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Porous Silicon Carbide/Carbon Composite Microspherules for Methane Storage

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Journal of Natural Gas Chemistry 2007年第4期16卷 363-370页

作者： Fengbo li qingli Qian Shufeng Zhang Fang Yan Guoqing Yuan Laboratory of New Materials Institute of Chemistry Chinese Academy of Sciences Beijing 100080 China

Porous silicon carbide/carbon （SiC/C） microspherules were prepared by the controlled heating treatment of polymer and silica hybrid precursors over 1000℃ in Ar/H2 stream. The resultant SiC/C composite shows improved physical properties such as excellent mechanical strength, regular physical form, and high packing density. Such improvement overcomes the main inherent problems encountered when using activated carbons as absorbents without sacrificing porosity properties. N2 sorption analysis shows that the SiC/C composite has a BET surface area of 1793 m^2/g and a pore volume of 0.92 ml/g. Methane adsorption isotherm is determined by the conventional volumetric method at 25℃ and up to 7.0 MPa. On volumetric basis, the SiC/C composite microspherules show methane storage of 145 （V/V） at 3.5 MPa and 25℃. The combination of excellent physical properties and porosity properties in this SiC/C composite lends a great possibility to develop a competitive storage system for natural gas.

关键词： carbides microporous materials energy storage

Microscopic hyperspectral imaging studies of normal and diabetic retina of rats

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Science China(life Sciences) 2008年第9期51卷 789-794页

作者： li qingli XUE YongQi ZHANG JingFa XIAO GongHai School of Information Science East China Normal UniversityShanghai 200241China Shanghai Institute of Technical Physics Chinese Academy of SciencesShanghai 200081China School of Medicine Shanghai JiaoTong UniversityShanghai 200025China

A microscopic hyperspectral imager was developed based on the microscopic technology and the spectral imaging technology. Some microscopic hyperspectral images of retina sections of the normal, the diabetic, and the treated rats were collected by the new imager. Single-band images and pseudo-color images of each group were obtained and the typical transmittance spectrums were ex-tracted. The results showed that the transmittance of outer nuclear layer cells of the diabetic group was generally higher than that of the normal. A small absorption peak appeared near the 180th band in the spectrum of the diabetic group and this peak weakened or disappeared in the spectrum of the treated group. Our findings indicate that the microscopic hyperspectral images include wealthy information of retina sections which is helpful for the ophthalmologist to reveal the pathogenesis of diabetic reti-nopathy and explore the therapeutic effect of drugs.

关键词： diabetic retinopathy retina microscopic hyperspectral imager spectrum

Effects of augmentation of liver regeneration recombinant plasmid on rat hepatic fibrosis

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World Journal of Gastroenterology 2005年第16期11卷 2438-2443页

作者： qingli Dian-Wuliu li-MeiZhang BingZhu Yu-TongHe Yong-HongXiao DepartmentofEpidemiology HebeiMedicalUniversityShijiazhuang050017HebeiProvinceChina

AIM: To investigate the effects of eukaryotic expression of plasmid on augmentation of liver regeneration (ALR) in rat hepatic fibrosis and to explore their mechanisms. METHODS: Ten rats were randomly selected from 50 Wistar rats as normal control group. The rest were administered intraperitoneally with porcine serum twice weekly. After 8 wk, they were randomly divided into: model control group, colchicine group (Col), first ALR group (ALR1), second ALR group (ALR2). Then colchicine ALR recombinant plasmid were used to treat them respectively. At the end of the 4th wk, rats were killed. Serum indicators were detected and histopathological changes were graded. Expression of type Ⅰ, Ⅲ, collagen and TIMP-1 were detected by immunohisto-chemistry and expression of TIMP-1 mRNA was detected by semi-quantified RT-PCR. RESULTS: The histologic examination showed that the degree of the rat hepatic fibrosis in two ALR groups was lower than those in model control group. Compared with model group, ALR significantly reduced the serum levels of ALT, AST, HA, LN, PCIII and IV (Pliorated dramatically compared with model group (I collagen: 6.94±1.42,5.80±1.66 and 10.83±3.58 in ALR1, ALR2 and model groups, respectively; Ⅲ collagen: 7.18±1.95, 4.50±1.67 and 10.25±2.61, respectively; TIMP-1: 0.39±0.05,0.20±0.06 and 0.53±0.12, respectively,Pliver tissues was markedly decreased in two ALR groups compared with model group (TIMP-1 mRNA/β-actin: 0.89±0.08, 0.65±0.11 and 1.36±0.11 in ALR1, ALR2 and model groups respectively, Pliver cells and inhibiting TIMP-1 expressions.

