single agents. Overall, these findings demonstrate that the photodynamic process can potentiate the antimicrobial effect of conventional ATBs without compromising their stability, supporting the potential of PS–ATB combination therapies as a valuable approach to improve antibacterial efficacy and mitigate ATB resistance. Full article

Precision spraying is a crucial goal for modern agriculture to achieve water and fertilizer conservation, reduced pesticide use, high yield, and green and sustainable development. This relies on the accurate identification of crop positions, high-precision path planning, and the positioning and control of intelligent agricultural machinery. For the precision production of corn, this paper proposes a new row detection method based on histogram peak detection and sliding window search, avoiding the issues of deep learning methods that are not conducive to lightweight deployment and large-scale promotion. Firstly, green channel segmentation and morphological operations are performed on high-resolution drone images to extract regions of interest (ROIs). Then, the ROIs are converted to a top-view image using perspective transformation, and a histogram analysis is performed using the find_peaks function to detect multiple peaks corresponding to row positions. Furthermore, a sliding window centered around the peak is constructed to search for complete single-row crop pixels in the vertical direction. Finally, the least squares method is used to fit the row curve, estimating the average row spacing (RowGap) and plant spacing (PlantGap) separately. The experimental results show that the accuracy of row detection reaches 93.8% ± 2.1% (n = 60), with a recall rate of 91.5% ± 1.8% and an F1 score of 0.925 ± 0.018. Under different growth stages, row numbers (6–8 rows), and weed interference conditions, the average row spacing measurement error is better than ±2.5 cm, and the plant spacing error is less than ±3.0 cm. Through field verification, this method reduces pesticide use by 23.6% and water consumption by 21.4% compared to traditional uniform spraying, providing important parameter support for field precision planting quality assessment and the dynamic monitoring of planting density, achieving variable irrigation and fertilization and water resource conservation. Full article

Water resources are fundamental to human survival, as well as critical to the sustainable progress of the economy and society. This study selects representative indicators and employs the TOPSIS model to evaluate the water resources carrying capacity (WRCC) in the Chang–Zhu–Tan region (2006–2022). Based on this, kernel density estimation and Moran’s I are applied to analyze the spatiotemporal distribution and evolution trends of WRCC. Additionally, the Lorenz curve, Gini coefficient, and imbalance index are utilized to examine the alignment between WRCC and socio-economic growth. Finally, a system dynamics model is used to simulate WRCC and matching dynamics under different scenarios. The findings reveal the following: (1) The overall WRCC is favorable but exhibits a declining temporal trend, with widening inter-district disparities and strong spatial agglomeration. (2) The match between WRCC and economic development is unbalanced, though alignment has gradually improved over time. (3) The WRCC varies across different scenarios. In current development scenario, WRCC declines significantly. In economic priority development and industrial restructuring scenarios, this reduction is slowed. Specifically, in water resource policy control scenario, WRCC can be enhanced. Aside from the industrial restructuring scenario, all other scenarios contribute to improving the coordination between WRCC and economic development. Full article

Diamond, as an exceptional material with many superior properties, requires a single crystal in a reasonably large size for practical industrial applications. However, achieving large-area single-crystal diamond (SCD) growth without the formation of polycrystalline rims remains challenging. Microwave plasma chemical vapor deposition (MPCVD) using a gas mixture of 10% CH₄-H₂ was used for the homoepitaxial growth of (001) SCD. The effect of nitrogen gas addition in the range of 0–2000 ppm on lateral growth was investigated. Deposition with 180 ppm N₂ over a growth duration of 20 h to reach a thickness of 0.95 mm resulted in significantly enhanced lateral growth without the appearance of a polycrystalline diamond (PCD) rim for the grown diamond, and the total top surface area of SCD increased by an area gain of 1.6 relative to the substrate. The corresponding vertical and lateral growth rates were 47.3 µm/h and 52.5 µm/h, respectively. Characterization by Raman spectroscopy and atomic force microscopy (AFM) revealed uniform structural integrity across the whole surface from the laterally grown regions to the center, including the entire expanded area, in terms of surface morphology and crystalline quality. Moreover, measurements of the etch pit densities (EPDs) showed a substantial reduction in the laterally grown regions, approximately an order of magnitude lower than those in the central region. The high quality of the homoepitaxial diamond layer was further verified with (004) X-ray rocking curve analysis, showing a narrow full width at half maximum (FWHM) of 11 arcsec. Full article

