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Chinese Physics B 2024年第4期33卷 640-648页

作者：陈登辉羊志付新宇秦申奥严岩王传奎李宗良邱帅 Shandong Key Laboratory of Medical Physics and image processing&Shandong Provincial Engineering and Technical center of Light Manipulations School of Physics and ElectronicsShandong Normal UniversityJinan 250358China

Orientation-dependent transport properties induced by anisotropic molecules are enticing in single-molecule junctions.Here,using the first-principles method,we theoretically investigate spin transport properties and photoresponse characteristics in trimesic acid magnetic single-molecule junctions with different molecular adsorption orientations and electrode contact sites.The transport calculations indicate that a single-molecule switch and a significant enhancement of spin transport and photoresponse can be achieved when the molecular adsorption orientation changes from planar geometry to upright geometry.The maximum spin polarization of current and photocurrent in upright molecular junctions exceeds 90%.Moreover,as the Ni tip electrode moves,the tunneling magnetoresistance of upright molecular junctions can be increased to 70%.The analysis of the spin-dependent PDOS elucidates that the spinterfaces between organic molecule and ferromagnetic electrodes are modulated by molecular adsorption orientation,where the molecule in upright molecular junctions yields higher spin polarization.Our theoretical work paves the way for designing spintronic devices and optoelectronic devices with anisotropic functionality base on anisotropic molecules.

关键词： molecular spintronics spin polarization tunneling magnetoresistance photocurrent single-molecule junctions

A Novel Multi-Stream Fusion Network for Underwater image Enhancement

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China Communications 2024年第2期21卷 166-182页

作者： Guijin Tang Lian Duan Haitao Zhao Feng Liu Jiangsu Key Laboratory of image processing and image Communication Nanjing University of Posts and TelecommunicationsNanjing 210003China Jiangsu Key Laboratory of Wireless Communications Nanjing University of Posts and TelecommunicationsNanjing 210003China

Due to the selective absorption of light and the existence of a large number of floating media in sea water, underwater images often suffer from color casts and detail blurs. It is therefore necessary to perform color correction and detail restoration. However,the existing enhancement algorithms cannot achieve the desired results. In order to solve the above problems, this paper proposes a multi-stream feature fusion network. First, an underwater image is preprocessed to obtain potential information from the illumination stream, color stream and structure stream by histogram equalization with contrast limitation, gamma correction and white balance, respectively. Next, these three streams and the original raw stream are sent to the residual blocks to extract the features. The features will be subsequently fused. It can enhance feature representation in underwater images. In the meantime, a composite loss function including three terms is used to ensure the quality of the enhanced image from the three aspects of color balance, structure preservation and image smoothness. Therefore, the enhanced image is more in line with human visual perception.Finally, the effectiveness of the proposed method is verified by comparison experiments with many stateof-the-art underwater image enhancement algorithms. Experimental results show that the proposed method provides superior results over them in terms of MSE,PSNR, SSIM, UIQM and UCIQE, and the enhanced images are more similar to their ground truth images.

关键词： image enhancement multi-stream fusion underwater image

Revolutionary entrapment model of uniformly distributed swarm robots in morphogenetic formation

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Defence Technology（防务技术） 2024年第1期31卷 496-509页

作者： Chen Wang Zhaohui Shi Minqiang Gu Weicheng Luo Xiaomin Zhu Zhun Fan Shantou University ShantouGuangdongChina National University of Defense Technology ChangshaChina Key Lab of Digital Signal and image processing of Guangdong Province China

This study proposes a method for uniformly revolving swarm robots to entrap multiple targets,which is based on a gene regulatory network,an adaptive decision mechanism,and an improved Vicsek-model.Using the gene regulatory network method,the robots can generate entrapping patterns according to the environmental input,including the positions of the targets and obstacles.Next,an adaptive decision mechanism is proposed,allowing each robot to choose the most well-adapted capture point on the pattern,based on its environment.The robots employ an improved Vicsek-model to maneuver to the planned capture point smoothly,without colliding with other robots or obstacles.The proposed decision mechanism,combined with the improved Vicsek-model,can form a uniform entrapment shape and create a revolving effect around targets while entrapping them.This study also enables swarm robots,with an adaptive pattern formation,to entrap multiple targets in complex environments.Swarm robots can be deployed in the military field of unmanned aerial vehicles’(UAVs)entrapping multiple targets.Simulation experiments demonstrate the feasibility and superiority of the proposed gene regulatory network method.