关键词： Hepatic fibrosis Rat Augmentation of liver regeneration Gene therapy Tissue inhibitor of metalloproteinases-1

Study on microscope hyperspectral medical imaging method for biomedical quantitative analysis

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Chinese Science Bulletin 2008年第9期53卷 1431-1434页

作者： li qingli XUE YongQi XIAO GongHai ZHANG JingFa Key Laboratory of Polor Materials and Devices School of Information Science East China Normal University Shanghai 200241 China Shanghai Institute of Technical Physics Chinese Academy of Sciences Shanghai 200081 China aboratory of Development and Diseases Institute of Health Sciences Shanghai Institutes for Biological Sciences Chinese Academy of Sciences Shanghai 200030 China School of Medicine Shanghai Jiao Tong University Shanghai 200025 China

A microscopic pushbroom hyperspectral imaging system was developed based on the microscopic technology and spectral imaging technology according to the principle of spectral imager in remote sensing. The basic principle and key technologies of this system were presented and the system per- formance was also analyzed. Some methods and algorithms were proposed to preprocess and nor- malize the microscopic hyperspectral data and retrieve the transmittance spectrum of samples. As a case study, the microscopic hyperspectral imaging system was used to image the retina sections of different rats and get some significant results. Experiment results show that the system can be used for the quantitative assessment and evaluating the effect of medication in biomedical research.

关键词：显微镜数量分析糖尿病性视网膜病变医学成像技术

Spatial-spectral identication of abnormal leukocytes based on microscopic hyperspectral imaging technology

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Journal of Innovative Optical Health Sciences 2020年第2期13卷 44-56页

作者： Xueqi Hu Jiahua Ou Mei Zhou Menghan Hu li Sun Song Qiu qingli li Junhao Chu Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai 200241 P.R.China

Screening and diagnosing of abnormal Leukocytes are crucial for the diagnosis of immune diseases and Acute Lymphoblastic Leukemia(ALL).As the deterioration of abnormal leukocytes is mainly due to the changes in the chromatin distribution,which signicantly affects the absorption and reflection of light,the spectral feature is proved to be important for leukocytes classication and *** paper proposes an accurate identication method for healthy and abnormal leukocytes based on microscopic hyperspectral imaging(HSI)technology which combines the spectral *** segmentation of nucleus and cytoplasm is obtained by the morphological watershed ***,the spectral features are extracted and combined with the spatial *** on this,the support vector machine(SVM)is applied for classication ofve types of leukocytes and abnormal *** with different classication methods,the proposed method utilizes spectral features which highlight the differences between healthy leukocytes and abnormal leukocytes,improving the accuracy in the classication and identication of *** paper only selects one subtype of ALL for test,and the proposed method can be applied for detection of other leukemia in the future.

关键词： Leukocyte microscopic hyperspectral imaging nucleus segmentation Acute Lymphoblastic Leukemia.