To investigate the photosynthetic characteristics and leaf anatomical structures of seedlings from the endangered plants Ormosia olivacea, Ormosia pachycarpa, and Ormosia sericeolucida, this study aimed to elucidate the influence of leaf structure on photosynthetic traits and light requirements among these three Ormosia species, thereby providing reference for their introduction and cultivation. This study measured the light response curves, CO₂ response curves, leaf epidermal and anatomical characteristics, and photosynthetic pigment content of the three Ormosia species. Results indicate: 1. All three species exhibit photophilic tendencies, with Ormosia olivacea demonstrating the highest photosynthetic capacity, achieving a maximum net photosynthetic rate (Pmax) of 1.9062 mol m⁻² s⁻¹. Ormosia pachycarpa exhibited the highest potential maximum net photosynthetic rate (Amax), demonstrating superior CO₂ utilisation capacity. The Amax values for all three species were significantly higher than their Pmax values. 2. Among the three Ormosia species, Ormosia sericeolucida exhibited the thickest leaf structure, with palisade tissue thickness ordered as follows: Ormosia sericeolucida > Ormosia pachycarpa > Ormosia olivacea. 3. Stomata were present on the lower epidermis of all three species. Ormosia sericeolucida possessed the largest individual stomatal area, while Ormosia olivacea exhibited the highest stomatal density. 4. The chlorophyll a content (Chl a) of all three Ormosia species exceeded their chlorophyll b content (Chl b), indicating they are photophilic plants. Ormosia sericeolucida exhibited higher chlorophyll a (Chl a), chlorophyll b (Chl b), and total chlorophyll (Chl) contents than both Ormosia olivacea and Ormosia pachycarpa. Ormosia olivacea possessed the highest carotenoid content (Car). In summary, Ormosia pachycarpa exhibited the highest potential maximum net photosynthetic rate (Amax), demonstrating the strongest CO₂ utilisation capacity, followed by Ormosia olivacea, with Ormosia sericeolucida showing the lowest. Appropriately increasing CO₂ levels in cultivation sites would benefit photosynthesis and material accumulation in all three Ormosia species, promoting robust growth. Full article

As a multi-ethnic border region of China, Xinjiang hosts revolutionary cultural tourism resources (RCTRs) that embody historical memory and the spirit of frontier reclamation, while also playing a strategic role in strengthening national identity and maintaining regional stability. Yet, their spatial distribution is highly uneven due to geographical, historical, and socio-economic constraints. This study analyzes 135 representative sites using a dual framework of spatial pattern analysis and driving mechanism quantification. Nearest neighbor index, imbalance index, Lorenz curve, geographic concentration index, kernel density estimation, and hotspot analysis results reveal a clustered “multi-core–peripheral attenuation” pattern with pronounced regional disparities. GIS-based overlay analysis identifies natural thresholds of moderate elevation (834–2865 m) and gentle slopes (0–8.65°), while socio-economic factors such as transportation corridors and population density amplify clustering effects. Geographic Detector results confirm road network density (q = 0.85, p < 0.01) and historical site density (q = 0.79, p < 0.01) as dominant drivers, with interactions between natural and social factors enhancing explanatory power above 0.90. These findings highlight the coupled influence of topographic suitability and socio-economic accessibility. Policy recommendations include optimizing road network layouts, adopting tiered heritage protection, and fostering cross-regional cooperation. The study provides scientific evidence for balanced development and sustainable conservation of RCTRs, contributing to the achievement of sustainable development goals (SDGs) related to cultural heritage, regional equity, and inclusive growth. Full article

