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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2009年第6期10卷 465-471页

作者： Li-juan XIE yi-bin ying College of Biosystems Engineering and Food Science Zhejiang University Hangzhou 310029 China

Near-infrared (NIR) transmittance spectroscopy combined with least-squares support vector machine (LS-SVM) was investigated to study the quality change of tomato juice during the storage. A total of 100 tomato juice samples were used. The spectrum of each tomato juice was collected twice: the first measurement was taken when the tomato juice was fresh and had not undergone any changes, and the second measurement was taken after a month. Principal component analysis (PCA) was used to examine a potential capability of separating juice before and after the storage. The soluble solid content (SSC) and pH of the juice samples were determined. The results show that changes in certain compounds between tomato juice before and after the storage period were obvious. An excellent precision was achieved by LS-SVM model compared with discriminant partial least-squares (DPLS), soft independent modeling of class analogy (SIMCA), and discriminant analysis (DA) models, with 100% of a total accuracy. It can be found that NIR spectroscopy coupled with LS-SVM, DPLS, SIMCA, and DA can be used to control the quality change of tomato juice during the storage.

关键词： Near-infrared (NIR) spectroscopy Least squares-support vector machine (LS-SVM) Quality change Tomato juice

Application of NIR spectroscopy for firmness evaluation of peaches

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2008年第7期9卷 552-557页

作者： Xia-ping FU yi-bin ying ying ZHOU Li-juan XIE Hui-rong XU College of Biosystems Engineering and Food Science Zhejiang University Hangzhou 310029 China

The use of near infrared （NIR） spectroscopy was proved to be a useful tool for quality analysis of fruits. A bifurcated fiber type NIR spectrometer, with a detection range of 800-2500 nm by InGaAs detector, was used to evaluate the firmness of peaches. Anisotropy of NIR spectra and firmness of peaches in relation to detecting positions of different parts （including three latitudes and three longitudes） were investigated. Both spectra absorbency and firmness of peach were influenced by longitudes （i, ii, iii） and latitudes （A, B, C）. For modeling, two thirds of the samples were used as the calibration set and the remaining one third were used as the validation or prediction set. Partial least square regression （PLSR） models for different longitude and latitude spectra and for the whole fruit show that collecting several NIR spectra from different longitudes and latitudes of a fruit for NIR calibration modeling can improve the modeling performance. In addition, proper spectra pretreatments like scattering correction or derivative also can enhance the modeling performance. The best results obtained in this study were from the holistic model with multiplicative scattering correction （MSC） pretreatment, with correlation coefficient of cross-validation γcv=0.864, root mean square error of cross-validation RMSECV=6.71 N, correlation coefficient of calibration r=0.948, root mean square error of calibration RMSEC=4.21 N and root mean square error of prediction RMSEP=5.42 N. The results of this study are useful for further research and application that when applying NIR spectroscopy for objectives with anisotropic differences, spectra and quality indices are necessarily measured from several parts of each object to improve the modeling performance.

关键词： Near infrared (NIR) Anisotropy Peach Firmness Partial least square regression (PLSR)

Development of a miniature silicon wafer fuel cell using L-ascorbic acid as fuel

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2008年第7期9卷 955-960页

作者： Jian WU Zhi-yong XIAO yi-bin ying Philip C.H. CHAN School of Biosvstems Engineering and Food Science Zhejiang University Hangzhou 310029 China Department of Electrical and Electronic Engineering Hong Kong University of Science and Technology Hong Kong China

In the current studies a miniature silicon wafer fuel cell(FC) using L-ascorbic acid as fuel was developed. The cell employs L-ascorbic acid and air as reactants and a thin polymer electrolyte as a separator. Inductively coupled plasma(ICP) silicon etching was employed to fabricate high aspect-ratio columns on the silicon substrate to increase the surface area. A thin platinum layer deposited directly on the silicon surface by the sputtering was used as the catalyst layer for L-ascorbic acid electro-oxidation. Cyclic voltammetry shows that the oxidation of L-ascorbic acid on the sputtered platinum layer is irreversible and that the onset potentials for the oxidation of L-ascorbic acid are from 0.27 V to 0.35 V versus an Ag/AgCl reference electrode. It is found that at the room temperature,with 1 mol/L L-ascorbic acid/PBS(phosphate buffered solution) solution pumped to the anode at 1 ml/min flow rate and air spontaneously diffusing to the cathode as the oxidant,the maximum output power density of the cell was 1.95 mW/cm2 at a current density of 10 mA/cm2.