Identification of various food residuals on denim based on hyperspectral imaging system and combination optimal strategy

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Artificial Intelligence in Agriculture 2021年第1期5卷 125-132页

作者： Yuzhen Chen Ziyi Xu Wencheng Tang Menghan Hu Douning Tang Guangtao Zhai qingli li Shanghai Key Laboratory of Multidimensional Information Processing School of Communication&Electronic EngineeringEast China Normal UniversityShanghai 200062China School of Statistics East China Normal UniversityShanghai 200062China Institute of Image Communication and Information Processing Shanghai Jiao Tong UniversityShanghai 200240China McCormick School of Engineering Northwestern UniversityEvanstonILUnited States

As the science and technology develop,crime methods and scenes have become increasingly complex and *** evidence analysis has become amore and more important criminal investigation technology and liquid is the main form of trace *** can provide not only energy,but clues to solve *** this study,we build a hyperspectral imaging system to detect liquid residue traces,including apple juice,coffee,cola,milk and tea,on denims with light,middle and dark *** obtained hyperspectral images are first subjected to spectral calibration and hyperspectral data ***,Partial Least Squares(PLS)is applied to select the informative wavelengths from the preprocessed *** modeling phase,the combination optimal strategy,support vector machine(SVM)combined with random forest(RF),is developed to establish classification *** experimental results demonstrate that the combination optimal model can achieve TPR,FPR,Precision,Recall,F1,and AUC of 83.5%,2.30%,79.7%,83.5%,81.6%,and 94.7%for classifying fabrics contaminated by various food *** respect to the classification of liquid and fabric types,the combination optimalmodel also yields satisfactory classification *** future work,wewill expand the types of liquid,and make appropriate adjustment to algorithms for improving the robustness of classification *** research may play a positive role in the construction of a harmonious society.

关键词： Hyperspectral imaging Food residual on denim Combination optimal strategy Variable selection Forensic application

Intelligent diagnosis of atrial septal defect in children using echocardiography with deep learning

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虚拟现实与智能硬件（中英文） 2024年第3期6卷 217-225页

作者： Yiman liU Size HOU Xiaoxiang HAN Tongtong liANG Menghan HU Xin WANG Wei GU Yuqi ZHANG qingli li Jiangang CHEN Shanghai Key Laboratory of Multidimensional Information Processing School of Communication&Electronic EngineeringEast China Normal UniversityShanghaiChina Department of Pediatric Cardiology Shanghai Children's Medical CenterSchool of MedicineShanghai Jiao Tong UniversityShanghaiChina Department of Applied Mathematics Xi'an Jiaotong-Liverpool UniversitySchool of ScienceSuzhouChina School of Health Sciences and Engineering University of Shanghai for Science and TechnologyShanghaiChina Minhang District Centers for Disease Control and Prevention ShanghaiChina Faculty of Traditional Chinese Medicine Naval Medical UniversityShanghaiChina Engineering Research Center of Traditional Chinese Medicine Intelligent Rehabilitation Ministry of EducationShanghai 201203China

Background Atrial septal defect(ASD)is one of the most common congenital heart *** diagnosis of ASD via transthoracic echocardiography is subjective and *** The objective of this study was to evaluate the feasibility and accuracy of automatic detection of ASD in children based on color Doppler echocardiographic static images using end-to-end convolutional neural *** proposed depthwise separable convolution model identifies ASDs with static color Doppler images in a standard *** the standard views,we selected two echocardiographic views,i.e.,the subcostal sagittal view of the atrium septum and the low parasternal four-chamber *** developed ASD detection system was validated using a training set consisting of 396 echocardiographic images corresponding to 198 ***,an independent test dataset of 112 images corresponding to 56 cases was used,including 101 cases with ASDs and 153 cases with normal *** The average area under the receiver operating characteristic curve,recall,precision,specificity,F1-score,and accuracy of the proposed ASD detection model were 91.99,80.00,82.22,87.50,79.57,and 83.04,*** The proposed model can accurately and automatically identify ASD,providing a strong foundation for the intelligent diagnosis of congenital heart diseases.

