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HWD-YOLO:A New Vision-Based Helmet Wearing Detection Method

Computers, Materials & Continua 2024年第9期80卷 4543-4560页

作者： Licheng Sun Heping Li Liang Wang College of Information Science and Technology Beijing University of TechnologyBeijing100124China Chinese Institute of Coal Science Beijing100013China State Key Laboratory for Intelligent Coal Mining and Strata Control Beijing100013China Engineering Research Center of Digital Community of Ministry of Education Beijing100124China

It is crucial to ensure workers wear safety helmets when working at a workplace with a high risk of safety accidents,such as construction sites and mine *** existing methods can achieve helmet detection in images,their accuracy and speed still need improvements since complex,cluttered,and large-scale scenes of real workplaces cause server occlusion,illumination change,scale variation,and perspective ***,a new safety helmet-wearing detection method based on deep learning is ***,a new multi-scale contextual aggregation module is proposed to aggregate multi-scale feature information globally and highlight the details of concerned objects in the backbone part of the deep neural ***,a new detection block combining the dilate convolution and attention mechanism is proposed and introduced into the prediction *** block can effectively extract deep featureswhile retaining information on fine-grained details,such as edges and small ***,some newly emerged modules are incorporated into the proposed network to improve safety helmetwearing detection performance *** experiments on open dataset validate the proposed *** reaches better performance on helmet-wearing detection and even outperforms the state-of-the-art *** be more specific,the mAP increases by 3.4%,and the speed increases from17 to 33 fps in comparison with the baseline,You Only Look Once(YOLO)version 5X,and themean average precision increases by 1.0%and the speed increases by 7 fps in comparison with the YOLO version *** generalization ability and portability experiment results show that the proposed improvements could serve as a springboard for deep neural network design to improve object detection performance in complex scenarios.

关键词： Object detection deep learning safety helmet wearing detection feature extraction attention mechanism

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Unveiling microplastic distribution and interactions in the benthic layer of the Yangtze River Estuary and East China Sea

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Environmental science and Ecotechnology 2024年第4期20卷 114-122页

作者： Xinyu Ge Feng Xu Bo Li Lili Liu Xiao Lu Lijuan Wang Yunxiao Zhang Jiangpeng Li Jiawei Li Yuanyuan Tang School of Environmental Science and Engineering College of EngineeringSouthern University of Science and TechnologyShenzhen518055China State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process School of Resource and Environmental EngineeringEast China University of Science and TechnologyShanghai200237China School of Marine Science and Technology Zhejiang Ocean UniversityZhoushan316004China

Microplastics(MPs),recognized as an emerging global environmental concern,have been extensively detected worldwide,with specific attention directed towards the Yangtze River Estuary(YRE)and East China Sea(ECS)*** their critical research significance,there remains a knowledge gap concerning the distribution of MPs in the benthic layer within this area,particularly regarding interactions governing their *** we illuminate the distribution of MPs within the benthic layer and unravel the intricate interplay between bottom water and sediment in the YRE and *** find that MPs are notably more abundant in bottom water,ranging from 8 to 175 times higher than in surface *** MPs predominantly consist of polyester fibers,exhibit a size range between 0.5 and 5.0 mm,and display distinct ***-occurrence network analysis and Principal Coordinate Analysis confirm a robust correlation between MPs in bottom water and sediment,signifying the pivotal role of bottom water in mediating the distribution and transportation of MPs within the benthic ***,a positive correlation between MPs in sediment and bottom water turbidity underscores the impact of surface sediment resuspension and upwelling on MPs *** study clarifies the intricate interactions within the benthic layer and highlights the crucial role of bottom water as a mediator in the vertical distribution of MPs,advancing our understanding of the“source-to-sink”transport processes governing MPs within water-sediment systems.

