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| 1 | In vivo fiber photometry of neural activity in response to optogenetically manipulated inputs in freely moving mice显示文摘In vito fber photometry is a powerful technique to analyze the dy namics of population neurons during fiunctional study of neuroscience.Here,we introduced a detailed protocol for fiber photometry-based calciun reording in freely moving mice,covering from virus injection,fiber stub insertion,optogenetical stimulation to data procurement and analysis.Furthemnore,we applied this protocol to explore neuronal activity of mice latenal-posterior(LP)thalaric nucleus in response to optogenetical stimulation of primary visual cortex(V1)neurons,and explore axon clusters activity of optogenetically evoked V1 neurons.Final confirmation of virus-based protein expression in V1 and precise fber insertion indicated that the surgery procedure of this protocol is reliable for functional calcium recording.The scripts for data analysis and some tips in our protocol are provided in details.Together,this protocol is simple,low-cost,and effective for neuronal activity detection by fiber photometry,which will hep neuroscience researchers to carry out fiunctional and behavioral study in vivo. | Liang Li Yajie Tang Leqiang Sun Khaista Rahman Kai Huang Weize Xu Jinsong Yu Jinxia Dai Gang Cao | 2017 | Journal of Innovative Optical Health Sciences2017，，5： | 1 |
| 2 | Comprehensive Evaluation on Impacts of Diseases on Quality of Paris polyphylla var. chinensis Based on Ultraviolet and Infrared Spectra显示文摘[Objectives] The research aimed to evaluate impacts of diseases on quality of Paris polyphylla var. chinensis. [Methods]Ultraviolet spectrophotometry was used to determine and contrast content of total saponins in root,stem and leaf from healthy and diseased plants. Infrared characteristic absorption peaks of healthy and diseased plants were found by infrared fingerprint method for comparative analysis.[Results]Total saponins content in root sample J4 of healthy plant reached 4. 89% and was the highest,while it was 0. 13% in stem sample J11 of healthy plant and was the lowest. Total saponins content in root sample B1 of diseased plant was 1. 68% and was the highest,while it was 0. 1% in stem sample B7 of diseased plant and was the lowest. In healthy and diseased plants,total saponins content in root was significantly higher than that in stem and leaf. Content of total saponins in root from healthy plant was significantly higher than that from diseased plant,and there was little difference in stem and leaf of healthy and diseased plants. Root sample Jg of healthy plant had obvious C-O characteristic vibration of polysaccharides and glycosides and absorption peak of O-H bending vibration in steroidal saponin near 1 160. 02 cm-1,while diseased plant had no obvious absorption peak. Near 861. 97 and 768. 07 cm-1,root sample Jg of healthy plant had significant C-C stretching vibration in sugar ring and characteristic absorption peak of characteristic vibration of steroidal saponin,while root sample Bg of diseased plant had no obvious characteristic peak. [Conclusions] Diseases significantly affected composition and content of total saponins and steroidal saponins from P. polyphylla var. chinensis,further affecting quality of P. polyphylla var. chinensis. | Yongxia KE Jixiu SHEN Hairong ZHONG Risha WEIZE Yunzhang XU Yuan LIU | 2019 | Medicinal Plant2019，10，3： | 1 |
| 3 | Clock feedthrough in CMOS analog transmission gate switches显示文摘 | XU Weize Friedman E G | 2005 | Analog Integrated Circuits and Signal Processing2005，44，： | 1 |
| 4 | Determination of Inorganic Elements in Paris daliensis H.Li et V.G.Souku and Paris dulongensis H.Li et S.Kuritap by ICP-OES显示文摘[Objectives] To determine 29 kinds of inorganic elements in samples of Paris daliensis H.Li et V.G.Souku and P. dulongensis H.Li et S.Kuritap produced in different regions, and to measure the content of 10 key inorganic elements: chromium(Cr), manganese(Mn), iron(Fe), copper(Cu), mercury(Hg), zinc(Zn), arsenic(As), antimony(Sr), cadmium(Cd) and lead(Pb). [Methods] The wet digestion and technique of inductively coupled plasma optical emission spectrometry(ICP-OES) were employed. [Results] Under the experimental conditions, elements were not related to each other, and many kinds of elements could be measured at the same time; toxic and heavy metals in samples of P. daliensis H.Li et V.G.Souku and P. dulongensis H.Li et S.Kuritap did not exceed the limit; Hg was not detected in all samples. [Conclusions] This method is simple, easy to operate and reproducible. It can be used for the detection of inorganic elements in P. daliensis H.Li et V.G.Souku and P. dulongensis H.Li et S.Kuritap; the heavy metals and Hg of the rhizome meet the requirements of the limit of medicinal materials. | Jixiu SHEN Zhongjie HUANG Risha WEIZE Xuexue LI Yunzhang XU Yuan LIU | 2019 | Medicinal Plant2019，10，1： | 1 |