关键词： Deep learning Atrial septal defect Echocardiography

PCA-U-Net based breast cancer nest segmentation from microarray(jj)hyperspectral images

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Fundamental Research 2021年第5期1卷 631-640页

作者： Jiansheng Wang Yan Wang Xiang Tao qingli li li Sun Jiangang Chen Mei Zhou Menghan Hu Xiufeng Zhou Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai 200241China Engineering Center of SHMEC for Space Information and GNSS Shanghai 200241China Obstetrics&Gynecology Hospital of Fudan University Shanghai 200011China Engineering Research Center of Nanophotonics&Advanced Instrument Ministry of EducationEast China Normal UniversityShanghai 200241China Dmetrix Ltd.Co. SuzhouJiangsu 210000China

The incidence of breast cancer is tending younger globally,and tumor development,clinical treatment,and prognosis are largely influenced by histopathological *** diagnosed patients,the distinction between the cancer nests and normal tissue is the basis of breast cancer *** hyperspectral imaging technology has shown its potential in auxiliary pathological examinations due to the superior imaging modality and data *** paper presents a method for cancer nest segmentation from hyperspectral images of breast cancer tissue microarray *** scheme combines the strengths of the U-Net neural network and unsupervised principal component analysis,which reduces the amount of calculation and improves the recognition *** experimental accuracy of cancer nest segmentation reaches 87.14%.Furthermore,a set of quantitative pathological characteristic parameters reflects the degree of breast cancer lesions from multiple angles,providing a relatively comprehensive reference for the pathologist’s ***-depth exploration of the combined development of deep learning and microscopic hyperspectral imaging technology is worthy to promote efficient diagnosis of breast tumors and concern for human health.

关键词： Microscopic hyperspectral imaging Breast cancer Tissue microarrays Deep learning

Auxiliary Diagnosis of Papillary Thyroid Carcinoma Based on Spectral Phenotype

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Phenomics 2023年第5期3卷 469-484页

作者： Bailiang Zhao Yan Wang Menghan Hu Yue Wu Jiannan liu qingli li Min Dai Wendell QSun Guangtao Zhai Shanghai Key Laboratory of Multidimensional Information Processing East China Normal UniversityShanghai 200241China School of Health Science and Engineering University of Shanghai for Science and TechnologyShanghai 200093China Department of Pathology The Second People’s Hospital of WuhuWuhu 241000AnhuiChina Ophthalmology Department Shanghai Ninth People’s HospitalShanghai Jiao Tong University School of MedicineShanghai 610101China Department of Oral Maxillofacial Head Neck Oncology Shanghai Ninth People’s HospitalShanghai Jiao Tong University School of MedicineShanghai 200011China Institute of Image Communication and Information Processing Shanghai Jiao Tong UniversityShanghai 200240China

Thyroid cancer,a common endocrine malignancy,is one of the leading death causes among endocrine *** diagnosis of pathological section analysis suffers from diagnostic delay and cumbersome operating ***,we intend to construct the models based on spectral data that can be potentially used for rapid intraoperative papillary thyroid carcinoma(PTC)diagnosis and characterize PTC *** alleviate any concerns pathologists may have about using the model,we conducted an analysis of the used bands that can be interpreted pathologically.A spectra acquisition system was first built to acquire spectra of pathological section images from 91 *** obtained spectral dataset contains 217 spectra of normal thyroid tissue and 217 spectra of PTC *** data of the corresponding patients were collected for subsequent model interpretability *** experiment has been approved by the Ethics Review Committee of the Wuhu Hospital of East China Normal *** spectral preprocessing method was used to process the spectra,and the preprocessed signal respectively optimized by the first and secondary informative wavelengths selection was used to develop the PTC detection *** PTC detection model using mean centering(MC)and multiple scattering correction(MSC)has optimal performance,and the reasons for the good performance were analyzed in combination with the spectral acquisition process and composition of the test *** model interpretable analysis,the near-ultraviolet band selected for modeling corresponds to the location of amino acid absorption peak,and this is consistent with the clinical phenomenon of significantly lower amino acid concentrations in PTC ***,the absorption peak of hemoglobin selected for modeling is consistent with the low hemoglobin index in PTC *** addition,the correlation analysis was performed between the selected wavelengths and the clinical data,and the results show:the ref

关键词： Interpretable pathologic model Pathological analysis Intraoperative detection Spectral phenotype