Search Results (43)

We report calculations of charging effect on an isolated conductor, gold nanosphere, under electron beam bombardment at primary electron energies of 0.1–10 keV based on an up-to-date Monte Carlo simulation method. The calculations consider electron flow in sample, in which the electron yield is almost equivalent to the case when the electron flow is not considered. The electron yields and charging spatial distribution are obtained. For comparison, the calculation for bulk conductor is also performed, for which the time average of electric potential is found to reproduce the law of electrostatics. Full article

Formation MicroScanner Image (FMI) technology is a key method for identifying fractured reservoirs and optimizing oil and gas exploration, but its inherent insufficient resolution severely constrains the fine characterization of geological features. This study innovatively applies a Super-Resolution Generative Adversarial Network (SRGAN) to the super-resolution reconstruction of FMI logging image to address this bottleneck problem. By collecting FMI logging image of glutenite from a well in Xinjiang, a training set containing 24,275 images was constructed, and preprocessing strategies such as grayscale conversion and binarization were employed to optimize input features. Leveraging SRGAN’s generator-discriminator adversarial mechanism and perceptual loss function, high-quality mapping from low-resolution FMI logging image to high-resolution images was achieved. This study yields significant results: in RGB image reconstruction, SRGAN achieved a Peak Signal-to-Noise Ratio (PSNR) of 41.39 dB, surpassing the optimal traditional method (bicubic interpolation) by 61.6%; its Structural Similarity Index (SSIM) reached 0.992, representing a 34.1% improvement; in grayscale image processing, SRGAN effectively eliminated edge blurring, with the PSNR (40.15 dB) and SSIM (0.990) exceeding the suboptimal method (bilinear interpolation) by 36.6% and 9.9%, respectively. These results fully confirm that SRGAN can significantly restore edge contours and structural details in FMI logging image, with performance far exceeding traditional interpolation methods. This study not only systematically verifies, for the first time, SRGAN’s exceptional capability in enhancing FMI resolution, but also provides a high-precision data foundation for reservoir parameter inversion and geological modeling, holding significant application value for advancing the intelligent exploration of complex hydrocarbon reservoirs. Full article

To achieve an efficient, non-destructive, and intelligent identification of tea plant seedlings under high-temperature stress, this study proposes an improved YOLOv11 model based on chlorophyll fluorescence imaging technology for intelligent identification. Using tea plant seedlings under varying degrees of high temperature as the research objects, raw fluorescence images were acquired through a chlorophyll fluorescence image acquisition device. The fluorescence parameters obtained by Spearman correlation analysis were found to be the maximum photochemical efficiency (Fv/Fm), and the fluorescence image of this parameter is used to construct the dataset. The YOLOv11 model was improved in the following ways. First, to reduce the number of network parameters and maintain a low computational cost, the lightweight MobileNetV4 network was introduced into the YOLOv11 model as a new backbone network. Second, to achieve efficient feature upsampling, enhance the efficiency and accuracy of feature extraction, and reduce computational redundancy and memory access volume, the EUCB (Efficient Up Convolution Block), iRMB (Inverted Residual Mobile Block), and PConv (Partial Convolution) modules were introduced into the YOLOv11 model. The research results show that the improved YOLOv11-MEIP model has the best performance, with precision, recall, and mAP50 reaching 99.25%, 99.19%, and 99.46%, respectively. Compared with the YOLOv11 model, the improved YOLOv11-MEIP model achieved increases of 4.05%, 7.86%, and 3.42% in precision, recall, and mAP50, respectively. Additionally, the number of model parameters was reduced by 29.45%. This study provides a new intelligent method for the classification of high-temperature stress levels of tea seedlings, as well as state detection and identification, and provides new theoretical support and technical reference for the monitoring and prevention of tea plants and other crops in tea gardens under high temperatures. Full article

