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| 1 | Clinical features and the traditional Chinese medicine therapeutic characteristics of 293 COVID-19 inpatient cases显示文摘Coronavirus disease 2019 (COVID-19) is now pandemic worldwide and has heavily overloaded hospitals in Wuhan City, China during the time between late January and February. We reported the clinical features and therapeutic characteristics of moderate COVID-19 cases in Wuhan that were treated via the integration of traditional Chinese medicine (TCM) and Western medicine. We collected electronic medical record (EMR) data, which included the full clinical profiles of patients, from a designated TCM hospital in Wuhan. The structured data of symptoms and drugs from admission notes were obtained through an information extraction process. Other key clinical entities were also confirmed and normalized to obtain information on the diagnosis, clinical treatments, laboratory tests, and outcomes of the patients. A total of 293 COVID-19 inpatient cases, including 207 moderate and 86 (29.3%) severe cases, were included in our research. Among these cases, 238 were discharged, 31 were transferred, and 24 (all severe cases) died in the hospital. Our COVID-19 cases involved elderly patients with advanced ages (57 years on average) and high comorbidity rates (61%). Our results reconfirmed several well-recognized risk factors, such as age, gender (male), and comorbidities, as well as provided novel laboratory indications (e.g., cholesterol) and TCM-specific phenotype markers (e.g., dull tongue) that were relevant to COVID-19 infections and prognosis. In addition to antiviral/antibiotics and standard supportive therapies, TCM herbal prescriptions incorporating 290 distinct herbs were used in 273 (93%) cases. The cases that received TCM treatment had lower death rates than those that did not receive TCM treatment (17/273= 6.2% vs. 7/20= 35%, P = 0.0004 for all cases;17/77= 22% vs. 7/9= 77.7%, P = 0.002 for severe cases). The TCM herbal prescriptions used for the treatment of COVID-19 infections mainly consisted of Pericarpium Citri Reticulatae, Radix Scutellariae, Rhizoma Pinellia, and their combinations, which reflected the practical TCM principles (e.g., clearing heat and dampening phlegm). Lastly, 59% of the patients received treatment, including antiviral, antibiotics, and Chinese patent medicine, before admission. This situation might have some effects on symptoms, such as fever and dry cough. By using EMR data, we described the clinical features and therapeutic characteristics of 293 COVID-19 cases treated via the integration of TCM herbal prescriptions and Western medicine. Clinical manifestations and treatments before admission and in the hospital were investigated. Our results preliminarily showed the potential effectiveness of TCM herbal prescriptions and their regularities in COVID-19 treatment. | Zixin Shu Yana Zhou Kai Chang Jifen Liu Xiaojun Min Qing Zhang Jing Sun Yajuan Xiong Qunsheng Zou Qiguang Zheng Jinghui Ji Josiah Poon Baoyan Liu Xuezhong Zhou Xiaodong Li | 2020 | Frontiers of Medicine2020，14，6： | 7 |
| 2 | How to compare market efficiency? The Sharpe ratio based on the ARMA-GARCH forecast显示文摘This paper derives a new method for comparing the weak-form efficiency of markets.The author derives the formula of the Sharpe ratio from the ARMA-GARCH model and finds that the Sharpe ratio just depends on the coefficients of the AR and MA terms and is not affected by the GARCH process.For empirical purposes,the Sharpe ratio can be formulated with a monotonic increasing function of R-squared if the sample size is large enough.One can utilize the Sharpe ratio to compare weak-form efficiency among different markets.The results of stochastic simulation demonstrate the validity of the proposed method.The author also constructs empirical AR-GARCH models and computes the Sharpe ratio for S&P 500 Index and the SSE Composite Index. | Lin Liu Qiguang Chen | 2020 | Financial Innovation2020，6，1： | 5 |
| 3 | Malware Detection Algorithm Based on the Attention Mechanism and ResNet显示文摘The cost of misclassifying a malware program as normal is often higher than that of misclassifying a normal program as malware.Therefore,how to improve the detection accuracy of malware programs is a very important problem.This paper proposes a deep learning malware program detection algorithm based on attention mechanism.Word2Vec model is used to map the Application programming interface(API)into word vectors,and all word vectors of each sample are arranged into a matrix with the same size.On this basis,residual network is used to extract features of samples.The features are input into the attention mechanism to learn the similarity between samples.Then,the features are weighted with the similarity to obtain the new features with better robustness.The new features and the original features are added element by element to obtain the sample features more suitable for classification.Finally,samples are classified by classifier.Experiments show that the classification effect of the proposed method is better than that of the traditional machine learning method. | WANG Lele WANG Binqiang ZHAO Peipei LIU Ruyi LIU Jiangang MIAO Qiguang | 2020 | Chinese Journal of Electronics2020，29，6： | 5 |
