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| 1 | Spatiotemporal characteristics of GNSS-derived precipitable water vapor during heavy rainfall events in Guilin,China显示文摘Precipitable Water Vapor(PWV),as an important indicator of atmospheric water vapor,can be derived from Global Navigation Satellite System(GNSS)observations with the advantages of high precision and all-weather capacity.GNSS-derived PWV with a high spatiotemporal resolution has become an important source of observations in mete-orology,particularly for severe weather conditions,for water vapor is not well sampled in the current meteorological observing systems.In this study,an empirical atmospheric weighted mean temperature(Tm)model for Guilin is estab-lished using the radiosonde data from 2012 to 2017.Then,the observations at 11 GNSS stations in Guilin are used to investigate the spatiotemporal features of GNSS-derived PWV under the heavy rainfalls from June to July 2017.The results show that the new Tm model in Guilin has better performance with the mean bias and Root Mean Square(RMS)of−0.51 and 2.12 K,respectively,compared with other widely used models.Moreover,the GNSS PWV estimates are validated with the data at Guilin radiosonde station.Good agreements are found between GNSS-derived PWV and radiosonde-derived PWV with the mean bias and RMS of−0.9 and 3.53 mm,respectively.Finally,an investigation on the spatiotemporal characteristics of GNSS PWV during heavy rainfalls in Guilin is performed.It is shown that variations of PWV retrieved from GNSS have a direct relationship with the in situ rainfall measurements,and the PWV increases sharply before the arrival of a heavy rainfall and decreases to a stable state after the cease of the rainfall.It also reveals the moisture variation in several regions of Guilin during a heavy rainfall,which is significant for the moni-toring of rainfalls and weather forecast. | Liangke Huang Zhixiang Mo Shaofeng Xie Lilong Liu Chuanli Kang Shitai Wang | 2021 | Satellite Navigation2021，2，1： | 6 |
| 2 | CLM3-simulated soil moisture in East Asia and its possible response to global warming during 1979 through 2003显示文摘Hydrological processes related to soil moisture play an important role in determining regional and global climate. In this study, using a state-of-art Community Land Model (CLM) developed by the National Center for Atmospheric Research (NCAR), we simulated soil moisture in East Asia and its possible response to global warming through a long off-line experiment under 0.5° (longitude) × 0.5° (latitude) resolution and real atmospheric forcing of the National Center for Environmental Protection/ Department of Energy (NCEP/DOE) reanalysis during 1979 through 2003. The 25-year simulation is examined and compared with limited observations. The results can be summarized as follows: (1) Soil moisture takes time in response to the atmospheric forcing. The equilibration time depends on the depth of the soil and is as much as 20 years in deep layers (>1.5 m); (2) In comparison with observations, the CLM reasonably reproduces the seasonal and inter-annual variability, spatial structure, and vertical pattern of soil moisture in East Asia; (3) The soil tends to be drier in the past 25 years in northeastern Asia-including northern China north of 30°N-while wetter in the southern China and the Tibetan Plateau, especially in summer. Our analysis shows that the regional drying is attributed to increase of the land-surface evaporation induced by global warming. | ChuanLi Du 1,2*, XiaoDong Liu 1, WanLi Wu 31. State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment,Chinese Academy of Sciences, Xi’an, Shaanxi 710075, China.2. Shaanxi Provincial Meteorological Institute, Xi’an, Shaanxi 710014, China.3. National Center for Atmospheric Research, Boulder, Colorado 80307, USA. | 2009 | Research in Cold and Arid Regions2009，1，1： | 2 |
| 3 | A germline variant N375S in MET and gastric cancer susceptibility in a Chinese population显示文摘MET tyrosine kinase and its ligand,hepatocyte growth factor(HGF),play a pivotal role in the activties of tumor cells.A germline missense variant in exon 2 of the MET gene,N375S(rs33917957 A>G),may alter the binding affinity of MET for HGF and thus modify the risk of tumorigenesis.In this study,we performed a case-control study to assess the association between N375S and gastric cancer risk in 1,681 gastric cancer cases and 1,858 cancer-free controls.Logistic regression analysis was applied to estimate crude and adjusted odds ratios(ORs) and 95% confidence intervals(CIs) for the associations between genotypes and gastric cancer risk.We found that MET N375S variant genotypes(NS/SS) were associated with a significantly decreased risk of gastric cancer(OR = 0.78,95% CI = 0.63-0.96,P = 0.021) compared with the wildtype homozygote(NN).The finding indicates that this germline variant in MET may decrease gastric cancer susceptibility in Han Chinese. | Yao Liu Qin Zhang Chuanli Ren Yanbing Drag Guangfu Jin Zhibin Hu Yaochu Xu Hongbing Shen | 2012 | The Journal of Biomedical Research2012，26，5： | 2 |