The root parasitic weed Phelipanche aegyptiaca (Pers.) Pomel poses a serious threat to solanaceous crops, leading to yield losses of up to 80% in tomato (Solanum lycopersicum L.). Strigolactones (SLs), derived from the carotenoid metabolic pathway, serve as key host-recognition signals for root-parasitic plants. This study investigated the molecular mechanisms of host resistance, focusing on the suppression of SL biosynthesis through altered carotenoid metabolism in the high-pigment tomato mutants hp-1 and og^c. Both pot experiment and in vitro seed germination assays demonstrated that the mutants exhibited reduced susceptibility to P. aegyptiaca and triggered lower germination rates in broomrape seeds compared to the wild-type cultivar AC. Quantitative RT-PCR analysis revealed a significant downregulation of SL biosynthesis genes (SlD27, SlCCD7, SlCCD8, SlMAX1, SlP450, SlDI4) in hp-1 at various parasitic stages post-inoculation, with a more pronounced suppression observed in hp-1 than in og^c. Notably, the extent of downregulation correlated with the enhanced resistance phenotype in hp-1. These findings highlight a synergistic resistance mechanism involving the coordinated regulation of carotenoid metabolism and SL biosynthesis, providing new insights into the molecular defense network underlying tomato-broomrape interactions. Full article

Tomato chlorosis virus (ToCV) is an emerging plant virus that poses a substantial threat to the cultivation of economically vital vegetable crops, particularly tomato (Solanum lycopersicum). Despite its substantial impact on crop yield, resistant or tolerant tomato germplasms have not been well documented, and the genetic basis of resistance to ToCV remains poorly understood. In this study, two wild accessions that were immune to ToCV and five accessions that were highly resistant to ToCV were identified from 58 tomato accessions. Additionally, a novel method was developed for evaluating resistance to ToCV in tomatoes, and it was observed that tomatoes exhibited typical pathological features on days 15 and 30 after ToCV inoculation, referred to as Stage 1 and Stage 2, respectively. Using quantitative trait locus (QTL) sequencing in conjunction with classical QTL approaches, ToCV resistance loci were identified in two F2 populations derived from the crosses between SG11 (susceptible) and LA1028 (resistant) and between SP15 (susceptible) and LA0444 (resistant). Genetic analysis indicated that resistance to ToCV in the wild-type ToCV-resistant tomato accessions LA1028 and LA0444 was quantitative and mainly governed by four loci (Qtc1.1 and Qtc11.1 from LA1028 and Qtc7.1 and Qtc9.1 from LA0444). Subsequently, transcriptome analysis of three resistant accessions (LA2157, LA0444, and LA1028) and two susceptible accessions (SG11 and SP15) revealed unique differentially expressed genes and specific biological processes in the two stages of ToCV infection. This study provides new resistant germplasms and potential genetic resources for ToCV resistance, which can be valuable in tomato molecular breeding programs in obtaining resistant varieties. Full article

Pigs serve as a mixing vessel for influenza viruses and can independently promote the emergence of pandemic strains in humans. During our surveillance of pig populations from 2021 to 2023 in China, 11 H1 subtype swine influenza viruses (SIVs) were isolated. All viruses were reassortants, possessing internal genes of identical origins (PB2, PB1, PA, NP, M: pdm09/H1N1 origin, NS: North American triple reassortant origin). The H1N1 isolates were all the dominant G4 EA H1N1 viruses in China. Two H1N2 isolates carried early human pdm09/H1N1 HA genes, suggesting a possible pig-to-human transmission route. Mutations that dictate host range specificity were identified in all isolates, a phenomenon which may enhance the affinity to human receptors. These H1 subtype viruses effectively replicated both in vivo and in vitro without prior adaptation and exhibited different pathogenicity and growth characteristics. Some of the H1 viruses were even found to cause lethal infections in mice. Taken together, our study indicates that the H1 subtype SIVs recently circulating in China pose a potential threat to human health and emphasizes the importance of continuing to closely monitor their evolution and spread. Full article

