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510 results on '"Xu, Chengdong"'

1. Spatiotemporal Analysis of Men Who Have Sex With Men in Mainland China: Social App Capture-Recapture Method

Author

Hu, Maogui, Xu, Chengdong, and Wang, Jinfeng

Subjects
Information technology, T58.5-58.64, Public aspects of medicine, RA1-1270
Abstract

BackgroundIn China, the cases of newly diagnosed HIV/AIDS in men who have sex with men (MSM) have increased more than tenfold since 2006. However, the MSM population size, geographical distribution, and migration patterns are largely unknown. ObjectiveOur aim is to estimate the number, spatial distribution, and migration of MSM populations in mainland China using big data from social networking. MethodsWe collected 85 days of data on online users of a social networking MSM app in mainland China. Daily online MSM users and their migration across the country were investigated during a holiday period and a nonholiday period. Using the capture-mark-recapture model, we designed an experiment consisting of two independent samples to estimate the total provincial MSM population. ResultsThe estimate of MSM in mainland China was 8,288,536 (95% CI 8,274,931-8,302,141), accounting for 1.732% (95% CI 1.729%-1.734%) of adult men aged 18 to 64 years. The average daily number of MSM social networking online across mainland China was 1,198,682 during the nonholiday period. The five provinces (including municipalities) with the highest average number of daily online MSM numbers were Guangdong (n=141,712), Jiangsu (n=90,710), Zhejiang (n=72,212), Shandong (n=68,065), and Beijing (n=66,057). The proportion of daily online MSM among adult men in different cities varied from 0.04% to 0.96%, with a mean of 0.20% (SD 0.14%). Three migrating centers—Guangdong, Beijing, and the Yangtze River Delta (Shanghai-Zhejiang-Jiangsu)—accounted for 57.23% of MSM migrants in the county. ConclusionsThe percentage of MSM among adult men in mainland China is at the middle level compared with other Asia and Pacific countries. However, the number of MSM is very large, and the distribution is uneven. Both MSM distribution and migration are highly affected by socioeconomic status.

Published
2020
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2. ARAIM Integrity and Continuity Considering Fault Detection and Exclusion

Author

Sun, Rui, Xu, Chengdong, Huang, Guoxian, Zhao, Jing, Lu, Zhiwei, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Yang, Changfeng, editor, and Xie, Jun, editor

Published
2024
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5. Statistics for Spatially Stratified Heterogeneous Data

Author

Wang, Jinfeng, Haining, Robert, Zhang, Tonglin, Xu, Chengdong, and Hu, Maogui

Subjects
Statistics - Methodology
Abstract

Spatial statistics is dominated by spatial autocorrelation (SAC) based Kriging and BHM, and spatial local heterogeneity based hotspots and geographical regression methods, appraised as the first and second laws of Geography (Tobler 1970; Goodchild 2004), respectively. Spatial stratified heterogeneity (SSH), the phenomena of a partition that within strata is more similar than between strata, examples are climate zones and landuse classes and remote sensing classification, is prevalent in geography and understood since ancient Greek, is surprisingly neglected in Spatial Statistics, probably due to the existence of hundreds of classification algorithms. In this article, we go beyond the classifications and disclose that SSH is the sources of sample bias, statistic bias, modelling confounding and misleading CI, and recommend robust solutions to overcome the negativity. In the meantime, we elaborate four benefits from SSH: creating identical PDF or equivalent to random sampling in stratum; the spatial pattern in strata, the borders between strata as a specific information for nonlinear causation; and general interaction by overlaying two spatial patterns. We developed the equation of SSH and discuss its context. The comprehensive investigation formulates the statistics for SSH, presenting a new principle and toolbox in spatial statistics.

Published
2022
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14. Seasonal association between viral causes of hospitalised acute lower respiratory infections and meteorological factors in China: a retrospective study

Author

Xu, Bing, Wang, Jinfeng, Li, Zhongjie, Xu, Chengdong, Liao, Yilan, Hu, Maogui, Yang, Jing, Lai, Shengjie, Wang, Liping, and Yang, Weizhong

