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- 저자 : ( Chuan-lai Hu ) (검색결과 2 건)
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Test Method for Determination of Optimum Moisture Content of Soil and Maximum Dry Density
Xiao-Chuan Ren,Yuan-Ming Lai,Fan-Yu Zhang,Kai Hu 대한토목학회 2015 KSCE Journal of Civil Engineering Vol.19 No.7
A method for accurately determining the optimum water content of soil and the corresponding maximum dry density has been developed using a small number of soil samples, based on the physical parameters of the confined compression modulus of soil. The peak value of the compression modulus on the force-compression modulus curve is used to determine the optimum moisture content and maximum dry density. The proposed method is validated using four different types of soils: Qinghai-Tibet clay, SiO2-clay, Lanzhou loess, and Qinghai-Tibet sand soil. The results show that as opposed to conventional compaction methods, the new method allows for accurate determination of the optimum water content and the maximum dry density for various types of soil. Additionally, for certain moisture contents, when the compaction of soil is the greatest, clay and SiO2-clay attain the theoretical saturation status, whereas sand soil and loess do not.
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Weight Gain in Pregnancy, Maternal Age and Gestational Age in Relation to Fetal Macrosomia
( Yi Li ),( Qi-fei Liu ),( Dan Zhang ),( Ying Shen ),( Kui Ye ),( Han-lin Lai ),( Hai-qing Wang ),( Chuan-lai Hu ),( Qi-hong Zhao ),( Li Li ) 한국임상영양학회 2015 Clinical Nutrition Research Vol.4 No.2
To investigate the possible risk factors related to macrosomia. Pregnant women and their newborns (n = 1041) were recruited from a cohort study in Maternal and Child Care Center of Hefei from January 2011 to July 2012. Questionnaires were applied to collect the demographic data besides the medical records. Detailed health records of the entire pregnancy were obtained using retrospective study. Meanwhile the data of neonatal outcomes was prospectively tracked. Associations between exposure risk factors and macrosomia were analyzed using Pearson’s chi squared test. Logistic regression models were used to assess the independent association between these potential predictors and macrosomia. The incidence of macrosomia of this cohort was 11.24% of which male: female = 2.55:1. Male incidence (8.07%) of macrosomia was higher than female (3.17%), p < 0.001. Body mass index (BMI) before pregnancy (pre-BMI), maternal height, parity were not independently associated with macrosomia; multiple logistic regression analysis indicated that macrosomia was mainly independently associated with weight gain in pregnancy (OR=1.14,95% CI [1.10-1.19]), maternal age (OR = 1.09,95% CI [1.03-1.15]) and gestational age (OR = 1.62,95% CI [1.31-1.99]), respectively. Our findings indicate that weight gain in pregnancy, maternal age and gestational age should be considered as independent risk factors for macrosomia.
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