Late blight is a destructive disease affecting tomato production. The identification and characterization of resistance (R) genes are critical for the breeding of late blight-resistant cultivars. The incompletely dominant gene Ph-2 confers resistance against the race T₁ of Phytophthora infestans in tomatoes. Herein, we identified Solyc10g085460 (RGA1) as a candidate gene for Ph-2 through the analysis of sequences and post-inoculation expression levels of genes located within the fine mapping interval. The RGA1 was subsequently validated to be a Ph-2 gene through targeted knockout and complementation analyses. It encodes a CC-NBS-LRR disease resistance protein, and transient expression assays conducted in the leaves of Nicotiana benthamiana indicate that Ph-2 is predominantly localized within the nucleus. In comparison to its susceptible allele (ph-2), the transient expression of Ph-2 can elicit hypersensitive responses (HR) in N. benthamiana, and subsequent investigations indicate that the structural integrity of the Ph-2 protein is likely a requirement for inducing HR in this species. Furthermore, ethylene and salicylic acid hormonal signaling pathways may mediate the transmission of the Ph-2 resistance signal, with PR1- and HR-related genes potentially involved in the Ph-2-mediated resistance. Our results could provide a theoretical foundation for the molecular breeding of tomato varieties resistant to late blight and offer valuable insights into elucidating the interaction mechanism between tomatoes and P. infestans. Full article

Background/Objectives: Leflunomide, an isoxazole immunosuppressant, is widely used in the treatment of diseases such as rheumatoid arthritis (RA) and psoriatic arthritis (PsA) as well as lupus nephritis (LN). In recent years, clinical data have shown that some patients have obvious weight loss, liver injury, and other serious adverse reactions after taking leflunomide. However, the causes and mechanisms by which leflunomide reduces weight are unclear. Methods: Therefore, we used a mouse animal model to administer leflunomide, and we observed that the weight of mice in the leflunomide experimental group was significantly reduced (p < 0.01). In this animal experiment, a metabolomic method was used to analyze the livers of the mice in the experimental group and found that the main difference in terms of metabolic pathways was in the metabolism of aromatic amino acids, and it was confirmed that leflunomide can inhibit the limitations of phenylalanine, tyrosine, and tryptophan biosynthesis. Results: Our study revealed that leflunomide inhibited the activity of DAHPS in the gut microbiota, disrupting the metabolism of phenylalanine, tyrosine, and tryptophan, as well as the metabolism of carbohydrates and lipids. Leflunomide also increased endoplasmic reticulum stress by activating the PERK pathway, thereby promoting CHOP expression and increasing apoptosis-induced liver damage. Conclusions: These effects may be related to the observed weight loss induced by leflunomide. Full article

Pest infestations in tea gardens are one of the common issues encountered during tea cultivation. This study introduces an improved YOLOv8 network model for the detection of tea pests to facilitate the rapid and accurate identification of early-stage micro-pests, addressing challenges such as small datasets and the difficulty of extracting phenotypic features of target pests in tea pest detection. Based on the original YOLOv8 network framework, this study adopts the SIoU optimized loss function to enhance the model’s learning ability for pest samples. AKConv is introduced to replace certain network structures, enhancing feature extraction capabilities and reducing the number of model parameters. Vision Transformer with Bi-Level Routing Attention is embedded to provide the model with a more flexible computation allocation and improve its ability to capture target position information. Experimental results show that the improved YOLOv8 network achieves a detection accuracy of 98.16% for tea pest detection, which is a 2.62% improvement over the original YOLOv8 network. Compared with the YOLOv10, YOLOv9, YOLOv7, Faster RCNN, and SSD models, the improved YOLOv8 network has increased the mAP value by 3.12%, 4.34%, 5.44%, 16.54%, and 11.29%, respectively, enabling fast and accurate identification of early-stage micro pests in tea gardens. This study proposes an improved YOLOv8 network model based on deep learning for the detection of micro-pests in tea, providing a viable research method and significant reference for addressing the identification of micro-pests in tea. It offers an effective pathway for the high-quality development of Yunnan’s ecological tea industry and ensures the healthy growth of the tea industry. Full article