| 5 | Determination of Moisture, Ash, Extract Content and TLC identification of Tibetan Medicinal Material Dracocephalum tanguticum Maxim.显示文摘[Objectives] The moisture, ash and extract content of Dracocephalum tanguticum Maxim. were measured.[Methods] The moisture, total ash, acid-insoluble ash and extract content of D. tanguticum Maxim collected from 16 producing areas were detected by using the methods in Chinese Pharmacopoeia (2015 edition, volume I), and D. tanguticum Maxim. was identified by thin layer chromatography in Chinese Pharmacopoeia (2015 edition, volume I).[Results] The moisture content of D. tanguticum Maxim collected from 16 producing areas ranged from 8.68% to 10.36%, averaging 9.28%. The content of total ash was between 7.21% and 11.60%, averaging 9.89%. The content of acid-insoluble ash was 0.21%-2.71%, averaging 1.51%. The extract content (water-soluble) was 26.67%-42.91%, averaging 32.65%. According to the results of TLC identification, the 16 samples and reference substance had the same characteristic spots at the corresponding positions.[Conclusions] It was recommended that the moisture, total ash and acid-insolue ash content of D. tanguticum Maxim were not be more than 11%, 12%, and 3% respectively, while the extract content was not less than 26%. It provides reference for filling the gaps in the quality standards of D. tanguticum Maxim. | Pei QUN Risha WEIZE Zhe LIU Haiyan XIANG Yunzhang XU Yuan LIU | 2019 | Medicinal Plant2019，10，4： | 1 |
| 6 | l_(1)-norm Based GWLP for Robust Frequency Estimation显示文摘In this work,we address the frequency estimation problem of a complex single-tone embedded in the heavy-tailed noise.With the use of the linear prediction(LP)property and l_(1)-norm minimization,a robust frequency estimator is developed.Since the proposed method employs the weighted l_(1)-norm on the LP errors,it can be regarded as an extension of the l_(1)-generalized weighted linear predictor.Computer simulations are conducted in the environment of α-stable noise,indicating the superiority of the proposed algorithm,in terms of its robust to outliers and nearly optimal estimation performance. | Yuan Chen Liangtao Duan Weize Sun Jingxin Xu | 2019 | Journal on Big Data2019，1，3： | 0 |
| 7 | Two-Dimensional Interpolation Criterion Using DFT Coefficients显示文摘In this paper,we address the frequency estimator for 2-dimensional(2-D)complex sinusoids in the presence of white Gaussian noise.With the use of the sinc function model of the discrete Fourier transform(DFT)coefficients on the input data,a fast and accurate frequency estimator is devised,where only the DFT coefficient with the highest magnitude and its four neighbors are required.Variance analysis is also included to investigate the accuracy of the proposed algorithm.Simulation results are conducted to demonstrate the superiority of the developed scheme,in terms of the estimation performance and computational complexity. | Yuan Chen Liangtao Duan Weize Sun Jingxin Xu | 2020 | Computers, Materials & Continua2020，，2： | 0 |
| 8 | Screening for congenital heart defects: diversified strategies in current China显示文摘background Congenital heart defects(CHD)is the most common type of birth defect and a leading cause of infant mortality in China.Detection of CHD during newborn is still challenging.The contradiction between the increasingly mature technology of diagnosis and treatment and the inability of early detection is the biggest current dilemma.A few pilot studies attempt to establish the universal screening for CHD in newborns;however,the rate of misdiagnosis is still high in most Chinese hospitals,especially in some undeveloped middle-western regions.Data sources Based on the recent publications on screening of congenital heart diseases in China.We reviewed the use of diversified screening strategies in current China.results Prenatal diagnosis by fetal echocardiography and postnatal detection by pulse oximetry combined with clinical assessment are the useful methods for CHD screening in most areas.The altitude should be taken into account when using pulse oximetry in the middle-western areas of China,where the incidence of CHD maybe higher.Echocardiography is suitable for CHD screening in almost all areas but it could add to financial burden in the developing regions.Genetic analysis could assist clinical doctors to perform