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1. The Global Infectious Diseases Epidemic Information Monitoring System: Development and Usability Study of an Effective Tool for Travel Health Management in China

Author

Gu, Dayong, He, Jianan, Sun, Jie, Shi, Xin, Ye, Ying, Zhang, Zishuai, Wang, Xiangjun, Su, Qun, Yu, Wenjin, Yuan, Xiaopeng, and Dong, Ruiling

Subjects
Public aspects of medicine, RA1-1270
Abstract

BackgroundObtaining comprehensive epidemic information for specific global infectious diseases is crucial to travel health. However, different infectious disease information websites may have different purposes, which may lead to misunderstanding by travelers and travel health staff when making accurate epidemic control and management decisions. ObjectiveThe objective of this study was to develop a Global Infectious Diseases Epidemic Information Monitoring System (GIDEIMS) in order to provide comprehensive and timely global epidemic information. MethodsDistributed web crawler and cloud agent acceleration technologies were used to automatically collect epidemic information about more than 200 infectious diseases from 26 established epidemic websites and Baidu News. Natural language processing and in-depth learning technologies have been utilized to intelligently process epidemic information collected in 28 languages. Currently, the GIDEIMS presents world epidemic information using a geographical map, including date, disease name, reported cases in different countries, and the epidemic situation in China. In order to make a practical assessment of the GIDEIMS, we compared infectious disease data collected from the GIDEIMS and other websites on July 16, 2019. ResultsCompared with the Global Incident Map and Outbreak News Today, the GIDEIMS provided more comprehensive information on human infectious diseases. The GIDEIMS is currently used in the Health Quarantine Department of Shenzhen Customs District (Shenzhen, China) and was recommended to the Health Quarantine Administrative Department of the General Administration of Customs (China) and travel health–related departments. ConclusionsThe GIDEIMS is one of the most intelligent tools that contributes to safeguarding the health of travelers, controlling infectious disease epidemics, and effectively managing public health in China.

Published
2021
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2. Primitive Graph Learning for Unified Vector Mapping

Author

Wang, Lei, Dai, Min, He, Jianan, Huang, Jingwei, and Sun, Mingwei

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Large-scale vector mapping is important for transportation, city planning, and survey and census. We propose GraphMapper, a unified framework for end-to-end vector map extraction from satellite images. Our key idea is a novel unified representation of shapes of different topologies named "primitive graph", which is a set of shape primitives and their pairwise relationship matrix. Then, we convert vector shape prediction, regularization, and topology reconstruction into a unique primitive graph learning problem. Specifically, GraphMapper is a generic primitive graph learning network based on global shape context modelling through multi-head-attention. An embedding space sorting method is developed for accurate primitive relationship modelling. We empirically demonstrate the effectiveness of GraphMapper on two challenging mapping tasks, building footprint regularization and road network topology reconstruction. Our model outperforms state-of-the-art methods in both tasks on public benchmarks. All code will be publicly available.

Published
2022

8. Earth Summit Mission 2022: Scientific Expedition and Research on Mt. Qomolangma Helps Reveal the Synergy between Westerly Winds and Monsoon and the Resulting Climatic and Environmental Effects

Author

Ma, Yaoming, Ma, Weiqiang, Dai, Huaguang, Zhang, Lei, Sun, Fanglin, Zhang, Jinqiang, Yao, Nan, He, Jianan, Bai, Zhixuan, Xuan, Yuejian, Zhang, Yunshuai, Yuan, Yuan, Yang, Chenyi, Sun, Weijun, Zhao, Ping, Ding, Minghu, Zhu, Kongju, Hu, Jie, Bazhuga, Bian, Juepingcuo, Bai, Ma, Zhuo, Qingnima, Ren, Langwangdui, Suo, Zong, Yang, and Wen, Haikun

Published
2023
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11. The rationality of M&A targets in the choice of payment methods

Author

Klitzka, Michael, He, Jianan, Schiereck, Dirk, Klitzka, Michael, He, Jianan, and Schiereck, Dirk

Abstract

This study analyzes mergers and acquisitions (M&A) payment methods in large transactions of public U.S. acquirers between 2009 and 2016. While we find consistent with previous evidence that asymmetric information between acquirers and targets significantly influences the choice of M&A payment methods, we show that contrary to prevailing findings in the literature, acquirers cannot exploit their overvaluation through stock-financed M&A at targets’ disadvantage. In addition, when facing larger uncertainty in the counterparty’s valuation, a higher ratio of cash is applied in M&A payment. Our results document that both acquirers and targets are rational in choosing M&A payment methods.

