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Effect of Chinese medicine Qinggan Huoxuefang on inducing HSC apoptosis in alcoholic liver fibrosis rats

World Journal of Gastroenterology 2006年第13期12卷 2047-2052页

作者： Guang Ji Lei Wang shui-hua zhang Jian-Wen Liu Pei-Yong Zheng Tao Liu Laboratory of Liver Disease Longhua Hospital Shanghai University of Traditional Chinese Medicine Shanghai 200032 China Clinic Evaluation Center Longhua Hospital Shanghai University of Traditional Chinese Medicine Shanghai 200032 Chin Department of Pharmacy EastChina University of Science and Technology Shanghai 200237 China

AIM： To investigate the effect of Qinggan Huoxuefang （QGHXF） on improvement of liver function and pathology in rats, and to analyze the mechanism. METHODS： Wistar rats were divided into three groups at random： normal control group （12）, micro-amount carbon tetrachlodde group （CCh）（12） and model group A （60）. The model group A was ingested with the mixture （500 mL/L alcohol, 8 mL/kg per day; corn oil, 2 mL/kg per day; pyrazole, 24 mg/kg per day） once a day and intraperitoneal injections of 0.25 mL/kg of a 250 mL/L solution of CCh in olive oil twice a week for 12 wk. The CCh group received intraperitoneal injections only. At the end of 8 wk the model group A （60） was divided into 5 subgroups： model group, Xiaochaihu Chongji （XCH） group, QGHXF high dose group, moderate dose group and low dose group, and were given the drugs respectively. At the end of 12 wk, all the rats were killed and blood samples collected, as well as liver tissue. Blood samples were used for evaluation of alanine transaminase （ALT）, aspartate aminotransferase （AST）, alkaline phosphatase （ALP）, gamma-glutamyltransferase （y-GT）. Liver specimens were obtained for routine HE, apoptosis gene array and flow cytometry analysis. RESULTS： A liver fibrosis animal model was successfully established. Fibrosis was obviously reduced in QGHXF high dose group, and no fibrosis formed in CCh group. Compared with model group the QGHXF group and XCH group could obviously decrease the level of ALT, AST, ALP, and GGT （P〈0.05）. QGHXF high dose group was better than XCH group in ALT （615± 190 vs 867± 115）,and AST（1972 ± 366 vs 2777 ± 608）. Moreover, QGHXF could reduce liver inflammation, fibrosis-induced hepatic stellate cell （HSC） apoptosis and regulate apoptosis gene expression. The HSC apoptosis rates of QGHXF groups were 22.4±3.13, 13.79±2.26 and 10.07± 1.14, higher than model group, 6.58±1.04 （P〈 0.05）. Compared to model group, 39 genes were up-regulated, 11 solely expressed and 17 down-regulated in high dose group.

关键词： Qinggan Huoxuefang Alcoholic liver fibrosis Apoptosis Gene array

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Immunological Effect of Subunit Influenza Vaccine Entrapped by Liposomes

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Biomedical and Environmental Sciences 2009年第5期22卷 388-393页

作者： shui-hua zhang JIA-XU LIANG SHU-YAN DAI XIAO-LIN QIU YAN-RONG YI YUN PAN College of Life Sciences and Technology Shanghai Jiao Tong University Shanghai 200240 China Shenzhen Neptunus Interlong Bio-technique Company Ltd Shenzhen 518054 Guangdong China

Objective To elevate the immunological effect of subunit influenza vaccine in infants and aged people （over 60） using liposomal adjuvant in the context of its relatively low immunity and to investigate the relation between vaccine antigens and liposomal characteristics. Methods Several formulations of liposomal subunit influenza vaccine were prepared. Their relevant characteristics were investigated to optimize the preparation method. Antisera obtained from immunizinged mice were used to evaluate the antibody titers of various samples by HI and EL1SA. Results Liposomal trivalent influenza vaccine prepared by film evaporation in combinedation with freeze-drying significantly increased its immunological effect in SPF Balb/e mice. Liposomal vaccine stimulated the antibody titer of H3N2, H1N1, and B much stronger than conventional influenza vaccine. As a result, liposomal vaccine （mean size： 4.5-5.5 pm, entrapment efficiency： 30%-40%） significantly increased the immunological effect of subunit influenza vaccine. Conclusion The immune effect of liposomal vaccine depends on different antigens, and enhanced immunity is not positively correlated with the mean size of liposome or its entrapped efficiency.

