Search Results (74,017)

In the field of hyperspectral image classification, deep learning technology, especially convolutional neural networks, has achieved remarkable progress. However, convolutional neural network models encounter challenges in hyperspectral image classification due to limitations in their receptive fields. Conversely, the global modeling capability of Transformers has garnered attention in hyperspectral image classification. Nevertheless, the high computational cost and inadequate local feature extraction hinder its widespread application. In this study, we propose a novel fusion model of convolutional neural networks and Transformers to enhance performance in hyperspectral image classification, namely the dual-branch multi-granularity convolutional cross-substitution Transformer (DMCCT). The proposed model adopts a dual-branch structure to separately extract spatial and spectral features, thereby mitigating mutual interference and information loss between spectral and spatial data during feature extraction. Moreover, a multi-granularity embedding module is introduced to facilitate multi-scale and multi-level local feature extraction for spatial and spectral information. In particular, the improved convolutional cross-substitution Transformer module effectively integrates convolution and Transformer, reducing the complexity of attention operations and enhancing the accuracy of hyperspectral image classification tasks. Subsequently, the proposed method is evaluated against existing approaches using three classical datasets, namely Pavia University, Kennedy Space Center, and Indian Pines. Experimental results demonstrate the efficacy of the proposed method, achieving significant classification results on these datasets with overall classification accuracies of 98.57%, 97.96%, and 96.59%, respectively. These results establish the superiority of the proposed method in the context of hyperspectral image classification under similar experimental conditions. Full article

Visual quality inspection of part surfaces is a crucial step in industrial production. Image edge detection is a common technique for assessing the surface conditions of parts. However, current methods have limitations, including poor noise filtering, low adaptability, and inadequate accuracy of edge detection. To overcome these challenges, this study proposes an adaptive edge detection method for part images using selective processing. Firstly, this method divides the input image into noise, edge, and noise-free blocks, followed by selective mixed filtering to remove noise while preserving original image details. Secondly, a four-parameter adaptive selective edge detection algorithm model is constructed, which adaptively adjusts parameter values based on image characteristics to address issues of missing edges and false detections, thereby enhancing the adaptability and accuracy of the method. Moreover, by comparing and adjusting the four parameter values, different edge information can be selectively detected, enabling rapid acquisition of desired edge detection results and improving detection efficiency and flexibility. Experimental results demonstrated that the proposed method outperformed existing classical techniques in both subjective and objective evaluations, maintaining stable detection under varying noise conditions. Thus, this method was validated for its effectiveness and stability, enhancing production efficiency in manufacturing processes of parts. Full article

Serine/arginine-rich (SR) proteins mostly function as splicing factors for pre-mRNA splicing in spliceosomes and play critical roles in plant development and adaptation to environments. However, detailed study about SR proteins in legume plants is still lacking. In this report, we performed a genome-wide investigation of SR protein genes in wild soybean (Glycine soja) and identified a total of 31 GsSR genes from the wild soybean genome. The analyses of chromosome location and synteny show that the GsSRs are unevenly distributed on 15 chromosomes and are mainly under the purifying selection. The GsSR proteins can be phylogenetically classified into six sub-families and are conserved in evolution. Prediction of protein phosphorylation sites indicates that GsSR proteins are highly phosphorylated proteins. The protein–protein interaction network implies that there exist numerous interactions between GsSR proteins. We experimentally confirmed their physical interactions with the representative SR proteins of spliceosome-associated components such as U1-70K or U2AF35 by yeast two-hybrid assays. In addition, we identified various stress-/hormone-responsive cis-acting elements in the promoter regions of these GsSR genes and verified their expression patterns by RT-qPCR analyses. The results show most GsSR genes are highly expressed in root and stem tissues and are responsive to salt and alkali stresses. Splicing analysis showed that the splicing patterns of GsSRs were in a tissue- and stress-dependent manner. Overall, these results will help us to further investigate the biological functions of leguminous plant SR proteins and shed new light on uncovering the regulatory mechanisms of plant SR proteins in growth, development, and stress responses. Full article