| 4 | Catalyst-free tandem Michael addition-cyclization reactions in aqueous media for the synthesis of benzimidazo[1,2-a]pyrimidinone derivatives显示文摘The catalyst-free reactions of Baylis-Hillman alcohols (1a-i) with 2-aminobenzimidazole (2) in THF-H2O (1:4) were developed for the convenient and greener synthesis of benzimidazo[1,2-a]pyrimidinone derivatives (3a-i).The pesticidal activities of 3a-i were examined to investigate a new biological activity of the imidazo[1,2-a]pyrimidinone-type compounds. | REN ChuanLi WANG Yan WANG Dong CHEN YongJun LIU Li | 2010 | Science China Chemistry2010，53，7： | 0 |
| 5 | A K-nearest Neighbor Model to Predict Early Recurrence of Hepatocellular Carcinoma After Resection显示文摘Background and Aims:Patients with hepatocellular carci-noma(HCC)surgically resected are at risk of recurrence;however,the risk factors of recurrence remain poorly un-derstood.This study intended to establish a novel machine learning model based on clinical data for predicting early re-currence of HCC after resection.Methods:A total of 220 HCC patients who underwent resection were enrolled.Clas-sification machine learning models were developed to predict HCC recurrence.The standard deviation,recall,and preci-sion of the model were used to assess the model’s accura-cy and identify efficiency of the model.Results:Recurrent HCC developed in 89(40.45%)patients at a median time of 14 months from primary resection.In principal compo-nent analysis,tumor size,tumor grade differentiation,por-tal vein tumor thrombus,alpha-fetoprotein,protein induced by vitamin K absence or antagonist-II(PIVKA-II),aspartate aminotransferase,platelet count,white blood cell count,and HBsAg were positive prognostic factors of HCC recurrence and were included in the preoperative model.After compar-ing different machine learning methods,including logistic re-gression,decision tree,naïve Bayes,deep neural networks,and k-nearest neighbor(K-NN),we choose the K-NN model as the optimal prediction model.The accuracy,recall,preci-sion of the K-NN model were 70.6%,51.9%,70.1%,respec-tively.The standard deviation was 0.020.Conclusions:The K-NN classification algorithm model performed better than the other classification models.Estimation of the recurrence rate of early HCC can help to allocate treatment,eventually achieving safe oncological outcomes. | Chuanli Liu Hongli Yang Yuemin Feng Cuihong Liu Fajuan Rui Yuankui Cao Xinyu Hu Jiawen Xu Junqing Fan Qiang Zhu Jie Li | 2022 | Journal of Clinical and Translational Hepatology2022，10，4： | 0 |
| 6 | Multiple Kernel Clustering Based on Self-Weighted Local Kernel Alignment显示文摘Multiple kernel clustering based on local kernel alignment has achieved outstanding clustering performance by applying local kernel alignment on each sample.However,we observe that most of existing works usually assume that each local kernel alignment has the equal contribution to clustering performance,while local kernel alignment on different sample actually has different contribution to clustering performance.Therefore this assumption could have a negative effective on clustering performance.To solve this issue,we design a multiple kernel clustering algorithm based on self-weighted local kernel alignment,which can learn a proper weight to clustering performance for each local kernel alignment.Specifically,we introduce a new optimization variable-weight-to denote the contribution of each local kernel alignment to clustering performance,and then,weight,kernel combination coefficients and cluster membership are alternately optimized under kernel alignment frame.In addition,we develop a three-step alternate iterative optimization algorithm to address the resultant optimization problem.Broad experiments on five benchmark data sets have been put into effect to evaluate the clustering performance of the proposed algorithm.The experimental results distinctly demonstrate that the proposed algorithm outperforms the typical multiple kernel clustering algorithms,which illustrates the effectiveness of the proposed algorithm. | Chuanli Wang En Zhu Xinwang Liu Jiaohua Qin Jianping Yin Kaikai Zhao | 2019 | Computers, Materials & Continua2019，，7： | 0 |
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