more earlier screening and give better counseling regarding the outcome.Due to disparities in economic and medical resources,the screening system should be carried out from multiple perspectives according to the present economic development.Notably,follow-up is an important issue in the screening of CHD,especially for the asymptomatic babies who discharged home.Policies should be formulated to address the epidemiology of CHD in deprived areas to better allocate medical resources and to develop local training programmes to screen and diagnose CHD.Conclusions Diversified strategies are available in current China.The two-indicator method for CHD screening is recommended to be implemented in routine postnatal care.We can do more in screening for CHD in the future. | Xiwang Liu Weize Xu Jiangen Yu Qiang Shu | 2019 | World Journal of Pediatric Surgery2019，2，1： | 0 |
| 9 | Behavior recognition and fuel consumption prediction of tractor sowing operations using smartphone显示文摘In order to qualitatively recognize the behaviors and investigate the relationship between fuel consumption and machinery driving modes of the tractor in a low-cost approach,this study proposed a method for behavior recognition and fuel consumption prediction of tractor sowing operations using a smartphone.First,three driving modes were developed for maize sowing scenarios:manual driving assisted driving and unmanned driving.While sowing,smartphone software and CAN(Controller Area Network)storage devices collected both positional data and engine operating conditions.Second,the tractor trajectory points were divided into kinematic sequences,with six driving cycle indicators built in each series based on the time window.Based on the semantic information of the kinematic sequences,the three operations of sowing,seeds filling,and turning round were well recognized.Last,a model for maize sowing fuel consumption forecast was advanced using the principal component analyses and random forest algorithm,regarding three factors:driving cycles,operating behaviors,and driving patterns.When compared to the traditional K-means algorithm,the results demonstrated that the harmonic mean of the precision and recall(F1 score)of sowing behavior recognition,seeds filling behavior recognition,and turning behavior recognition were enhanced by 2.06%,8.99%,and 21.79%,respectively.In terms of the impacts of driving modes and operating behaviors on fuel consumption,assisted driving mode had the lowest fuel usage for both sowing and turning behavior.Therefore,assisted driving is the most fuel-efficient mode for maize sowing.Combining the three driving modes,the relative error of the fuel consumption prediction model was 0.11 L/h,with the manual driving mode having the lowest relative error at 0.09 L/h.This research method lays the foundation for the optimization of tractor operation behavior,the selection of tractor driving mode,and the fine management of tractor fuel consumption. | Lili Yang Weize Tian Weixin Zhai Xinxin Wang Zhibo Chen Long Wen Yuanyuan Xu Caicong Wu | 2022 | International Journal of Agricultural and Biological Engineering2022，15，4： | 0 |
| 10 | CT quantification of ventricular volumetric parameters based on semiautomatic 3D threshold-based segmentation in porcine heart and children with tetralogy of Fallot:accuracy and feasibility显示文摘background To investigate the accuracy and feasibility of CT in quantification of ventricular volume based on semiautomatic three-dimensional(3D)threshold-based segmentation in porcine heart and children with tetralogy of Fallot(TOF).Methods Eight porcine hearts were used in the study.The atria were resected and both ventricles of the eight porcine hearts were filled with solidifiable silica gel and performed CT scanning.The water displacement volume of silica gel casting mould was referred as gold standard of ventricular volume.Results of left and right ventricular volumes measured by CT were compared with reference standard.Twenty-three children diagnosed with TOF were retrospectively included.The ventricular volumetric parameters were assessed by cardiac CT before and 6 months after surgery.results Left ventricular and right ventricular volumes of porcine hearts measured by CT were highly correlated to casting mould(r=0.845,p=0.008;r=0.933,p=0.001),and there were no statistically significant differences(t=−1.059,p=0.325;t=−1.121,p=0.299).In children with TOF,right ventricular end-systole volumes 6 months after operation were higher than that before surgery,21.93±4.44 vs 19.80±4.52 mL/m^(2),p=0.001.Right ventricular ejection fractions 6 months after surgery were lower compared with that before surgery 59.79%±4.26%vs 63.05%±5.04%,p=0.000.Conclusions CT is able to accurately assess ventricular volumetric parameters based on semiautomatic 3D threshold-based segmentation.Both of the right and left ventricular volumetric parameters could be evaluated by CT in children with TOF. | Jiajun Xu Yangfan Tian Jinhua Wang Weize Xu Zhuo Shi Jianzhong Fu Qiang Shu | 2019 | World Journal of Pediatric Surgery2019，2，3： | 0 |