In order to alleviate the shortage of water in Xinjiang cotton fields, to ensure the sustainable development of the cotton industry in southern Xinjiang, it is necessary to determine a suitable “dry sowing and wet emergence” water quantity plan for cotton fields in southern Xinjiang to change the current situation. In this study, to explore the irrigation regime of “dry sowing and wet emergence” for cotton in Korla, Xinjiang, by combining field experiments and modeling simulations, the effects of different irrigation amounts on the water–heat–salt and seedling emergence characteristics of “dry sowing and wet emergence” cotton fields were investigated; the soil, water, and salt transport under different irrigation regimes was simulated by using HYDRUS-2D, and the seedling emergence rate of the cotton under different irrigation regimes was obtained through the establishment of a regression model. The results indicated that, in the field experiment, the soil water content of the 0−40 cm soil layer showed an overall trend of first increasing and then decreasing with time, while the soil salt content showed an overall trend of first decreasing and then increasing over time. The soil water content at the drip heads and cotton rows position, as well as on the 15th day, increased by an average of 5.58 cm³·cm⁻³ compared to before irrigation, and the soil salt content decreased by an average of 2.74 g/kg compared to before irrigation. In the irrigation water range of 675−825 m³/hm², reducing the irrigation water amount increased the cotton emergence rate by 3.86% and the cotton vigor index by 70.53%. After the model simulation, it is recommended to choose the cotton “dry sowing and wet emergence” irrigation regime with a low to medium water amount (300−450 m³/hm²) at 14-day intervals or a low to medium water amount (300−375 m³/hm²) at 7-day intervals, which can obtain a higher seedling emergence rate. Full article

Aqueous zinc-ion batteries (AZIBs) have become a promising and cost-effective alternative to lithium-ion batteries due to their low cost, high energy, and high safety. However, dendrite growth, hydrogen evolution reactions (HERs), and corrosion significantly restrict the performance and scalability of AZIBs. We propose the introduction of a BaTiO₃ (BTO) piezoelectric polarized coating as an interface modification strategy for ZIBs. The low surface energy of the BTO (110) crystal plane ensures its thermodynamic preference during crystal growth in experimental processes and exhibits very low reactivity toward oxidation and corrosion. Calculations of interlayer coupling mechanisms reveal a stable junction between BTO (110) and Zn (002), ensuring system stability. Furthermore, the BTO (110) coating also effectively inhibits HERs. Diffusion kinetics studies of Zn ions demonstrate that BTO effectively suppresses the dendrite growth of Zn due to its piezoelectric effect, ensuring uniform zinc deposition. Our work proposes the introduction of a piezoelectric material coating into AZIBs for interface modification, which provides an important theoretical perspective for the mechanism of inhibiting dendrite growth and side reactions in AZIBs. Full article

Some basic aspects of plant disease epidemiology remain largely unknown due to a lack of empirical study methods to experimentally manipulate the position of infections within a single plant or within a plant canopy and the dispersal behaviors of small insects that vector important plant diseases, for example. We present two methods using UV fluorescent particles that, when mixed in a 10% ethanol solution, can be used to create surrogate fungal infections on plant leaves and to field mark whiteflies in situ. When we used a custom-made experimental chamber to measure the velocity of falling particles, we found that the UV fluorescent particles had settlement velocities that overlapped with known fungal plant pathogen spores. In a separate experiment, field applied marks to whiteflies, Bemisia tabaci, were used to estimate straight-line insect vector displacement from source plants as a simple dispersal gradient over a limited distance in a 48 h period. The UV fluorescent particles and airbrushes were relatively inexpensive (USD < 100 total), easily sourced, and usable in a field setting. We believe that the approaches and methods shared in this manuscript can be used to design specific experiments that will fill important plant epidemiological knowledge gaps in future studies. Full article

Sediment transport is a geophysical phenomenon characterized by the displacement of sediment particles in both the horizontal and vertical directions due to various forces. Most of the sediment transport equations currently used include only parameters related to the horizontal direction. This study measured both instantaneous longitudinal and vertical parameters, i.e., velocities and forces, and found that the magnitude and direction of the vertical force play an important role in sediment incipient motion. An innovative experimental system was developed to investigate the effect of vertical force on incipient motion in rapidly varying flows. A quadrant analysis of the instantaneous measured forces on the critical shear stress was performed. The research revealed that upward positive vertical forces enhance particle mobility, whereas downward negative vertical forces increase particle stability. Novel equations have been developed to represent the influence of vertical forces on sediment transport. A comprehensive critical Shields stress for sediment transport was proposed, extending the Classic Shields diagram to encompass the incipient motion in highly unsteady flows. Full article

Triphenyltin (TPT) is a commonly encountered organotin compound known for its endocrine-disrupting properties; it frequently interacts with antibiotics in aquatic environments. In this study, common carp (Cyprinus carpio) (17.43 ± 4.34 g, 11.84 ± 0.88 cm) were chosen as the experimental organisms. According to the environmental concentration in the heavily polluted area, the control group and the experimental groups were exposed for 21 days to the following treatments: 1 μg/L TPT, 1 mg/L NOR, and a combination of 1 μg/L TPT plus 1 mg/L NOR. The investigation examined the individual and combined toxicities of TPT and norfloxacin (NOR) on the gill, liver, and gut tissues of common carp in highly polluted areas. The findings revealed tissue-specific variations in 1L-1β enzyme activity; specifically, 1L-1β enzyme activity exhibited a significant reduction in liver tissue under both NOR exposure and combined exposure, indicating that high concentrations of NOR had the most pronounced impact on the immune system of liver tissue. Furthermore, the gene expression levels of IL-1β, Lysozyme-C, NKA, and CPT1 in the liver, intestinal, and gill tissues showed differences after exposure. In addition, TPT exerted the most significant effect on intestinal tissue, followed by the liver and gill tissues. Interestingly, when TPT and NOR were exposed together, the toxic effects on all tissues were reduced, suggesting the existence of antagonistic effects. Full article