Aluminum electrolysis is a typical industry with high energy consumption, and the energy saving of aluminum electrolysis cells is conducive to the sustainable development of the ecological environment. The current density distribution on the steel claws of conventional aluminum electrolysis cells is uneven, resulting in a large amount of power loss. Therefore, a new type of current-equalized steel claw (CESC) is designed in this paper. The ANSYS simulation study shows that the CESC can achieve a more uniform current density distribution and reduce the voltage drop by about 36 mV compared with the traditional steel claw (TSC). In addition, the use of CESC optimizes the temperature distribution of the steel claws and reduces the risk of cracking and deformation. The results of the industrial application tests are highly consistent with the simulation results, confirming the accuracy of the simulation results. The economic benefit analysis shows that using CESC saves 114.1 kWh of electricity per ton of aluminum produced. If this technology can be promoted throughout China, it is expected to save up to 4.75 billion kWh of electricity annually. The development of CESC is promising and of great significance for improving the overall technical level of the aluminum electrolysis industry. Full article

Grading tea leaves efficiently in a natural environment is a crucial technological foundation for the automation of tea-picking robots. In this study, to solve the problems of dense distribution, limited feature-extraction ability, and false detection in the field of tea grading recognition, an improved YOLOv8n model for tea grading and counting recognition was proposed. Firstly, the SPD-Conv module was embedded into the backbone of the network model to enhance the deep feature-extraction ability of the target. Secondly, the Super-Token Vision Transformer was integrated to reduce the model’s attention to redundant information, thus improving its perception ability for tea. Subsequently, the loss function was improved to MPDIoU, which accelerated the convergence speed and optimized the performance. Finally, a classification-positioning counting function was added to achieve the purpose of classification counting. The experimental results showed that, compared to the original model, the precision, recall and average precision improved by 17.6%, 19.3%, and 18.7%, respectively. The average precision of single bud, one bud with one leaf, and one bud with two leaves were 88.5%, 89.5% and 89.1%. In this study, the improved model demonstrated strong robustness and proved suitable for tea grading and edge-picking equipment, laying a solid foundation for the mechanization of the tea industry. Full article

Measurements of Very-Low-Frequency (VLF) transmitter signals have been widely used to investigate the effects of various space weather events on the D-region ionosphere, including nowcasting solar flares. Previous studies have established a method to nowcast solar flares using VLF measurements, but only using measurements from dayside propagation paths, and there remains limited focus on day–night mixed paths, which are important for method applicability. Between March and May of 2022, the Sun erupted a total of 56 M-class and 6 X-class solar flares, all of which were well captured by our VLF receiver in Antarctica. Using these VLF measurements, we reexamine the capability of the VLF technique to nowcast solar flares by including day–night mixed propagation paths and expanding the path coverage in longitude compared to that in previous studies. The amplitude and phase maximum changes are generally positively correlated with X-ray fluxes, whereas the time delay is negatively correlated. The curve-fitting parameters that we obtain for the X-ray fluxes and VLF signal maximum changes are consistent with those in previous studies for dayside paths, even though different instruments are used, supporting the flare-nowcasting method. Moreover, the present results show that, for day–night mixed paths, the amplitude and phase maximum changes also scale linearly with the logarithm of the flare X-ray fluxes, but the level of change is notably different from that for dayside paths. The coefficients used in the flare-nowcasting method need to be updated for mixed propagation paths. Full article

