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| 1 | Aboveground biomass and its spatial distribution pattern of herbaceous marsh vegetation in China显示文摘Herbaceous marsh is the most widely distributed type of marsh wetland ecosystem,and has important ecological functions such as water conservation,climate regulation,carbon storage and fixation,and sheltering rare species.The carbon sequestration function of herbaceous marsh plays a key role in slowing climate warming and maintaining regional environmental stability.Vegetation biomass is an important index reflecting the carbon sequestration capacity of wetlands.Investigating the biomass of marsh vegetation can provide a scientific basis for estimating the carbon storage and carbon sequestration capacity of marshes.Based on field survey data of aboveground biomass of herbaceous marsh vegetation and the distribution data set of marsh in China,we analyzed the aboveground biomass and its spatial distribution pattern of herbaceous marsh on a national scale for the first time.The results showed that in China the total area of herbaceous marsh was 9.7×10^(4) km^(2),the average density of aboveground biomass of herbaceous marsh vegetation was 227.5±23.0 g C m-2(95%confidence interval,the same below),and the total aboveground biomass was 22.2±2.2 Tg C(1 Tg=1012 g).The aboveground biomass density of herbaceous marsh vegetation is generally low in Northeast China and the Tibetan Plateau,and high in central North China and coastal regions in China.In different marsh distribution regions of China,the average biomass density of herbaceous marsh vegetation from small to large was as follows:temperate humid and semi-humid marsh region(182.3±49.3 g C m^(-2)) | Xiangjin SHEN Ming JIANG Xianguo LU Xingtu LIU Bo LIU Jiaqi ZHANG Xianwei WANG Shouzheng TONG Guangchun LEI Shengzhong WANG Chuan TONG Hangqing FAN Kun TIAN Xiaolong WANG Yuanman HU Yonghong XIE Muyuan MA Shuwen ZHANG Chunxiang CAO Zhichen WANG | 2021 | Science China Earth Sciences2021，64，7： | 4 |
| 2 | Application of fluorescence in situ hybridization in the detection of bladder transitional-cell carcinoma: A multi-center clinical study based on Chinese population显示文摘Objective:To evaluate the diagnostic value of fluorescence in situ hybridization(FISH)in bladder cancer.Methods:We enrolled healthy volunteers and patients who were clinically suspected to have bladder cancer and conducted FISH tests and cytology examinations from August 2007 to December 2008.Receiver operating characteristic(ROC)curve analysis was performed and the area under curve(AUC)values were calculated for both the FISH and urine cytology tests.Results:A cohort of 988 healthy volunteers was enrolled to establish a reference range for the normal population.A total of 4807 patients with hematuria were prospectively,randomly enrolled for the simultaneous analysis of urine cytology,FISH testing,and a final diagnosis as determined by the pathologic findings of a biopsy or a surgically-excised specimen.Overall,the sensitivity of FISH in detecting transitional-cell carcinoma was 82.7%,while that of cytology was 33.4%(p<0.001).The sensitivity values of FISH for non-muscle invasive and muscle invasive bladder transitional-cell carcinoma were 81.7%and 89.6%,respectively(p=0.004).The sensitivity values of FISH for low and high grade bladder cancer were 82.6%and 90.1%,respectively(p=0.002).Conclusion:FISH is significantly more sensitive than voided urine cytology for detecting bladder cancer in patients evaluated for gross hematuria at all cancer grades and stages.Higher sensitivity using FISH was obtained in high grade and muscle invasive tumors. | Liqun Zhou Kaiwei Yang Xuesong Li Yi Ding Dawei Mu Hanzhong Li Yong Yan Jinyi Li Dongwen Wang Wei Li Yulong Cong Jiangping Gao Kewei Ma Yajun Xiao Sheng Zhang Hongyi Jiang Weilie Hu Qiang Wei Xunbo Jin Zhichen Guan Qingyong Liu Danfeng Xu Xin Gao Yongguang Jiang Weimin Gan Guang Sun Qing Wang Yanhui Liu Jianquan Hou Liping Xie Xishuang Song Fengshuo Jin Jiafu Feng Ming Cai Zhaozhao Liang Jie Zhang Dingwei Ye Lin Qi Lulin Ma Jianzhong Shou Yuping Dai Jianyong Shao Ye Tian Shizhe Hong Tao Xu Chuize Kong Zefeng Kang Yuexin Liu Xun Qu Benkang Shi Shaobin Zheng Yi Lin Shujie Xia Dong Wei Jianbo Wu Weiling Fu Zhiping Wang Jianbo Liang | 2019 | Asian Journal of Urology2019，6，1： | 2 |
| 3 | Data Masking for Chinese Electronic Medical Records with Named Entity Recognition显示文摘With the rapid development of information technology,the electronifi-cation of medical records has gradually become a trend.In China,the population base is huge and the supporting medical institutions are numerous,so this reality drives the conversion of paper medical records to electronic medical records.Electronic medical records are the basis for establishing a smart hospital and an important guarantee for achieving medical intelligence,and the massive amount of electronic medical record data is also an important data set for conducting research in the medical field.However,electronic medical records contain a large amount of private patient information,which must be desensitized before they are used as open resources.Therefore,to solve the above problems,data masking for Chinese electronic medical records with named entity recognition is proposed in this paper.Firstly,the text is vectorized to satisfy the required format of the model input.Secondly,since the input sentences may have a long or short length and the relationship between sentences in context is not negligible.To this end,a neural network model for named entity recognition based on bidirectional long short-term memory(BiLSTM)with conditional random fields(CRF)is constructed.Finally,the data masking operation is performed based on the named entity recog-nition results,mainly using regular expression filtering encryption and principal component analysis(PCA)word vector compression and replacement.In addi-tion,comparison experiments with the hidden markov model(HMM)model,LSTM-CRF model,and BiLSTM model are conducted in this paper.The experi-mental results show that the method used in this paper achieves 92.72%Accuracy,92.30%Recall,and 92.51%F1_score,which has higher accuracy compared with other models. | Tianyu He Xiaolong Xu Zhichen Hu Qingzhan Zhao Jianguo Dai Fei Dai | 2023 | Intelligent Automation & Soft Computing2023，，6： | 0 |
| 4 | Corpus of Carbonate Platforms with Lexical Annotations for Named Entity Recognition显示文摘An obviously challenging problem in named entity recognition is the construction of the kind data set of entities.Although some research has been conducted on entity database construction,the majority of them are directed at Wikipedia or the minority at structured entities such as people,locations and organizational nouns in the news.This paper focuses on the identification of scientific entities in carbonate platforms in English literature,using the example of carbonate platforms in sedimentology.Firstly,based on the fact that the reasons for writing literature in key disciplines are likely to be provided by multidisciplinary experts,this paper designs a literature content extraction method that allows dealing with complex text structures.Secondly,based on the literature extraction content,we formalize the entity extraction task(lexicon and lexical-based entity extraction)for entity extraction.Furthermore,for testing the accuracy of entity extraction,three currently popular recognition methods are chosen to perform entity detection in this paper.Experiments show that the entity data set provided by the lexicon and lexical-based entity extraction method is of significant assistance for the named entity recognition task.This study presents a pilot study of entity extraction,which involves the use of a complex structure and specialized literature on carbonate platforms in English. | Zhichen Hu Huali Ren Jielin Jiang Yan Cui Xiumian Hu Xiaolong Xu | 2023 | Computer Modeling in Engineering & Sciences2023，，4： | 0 |
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