Subjects
Statistics - Applications
Abstract

Acute lower respiratory infections caused by respiratory viruses are common and persistent infectious diseases worldwide and in China, which have pronounced seasonal patterns. Meteorological factors have important roles in the seasonality of some major viruses. Our aim was to identify the dominant meteorological factors and to model their effects on common respiratory viruses in different regions of China. We analysed monthly virus data on patients from 81 sentinel hospitals in 22 provinces in mainland China from 2009 to 2013. The geographical detector method was used to quantify the explanatory power of each meteorological factor, individually and interacting in pairs. 28369 hospitalised patients with ALRI were tested, 10387 were positive for at least one virus, including RSV, influenza virus, PIV, ADV, hBoV, hCoV and hMPV. RSV and influenza virus had annual peaks in the north and biannual peaks in the south. PIV and hBoV had higher positive rates in the spring summer months. hMPV had an annual peak in winter spring, especially in the north. ADV and hCoV exhibited no clear annual seasonality. Temperature, atmospheric pressure, vapour pressure, and rainfall had most explanatory power on most respiratory viruses in each region. Relative humidity was only dominant in the north, but had no significant explanatory power for most viruses in the south. Hours of sunlight had significant explanatory power for RSV and influenza virus in the north, and for most viruses in the south. Wind speed was the only factor with significant explanatory power for human coronavirus in the south. For all viruses, interactions between any two of the paired factors resulted in enhanced explanatory power, either bivariately or non-linearly., Comment: 6 figures and tables

Published
2020
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19. Protection Level for Precise Point Positioning Based on Gaussian Mixture Model

Author

Wang, Jitao, Xu, Chengdong, Shi, Moran, Lu, Zhiwei, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Yang, Changfeng, editor, and Xie, Jun, editor

Published
2022
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26. Spatial Dynamics of Chickenpox Outbreaks in Rapidly Developing Regions: Implications for Global Public Health*.

Author

Wang, Li, Wang, Miaomiao, Xu, Chengdong, Wang, Peihan, You, Meiying, Li, Zihan, Chen, Xinmei, Liu, Xinyu, Li, Xudong, Wang, Yuanyuan, Hu, Yuehua, and Yin, Dapeng

Subjects
CHICKENPOX, RENTAL housing, SOCIOECONOMIC factors, INFECTIOUS disease transmission, RESIDENTIAL areas
Abstract

The occurrence of chickenpox in rapidly developing areas poses substantial seasonal risk to children. However, certain factors influencing local chickenpox outbreaks have not been studied. Here, we examined the relationship between spatial clustering, heterogeneity of chickenpox outbreaks, and socioeconomic factors in Southern China. We assessed chickenpox outbreak data from Southern China between 2006 and 2021, comprising both relatively fast-growing parts and slower sub-regions, and provides a representative sample of many developing regions. We analyzed the spatial clustering attributes associated with chickenpox outbreaks using Moran's I and local indicators of spatial association and quantified their socioeconomic determinants using Geodetector q statistics. There were significant spatial heterogeneity in the risk of chickenpox outbreaks, with strong correlations between chickenpox risk and various factors, particularly demographics and living environment. Furthermore, interactive effects among specific are factors, such as population density and per capita residential building area, percentage of households with toilets, percentage of rental housing, exhibited q statistics of 0.28, 0.25, and 0.24, respectively. This study provides valuable insights into the spatial dynamics of chickenpox outbreaks in rapidly developing regions, revealing the socioeconomic factors affecting disease transmission. These implications extend the formulation of effective public health strategies and interventions to prevent and control chickenpox outbreaks in similar global contexts. [ABSTRACT FROM AUTHOR]

Published
2024
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38. Error Prediction Model of Klobuchar Ionospheric Delay Based on TS Fuzzy Neural Network

Author

Peng, Yaqi, Xu, Chengdong, Niu, Fei, Wang, Yiwen, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martin, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Sun, Jiadong, editor, Yang, Changfeng, editor, and Yang, Yuanxi, editor

Published
2019
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44. In situ transformation of ethoxylate and glycol surfactants by shale-colonizing microorganisms during hydraulic fracturing

Author

Evans, Morgan V., Getzinger, Gordon, Luek, Jenna L., Hanson, Andrea J., McLaughlin, Molly C., Blotevogel, Jens, Welch, Susan A., Nicora, Carrie D., Purvine, Samuel O., Xu, Chengdong, Cole, David R., Darrah, Thomas H., Hoyt, David W., Metz, Thomas O., Lee Ferguson, P., Lipton, Mary S., Wilkins, Michael J., and Mouser, Paula J.

Published
2019
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