关键词： Swarm intelligence Revolutionary entrapment Flocking Robots Gene regulatory network Vicsek-model Entrapping multiple targets

RepBoTNet-CESA:An Alzheimer’s Disease Computer Aided Diagnosis Method Using Structural Reparameterization BoTNet and Cubic Embedding Self Attention

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Computers, Materials & Continua 2024年第5期79卷 2879-2905页

作者： Xiabin Zhang Zhongyi Hu Lei Xiao Hui Huang College of Computer Science and Artificial Intelligence Wenzhou UniversityWenzhou325035China Key Laboratory of Intelligence image processing and Analysis Wenzhou UniversityWenzhou325035China

Various deep learning models have been proposed for the accurate assisted diagnosis of early-stage Alzheimer’s disease(AD).Most studies predominantly employ Convolutional Neural Networks(CNNs),which focus solely on local features,thus encountering difficulties in handling global features.In contrast to natural images,Structural Magnetic Resonance Imaging(sMRI)images exhibit a higher number of channel dimensions.However,during the Position Embedding stage ofMulti Head Self Attention(MHSA),the coded information related to the channel dimension is disregarded.To tackle these issues,we propose theRepBoTNet-CESA network,an advanced AD-aided diagnostic model that is capable of learning local and global features simultaneously.It combines the advantages of CNN networks in capturing local information and Transformer networks in integrating global information,reducing computational costs while achieving excellent classification performance.Moreover,it uses the Cubic Embedding Self Attention(CESA)proposed in this paper to incorporate the channel code information,enhancing the classification performance within the Transformer structure.Finally,the RepBoTNet-CESA performs well in various AD-aided diagnosis tasks,with an accuracy of 96.58%,precision of 97.26%,and recall of 96.23%in the AD/NC task;an accuracy of 92.75%,precision of 92.84%,and recall of 93.18%in the EMCI/NC task;and an accuracy of 80.97%,precision of 83.86%,and recall of 80.91%in the AD/EMCI/LMCI/NC task.This demonstrates that RepBoTNet-CESA delivers outstanding outcomes in various AD-aided diagnostic tasks.Furthermore,our study has shown that MHSA exhibits superior performance compared to conventional attention mechanisms in enhancing ResNet performance.Besides,the Deeper RepBoTNet-CESA network fails to make further progress in AD-aided diagnostic tasks.

关键词： Alzheimer CNN structural reparameterization multi head self attention computer aided diagnosis

Plant-based meat analogues aggravated lipid accumulation by regulating lipid metabolism homeostasis in mice

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Food Science and Human Wellness 2024年第2期13卷 946-960页

作者： Yunting Xie Linlin Cai Zhiji Huang Kai Shan Xinglian Xu Guanghong Zhou Chunbao Li Key Laboratory of Meat processing and Quality Control MOEKey Laboratory of Meat ProcessingMARAJiangsu Innovative Center of Meat ProductionProcessing and Quality ControlCollege of Food Science and TechnologyNanjing Agricultural UniversityNanjing 210095China

To determine the effects of plant-based meat analogues on the metabolic health and the possible mechanisms,mice were fed with a real pork diet(AP),a real beef diet(AB),a plant-based pork analogue diet(PP)and plant-based beef analogue diet(PB)for 68 days.Compared with real meat,the plant-based meat analogues increased food and energy intake,body weight,white fat and liver weight and caused adipocyte hypertrophy,hepatic lipid droplet accumulation,and inflammatory responses in mice.Metabolomics revealed that plantbased meat analogues altered the composition of serum metabolites,which regulated lipid metabolism homeostasis.The PB diet upregulated gene expression related to lipid synthesis,lipolysis and adipocyte differentiation while the PP diet upregulated expression of lipolysis-related genes but downregulated expression of adipocyte differentiation-related genes in white adipose tissue.Meanwhile,both PP and PB diets upregulated lipid influx-and synthesis-related genes but downregulated lipid oxidation-related genes in liver.The specific metabolite biomarkers may affect fat accumulation mainly by direct lipid metabolism pathways or indirect amino acid metabolism,protein digestion and absorption,bile secretion,aminoacyl-tRNA biosynthesis,neuroactive ligand-receptor interaction and ABC transporters pathways.These findings provide a new insight into understanding the differences in nutritional functions of meat and plant-based meat analogues.

