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| 1 | The “Traditional Chinese medicine regulating liver regeneration” treatment plan for reducing mortality of patients with hepatitis B-related liver failure based on real-world clinical data显示文摘On the basis of real-world clinical data,the study aimed to explore the effect and mechanisms of the treatment plan of“traditional Chinese medicine(TCM)regulating liver regeneration.”A total of 457 patients with HBV-related liver failure were retrospectively collected.The patients were divided into three groups:the modern medicine control group(MMC group),patients treated with routine medical treatment;the control group combining traditional Chinese and Western medicine(CTW),patients treated with routine medical treatment plus the common TCM formula;and the treatment group of“TCM regulating liver regeneration”(RLR),patients treated with both routine medical treatment and the special TCM formula of RLR.After 8 weeks of treatment,the mortality of patients in the RLR group(12.31%)was significantly lower than those in the MMC(50%)and CTW(29.11%)groups.Total bilirubin level significantly decreased and albumin increased in the RLR group when compared with the MMC and CTW groups(P<0.05).In addition,there were significant differences in the expression of several cytokines related to liver regeneration in the RLR group compared with the MMC group.RLR treatment can decrease jaundice,improve liver function,and significantly reduce the mortality in patients with HBV-related liver failure.The mechanism may be related to the role of RLR treatment in influencing cytokines related to liver regeneration. | Ling Dai Xiang Gao Zhihua Ye Hanmin Li Xin Yao Dingbo Lu Na Wu | 2021 | Frontiers of Medicine2021，15，3： | 4 |
| 2 | Study on the suitable thickness of a PAC-preeoated dynamic membrane coupled with a bioreactor for municipal wastewater treatment显示文摘 | Maosheng Ye Hanmin Zhang Qifeng Wei | 2006 | Desalination2006，194，： | 1 |
| 3 | Study on the suitable thickness of a PAC-precoated dynamic membrane coupled with a bioreactor for municipal wastewater treatment 显示文摘 | Ye Maosheng Zhang Hanmin Wei Qifeng | 2006 | Desalination2006，194，13： | 1 |
| 4 | Mechanical Properties and Toughening Mechanisms of Polypropylene/Barium Sulfate Composites显示文摘 | Ke Wang Jingshen Wu Liu Ye Hanmin Zeng | 2003 | Composites: Part A2003，34，： | 1 |
| 5 | A Method of Multimodal Emotion Recognition in Video Learning Based on Knowledge Enhancement显示文摘With the popularity of online learning and due to the significant influence of emotion on the learning effect,more and more researches focus on emotion recognition in online learning.Most of the current research uses the comments of the learning platform or the learner’s expression for emotion recognition.The research data on other modalities are scarce.Most of the studies also ignore the impact of instructional videos on learners and the guidance of knowledge on data.Because of the need for other modal research data,we construct a synchronous multimodal data set for analyzing learners’emotional states in online learning scenarios.The data set recorded the eye movement data and photoplethysmography(PPG)signals of 68 subjects and the instructional video they watched.For the problem of ignoring the instructional videos on learners and ignoring the knowledge,a multimodal emotion recognition method in video learning based on knowledge enhancement is proposed.This method uses the knowledge-based features extracted from instructional videos,such as brightness,hue,saturation,the videos’clickthrough rate,and emotion generation time,to guide the emotion recognition process of physiological signals.This method uses Convolutional Neural Networks(CNN)and Long Short-Term Memory(LSTM)networks to extract deeper emotional representation and spatiotemporal information from shallow features.The model uses multi-head attention(MHA)mechanism to obtain critical information in the extracted deep features.Then,Temporal Convolutional Network(TCN)is used to learn the information in the deep features and knowledge-based features.Knowledge-based features are used to supplement and enhance the deep features of physiological signals.Finally,the fully connected layer is used for emotion recognition,and the recognition accuracy reaches 97.51%.Compared with two recent researches,the accuracy improved by 8.57%and 2.11%,respectively.On the four public data sets,our proposed method also achieves better results compared with the two recent researches.The experiment results show that the proposed multimodal emotion recognition method based on knowledge enhancement has good performance and robustness. | Hanmin Ye Yinghui Zhou Xiaomei Tao | 2023 | Computer Systems Science & Engineering2023，47，11： | 0 |
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