Published
2024

18. The Fault Ride-Through Characteristics of a Double-Fed Induction Generator Using a Dynamic Voltage Restorer with Superconducting Magnetic Energy Storage.

Author

Li, Lei, Liang, Yabo, Niu, Jian, He, Jianan, Liu, Haitao, Li, Bin, Li, Chao, and Cao, Yunzhu

Subjects
MAGNETIC energy storage, INDUCTION generators, RENEWABLE energy sources, VOLTAGE, ELECTROSTATIC induction, FAULT currents, WIND power, WIND turbines
Abstract

With the prevalence of renewable energy sources such as wind power in the power system, analyzing the fault characteristics of systems composed of DFIGs is becoming increasingly important. Therefore, this article analyzes, at first theoretically, the fault characteristics of a doubly fed induction generator (DFIG) during fault periods. It was found that the fault current of the DFIG exhibited the frequency offset phenomenon, which is affected by the depth of voltage dips and can negatively impact traditional distance protection. Furthermore, a method using a dynamic voltage restorer (DVR) based on superconducting magnetic energy storage (SMES) was adopted to compensate for the fault voltage of DFIG, which can mitigate the voltage dips of the DFIG. This method can not only achieve the fault ride through for DFIG but also significantly improve the frequency offset of the fault current during fault periods. Finally, a model composed of a 2.5 MW DFIG-based wind turbine and a 2.5 MW DVR-based SMES was built using a real-time digital simulator (RTDS) platform, and the simulation results showed that the fault stator voltage of DFIG can be compensated at a rated value of 0.69 kV, and the frequency of fault current can be maintained at 50 Hz These results validate the excellent performance of the method in achieving the fault ride through of DFIG and improving the frequency offset of the fault current by comparing multiple type faults while employing different protection methods. [ABSTRACT FROM AUTHOR]

Published
2023
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19. Earth Summit Mission 2022: Scientific Expedition and Research on Mt. Qomolangma Helps Reveal the Synergy between Westerly Winds and Monsoon and the Resulting Climatic and Environmental Effects

Author

Ma, Yaoming, primary, Ma, Weiqiang, additional, Dai, Huaguang, additional, Zhang, Lei, additional, Sun, Fanglin, additional, Zhang, Jinqiang, additional, Yao, Nan, additional, He, Jianan, additional, Bai, Zhixuan, additional, Xuan, Yuejian, additional, Zhang, Yunshuai, additional, Yuan, Yuan, additional, Yang, Chenyi, additional, Sun, Weijun, additional, Zhao, Ping, additional, Ding, Minghu, additional, Zhu, Kongju, additional, Hu, Jie, additional, Bazhuga, Bian, additional, Juepingcuo, Bai, additional, Ma, Zhuo, additional, Qingnima, Ren, additional, Langwangdui, Suo, additional, Zong, Yang, additional, and Wen, Haikun, additional

Published
2022
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20. Microbial and human transcriptional profiling of coronavirus disease 2019 patients: Potential predictors of disease severity

Author

Gan, Hairun, primary, Min, Jiumeng, additional, Long, Haoyu, additional, Li, Bing, additional, Hu, Xinyan, additional, Zhu, Zhongyi, additional, Li, Luting, additional, Wang, Tiancheng, additional, He, Xiangyan, additional, Cai, Jianxun, additional, Zhang, Yongyu, additional, He, Jianan, additional, Chen, Luan, additional, Wang, Dashuai, additional, Su, Jintao, additional, Zhao, Ni, additional, Huang, Weile, additional, Zhang, Jingjing, additional, Su, Ziqi, additional, Guo, Hui, additional, Hu, Xiaojun, additional, Mao, Junjie, additional, Ma, Jinmin, additional, and Pang, Pengfei, additional

Published
2022
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21. Factors explaining capital market reactions during corporate, sovereign, and pandemic events