The multi-scale representation of remote sensing images is crucial for information extraction, data analysis, and image processing. However, traditional methods such as image pyramid and image filtering often result in the loss of image details, particularly edge information, during the simplification and merging processes at different scales and resolutions. Furthermore, when applied to coastal landforms with rich texture features, such as biologically diverse areas covered with vegetation, these methods struggle to preserve the original texture characteristics. In this study, we propose a new method, multi-scale expression of coastal landforms considering texture features (METF-C), based on computer vision techniques. This method combines superpixel segmentation and texture transfer technology to improve the multi-scale representation of coastal landforms in remote sensing images. First, coastal landform elements are segmented using superpixel technology. Then, global merging is performed by selecting different classes of superpixels, with boundaries smoothed using median filtering and morphological operators. Finally, texture transfer is applied to create a fusion image that maintains both scale and level consistency. Experimental results demonstrate that METF-C outperforms traditional methods by effectively simplifying images while preserving important geomorphic features and maintaining global texture information across multiple scales. This approach offers significant improvements in edge preservation and texture retention, making it a valuable tool for analyzing coastal landforms in remote sensing imagery. Full article

Power transformers play a vital role in adjusting voltage levels during transmission. This study focuses on optimizing the structural design of power transformer tanks, particularly high-voltage (HV) tank walls, to enhance their mechanical robustness, performance, and operational reliability. This research investigates various stiffener designs and their impact on stress distribution and deformation through finite element analysis (FEA). Ten different configurations of stiffeners, including thickness, width, type, and position variations, were evaluated to identify the optimal design that minimizes stress and deflection while considering weight constraints. The results indicate that specific configurations, particularly those incorporating 16 mm thick H beams, significantly enhance structural integrity. Experimental validation through pressure testing corroborated the simulation findings, ensuring the practical applicability of the optimized designs. This study’s findings have implications for enhancing the longevity and reliability of power transformers, ultimately contributing to more efficient and resilient power transmission systems. Full article

Hydroxyapatite (HA, Ca₁₀(PO₄)₆(OH)₂) composite coatings added in the second phase could improve the mechanical properties and bonding strength. The cold spraying technique, as a technology for the deposition of solid particles at low temperatures, is employed to deposit HA ceramic composite coatings. The nano HA material possesses characteristics that enhance properties and promote interface bonding. Due to the exceptional mechanical properties of Ti material, adding Ti particles could improve the mechanical properties of nano HA/Ti composite coatings. In order to explore the deposition deformation mechanism of composite particles under different cold spraying conditions, numerical simulation and experimental testing of deposition behaviors of dual nano HA/Ti composite particles were analyzed. As the particle velocity increased from 400 m/s to 800 m/s in the numerical simulation analysis, the more serious the deposition deformation. Meanwhile, more cracking and splashing phenomena occurred on the surface of the particle. By analyzing the stress value curve of Ti and HA units under different particle velocities, it was found that the adiabatic shear instability phenomenon occurred during the particle deposition on the substrate. In addition, the degree of particle deformation increased with the decrease in the particle size. The results of the experimental investigation were consistent with that of the numerical simulation. Full article

The distorted spots induced by atmospheric turbulence significantly degrade the spot position detection accuracy of the quadrant detector (QD). In this paper, we utilize angular measurement and homogenization characteristics of non-imaging microlens array (NI-MLA) systems, effectively reducing the distortion degree of the spots received on the QD target surface, thereby significantly enhancing the spot detection accuracy of the QD. First, based on the principles of geometric optics and Fourier optics, it is proved that the NI-MLA system possesses the angular measurement characteristic (AMC) within the paraxial region while deriving and verifying the focal length of the system. Then, the QD computation curve characteristics of the system under non-turbulence are explored. This study further elucidates the mathematical principle of the NI-MLA system for mitigating the spot position detection random error of QD (SPDRE-QD) and discusses in depth the relationship between the NI-MLA system’s capability to mitigate the SPDRE-QD and the system’s parameters under various turbulence intensities. Finally, it is experimentally verified that the root-mean-square error (RMSE) of the QD computation values using the NI-MLA system are reduced by a significant improvement of at least 2.44 times and up to 17.36 times compared with that of the conventional optical system of QD (COS-QD) under turbulence conditions ranging from weak to strong. Full article