关键词： Meat analogues Metabolomics Lipid metabolism Adipose tissue dysfunction Ectopic fat deposition

Food nutrition and toxicology targeting on specific organs in the era of single-cell sequencing

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Food Science and Human Wellness 2024年第1期13卷 75-89页

作者： Xiaofei Wang Xiaowen Cheng Huiling Liu Xiaohuan Mu Hao Zheng National Engineering Technology Research center for Fruit and Vegetable processing Key Open Laboratory of Fruit and Vegetable ProcessingMinistry of Agriculture and Rural AffairsBeijing Key Laboratory of Food Non-Thermal ProcessingCollege of Food Science and Nutritional EngineeringChina Agricultural UniversityBeijing 100083China

Due to the complex natures of dietary food components,it is difficult to elucidate how the compounds affect host health.Dietary food often selectively presents its mechanism of action on different cell types,and participates in the modulation of targeted cells and their microenvironments within organs.However,the limitations of traditional in vitro assays or in vivo animal experiments cannot comprehensively examine cellular heterogeneity and the tissue-biased influences.Single-cell RNA sequencing(sc RNA-seq)has emerged as an indispensable methodology to decompose tissues into different cell types for the demonstration of transcriptional profiles of individual cells.Sc RNA-seq applications has been summarized on three typical organs(brain,liver,kidney),and two representative immune-and tumor related health problems.The everincreasing role of sc RNA-seq in dietary food research with further improvement can provide sub-cellular information and the coupling between other cellular modalities.In this review,we propose utilizing sc RNAseq to more effectively capture the subtle and complex effects of food chemicals,and how they may lead to health problems at single-cell resolution.This novel technique will be valuable to elucidate the underlying mechanism of both the health benefits of food nutrients and the detrimental consequences food toxicants at the cellular level.

关键词： Dietary food Cellular heterogeneity Single-cell RNA sequencing Food nutrients Food toxicants

Effects of prebiotics on the fermentation of traditional suancai of Northeast China

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Food Science and Human Wellness 2024年第3期13卷 1358-1367页

作者： Mingwei Zhao Xinying Cao Yuzheng Wu Sibo Zou Zhigao Li Xinping Lin Chaofan Ji Liang Dong Sufang Zhang Chenxu Yu Huipeng Liang National Engineering Research center of Seafood Collaborative Innovation Center of Provincial and Ministerial Co-construction for Deep ProcessingCollaborative Innovation Center of Seafood Deep ProcessingSchool of Food Science and TechnologyDalian Polytechnic UniversityDalian 116034China Department of Agricultural and Biosystems Engineering Iowa State UniversityIA 50011USA

Suancai is a traditional fermented vegetable widely consumed in Northeast China.In this study,different prebiotics were used to improve the quality of suancai.Four prebiotics(inulin(INU),xylooligosaccharide(XO S),galactooligosaccharide(GOS),and stachyose(STA))were shown to reduce the pH value and increase the content of total titratable acidity(TTA)in suancai,while the contents of most organic acids were also increased.The addition of prebiotics had significant effects on the bacterial microbiota during the suancai fermentation process.All prebiotics were shown to contribute to the growth of Lactobacillus.The suancai sample with fructooligosaccharides(FOS)had the highest relative abundance of Lactobacillus.Besides,INU and XOS could increase the abundance of Weissella.To evaluate the quality of suancai fermented with prebiotics,profiles of volatile flavor compounds(VOCs)and free amino acids(FAA)were analyzed.The prebiotics affected the VOCs and FAA profiles via transforming the bacterial microbiota.In addition,the addition of prebiotics also changed the taste profiles of the suancai samples.This study is among the first attempts to reveal the effects of different prebiotics on suancai fermentation,and the findings provide a foundation to develop new ways for improving the quality of suancai.

关键词： Bacterial microbiota Lactic acid bacteria Flavor Amino acid Taste

Noncovalent cross-linked engineering hydrogel with low hysteresis and high sensitivity for flexible self-powered electronics

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Journal of Energy Chemistry 2024年第7期94卷 136-147页

作者： Hang Yuan Shaowei Han Jia Wei Songwei Li Peipei Yang Hao-Yang Mi Chuntai Liu Changyu Shen National Engineering Research center for Advanced Polymer processing Technology Key Laboratory of Materials Processing and Mold(Ministry of Education)Zhengzhou UniversityZhengzhou450002HenanChina Yunnan TobaccoQuality Inspection&Supervision Station Kunming 650106YunnanChina