关键词： L-ascorbic acid Fuel cell (FC) Silicon wafer

On-site variety discrimination of tomato plant using visible-near infrared reflectance spectroscopy

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2009年第2期10卷 126-132页

作者： Hui-rong XU Peng YU Xia-ping FU yi-bin ying College of Biosystems Engineering and Food Science Zhejiang University Hangzhou 310029 China

The use of visible-near infrared (NIR) spectroscopy was explored as a tool to discriminate two new tomato plant varieties in China (Zheza205 and Zheza207). In this study, 82 top-canopy leaves of Zheza205 and 86 top-canopy leaves of Zheza207 were measured in visible-NIR reflectance mode. Discriminant models were developed using principal component analysis (PCA), discriminant analysis (DA), and discriminant partial least squares (DPLS) regression methods. After outliers detection, the samples were randomly split into two sets, one used as a calibration set (n=82) and the remaining samples as a validation set (n=82). When predicting the variety of the samples in validation set, the classification correctness of the DPLS model after optimizing spectral pretreatment was up to 93%. The DPLS model with raw spectra after multiplicative scatter cor- rection and Savitzky-Golay filter smoothing pretreatments had the best satisfactory calibration and prediction abilities (correlation coefficient of calibration (Rc)=0.920, root mean square errors of calibration=0.196, and root mean square errors of predic- tion=0.216). The results show that visible-NIR spectroscopy might be a suitable alternative tool to discriminate tomato plant varieties on-site.

关键词： Visible-NIR spectroscopy Tomato plant variety Discrimination Principal component analysis (PCA) Discriminant analysis (DA) Discriminant partial least squares (DPLS)

Application of principal component-radial basis function neural networks (PC-RBFNN) for the detection of water-adulterated bayberry juice by near-infrared spectroscopy

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2008年第12期9卷 982-989页

作者： Li-juan XIE Xing-qian YE Dong-hong LIU yi-bin ying College of Biosystems Engineering and Food Science Zhejiang University Hangzhou 310029 China

Near-infrared (NIR) spectroscopy combined with chemometrics techniques was used to classify the pure bayberry juice and the one adulterated with 10% (w/w) and 20% (w/w) water. Principal component analysis (PCA) was applied to reduce the dimensions of spectral data, give information regarding a potential capability of separation of objects, and provide principal component (PC) scores for radial basis function neural networks (RBFNN). RBFNN was used to detect bayberry juice adulterant. Multiplicative scatter correction (MSC) and standard normal variate (SNV) transformation were used to preprocess spectra. The results demonstrate that PC-RBFNN with optimum parameters can separate pure bayberry juice samples from water-adulterated bayberry at a recognition rate of 97.62%, but cannot clearly detect water levels in the adulterated bayberry juice. We conclude that NIR technology can be successfully applied to detect water-adulterated bayberry juice.

关键词： Near-infrared (NIR) spectroscopy Principal component-radial basis function neural networks (PC-RBFNN) Bayberry juice Adulteration Chemometrics technique

Determination of soluble solid content and acidity of loquats based on FT-NIR spectroscopy

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2009年第2期10卷 120-125页

作者： Xia-ping FU Jian-ping LI ying ZHOU yi-bin ying Li-juan XIE Xiao-ying NIU Zhan-ke YAN Hai-yan YU College of Biosystem Engineering and Food Science Zhejiang University Hangzhou 310029 China

The near infrared （NIR） spectroscopy technique has been applied in many fields because of its advantages of simple preparation, fast response, and non-destructiveness. We investigated the potential of NIR spectroscopy in diffuse reflectance mode for determining the soluble solid content （SSC） and acidity （pH） of intact loquats. Two cultivars of loquats （Dahongpao and Jiajiaozhong） harvested from two orchards （Tangxi and Chun＇an, Zhejiang, China） were used for the measurement of NIR spectra between 800 and 2500 nm. A total of 400 loquats （100 samples of each cultivar from each orchard） were used in this study. Relationships between NIR spectra and SSC and acidity of loquats were evaluated using partial least square （PLS） method. Spectra preprocessing options included the first and second derivatives, multiple scatter correction （MSC）, and the standard normal variate （SNV）. Three separate spectral windows identified as full NIR （800-2500 nm）, short NIR （800-1100 rim）, and long NIR （1100-2500 nm） were studied in factorial combination with the preprocessing options. The models gave relatively good predictions of the SSC of loquats, with root mean square error of prediction （RMSEP） values of 1.21, 1.00, 0.965, and 1.16 °Brix for Tangxi-Dahongpao, Tangxi-Jiajiaozhong, Chun＇an-Dahongpao, and Chun＇an-Jiajiaozhong, respectively. The acidity prediction was not satisfactory, with the RMSEP of 0.382, 0.194, 0.388, and 0.361 for the above four loquats, respectively. The results indicate that NIR diffuse reflectance spectroscopy can be used to predict the SSC and acidity of loquat fruit.

