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| 1 | Diffraction-limited imaging with monolayer 2D material-based ultrathin flat lenses显示文摘Ultrathin flat optics allow control of light at the subwavelength scale that is unmatched by traditional refractive optics.To approach the atomically thin limit,the use of 2D materials is an attractive possibility due to their high refractive indices.However,achievement of diffraction-limited focusing and imaging is challenged by their thickness-limited spatial resolution and focusing efficiency.Here we report a universal method to transform 2D monolayers into ultrathin flat lenses.Femtosecond laser direct writing was applied to generate local scattering media inside a monolayer,which overcomes the longstanding challenge of obtaining sufficient phase or amplitude modulation in atomically thin 2D materials.We achieved highly efficient 3D focusing with subwavelength resolution and diffractionlimited imaging.The high focusing performance even allows diffraction-limited imaging at different focal positions with varying magnifications.Our work paves the way for downscaling of optical devices using 2D materials and reports an unprecedented approach for fabricating ultrathin imaging devices. | Han Lin Zai-Quan Xu Guiyuan Cao Yupeng Zhang Jiadong Zhou Ziyu Wang Zhichen Wan Zheng Liu Kian Ping Loh Cheng-Wei Qiu Qiaoliang Bao Baohua Jia | 2020 | Light(Science & Applications)2020，9，1： | 9 |
| 2 | Overactive bladder symptom score to evaluate efficacy of solifenacin for the treatment of overactive bladder symptoms显示文摘 | Liu Ming Wang Jianye Yang Yong An Ruihua Wen Jianguo Guan Zhichen Zheng Shaobin Wang Dongwen Song Bo Liao Limin Guo Hongqian Xiao Jiaquan Sun Yinghao Shen Zhoujun Kong Chuize He Dalin Huang Yiran Wang Xiaofeng Zhang Xu Li Hanzhong Huang Jian Zhao Xiaokun Zeng Puqing Song Xishuang Ye Zhangqun | 2014 | Chinese Medical Journal2014，，2： | 7 |
| 3 | Machine learning-based real-time visible fatigue crack growth detection显示文摘Many large-scale and complex structural components are applied in the aeronautics and automobile industries.However,the repeated alternating or cyclic loads in service tend to cause unexpected fatigue fractures.Therefore,developing real-time and visible monitoring methods for fatigue crack initiation and propagation is critically important for structural safety.This paper proposes a machine learning-based fatigue crack growth detection method that combines computer vision and machine learning.In our model,computer vision is used for data creation,and the machine learning model is used for crack detection.Then computer vision is used for marking and analyzing the crack growth path and length.We apply seven models for the crack classification and find that the decision tree is the best model in this research.The experimental results prove the effectiveness of our method,and the crack length measurement accuracy achieved is 0.6 mm.Furthermore,the slight machine learning models help us realize real-time and visible fatigue crack detection. | Le Zhang Zhichen Wang Lei Wang Zhe Zhang Xu Chen Lin Meng | 2021 | Digital Communications and Networks2021，7，4： | 2 |
| 4 | FAST: Its Scientific Achievements and Prospects显示文摘FAST is the largest single-dish radio telescope in the world.The characteristics of FAST are presented and analyzed in the context of the parameter space to show how FAST science achievements are affected.We summarize the scientific achievements of FAST and discuss its future science based on the new parts of the parameter space that can be explored by FAST. | Lei Qian Rui Yao Jinghai Sun Jinlong Xu Zhichen Pan Peng Jiang | 2020 | The Innovation2020，1，3： | 2 |
| 5 | 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 |
| 6 | PeerSearch: Efficient Information Retrieval in Peer-to-Peer Networks 显示文摘 | Chunqiang Tang Zhichen Xu Mallik Mahalingam | 2003 | ACM SIGCOMM Computer Communication Review2003，33，1： | 1 |
| 7 | pSeareh : information retrieval in structured overlays显示文摘 | TANG Chunqiang XU Zhichen MAHLINGAM M | 2003 | Computer Communication Review2003，33，1： | 1 |
| 8 | In vitro generation of osteochondral differentiation of human marrow mesenchymal stem cells in novel collagen–hydroxyapatite layered scaffolds显示文摘 | Jiaan Zhou Caixia Xu Gang Wu Xiaodong Cao Liangming Zhang Zhichen Zhai Zhiwen Zheng Xiaofeng Chen Yingjun Wang | 2011 | Acta Biomaterialia2011，，11： | 1 |
| 9 | pSearch :information retrieval in structured overlays显示文摘 | Tang Chunqiang Xu Zhichen Mahalingam M | 2003 | Computer Communication Review2003，33，1： | 1 |
| 10 | Information retrieval in structured overlays显示文摘 | Tang Chunqiang Xu Zhichen Mahalingam M | 2002 | ACM SIGCOMM Computer Communication Review2002，33，1： | 1 |
| 11 | Towards a semantic aware file store显示文摘 | Zhichen Xu Magnus Karlsson Chunqiang Tang Christos Karamanolis | 2003 | HP laboratories palo Alto CA943042003，4，： | 1 |
| 12 | 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 |
| 13 | 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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