In this study,the hydrogel network was reinforced by covalent-like hydrogen bonding,and the strong binding ability of boron-nitrogen coordination served as the main driving force.Among them,acrylamide(AM)and 3-acrylamidophenylboronic acid(AAPBA)were the main body,and the numerous hydroxyl groups in the trehalose(Treh)molecule and other polymer groups formed strong hydrogen bonding interactions to improve the mechanical properties of the PAM/PAAPBA/Treh(PAAT)hydrogel and ensured the simplicity of the synthesis process.The hydrogel possessed high strain at break(1239%),stress(64.7 kPa),low hysteresis(100%to 500%strain,corresponding to dissipation energy from 1.37 to 7.80 kJ/m^(3)),and outstanding cycling stability(retained more than 90%of maximum stress after 200 ten-sile cycles).By integrating carbon nanotubes(CNTs)into PAAT hydrogel(PAATC),the PAATC hydrogel with excellent strain response performance was successfully constructed.The PAATC conductive hydro-gel exhibited high sensitivity(gauge factor(GF)=10.58 and sensitivity(S)=0.304 kPa^(-1)),wide strain response range(0.5%-1000%),fast response time(450 ms),and short recovery time(350 ms),excellent fatigue resistance,and strain response stability.Furthermore,the PAATC-based triboelectric nanogener-ator(TENG)displayed outstanding energy harvesting performance,which shows its potential for appli-cation in self-powered electronic devices.

关键词： Low hysteresis Covalent-like hydrogen bonding Boron-nitrogen coordination Hydrogel sensor Triboelectric nanogenerator

Multi-scale sparse feature point correspondence by graph cuts

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Science China(Information Sciences) 2010年第6期53卷 1224-1232页

作者： ZHANG Hong 1 , MU Ying 1 , YOU YuHu 2 & LI JunWei 3 1 image processing center, Beihang University, Beijing 100191, China 2 Beijing Research Institute of Special Electromechanical Technology, Beijing 100012, China 3 National Key Laboratory on Optical Features of Environment and Target, Beijing 100854, China image processing center Beihang University Beijing China Beijing Research Institute of Special Electromechanical Technology Beijing China National Key Laboratory on Optical Features of Environment and Target Beijing China

This paper presents a global stereo sparse matching technique based on graph cut theory to obtain accurate correspondence of stereo point pair in vision measurement applications.First, in order to obtain accurate location of feature points, a new multi-scale corner detection algorithm is proposed where wavelet coefficients are used to determine feature points by calculating an auto-correlation matrix.A sparse graph is constructed based on the feature points according to the graph cut theory.Then, the feature point correspondence problem is transformed into a labeling problem in the sparse graph which can be solved by energy minimization.Multi-scale analysis is utilized to improve the precision of matching results.It was found that the use of sparse feature points in the construction of the graph can lead to both a simple graph structure and a reduced computational complexity.It was also found that node labeling in the graph can be performed using fewer disparity values instead of all disparity values.Our experimental results show that the new global stereo sparse matching technique can obtain more accurate results than the existing techniques.

关键词： multi-scale feature point extraction graph cut theory stereo correspondence sparse point matching

Study on the green extraction of corncob xylan by deep eutectic solvent

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Grain & Oil Science and Technology 2024年第1期7卷 50-59页

作者： Bingyu Jiao Le Wang Haitao Gui Zifu Ni Rong Du Yuansen Hu School of Biological Engineering National Engineering Research Center of Wheat and Corn Further ProcessingZhengzhou 450001China

Corn as one of the world's major food crops,its by-product corn cob is also rich in resources.However,the unreasonable utilization of corn cob often causes the environmental pollution,waste of resources and other problems.As one of the most abundant polymers in nature,xylan is widely used in food,medicine,materials and other fields.Corn cob is rich in xylan,which is an ideal raw material for extracting xylan.However,the intractable lignin is covalently linked to xylan,which increases the difficulty of xylan extraction.It has been reported that the deep eutectic solvent(DES)could preferentially dissolve lignin in biomass,thereby dissolving the xylan.Then,the xylan in the extract was separated by ethanol precipitation method.The xylan precipitate was obtained after centrifugation,while the supernatant was retained.The components of the supernatant after ethanol precipitation were separated by the rotary evaporator.The ethanol,water and DES were collected for the subsequent extraction of corn cob xylan.In this study,a novel way was provided for the green production of corn cob xylan.The DES was used to extract xylan from corn cob which was used as the raw material.The effects of solid-liquid ratio,reaction time,reaction temperature and water content of DES on the extraction rate of corn cob xylan were investigated by the single factor test.Furthermore,the orthogonal test was designed to optimize the xylan extraction process.The structure of corn cob xylan was analyzed and verified.The results showed that the optimum extraction conditions of corn cob xylan were as follows:the ratio of corn cob to DES was 1:15(g:mL),the extraction time was 3 h,the extraction temperature was 60℃,and the water content of DES was 70%.Under these conditions,the extraction rate of xylan was 16.46%.The extracted corn cob xylan was distinctive triple helix of polysaccharide,which was similar to the structure of commercially available xylan.Xylan was effectively and workably extracted from corn cob by the DES method.This study provided a new

关键词： Corncob Deep eutectic solvent Xylan Process optimization Extraction