关键词： Liposome Subunit influenza vaccine Size distribution Mean size Entrapped efficiency

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On the Pathwise Uniqueness of Solutions of One-dimensional Reflected Stochastic Differential Equations with Jumps

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Acta Mathematicae Applicatae Sinica 2024年第1期40卷 149-163页

作者： hua zhang School of Statistics and Data Science&Key Laboratory of Data Science in Finance and Economics Jiangxi University of Finance and EconomicsNanchang330013China

In this paper, we are concerned with the problem of the pathwise uniqueness of one-dimensional reflected stochastic differential equations with jumps under the assumption of non-Lipschitz continuous coefficients whose... 详细信息

关键词： reflected diffusion processes with jumps pathwise uniqueness local time Meyer It?'s formula

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Nuclear charge radius predictions by kernel ridge regression with odd-even effects

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Nuclear Science and Techniques 2024年第2期35卷 94-102页

作者： Lu Tang Zhen-hua zhang Mathematics and Physics Department North China Electric Power UniversityBeijing 102206China Hebei Key Laboratory of Physics and Energy Technology North China Electric Power UniversityBaoding 071000China

The extended kernel ridge regression(EKRR)method with odd-even effects was adopted to improve the description of the nuclear charge radius using five commonly used nuclear *** are:(i)the isospin-dependent A^(1∕3) formula,(ii)relativistic continuum Hartree-Bogoliubov(RCHB)theory,(iii)Hartree-Fock-Bogoliubov(HFB)model HFB25,(iv)the Weizsacker-Skyrme(WS)model WS*,and(v)HFB25**** the last two models,the charge radii were calculated using a five-parameter formula with the nuclear shell corrections and deformations obtained from the WS and HFB25 models,*** each model,the resultant root-mean-square deviation for the 1014 nuclei with proton number Z≥8 can be significantly reduced to 0.009-0.013 fm after considering the modification with the EKRR *** best among them was the RCHB model,with a root-mean-square deviation of 0.0092 *** extrapolation abilities of the KRR and EKRR methods for the neutron-rich region were examined,and it was found that after considering the odd-even effects,the extrapolation power was improved compared with that of the original KRR *** strong odd-even staggering of nuclear charge radii of Ca and Cu isotopes and the abrupt kinks across the neutron N=126 and 82 shell closures were also calculated and could be reproduced quite well by calculations using the EKRR method.

关键词： Nuclear charge radius Machine learning Kernel ridge regression method

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Probabilistic back-analysis of rainfall-induced landslides for slope reliability prediction with multi-source information

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第9期16卷 3575-3594页

作者： shui-hua Jiang Hong-Hu Jie Jiawei Xie Jinsong huang Chuang-Bing Zhou School of Infrastructure Engineering Nanchang UniversityXuefu Road 999Nanchang330031China Discipline of Civil Surveying and Environmental EngineeringFaculty of Engineering and Built EnvironmentThe University of NewcastleCallaghanNSW2308Australia

Probabilistic back-analysis is an important means to infer the statistics of uncertain soil parameters,making the slope reliability assessment closer to the engineering ***,multi-source information(including test data,monitored data,field observation and slope survival records)is rarely used in current probabilistic *** the probabilistic back-analysis of spatially varying soil parameters and slope reliability prediction under rainfalls by integrating multi-source information is a challenging task since thousands of random variables and high-dimensional likelihood function are usually *** this paper,a framework by integrating a modified Bayesian Updating with Subset simulation(mBUS)method with adaptive Conditional Sampling(aCS)algorithm is established for the probabilistic back-analysis of spatially varying soil parameters and slope reliability *** this framework,the high-dimensional probabilistic back-analysis problem can be easily tackled,and the multi-source information(*** pressure heads and slope survival records)can be fully used in the back-analysis.A real Taoyuan landslide case in Taiwan,China is investigated to illustrate the effectiveness and performance of the established *** findings show that the posterior knowledge of soil parameters obtained from the established framework is in good agreement with the field ***,the updated knowledge of soil parameters can be utilized to reliably predict the occurrence probability of a landslide caused by the heavy rainfall event on September 12,2004 or forecast the potential landslides under future rainfalls in the Fuhsing District of Taoyuan City,Taiwan,China.