Artificial light at night (ALAN), also known as light pollution, is a growing environmental problem worldwide. However, only a few studies have examined whether soil organisms that search for food at the surface at night can be affected by ALAN. We investigated the effects of ALAN on the above-ground foraging activity of anecic earthworms (Lumbricus terrestris), on the soil water infiltration and on the germination and growth of a cover crop (Phacelia tanacetifolia). In a full-factorial greenhouse experiment, we tested four factors: ALAN (about 5 lx during the night vs. total darkness), earthworms (two specimens vs. none), plant species (Phacelia alone vs. mixed with ragweed Ambrosia artemisiifolia) and sowing depth (surface-sown vs. sown in 5 cm depth). Data were analysed using multifactorial ANOVAs. Earthworms removed 51% less surface litter under ALAN than under dark conditions. ALAN had no effect on Phacelia germination but resulted in increased height growth and biomass production when the seeds were buried. Earthworms reduced Phacelia germination and biomass production. ALAN reduced water leaching through the experimental units, probably due to interactions between the subsurface casts and plant roots. We conclude that ALAN, as emitted from streetlights, can lead to complex ecological effects in ecosystems that merit further investigation. Full article

Aiming at the problems of small stems and irregular contours of bitter gourd, which lead to difficult and inaccurate location of picking points in the picking process of mechanical arms, this paper proposes an improved YOLOv5-seg instance segmentation algorithm with a coordinate attention (CA) mechanism module, and combines it with a refinement algorithm to identify and locate the picking points of bitter gourd. Firstly, the improved algorithm model was used to identify and segment bitter gourd and melon stems. Secondly, the melon stem mask was extracted, and the thinning algorithm was used to refine the skeleton of the extracted melon stem mask image. Finally, a skeleton refinement graph of bitter gourd stem was traversed, and the midpoint of the largest connected region was selected as the picking point of bitter gourd. The experimental results show that the prediction precision (P), precision (R) and mean average precision (mAP) of the improved YOLOv5-seg model in object recognition were 98.04%, 97.79% and 98.15%, respectively. Compared with YOLOv5-seg, the P, R and mA values were increased by 2.91%, 4.30% and 1.39%, respectively. In terms of object segmentation, mask precision (P(M)) was 99.91%, mask recall (R(M)) 99.89%, and mask mean average precision (mAP(M)) 99.29%. Compared with YOLOv5-seg, the P(M), R(M), and mAP(M) values were increased by 6.22%, 7.81%, and 5.12%, respectively. After testing, the positioning error of the three-dimensional coordinate recognition of bitter gourd picking points was X-axis = 7.025 mm, Y-axis =5.6135 mm, and Z-axis = 11.535 mm, and the maximum allowable error of the cutting mechanism at the end of the picking manipulator was X-axis = 30 mm, Y-axis = 24.3 mm, and Z-axis = 50 mm. Therefore, this results of study meet the positioning accuracy requirements of the cutting mechanism at the end of the manipulator. The experimental data show that the research method in this paper has certain reference significance for the accurate identification and location of bitter gourd picking points. Full article

Background: Alzheimer’s disease is a slowly progressing neurodegenerative illness and the most common form of dementia. This pathology leads to an increase in cognitive decline and is responsible, in patients, for several difficulties in performing various activities of daily living, such as oral hygiene. Several experimental studies have shown that oral health in patients with Alzheimer’s disease worsens in direct proportion to the progression of the disease due to the appearance of gingivitis and periodontitis. Methods: This clinical literature review aims to evaluate a possible correlation between periodontal disease and Alzheimer’s disease, trying to understand if the periopathogens can contribute to the onset or the progression of Alzheimer’s disease (AD). The study was conducted on the database PubMed (MEDLINE) of full-text systematic reviews in English on humans and animals that were published in the last five years, from 2018 to 2023. This returned 50 publications, which, once the eligibility criteria were applied, resulted in the 10 publications examined in this review. The selected articles were organized through the construction of tables, analyzed, and compared through Judith Garrard’s Matrix method to arrive at the review results. Results: Infection by periopathogens can increase the risk of developing Alzheimer’s disease, but also the onset of the latter can make it more difficult to maintain proper oral hygiene, favoring the onset of periodontal disease: it is possible to affirm the existence of a correlation between periodontitis and AD. It was found that patients exposed to chronic periodontitis have a greater risk of developing a cognitive decline or AD and that oral pathogens can be responsible for neuropathologies and increasing systemic inflammation. Conclusions: Periodontitis and periodontal pathogens represent a real risk factor for the onset or worsening of AD; however, the pathogenetic mechanism is still not completely clear. Full article