关键词： Near infrared (NIR) spectroscopy Loquats Soluble solid content (SSC) Acidity Partial least square (PLS) Modeling Spectra preprocessing

DLP:towards active defense against backdoor attacks with decoupled learning process

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Cybersecurity 2024年第1期7卷 122-134页

作者： Zonghao ying bin Wu State Key Laboratory of Information Security Institute of Information EngineeringChinese Academy of SciencesBeijingChina School of Cyber Security University of Chinese Academy of SciencesBeijingChina

Deep learning models are well known to be susceptible to backdoor attack,where the attacker only needs to provide a tampered dataset on which the triggers are *** trained on the dataset will passively implant the backdoor,and triggers on the input can mislead the models during *** study shows that the model shows different learning behaviors in clean and poisoned subsets during *** on this observation,we propose a general training pipeline to defend against backdoor attacks *** models can be trained from the unreli-able dataset by decoupling the learning process into three stages,i.e.,supervised learning,active unlearning,and active semi-supervised *** effectiveness of our approach has been shown in numerous experiments across various backdoor attacks and datasets.

关键词： Deep learning Backdoor attack Active defense

Scattering for the Radial Schrodinger Equation with Combined Power-type and Choquard-type Nonlinearities

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Acta Mathematica Sinica,English Series 2024年第4期40卷 1029-1041页

作者： ying WANG Cheng bin XU The Graduate School of China Academy of Engineering Physics Beijing 100088P.R.China School of Mathematics and Statistics Qinghai Normal UniversityXining 810008P.R.China

In this paper,we show the scattering of the radial solution for the nonlinear Schrodinger equation with combined power-type and Choquard-type nonlinearities iut+△u=λ1|u|p1-1u+λ2(Iα*|u|^(p2))|u|p^(2-2)*** the energy space H^(1)(R^(N))forλ_(1)λ_(2)=-*** establish a scattering criterion for radial solution together with Morawetz estimate which implies the scattering *** show that the defocusing perturbation terms does not determine the scattering solution in energy space.

关键词： Schrodinger equation Choquard-type Scattering theory

Gene therapy for monogenic disorders: challenges, strategies, and perspectives

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Journal of Genetics and Genomics 2024年第2期51卷 133-143页

作者： yi Zhang Zhi-ying Wu Department of Medical Genetics and Center for Rare Diseases Second Affiliated HospitalZhejiang University School of MedicineHangzhouZhejiang 310009China Department of Neurology Second Affiliated HospitalZhejiang University School of MedicineHangzhouZhejiang 310009China Key Laboratory of Medical Neurobiology of Zhejiang Province HangzhouZhejiang 310009China

Monogenic disorders refer to a group of human diseases caused by mutations in single genes. While disease-modifying therapies have offered some relief from symptoms and delayed progression for some monogenic diseases, most of these diseases still lack effective treatments. In recent decades, gene therapy has emerged as a promising therapeutic strategy for genetic disorders. Researchers have developed various gene manipulation tools and gene delivery systems to treat monogenic diseases. Despite this progress, concerns about inefficient delivery, persistent expression, immunogenicity, toxicity, capacity limitation, genomic integration, and limited tissue specificity still need to be addressed. This review gives an overview of commonly used gene therapy and delivery tools, along with the challenges they face and potential strategies to counter them.

关键词： Gene therapy Monogenic diseases Geneediting Genedelivery Challenges

Advanced Design of Soft Robots with Artificial Intelligence

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Nano-Micro Letters 2024年第10期16卷 474-521页

作者： ying Cao bingang Xu bin Li Hong Fu Nanotechnology Center School of Fashion and TextilesThe Hong Kong Polytechnic UniversityHong Kong 999077People's Republic of China Department of Mathematics and Information Technology The Education University of Hong KongHong Kong 999077People's Republic of China Bioinspired Engineering and Biomechanics Center Xi'an Jiaotong UniversityXi'an 710049People's Republic of China

In recent years,breakthrough has been made in the field of artificial intelligence(AI),which has also revolutionized the industry of *** robots featured with high-level safety,less weight,lower power consumption have always been one of the research ***,multifunctional sensors for perception of soft robotics have been rapidly developed,while more algorithms and models of machine learning with high accuracy have been optimized and *** of soft robots with AI have also been advanced ranging from multimodal sensing,human-machine interaction to effective actuation in robotic ***-less,comprehensive reviews concerning the new developments and strategies for the ingenious design of the soft robotic systems equipped with AI are ***,the new development is systematically reviewed in the field of soft robots with ***,background and mechanisms of soft robotic systems are briefed,after which development focused on how to endow the soft robots with AI,including the aspects of feeling,thought and reaction,is ***,applications of soft robots with AI are systematically summarized and discussed together with advanced strategies proposed for performance *** thoughts for future intelligent soft robotics are pointed ***,some perspectives are put forward.

关键词： Soft robotic systems Artificial intelligence Design tactics Review and perspective