| 11 | Rapid bacteria identification using structured illumination microscopy and machine learning显示文摘Traditionally,optical microscopy is used to visualize the morphological features of pathogenic bacteria,of which the features are further used for the detection and ident ification of the bacteria.However,due to the resolution limitation of conventional optical microscopy as well as the lack of standard pattern library for bacteria identification,the ffectiveness of this optical microscopy-based method is limited.Here,we reported a pilot study on a combined use of Structured Illumination Microscopy(SIM)with machine learning for rapid bacteria identification.After applying machine learning to the SIM image datasets from three model bacteria(including Escherichia coli,Mycobacterium smegmatis,and Pseudomonas aeruginosa),we obtained a classifcation accuracy of up to 98%.This study points out a promising possibility for rapid bacterial identification by morphological features. | Yingchuan He Weize Xu Yao Zhi Rohit Tyagi Zhe Hu Gang Cao | 2018 | Journal of Innovative Optical Health Sciences2018，，1： | 0 |
| 12 | Outlier Detection for Water Supply Data Based on Joint Auto-Encoder显示文摘With the development of science and technology,the status of the water environment has received more and more attention.In this paper,we propose a deep learning model,named a Joint Auto-Encoder network,to solve the problem of outlier detection in water supply data.The Joint Auto-Encoder network first expands the size of training data and extracts the useful features from the input data,and then reconstructs the input data effectively into an output.The outliers are detected based on the network’s reconstruction errors,with a larger reconstruction error indicating a higher rate to be an outlier.For water supply data,there are mainly two types of outliers:outliers with large values and those with values closed to zero.We set two separate thresholds,and,for the reconstruction errors to detect the two types of outliers respectively.The data samples with reconstruction errors exceeding the thresholds are voted to be outliers.The two thresholds can be calculated by the classification confusion matrix and the receiver operating characteristic(ROC)curve.We have also performed comparisons between the Joint Auto-Encoder and the vanilla Auto-Encoder in this paper on both the synthesis data set and the MNIST data set.As a result,our model has proved to outperform the vanilla Auto-Encoder and some other outlier detection approaches with the recall rate of 98.94 percent in water supply data. | Shu Fang Lei Huang Yi Wan Weize Sun Jingxin Xu | 2020 | Computers, Materials & Continua2020，，7： | 0 |
| 13 | An unusual cause of cyanosis after intra-extra cardiac Fontan procedure: anastomotic leakage between conduit and inferior vena cava显示文摘A child aged 7 years was admitted to our hospital nearly 5 years after an intra-extra cardiac Fontan operation due to aggravated cyanosis.He was diagnosed with pulmonary atresia(PA),atrial septal defect,patent ductus arteriosus(PDA)and thickened tricuspid valve with severe regurgitation 1 month after being born,which was considered PA with intact ventricular septum(IVS)with severely hypoplastic right ventricle and was similar to functional single ventricle. | Jiajun Xu Weize Xu Jin Yu Shanshan Shi Qiang Shu Zhuo Shi | 2023 | World Journal of Pediatric Surgery2023，6，4： | 0 |
| 14 | Accurate and Computational Efficient Joint Multiple Kronecker Pursuit for Tensor Data Recovery显示文摘This paper addresses the problem of tensor completion from limited samplings.Generally speaking,in order to achieve good recovery result,many tensor completion methods employ alternative optimization or minimization with SVD operations,leading to a high computational complexity.In this paper,we aim to propose algorithms with high recovery accuracy and moderate computational complexity.It is shown that the data to be recovered contains structure of Kronecker Tensor decomposition under multiple patterns,and therefore the tensor completion problem becomes a Kronecker rank optimization one,which can be further relaxed into tensor Frobenius-norm minimization with a constraint of a maximum number of rank-1 basis or tensors.Then the