关键词： Microplastics Bottom water Sediment Distribution Correlation analysis

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MaBEL1 regulates banana fruit ripening by activating cell wall and starch degradation-related genes

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Journal of Integrative Plant Biology 2023年第9期65卷 2036-2055页

作者： Zunyang Song Xiaoyang Zhu Xiuhua Lai Hangcong Chen Lihua Wang Yulin Yao Weixin Chen Xueping Li Guangdong Provincial Key Laboratory of Postharvest Science of Fruits and Vegetables/Engineering Research Center for Postharvest Technology of Horticultural Crops in South China Ministry of EducationCollege of HorticultureSouth China Agricultural UniversityGuangzhou 510642China Key Laboratory of Food Processing Technology and Quality Control in Shandong Province College of Food Science and EngineeringShandong Agricultural UniversityTai'an 271018China

Banana is a typical subtropical fruit, sensitive to chilling injuries and prone to softening ***, the underlying regulatory mechanisms of the softening disorder caused by cold stress remain obscure. Herein, we found that BEL1-LIKE HOMEODOMAIN transcription factor 1(MaBEL1)and its associated proteins regulate the fruit softening and ripening process. The transcript and protein levels of MaBEL1 were up-regulated with fruit ripening but severely repressed by the chilling stress. Moreover, the MaBEL1 protein interacted directly with the promoters of the cell wall and starch degradation-related genes, such as MaAMY3, MaXYL32, and MaEXP-A8. The transient overexpression of MaBEL1 alleviated fruit chilling injury and ripening disorder caused by cold stress and promoted fruit softening and ripening of “Fenjiao” banana by inducing ethylene production and starch and cell wall degradation. The accelerated ripening was also validated by the ectopic overexpression in ***, MaBEL1-silencing aggravated the chilling injury and ripening disorder and repressed fruit softening and ripening by inhibiting ethylene production and starch and cell wall degradation. MaABI5-like and MaEBF1, the two positive regulators of the fruit softening process,interacted with MaBEL1 to enhance the promoter activity of the starch and cell wall degradationrelated genes. Moreover, the F-box protein MaEBF1 does not modulate the degradation of MaBEL1, which regulates the transcription of MaABI5-like protein. Overall, we report a novel MaBEL1-MaEBF1-MaABI5-like complex system that mediates the fruit softening and ripening disorder in “Fenjiao” bananas caused by cold stress.

关键词： cold stress fruit ripening interaction MaBEL1 softening disorder transcriptional regulation

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Gut liver brain axis in diseases:the implications for therapeutic interventions

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Signal Transduction and Targeted Therapy 2024年第1期9卷 79-104页

作者： Mengyao Yan Shuli Man Benyue Sun Long Ma Lanping Guo Luqi Huang Wenyuan Gao State Key Laboratory of Food Nutrition and Safety Key Laboratory of Industrial MicrobiologyMinistry of EducationTianjin Key Laboratory of Industry MicrobiologyNational and Local United Engineering Lab of Metabolic Control Fermentation TechnologyChina International Science and Technology Cooperation Base of Food Nutrition/Safety and Medicinal ChemistryCollege of BiotechnologyTianjin University of Science&Technology300457 TianjinChina National Resource Center for Chinese Materia Medica China Academy of Chinese Medical Sciences100700 BeijingChina Tianjin Key Laboratory for Modern Drug Delivery&High-Efficiency School of Pharmaceutical Science and TechnologyTianjin UniversityWeijin Road300072 TianjinChina

Gut-liver-brain axis is a three-way highway of information interaction system among the gastrointestinal tract,liver,and nervous *** the past few decades,breakthrough progress has been made in the gut liver brain axis,mainly through understanding its formation mechanism and increasing treatment *** this review,we discuss various complex networks including barrier permeability,gut hormones,gut microbial metabolites,vagus nerve,neurotransmitters,immunity,brain toxic metabolites,β-amyloid(Aβ)metabolism,and epigenetic regulation in the gut-liver-brain *** therapies containing antibiotics,probiotics,prebiotics,synbiotics,fecal microbiota transplantation(FMT),polyphenols,low FODMAP diet and nanotechnology application regulate the gut liver brain ***,some special treatments targeting gut-liver axis include farnesoid X receptor(FXR)agonists,takeda G protein-coupled receptor 5(TGR5)agonists,glucagon-like peptide-1(GLP-1)receptor antagonists and fibroblast growth factor 19(FGF19)*** gut-brain axis embraces cognitive behavioral therapy(CBT),antidepressants and tryptophan metabolism-related *** liver-brain axis contains epigenetic regulation and Aβmetabolism-related *** the future,a better understanding of gut-liver-brain axis interactions will promote the development of novel preventative strategies and the discovery of precise therapeutic targets in multiple diseases.

关键词： metabolism therapeutic immunity

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Pointer Meter Reading under Noise Based on Virtual Data Generation

Pointer Meter Reading under Noise Based on Virtual Data Gene...

