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Copyright of Acta Scientiarum Naturalium Universitatis Pekinensis is the property of Editorial Office of Acta Scientiarum Naturalium Universitatis Pekinensis and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Oncology is the property of Chinese Journal of Oncology / Zhonghua Zhongliu Zazhi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Modern Laboratory Medicine is the property of Journal of Modern Laboratory Medicine Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Geology & Exploration is the property of Geology & Exploration Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Objective] To clarify the biological characteristics of Trichoderma viride and their mechanisms of alleviating salt stress in corn seedlings. [Method] The biological characteristics of a Trichoderma viride strain screened in the early stage were analyzed,and the effects of Trichoderma viride on corn seedling height,root length,aboveground dry weight,underground dry weight,root crown ratio,chlorophyll a content, chlorophyll b content,SOD,POD,CAT,PPO and other indicators under salt stress were measured,exploring the effects of Trichoderma viride on the growth and physiological indicators of corn seedlings under salt stress. [Result]The optimal growth temperature for the strain was 25 ℃ ;the requirements for light were not strict,but the colony diameter under 24 hours of darkness treatment was significantly higher than 12 hours of darkness+12 hours of light,and 24 hours of light;the strain grows fastest at pH = 5. After adding different concentrations of spore suspension,the plant height,root length,dry weight of underground and aboveground parts,chlorophyll a and chlorophyll b content,SOD activity,POD activity, CAT activity,and PPO activity of corn seedlings showed a gradually increasing trend under salt stress. [Conclusion]The research results can provide basic data for improving the planting efficiency of corn in saline alkali soil. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Materials Science & Engineering (1673-2812) is the property of Journal of Materials Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Anhui Agricultural Sciences is the property of Journal of Anhui Agricultural Sciences Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Objective] There's a growing demand among plant cultivators and breeders for efficient methods to acquire plant phenotypic traits at high throughput, facilitating the establishment of mappings from phenotypes to genotypes. By integrating mobile phenotyping platforms with improved instance segmentation techniques, researchers have achieved a significant advancement in the automation and accuracy of phenotypic data extraction. Addressing the need for rapid extraction of leaf age and canopy width phenotypes in strawberry plants cultivated in controlled environments, this study introduces a novel high-throughput phenotyping extraction approach leveraging a mobile phenotyping platform and instance segmentation technology. [Methods] Data acquisition was conducted using a compact mobile phenotyping platform equipped with an array of sensors, including an RGB sensor, and edge control computers, capable of capturing overhead images of potted strawberry plants in greenhouses. Targeted adjustments to the network structure were made to develop an enhanced convolutional neural network (Mask R-CNN) model for processing strawberry plant image data and rapidly extracting plant phenotypic information. The model initially employed a split-attention networks (ResNeSt) backbone with a group attention module, replacing the original network to improve the precision and efficiency of image feature extraction. During training, the model adopted the Mosaic method, suitable for instance segmentation data augmentation, to expand the dataset of strawberry images. Additionally, it optimized the original cross-entropy classification loss function with a binary cross-entropy loss function to achieve better detection accuracy of plants and leaves. Based on this, the improved Mask R-CNN description involves post-processing of training results. It utilized the positional relationship between leaf and plant masks to statistically count the number of leaves. Additionally, it employed segmentation masks and image calibration against true values to calculate the canopy width of the plant. [Results and Discussions] This research conducted a thorough evaluation and comparison of the performance of an improved Mask RCNN model, underpinned by the ResNeSt-101 backbone network. This model achieved a commendable mask accuracy of 80.1% and a detection box accuracy of 89.6%. It demonstrated the ability to efficiently estimate the age of strawberry leaves, demonstrating a high plant detection rate of 99.3% and a leaf count accuracy of 98.0%. This accuracy marked a significant improvement over the original Mask R-CNN model and meeting the precise needs for phenotypic data extraction. The method displayed notable accuracy in measuring the canopy widths of strawberry plants, with