关键词： Rainfall-induced landslide Spatial variability Probabilistic back-analysis Slope reliability analysis Bayesian updating

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Novel intelligent reasoning system for tool wear prediction and parameter optimization in intelligent milling

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Advances in Manufacturing 2024年第1期12卷 76-93页

作者： Long-hua Xu Chuan-Zhen huang Zhen Wang Han-Lian Liu shui-Quan huang Jun Wang School of Mechanical Engineering Yanshan UniversityQinhuangdao066004HebeiPeople’s Republic of China Center for Advanced Jet Engineering Technologies(CaJET) Key Laboratory of High-efficiency and Clean Mechanical Manufacture(Ministry of Education)National Experimental Teaching Demonstration Center for Mechanical Engineering(Shandong University)School of Mechanical EngineeringShandong UniversityJinan250061People’s Republic of China Institute of Manufacturing Technology Guangdong University of TechnologyGuangzhou510006People’s Republic of China

Accurate intelligent reasoning systems are vital for intelligent *** this study,a new intelligent reasoning system was developed for milling processes to accurately predict tool wear and dynamically optimize machining *** developed system consists of a self-learning algorithm with an improved particle swarm optimization(IPSO)learning algorithm,prediction model determined by an improved case-based reasoning(ICBR)method,and optimization model containing an improved adaptive neural fuzzy inference system(IANFIS)and *** results showed that the IPSO algorithm exhibited the best global convergence *** ICBR method was observed to have a better performance in predicting tool wear than standard CBR *** IANFIS model,in combination with IPSO,enabled the optimization of multiple objectives,thus generating optimal milling *** paper offers a practical approach to developing accurate intelligent reasoning systems for sustainable and intelligent manufacturing.

关键词： Improved particle swarm optimization(IPSO)algorithm Improved case-based reasoning(ICBR)method Adaptive neural fuzzy inference system(ANFIS)model Tool wear prediction Intelligent manufacturing

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Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第1期16卷 213-230页

作者： Faming huang Zuokui Teng Chi Yao shui-hua Jiang Filippo Catani Wei Chen Jinsong huang School of Infrastructure Engineering Nanchang UniversityNanchang330031China State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Chengdu University of TechnologyChengdu610059China Department of Geosciences University of PadovaPadovaItaly College of Geology and Environment Xi’an University of Science and TechnologyXi’an710054China Discipline of Civil Surveying and Conditioning EngineeringPriority Research Centre for Geotechnical Science and EngineeringUniversity of NewcastleNewcastleNSWAustralia

In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP *** study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning *** original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP ***,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter ***,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study *** typical machine learning models,*** perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP ***,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide *** conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random e

关键词： Landslide susceptibility prediction Conditioning factor errors Low-pass filter method Machine learning models Interpretability analysis

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A novel weld-pool-length monitoring method based on pixel analysis in plasma arc additive manufacturing

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Advances in Manufacturing 2024年第2期12卷 335-348页

作者： Bao-Ri zhang Yong-hua Shi Bionic Robot Research Department Ji Hua LaboratoryFoshan528200GuangdongPeople’s Republic of China Guangdong Provincial Engineering Research Center for Special Welding Technology and Equipment School of Mechanical and Automotive EngineeringSouth China University of TechnologyGuangzhou510640People’s Republic of China

The real-time monitoring of the weld pool during deposition is important for automatic control in plasma arc additive *** obtain a high deposition accuracy,it is essential to maintain a stable weld pool *** this study,a novel passive visual method is proposed to measure the weld pool *** the proposed method,the image quality was improved by designing a special visual system that employed an endoscope and a *** also includes pixel brightness-based and gradient-based algorithms that can adaptively detect feature points at the boundary when the weld pool geometry *** algorithm can also be applied to materials with different solidification *** was performed to measure the real weld pool length in world coordinates,and outlier rejection was performed to increase the accuracy of the ***,tests were carried out on the intersection component,and the results showed that the proposed method performed well in tracking the changing weld pool length and was applicable to the real-time monitoring of different types of materials.