Author

He, Jianan and He, Jianan

Abstract

The presented studies show evidence of the semi-strong market efficiency, where security prices react significantly to public announcements of the events that are crucial to firms’ valuation. We focus on two trends in capital markets. One is industry integration, where companies improve their efficiency to adapt to the changing environment. In this context, many firms choose M&A to achieve external growth and strengthen their competitiveness. The other is investment diversification, where investors actively search for low correlated markets and assets with global portfolios to reduce their investment risk. These two trends have been well explored in previous studies, where researchers provide deep insights to market participants. Nevertheless, the recent changes in regulation and market environment have put many findings in question, and some emerging markets and assets are still unfamiliar to investors. These unknowns gain more importance during the Covid-19 crisis. On the one side, the pandemic has accelerated the industry integration as many inefficient firms suffered liquidity shortages and were acquired by better-positioned firms; on the other side, investors have been searching for alternatives to diversify investment risk as central banks have injected massive liquidity into capital markets, leading to soaring inflation risk. This dissertation addresses new findings on the aforementioned trends and important implications for different groups of interests.

Published
2022

35. Association between quantitative analyses of periodontal pathogens and the depth of periodontal pockets.

Author

He, Jianan, Da, Lyu, Pan, Yining, Tan, Xuanping, Li, Zhitian, Luo, Feiyue, Xie, Weidong, and Gu, Dayong

Subjects
*PORPHYROMONAS gingivalis, *ACTINOBACILLUS actinomycetemcomitans, *PERIODONTAL pockets, *RECEIVER operating characteristic curves, *MOUTH
Abstract

The aim of this study was to investigate the association between expressions of five periodontal pathogens (Actinobacillus actinomycetemcomitans (Aa), Porphyromonas gingivalis (Pg), Tannerella forsythensis (Tf), Treponema denticola (Td) and Prevotella intermedia (Pi) and the periodontal pocket depth (PD) in people suffering from periodontitis. A study of 1164 plaque samples from individuals with periodontitis were conducted by multiplex real-time quantitative fluorescence-polymerase chain reaction to evaluate the PD and loads of five periodontal pathogens. The total bacterial number did not differ significantly between people with different subtypes of periodontitis. However, expression of specific pathogens (Pg, Td, Tf, Pi) showed a significant increase with the development of periodontitis. Expression of Pg, Td and Tf showed close correlation between them as well as with PD. Analyses of receiver operating characteristic curves showed that expression of Pg, Td, Tf and Pi had good potential for grading periodontitis severity. We found a close correlation between the relative expression of Pg, Td and Tf and PD. Measuring expression of target bacteria in the oral cavity could facilitate the understanding of the role of bacteria in periodontitis. Taking the appropriate steps to eliminate these pathogens might aid the prevention of periodontitis development. [ABSTRACT FROM AUTHOR]

Published
2020
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49. n Electronic Component Recognition Algorithm Based on Deep Learning with a Faster SqueezeNet.

Author

Xu, Yuanyuan, Yang, Genke, Luo, Jiliang, and He, Jianan

Subjects
*ELECTRONIC equipment, *ALGORITHMS, *RECEIVER operating characteristic curves, *DEEP learning, *PRINCIPAL components analysis, *SUPPORT vector machines
Abstract

Electronic component recognition plays an important role in industrial production, electronic manufacturing, and testing. In order to address the problem of the low recognition recall and accuracy of traditional image recognition technologies (such as principal component analysis (PCA) and support vector machine (SVM)), this paper selects multiple deep learning networks for testing and optimizes the SqueezeNet network. The paper then presents an electronic component recognition algorithm based on the Faster SqueezeNet network. This structure can reduce the size of network parameters and computational complexity without deteriorating the performance of the network. The results show that the proposed algorithm performs well, where the Receiver Operating Characteristic Curve (ROC) and Area Under the Curve (AUC), capacitor and inductor, reach 1.0. When the FPR is less than or equal 10 − 6 level, the TPR is greater than or equal to 0.99; its reasoning time is about 2.67 ms, achieving the industrial application level in terms of time consumption and performance. [ABSTRACT FROM AUTHOR]

Published
2020
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