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| 1 | High probability impulse noise-removing algorithm based on mathematical morphology 显示文摘 | DENG Zefeng YIN Zhouping XIONG Youlun | 2007 | IEEE Signal Processing Letters2007，14，1： | 1 |
| 2 | COVID-19 induces new-onset insulin resistance and lipid metabolic dysregulation via regulation of secreted metabolic factors显示文摘Abnormal glucose and lipid metabolism in COVID-19 patients were recently reported with unclear mechanism.In this study,we retrospectively investigated a cohort of COVID-19 patients without pre-existing metabolic-related diseases,and found new-onset in suli n resista nee,hyperglycemia,and decreased HDL-C in these patie nts.Mecha nistically,SARS-CoV-2 infecti on in creased the expression of RE1-silencing transcription factor(REST),which modulated the expression of secreted metabolic factors including myeloperoxidase,apelin,and myostatin at the transcriptional level,resulting in the perturbation of glucose and lipid metabolism.Furthermore,several lipids,including(±)5-HETE,(±)12-HETE,propionic acid,and isobutyric acid were identified as the potential biomarkers of COVID-19-induced metabolic dysregulation,especially in insulin resistance.Taken together,our study revealed insulin resistance as the direct cause of hyperglycemia upon COVID-19,and further illustrated the underlying mechanisms,providing potential therapeutic targets for COVID-19-induced metabolic complications. | Xi He Chenshu Liu Jiangyun Peng Zilun Li Fang Li Jian Wang Ao Hu Meixiu Peng Kan Huang Dongxiao Fan Na Li Fuchun Zhang Weiping Cai Xinghua Tan Zhongwei Hu Xilong Deng Yueping Li Xiaoneng Mo Linghua Li Yaling Shi Li Yang Yuanyuan Zhu Yanrong Wu Huichao Liang Baolin Liao Wenxin Hong Ruiying He Jiaojiao Li Pengle Guo Youguang Zhuo Lingzhai Zhao Fengyu Hu Wenxue Li Wei Zhu Zefeng Zhang Zeling Guo Wei Zhang Xiqiang Hong Wei kang Cai Lei Gu Ziming Du Yang Zhang Jin Xu Tao Zuo Kai Deng Li Yan Xinwen Chen Sifan Chen Chunliang Lei | 2022 | Signal Transduction and Targeted Therapy2022，7，1： | 0 |
| 3 | Machine learning models for stroke detection by observing the eye-movement features under five-color visual stimuli in traditional Chinese medicine显示文摘Objective:To develop a novel diagnostic modality to identify and diagnose stroke in daily life scenarios for improving the therapeutic effects and prognoses of patients.Methods:In this study,16 stroke patients and 24 age-matched healthy participants as controls were recruited for comparative analysis.Leveraging a portable eye-tracking device and integrating traditional Chinese medicine theory with modern color psychology principles,we recorded the eye movement signals and calculated eye movement features.Meanwhile,the stroke recognition models based on eye movement features were further trained by using random forest(RF),k-nearest neighbors(KNN),decision tree(DT),gradient boosting classifier(GBC),XGBoost,and CatBoost.Results:The stroke group and the healthy group showed significant differences in some eye movement features(P<.05).The models trained based on eye movement characteristics had good performances in recognizing stroke individuals,with accuracies ranging from 77.40%to 88.45%.Under the red stimulus,the eye movement model trained by RF became the best machine learning model with a recall of 84.65%,a precision of 86.48%,a F1 score of 85.47%.Among the six algorithms,RF and CatBoost performed better in classification.Conclusion:This study pioneers the application of traditional Chinese medicine's five-color stimuli to visual observation tasks.On the basis of the combined design,the eye-movement models can accurately identify stroke,and the developed high-performance models may be used in daily life scenarios. | Qingya Lu Jingyuan Deng Ying Yu Yang Li Kunni Wei Xia Han Zefeng Wang Xun Zhang Xu Wang Cong Yan | 2023 | Journal of Traditional Chinese Medical Sciences2023，10，3： | 0 |
| 4 | Thermal shock resistance enhancement by improved interfacial bonding for carbon/aluminium composites显示文摘Carbon/aluminium(C/Al)composites have the advantages of low density and high electrical conductivity,which have potential applications in aerospace,rail transportation and other fields.However,the unstable bonding of the C/Al interface and significant thermal expansion differences have resulted in risks of the composites'failure once suffering from severe thermal shock.In this work,the C/Al composites were prepared by the pressure impregnation method,and silicon(Si)was added to overcome the problems of C/Al non-wettability and thermal expansion differences.The effects of mass fractions of doped silicon on the mechanical properties,electrical conductivity and thermal shock resistance of C/Al composites were also examined.Results show that the formed SiC interlayer has effectively enhanced the interfacial bonding and reduced the differences in the thermal expansion coefficient of each component.As a result,the thermal shock resistance of the composites has been remarkably improved,and the flexural strength could remain 90%of the original level after the thermal shock test,compared with 50%of that without Si doping. | Wenfu Wei Zhanglin Huang Guofeng Yin Zefeng Yang Xiaobo Li Haozi Zuo Qin Deng Guizao Huang Junwen Ren Qianhua Liao Yan Yang Guangning Wu | 2022 | High Voltage2022，7，5： | 0 |
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