| 4 | Physically based simulation of thin:shell objects' burning 显示文摘 | LIU SHIGUANG LIU QIGUANG AN TAI | 2009 | The Visual Computer2009，25，57： | 1 |
| 5 | Three novel invariant moments based on radon and polar harmonic transforms显示文摘 | Qiguang Miao Juan Liu Weisheng Li Junjie Shi Yiding Wang | 2011 | Optics Communications2011，，6： | 1 |
| 6 | Linear feature sepa- ration from topographic maps using energy density and shear transform 显示文摘 | Miao Qiguang Xu Pefei Liu Tiange | 2013 | IEEE Transaction on Image Processing2013，22，4： | 1 |
| 7 | Three novel invariant moments based on radon and polar harmonic transforms显示文摘 | Miao Qiguang Liu Juan Li Weisheng | | 0，，： | 1 |
| 8 | Linear Feature Separa- tion from Topographic Maps Using Energy Density and Shear Transform 显示文摘 | Miao Qiguang Xu Pengfei Liu Tiange Yang Yun Zhang Junying g Li Weishen | 2013 | IEEE Transaction On Image Pro- cessing2013，22，4： | 1 |
| 9 | Physically based simulation of thin-shell ob- jects'burning显示文摘 | Shiguang Liu Qiguang Liu Tai An Jizhou Sun Qunsheng Peng | 2009 | The Visual Computer2009，25，57： | 1 |
| 10 | A new discovered ABCA1 gene polymorphisms and the association of ABCA1 SNPs with coronary artery disease and plasma lipids in Chinese population显示文摘Objective: Single nucleotide polymorphisms (SNP) of ATP-binding cassette transporter A1 (ABCA1) gene are related to plasma lipid and susceptibility to coronary artery disease (CAD). Our first goal was to screen all 50 coding regions of ABCA1 to find new SNPs. Our second goal was to investigate the frequency distribution of R1587K and M883I polymorphisms of ABCA1 gene, which are the variant occurred most frequently, in Chinese people and to evaluate their association with the CAD phenotype and plasma lipids. Methods: Single-strand conformation polymorphism (SSCP) and DNA sequence were used for confirming new SNP of ABCA1, and restriction fragment length polymorphism (RFLP) were applied for confirming genotypes of R1587K and M883I in 112 CAD cases and 108 healthy people. Results: We discovered a new ABCA1 SNP in Chinese population, which converse 233 amino acids from Methionine to Valine (M233V). This new ABCA1 SNP located in exon7, and might potentially modulate the biological function of lipid metabolism. For R1587K and M883I SNPs, the K allele and I allele frequency was 28.9%and 31.1%, respectively. The K allele at R1587K conferred lower mean values of HDL-C in a dose-dependent manner in both CAD patients and healthy people. However, 883I allele was not associated with plasma lipid level. Neither 1587KK nor 883II associated with increased risk of CAD. Conclusion: Our study finds a potential functional ABCA1 SNPs and revealed K allele of R1587K associated decreased HDL-C level in Chinese population. | Guo Zhigang Wu Pingsheng Xie Di Wang Qiguang Liu Yayang Cha Zheng Li Peng Lai Wenyan Tu Yan | 2011 | Journal of Medical Colleges of PLA(China)2011，26，4： | 1 |
| 11 | Adaptive Bistable Stochastic Resonance Based Weak Signal Reception in Additive Laplacian Noise显示文摘Weak signal reception is a very important and challenging problem for communication systems especially in the presence of non-Gaussian noise,and in which case the performance of optimal linear correlated receiver degrades dramatically.Aiming at this,a novel uncorrelated reception scheme based on adaptive bistable stochastic resonance(ABSR)for a weak signal in additive Laplacian noise is investigated.By analyzing the key issue that the quantitative cooperative resonance matching relationship between the characteristics of the noisy signal and the nonlinear bistable system,an analytical expression of the bistable system parameters is derived.On this basis,by means of bistable system parameters self-adaptive adjustment,the counterintuitive stochastic resonance(SR)phenomenon can be easily generated at which the random noise is changed into a benefit to assist signal transmission.Finally,it is demonstrated that approximately 8dB bit error ratio(BER)performance improvement for the ABSR-based uncorrelated receiver when compared with the traditional uncorrelated receiver at low signal to noise ratio(SNR)conditions varying from-30dB to-5dB. | Jin Liu Zan Li Qiguang Miao Li Yang | 2024 | China Communications2024，21，1： | 0 |
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