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2024 China Automation Congress, CAC 2024

作者： Zhu, Jinyang Xu, Zhezhuang Lin, Ye College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China

ISBN: (纸本)9798350368604

Using machine vision for meter reading significantly enhances the efficiency of industrial monitoring. However, meters in outdoor environment are often subject to the noise such as rain and fog, which affect the accuracy of meter readings. Additionally, the meter images and labels under noise are hard to obtain. To address these challenges, We propose a method for pointer meter reading under noise based on virtual data generation. Firstly, We utilize Unity to construct an industrial meter scene, which generates the images of meter under noise and theri labels. Secondly, we develop a U-Net network with an ASPP module, which expands the receptive field of network and enhances the ability of segmentation network to capture global semantic information under noise. Finally, the angular method is used to calculate the meter readings. Experimental results show that this method can effectively read meters under noise in outdoor environments. © 2024 IEEE.

关键词： Virtual addresses

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Adaptive fuzzy asymptotic control design for MIMO nonlinear systems with state constraints

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Journal of control and Decision 2023年第4期10卷 610-623页

作者： Yongchao Liu Bowen Zeng Qidan Zhu Lipeng Wang Institute of Complexity Science School of AutomationQingdao UniversityQingdaoPeople’s Republic of China Shandong Key Laboratory of Industrial Control Technology QingdaoPeople’s Republic of China College of Intelligent Systems Science and Engineering Harbin Engineering UniversityHarbinPeople’s Republic of China

This paper addresses the asymptotic control problem of uncertain multi-input and multi-output(MIMO)nonlinear *** considered MIMO systems contain unknown virtual control coefficients(UVCCs)and state *** Lyapunov function by associating with the lower bounds of UVCCs is presented to counteract the adverse effect deriving from *** state constraints are ensured by utilising the barrier Lyapunov ***,the asymptotic tracking controller is recursively constructed by combining the backstepping technique with fuzzy logic *** remarkable character of the designed controller is that the asymptotic tracking performance can be achieved by introducing some smooth functions into adaptive backstepping *** contrast to the existing results,the conditions on the UVCCs are ***,the new control design is illustrated by a practical example.

关键词： Asymptotic tracking control state constraints bound estimation method nonlinear systems

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Semi-supervised learning with GAN for Semantic Segmentation of Wood Defect image

Semi-supervised learning with GAN for Semantic Segmentation ...

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2024 China Automation Congress, CAC 2024

作者： Zheng, Kunxin Zheng, Song Xu, Zhezhuang Lin, Ye Zhu, Yuhang College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China

ISBN: (纸本)9798350368604

Automatic defect detection on wood surface is essential for ensuring product quality. Semantic segmentation methods have shown outstanding performance in wood defect detection. However, it is costly to acquire correct pixel-level labels of wood surface defects due to the complicated characteristics. To mitigate the cost of acquiring high-quality datasets, this study proposes a semi-supervised defect detection approach based on generative adversarial networks, which contains a generator and a discriminator. The generator is utilized to generate pixel-level segmentation results of wood defect images. To improve the segmentation performance, the discriminator learns against the generator by judging the goodness of the prediction results and generates supervised signals for the prediction results of unlabeled images. With this learning model, the proposed method can enhance segmentation performance using unlabeled images and alleviate the burden of data annotation. We validate the effectiveness of the proposed approach on a collected dataset of wood defects. Experimental results demonstrate the remarkable performance of our method even when utilizing only a small amount of annotated data. © 2024 IEEE.

关键词： Generative adversarial networks

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Analyzing the Correlation between Student Learning Behaviors and Academic Performance in Blended Learning Environments

Analyzing the Correlation between Student Learning Behaviors...