Background/Objectives: Transferrin is a multi-task protein commonly known for binding iron; however, it is involved in multiple crucial processes, including antimicrobial activity, the growth of different cell types, differentiation, chemotaxis, the cell cycle, and cytoprotection. Vascular cell adhesion molecule 1 (VCAM-1) is a cell surface glycoprotein which participates in inflammation and the trans-endothelial movement of leukocytes. Neither transferrin nor VCAM-1 has been studied in the context of progressive supranuclear palsy (PSP) or corticobasal syndrome (CBS). This study aimed to evaluate the utility of transferrin and VCAM-1 assessment for the in vivo examination of tauopathic atypical Parkinsonian syndromes. Methods: This study included 10 patients with clinically probable PSP-RS, 10 with clinically probable PSP-P, and 8 with probable CBS. Patients’ blood and urine were collected and analyzed. Twenty-four serum samples (from twelve males and twelve females) were obtained from age-matched healthy volunteers. Peripheral blood inflammatory ratios, including the neutrophil-to-lymphocyte ratio, the platelet-to-lymphocyte ratio, the neutrophil-to-monocyte ratio, the neutrophil-to-high-density lipoprotein ratio, and the monocyte-to-high-density lipoprotein ratio, were calculated. VCAM-1 and transferrin concentrations were measured in the serum and urine. The urinary biomarker results are not included in the main analysis due to the absence of a control group. Results: The highest concentrations of transferrin in the serum were observed in patients with PSP-P, followed by PSP-RS and CBS. Statistically significant differences were found between PSP-P and healthy controls (p < 0.0001) and PSP-RS and healthy controls (p < 0.0001). The highest levels of serum VCAM-1 were observed in the PSP-P group. Significant differences were found between PSP-P and healthy controls (p < 0.0001), PSP-P and CBS (p < 0.001), and PSP-RS and healthy controls (p < 0.001). Serum VCAM-1 levels were negatively correlated with the NLR in CBS patients (p < 0.03; r = −0.74). Serum transferrin levels were negatively correlated with the NHR in CBS patients (p < 0.04; r = −0.64). ROC curve analyses were conducted to evaluate the diagnostic utility of serum transferrin and VCAM-1 in distinguishing tauopathic APS patients from controls. Transferrin showed excellent diagnostic performance, with an AUC of 0.975 (95% CI: 0.888–0.999; p < 0.0001), a sensitivity of 96.4%, and a specificity of 95.8% at the optimal cut-off (>503.0). VCAM-1 demonstrated good accuracy, with an AUC of 0.839 (95% CI: 0.711–0.926; p < 0.0001), a sensitivity of 75.0%, and a specificity of 91.7% at the optimal cut-off (>463.9). Conclusions: The obtained results indicate the potential role of transferrin and VCAM-1 in the pathogenesis of tauopathic APSs and highlight the need for further exploration in this field. Full article

To analyze the dynamic response of tension leg platform (TLP) tendons under irregular ocean wave action, the governing equations of coupled vibration between the platform and tendon under irregular wave action are established based on Hamilton’s principle and the Kirchhoff hypothesis. Using the spectrum representation–random function method, the power spectral density function of the irregular wave load is derived, and the lateral wave forces at different tendon locations are calculated. The coupled lateral and axial responses of the tendon system are obtained through the fourth-order Runge–Kutta method. Considering the parametric vibrations of both the platform and tendon, the extreme lateral deflection of the tendon is employed as the control index to derive the probability density curves of the tendon deflection under irregular wave load. The results show that the amplitude of the wave load increases gradually along the height of the tendon, with a faster growth rate at locations closer to the water surface. The tendon’s lateral deflection response changes more drastically due to coupled parametric vibration of the platform. Based on 628 complete samples of irregular wave loads, the probability density curve and cumulative distribution curve of the extreme lateral deflection of the tendon under irregular wave loads are obtained. Under typical sea state conditions generated from the P-M wave spectrum, the reliability of the tendon under irregular wave load increases with the initial tension force. Full article

This study investigates the relationship between economic growth and energy consumption using the Energy Kuznets Curve (EKC) framework. Spatial econometric models, including the Spatial Panel Lag Model and the Spatial Dynamic Panel Lag IV Model, are employed to capture both spatial and dynamic effects. The results indicate that energy consumption in Thailand is spatially clustered, with energy use tending to spill over into neighboring provinces and concentrating in specific regions. Key factors that positively influence energy consumption include gross provincial product (GPP) per capita, population density, and road density. Regions characterized by favorable climates, sufficient infrastructure, and high levels of economic activity exhibit higher per capita energy consumption. The EKC analysis reveals a U-shape relationship between GPP per capita and energy consumption in the BKK&VIC, CE, EA, WE, and NE regions. As many regions continue to experience rising energy consumption, the findings underscore the importance of Thailand adopting more efficient energy usage strategies in tandem with its economic development. Full article