errors falling below 5% in about 98.1% of cases, highlighting its effectiveness in phenotypic dimension evaluation. Moreover, the model operated at a speed of 12.9 frames per second (FPS) on edge devices, effectively balancing accuracy and operational efficiency. This speed proved adequate for real-time applications, enabling rapid phenotypic data extraction even on devices with limited computational capabilitie. [Conclusions] This study successfully deployed a mobile phenotyping platform combined with instance segmentation techniques to analyze image data and extract various phenotypic indicators of strawberry plant. Notably, the method demonstrates remarkable robustness. The seamless fusion of mobile platforms and advanced image processing methods not only enhances efficiency but also ignifies a shift towards data-driven decision-making in agriculture [ABSTRACT FROM AUTHOR]

Copyright of Science Technology & Engineering is the property of Chinese Society of Technology Economics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Zhejiang Electric Power is the property of Zhejiang Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food & Fermentation Industries is the property of Food & Fermentation Industries and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Shenyang Pharmaceutical University is the property of Shenyang Pharmaceutical University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food & Fermentation Industries is the property of Food & Fermentation Industries and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Acta Scientiarum Naturalium Universitatis Pekinensis is the property of Editorial Office of Acta Scientiarum Naturalium Universitatis Pekinensis and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Zhejiang Electric Power is the property of Zhejiang Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Functional Materials / Gongneng Cailiao is the property of Chongqing Functional Materials Periodical Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective To investigate the prognostic role of EHD3 and its association with immune cell infiltration in gastric cancer. Methods In this study, EHD3 expression was analyzed using RNA sequencing data from Cancer Genome Atlas (TCGA). Differential analysis, functional enrichment, immune infiltration, immune checkpoint exploration, and clinical baseline data analysis were performed. Independent prognostic factors were identified using univariate and multivariate Cox regression analysis; a column diagram model was developed and evaluated using C-index and calibration diagrams. Results EHD3 was significantly upregulated in STAD and functional enrichment analysis showed that EHD3 expression was associated with immune response, with most immune cells and immune checkpoints positively correlated with their expression. Cox regression showed that EHD3 was an independent prognostic factor in STAD patients (HR=2.112, 95% CI: 1.340-3.327, P=0.001). Conclusion EHD3 is considered to be a novel prognostic biomarker for STAD patients, and this study provides a potential therapeutic target for STAD treatment. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Mechanical Strength / Jixie Qiangdu is the property of Zhengzhou Research Institute of Mechanical Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Polymer Materials Science & Engineering is the property of Sichuan University, Polymer Research Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the process of bearing fault diagnosis of wind turbine, the fault diagnosis method based on deep learning is limited by limited labeled samples, which has problems such as difficulties in model convergence and low recognition accuracy. For this purpose, a parallel convolutional neural network（P-CNN) and feature fusion-based fault diagnosis method for small sample wind turbine bearings was proposed. Firstly, the vibration signal of the bearing was decomposed into several intrinsic mode functions (IMF） components and residual components by ensemble empirical mode decomposition（EEMD). Then, the short time Fourier transform (STFT) was performed on them, and they were respectively converted into time-frequency characteristic maps, and multiple identical convolutional neural network branches were constructed as feature extractors. Finally, the extracted time-frequency domain features were fused in the fusion layer and used as the input of the final classifier to achieve fault identification of wind turbine bearings, the applicability and effectiveness of this method was validated using different size bearing datasets from Case Western Reserve University. The results show that the parallel convolutional neural network (P-CNN) and feature fusion-based fault diagnosis method has an average accuracy of 94.5% when containing only 160 samples, which has higher accuracy and stronger robustness compared to support vector machine (SVM) 、FaultNet and deep convolutional neural networks with wide first-layer kernel (WDCNN). [ABSTRACT FROM AUTHOR]