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2024 China Automation Congress, CAC 2024

作者： Zhang, Ying Chen, Kang Xu, Zhezhuang Lin, Ye Zeng, Qingbo College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China

ISBN: (纸本)9798350368604

Blended learning integrates online and face-to-face (FTF) teaching methods to offer students in higher education a flexible and customized educational experience. Despite its significant advantages in promoting academic achievement and increasing student participation, blended learning presents challenges for educators due to difficulties in collecting and analyzing learning behavior data. Existing research mainly focuses on single learning modes, and data collection methods primarily rely on interviews and questionnaires, which can be subjective. To address these challenges, this study developed a mobile software called EasyClass, integrated with an online Small Private Online Course(SPOC) platform, to automatically record student behaviors in a blended learning environment. Obtaining data from an undergraduate blended learning course, statistical methods are used to analyze the correlation between student behaviors and final grades, as well as to identify factors affecting grades. The results of multivariate linear regression models confirmed the feasibility and effectiveness of blended instruction. This study provides a new approach to identifying and disseminating effective data collection strategies in blended learning, enabling educators and educational institutions to better understand and assess student behaviors, and to further explore their impact on final academic achievement. © 2024 IEEE.

关键词： Contrastive Learning

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Repeated inoculation with rumen fluid accelerates the rumen bacterial transition with no benefit on production performance in postpartum Holstein dairy cows

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Journal of Animal science and Biotechnology 2024年第2期15卷 795-811页

作者： Fanlin Kong Feiran Wang Yijia Zhang Shuo Wang Wei Wang Shengli Li Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control State Key Laboratory of Animal NutritionDepartment of Animal Nutrition and Feed ScienceCollege of Animal Science and TechnologyChina Agricultural UniversityBeijing 100193PR China College of Veterinary Medicine Nanjing Agricultural UniversityNanjingJiangsu 210095PR China

Background The dairy cow’s postpartum period is characterized by dramatic physiological changes,therefore imposing severe challenges on the animal for maintaining health and milk *** dynamics of the ruminal microbiota are also tremendous and may play a crucial role in lactation *** aim to investigate the potential benefits of early microbial intervention by fresh rumen microbiota transplantation(RMT)and sterile RMT in postpartum dairy *** fistulated peak-lactation dairy cows were selected to be the donors for rumen fluid *** postpartum cows were divided into 3 groups as the transplantation receptors respectively receiving 10 L fresh rumen fluid(FR),10 L sterile rumen fluid(SR),or 10 L saline(CON)during 3 d after *** Production performance,plasma indices,plasma lipidome,ruminal microbiome,and liver transcriptome were *** fresh and sterile RMT,we found that the molar proportion of propionic acid was increased on d 7 in the FR and SR groups and the bacterial composition was also significantly changed when compared with the CON group.A similarity analysis showed that the similarities between the CON group and FR or SR group on d 7 were 48.40%or 47.85%,whereas the similarities between microbiota on d 7 and 21 in the FR and SR groups were 68.34%or 66.85%.Dry matter intake and feed efficiency were not affected by ***β-hydroxybutyrate concentration in the FR group was decreased and significantly different lipids mainly included phosphatidylcholine and lysophosphatidylcholine containing polyunsaturated fatty *** transcriptomics analysis indicated acutephase response pathways were upregulated in the SR *** Our study suggests that RMT can shorten the transition process of the ruminal microbiota of postpartum dairy cows with no benefit on dry matter intake or feed *** with rumen fluid may not be a useful approach to promote the recovery of postpartum dairy cows.

关键词： Dairy cow Lipidomics Liver Rumen microbiota transplantation Transition period

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Wood Surface Discoloration Defect Detection Based on Improved HRNet

Wood Surface Discoloration Defect Detection Based on Improve...

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2024 China Automation Congress, CAC 2024

作者： Zhang, Haoran Xu, Zhezhuang Zhu, Yuhang Lin, Ye College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China

ISBN: (纸本)9798350368604

Discoloration defect detection is a significant task in the wood industry for ensuring the appearance and quality of wooden products. However, discoloration defect detection still faces some challenges due to the low contrast, blurred boundary, and slender shape of discoloration defects. To overcome these challenges, we propose a multi-branch feature encoding HRNet(MFE-HRNet) for wood surface discoloration defect detection. The network maintains high-resolution features and builds a parallel multi-resolution architecture to prevent the dilution of low-contrast discoloration defect features. Through repeated cross-fusion of multi-scale features, the network enhances the global representation of blurry features. In order to effectively preserve the detail features of the defect edge, a multi-branch feature encoding module (MFEM) is proposed as the encoding layer of the network. In the MFEM, multiple branches concurrently extract features, generating feature maps with complementary characteristics, thereby enhancing the ability of network to recognize fine details of defects. Experimental results verify the effectiveness of our method in detecting discoloration defects on wood surface. © 2024 IEEE.

关键词： Discoloration

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