The 6-DOF Stewart parallel elevation platform serves as the platform for mounting the tea-picking robotic arm, significantly impacting the operational scope, velocity, and harvesting precision of the robotic arm. Utilizing the Stewart setup, a parallel elevation platform with automated lifting and leveling capabilities was devised, ensuring precise halts at designated elevations for seamless harvesting operations. The effectiveness of the platform parameter configuration and the reasonableness of the posture changes were verified. Firstly, the planting mode and growth characteristics of Yunnan large-leaf tea trees were analyzed to determine the preset path, posture changes, and mechanism stroke of the Stewart parallel lifting platform, thereby determining the basic design specifications of the platform. Secondly, a 3D model was established using SolidWorks, a robust adaptive PD control model was built using MATLAB for simulation, and dynamic calculations were carried out through data interaction in Simulink and ADAMS. Finally, the rationality of the lifting platform design requirements was determined based on simulation data, a 6-DOF Stewart parallel lifting platform was manufactured, and a motion control system was built for experimental verification according to the design specifications and simulation data. The results showed that the maximum deviation angle around the X, Y, and Z axes was 10°, the maximum lifting distance was 15 cm, the maximum load capacity was 60 kg, the platform response error was within ±0.1 mm, and the stable motion characteristics reached below the millimeter level, which can meet the requirements of automated operation of the auxiliary picking robotic arm. Full article

With the continuous emergence and development of 3D sensors in recent years, it has become increasingly convenient to collect point cloud data for 3D object detection tasks, such as the field of autonomous driving. But when using these existing methods, there are two problems that cannot be ignored: (1) The bird’s eye view (BEV) is a widely used method in 3D objective detection; however, the BEV usually compresses dimensions by combined height, dimension, and channels, which makes the process of feature extraction in feature fusion more difficult. (2) Light detection and ranging (LiDAR) has a much larger effective scanning depth, which causes the sector to become sparse in deep space and the uneven distribution of point cloud data. This results in few features in the distribution of neighboring points around the key points of interest. The following is the solution proposed in this paper: (1) This paper proposes multi-scale feature fusion composed of feature maps at different levels made of Deep Layer Aggregation (DLA) and a feature fusion module for the BEV. (2) A point completion network is used to improve the prediction results by completing the feature points inside the candidate boxes in the second stage, thereby strengthening their position features. Supervised contrastive learning is applied to enhance the segmentation results, improving the discrimination capability between the foreground and background. Experiments show these new additions can achieve improvements of 2.7%, 2.4%, and 2.5%, respectively, on KITTI easy, moderate, and hard tasks. Further ablation experiments show that each addition has promising improvement over the baseline. Full article

Background: Mpox virus (MPXV) infections have increased in many countries since May 2022, increasing demand for diagnostic tests and research on the virus. To ensure personnel safety, appropriate and reliable measures are needed to disinfect and inactivate infectious samples; Methods: We evaluated the stability of infectious MPXV cultures stored at different temperatures and through freeze–thaw cycles. Heat physical treatment (56 °C, 70 °C, 95 °C), chemical treatment (beta-propiolactone (BPL)) and two commercialized disinfectants (Micro-Chem Plus (MCP) and ethanol) were tested against infectious MPXV cultures; Results: The results indicated that MPXV stability increases with lower temperatures. The MPXV titer was stable within three freeze–thaw cycles and only decreased by 1.04 log₁₀ (lg) 50% cell culture infective dose (CCID₅₀) per milliliter (12.44%) after twelve cycles. MPXV could be effectively inactivated at 56 °C for 40 min, 70 °C for 10 min, and 95 °C for 5 min. For BPL inactivation, a 1:1000 volume ratio (BPL:virus) could also effectively inactivate MPXV. A total of 2% or 5% MCP and 75% ethanol treated with MPXV for at least 1 min could reduce >4.25 lg; Conclusions: MPXV shows high stability to temperature and freeze–thaw. Heat and BPL treatments are effective for the inactivation of MPXV, while MCP and ethanol are effective for disinfection, which could help laboratory staff operate the MPXV under safer conditions and improve operational protocols. Full article