Antiviral therapy is the basic treatment method for improving prognosis recommended in the management guidelines of chronic hepatitis B in China and globally. For patients with chronic HBV infection and normal transaminases, it is difficult in clinical practice to accurately evaluate the progression of hepatitis and identify suitable patients who need antiviral therapy. In order to objectively and accurately evaluate the degree of liver inflammatory activity in such patients, more and more noninvasive evaluation indicators have been used in addition to conventional liver biopsy. This article reviews the new serological indicators that can reflect the degree of liver inflammation and/or fibrosis in patients with chronic HBV infection and normal aminotransferase levels, hoping to provide a reference for antiviral decision-making in these patients. [ABSTRACT FROM AUTHOR]

The introduction of Laplace transform theory into the principles of automatic control allows complex differential equations to be transformed into algebraic equations after modelling the system, which plays an important role in analyzing stability and system correction. The researchers use a ball-and-stick system for modelling, combine the properties of the Laplace transform, and derive its corresponding algebraic equations. The stability of the system is analyzed in three ways: time domain, root trajectory and frequency domain. Next, the unstable system is corrected to achieve the desired effect, and tested for stability with multiple signals in the Simulink module of Matlab. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Jilin University (Science Edition) / Jilin Daxue Xuebao (Lixue Ban) is the property of Zhongguo Xue shu qi Kan (Guang Pan Ban) Dian zi Za zhi She and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Imaging Science & Photochemistry is the property of Imaging Science & Photochemistry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective：This study aims to to develop rapid detection methods and establish a new method for a common foodborne pathogenic microorganism enterohemorrhagic E.coli（EHEC）O157：H7 detection. Methods：Two EHEC O157：H7 detection methods were established and optimized based on the conserved region sequence of EHEC O157：H7 combined with recombinase ⁃ aided amplification（RAA）and fluorescence quantitative method or lateral flow dipstick（LFD），then the sensitivity and specificity of the two methods（RAA fluorescence method and RAA ⁃ LFD method）were evaluated. Results：Both detection methods can be completed within 16 min at 39 ℃，and can detect 1 × 104 copies，showing high sensitivity. The two methods did not cross react with plasmid templates of other common intestinal pathogens（Staphylococcus aureus，Salmonella，Campylobacter，Yersinia，Shigella）and showed good specificity. Conclusion：The two EHEC O157：H7 detection methods established in this study have short detection time，good specificity，sensitivity and repeatability，and can be used for rapid detection of EHEC O157：H7. [ABSTRACT FROM AUTHOR]

Copyright of Hydrometallurgy of China is the property of Hydrometallurgy of China Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to improve the noise, vibration and harshness (NVH) level of the whole vehicle, a multi, objective optimization design was carried out for the intermediate support of the drive shaft, and the stiffness value of the support was calculated, simulated and analyzed. Firstly, the process and optimization theory of frequency ratio calculation and design were introduced, and the suspension mass, natural fre, quency and frequency ratio of a certain transmission shaft were calculated and analyzed. Then, based on multi, objective genetic algorithm (NSGA), the objective function was constructed, which used the vibration transmissibility, first order modal change rate, rubber damping ratio and frequency ratio as the objective function, s constraints. The multi, objective optimization theory was used to re, match and optimize the stiffness of the intermediate support, and the optimal stiffness value was obtained. Finally, the original intermediate support and the new in, termediate support with the optimized stiffness values were simulated. Both the intermediate supports were tested with the electric light bus by NVH test program. The vibration acceleration of the improved intermediate support was decreased by about 19% at 80 km/ h speed. The optimized intermediate support with optimal stiffness value, can well reduce the vehicle vibration, and decrease the negative impact of the trans, mission shaft on the vehicle vibration, which proves the effectiveness of the optimization method. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Nanjing Agricultural University / Nanjuing Nongye Daxue Xuebao is the property of Journal of Nanjing Agricultural University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Guangdong Architecture Civil Engineering is the property of Guangdong Architecture Civil Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Water Conservancy & Electric Power Technology & Application is the property of Omniscient Pte. Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)