关键词： Plasma arc additive manufacturing(PAAM) Weld pool geometry Gradient analysis Real-time detection

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Synthesis strategies of hard carbon anodes for sodium-ion batteries

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Materials Reports(Energy) 2024年第2期4卷 1-22页

作者： Jian Yin Ye shui zhang Hanfeng Liang Wenli zhang Yunpei Zhu Laboratory of Environmental Sciences and Technology Xinjiang Technical Institute of Physics&ChemistryChinese Academy of SciencesUrumqi830011China Materials Science and Engineering Physical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal23955-6900Saudi Arabia School of Engineering University of AberdeenAberdeenAB243UEUK State Key Laboratory of Physical Chemistry of Solid Surfaces Tan Kah Kee Innovation Laboratory(IKKEM)College of Chemistry and Chemical EngineeringXiamen UniversityXiamen361005China Guangdong Provincial Laboratory of Chemistry and Fine Chemical Engineering Jieyang Center Jieyang515200China Guangdong Provincial Key Laboratory of Plant Resources Biorefinery School of Chemical Engineering and Light IndustryGuangdong University of Technology(GDUT)Panyu DistrictGuangzhou510006China School of Advanced Manufacturing Guangdong University of Technology(GDUT)Jieyang522000China

Sodium-ion battery(SIB)is an ideal candidate for large-scale energy storage due to high abundant sodium sources,relatively high energy density,and potentially low *** carbons,as one of the most promising anodes,could deliver high plateau capacities at low potentials,which boosts the energy densities of *** slope capacities have been demonstrated from the defect adsorption of sodium ions,while the plateau capacity depends highly on intercalation and pore ***,the specific structures of sodium ions stored in hard carbons have not been clarified,namely active sites of adsorption,intercalation,and pore-filling ***,delicate synthesis methods are required to prepare hard carbons with controllable specific structures,along with elucidating the precise active sites for enhancing the Na-ion storage *** offer databases for future designs,we summarized the synthesis strategies of hard carbon anodes for constructing active sites of plateau *** methods were highlighted with corresponding influences on the meticulous structures of hard carbons and Na-ion storage *** but not least,perspectives were proposed for developing hard carbon anodes from the points of research and practical applications.

关键词： Hard carbon anodeCarbon synthesisSodium-ion batteryStructure-function relationship

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CF-DAN: Facial-expression recognition based on cross-fusion dual-attention network

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Computational Visual Media 2024年第3期10卷 593-608页

作者： Fan zhang Gongguan Chen hua Wang Caiming zhang Shandong Technology and Business University Shandong 264005China School of Information and Electrical Engineering Ludong UniversityYantai 264025China Shangdong University Shandong 250100China

Recently, facial-expression recognition (FER)has primarily focused on images in the wild, includingfactors such as face occlusion and image blurring, ratherthan laboratory images. Complex field environmentshave introduced new challenges to FER. To addressthese challenges, this study proposes a cross-fusion dualattention network. The network comprises three parts:(1) a cross-fusion grouped dual-attention mechanism torefine local features and obtain global information;(2) aproposed C2 activation function construction method,which is a piecewise cubic polynomial with threedegrees of freedom, requiring less computation withimproved ﬂexibility and recognition abilities, whichcan better address slow running speeds and neuroninactivation problems;and (3) a closed-loop operationbetween the self-attention distillation process andresidual connections to suppress redundant informationand improve the generalization ability of the *** recognition accuracies on the RAF-DB, FERPlus,and AffectNet datasets were 92.78%, 92.02%, and63.58%, respectively. Experiments show that this modelcan provide more effective solutions for FER tasks.

关键词： facial-expression recognition(FER) cubic polynomial activation function dualattention mechanism interactive learning self-attention distillation

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