idea of orthogonal matching pursuit is employed to avoid the burdensome SVD operations.Based on these,two methods,namely iterative rank-1 tensor pursuit and joint rank-1 tensor pursuit are proposed.Their economic variants are also included to further reduce the computational and storage complexity,making them effective for large-scale data tensor recovery.To verify the proposed algorithms,both synthesis data and real world data,including SAR data and video data completion,are used.Comparing to the single pattern case,when multiple patterns are used,more stable performance can be achieved with higher complexity by the proposed methods.Furthermore,both results from synthesis and real world data shows the advantage of the proposed methods in term of recovery accuracy and/or computational complexity over the state-of-the-art methods.To conclude,the proposed tensor completion methods are suitable for large scale data completion with high recovery accuracy and moderate computational complexity. | Weize Sun Peng Zhang Jingxin Xu Huochao Tan | 2021 | Computers, Materials & Continua2021，，8： | 0 |
| 15 | Reprogramming Mycobacterium tuberculosis CRISPR System for Gene Editing and Genomewide RNA Interference Screening显示文摘Mycobacterium tuberculosis is the causative agent of tuberculosis(TB), which is still the leading cause of mortality from a single infectious disease worldwide. The development of novel anti-TB drugs and vaccines is severely hampered by the complicated and time-consuming genetic manipulation techniques for M. tuberculosis. Here, we harnessed an endogenous type Ⅲ-A CRISPR/Cas10 system of M. tuberculosis for efficient gene editing and RNA interference(RNAi).This simple and easy method only needs to transform a single mini-CRISPR array plasmid, thus avoiding the introduction of exogenous protein and minimizing proteotoxicity. We demonstrated that M. tuberculosis genes can be efficiently and specifically knocked in/out by this system as confirmed by DNA high-throughput sequencing. This system was further applied to single-and multiple-gene RNAi. Moreover, we successfully performed genome-wide RNAi screening to identify M. tuberculosis genes regulating in vitro and intracellular growth. This system can be extensively used for exploring the functional genomics of M. tuberculosis and facilitate the development of novel anti-TB drugs and vaccines. | Khaista Rahman Muhammad Jamal Xi Chen Wei Zhou Bin Yang Yanyan Zou Weize Xu Yingying Lei Chengchao Wu Xiaojian Cao Rohit Tyagi Muhammad Ahsan Naeem Da Lin Zeshan Habib Nan Peng Zhen F.Fu Gang Cao | 2022 | Genomics, Proteomics & Bioinformatics2022，20，6： | 0 |
| 16 | A deep learning-based method for pediatric congenital heart disease detection with seven standard views in echocardiography显示文摘Background With the aggregation of clinical data and the evolution of computational resources,artificial intelligence-based methods have become possible to facilitate clinical diagnosis.For congenital heart disease(CHD)detection,recent deep learning-based methods tend to achieve classification with few views or even a single view.Due to the complexity of CHD,the input images for the deep learning model should cover as many anatomical structures of the heart as possible to enhance the accuracy and robustness of the algorithm.In this paper,we first propose a deep learning method based on seven views for CHD classification and then validate it with clinical data,the results of which show the competitiveness of our approach.Methods A total of 1411 children admitted to the Children’s Hospital of Zhejiang University School of Medicine were selected,and their echocardiographic videos were obtained.Then,seven standard views were selected from each video,which were used as the input to the deep learning model to obtain the final result after training,validation and testing.Results In the test set,when a reasonable type of image was input,the area under the curve(AUC)value could reach 0.91,and the accuracy could reach 92.3%.During the experiment,shear transformation was used as interference to test the infection resistance of our method.As long as appropriate data were input,the above experimental results would not fluctuate obviously even if artificial interference was applied.Conclusions These results indicate that the deep learning model based on the seven standard echocardiographic views can effectively detect CHD in children,and this approach has considerable value in practical application. | Xusheng Jiang Jin Yu Jingjing Ye Weijie Jia Weize Xu Qiang Shu | 2023 | World Journal of Pediatric Surgery2023，6，3： | 0 |
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