The Reliability-Based Design Optimization(RBDO)of complex engineering structures considering uncertainties has problems of being high-dimensional,highly nonlinear,and timeconsuming,which requires a significant amount ...The Reliability-Based Design Optimization(RBDO)of complex engineering structures considering uncertainties has problems of being high-dimensional,highly nonlinear,and timeconsuming,which requires a significant amount of sampling simulation computation.In this paper,a basis-adaptive Polynomial Chaos(PC)-Kriging surrogate model is proposed,in order to relieve the computational burden and enhance the predictive accuracy of a metamodel.The active learning basis-adaptive PC-Kriging model is combined with a quantile-based RBDO framework.Finally,five engineering cases have been implemented,including a benchmark RBDO problem,three high-dimensional explicit problems,and a high-dimensional implicit problem.Compared with Support Vector Regression(SVR),Kriging,and polynomial chaos expansion models,results show that the proposed basis-adaptive PC-Kriging model is more accurate and efficient for RBDO problems of complex engineering structures.展开更多
Metal may affect maternal immune function,but few epidemiological studies have reported the associations between multiple-metal exposure and maternal immunoglobulin(Ig)levels.Based on the Hangzhou Birth Cohort Study,1...Metal may affect maternal immune function,but few epidemiological studies have reported the associations between multiple-metal exposure and maternal immunoglobulin(Ig)levels.Based on the Hangzhou Birth Cohort Study,1059 participants were included,and eleven metals in whole blood samples and serum IgA,IgG,IgE and IgM levels were measured.Linear regression,quantile-based g-computation(QGC),and Bayesian kernel machine regression(BKMR)models were used to evaluate the associations.Compared with the first tertile of metal levels,arsenic(As)was negatively associated with IgE(β=-0.25,95%confidence interval(CI)=-0.48 to-0.02).Moreover,significant associations of manganese(Mn)with IgA,IgG and IgM were demonstrated(β=0.10,95%CI=0.04 to 0.18;β=0.07,95%CI=0.03 to 0.12;β=0.10,95%CI=0.03 to 0.18,respectively).Cadmium(Cd)were associated with higher levels of IgM.QGC models showed the positive association of the metalmixtures with IgA and IgG,with Mn playing amajor role.Mn and Cd had positive contributions to IgM,while As had negative contributions to IgE.In the BKMR models,the latent continuous outcomes of IgA and IgG showed a significant increase when all the metals were at their 60th percentile or above compared to those at their 50th percentile.Therefore,exposure to metals was associated with maternal Igs,and mainly showed that Mn was associated with increased levels of IgA,IgG and IgM,and As was associated with low IgE levels.展开更多
BACKGROUND Dyslipidemia and type 2 diabetes mellitus(T2DM)are chronic conditions with substantial public health implications.Effective management of lipid metabolism in patients with T2DM is critical.However,there has...BACKGROUND Dyslipidemia and type 2 diabetes mellitus(T2DM)are chronic conditions with substantial public health implications.Effective management of lipid metabolism in patients with T2DM is critical.However,there has been insufficient attention given to the relationship between thyroid hormone sensitivity and dyslipidemia in the T2DM population,particularly concerning non-high-density lipoprotein cholesterol(non-HDL-C).AIM To clarify the association between thyroid hormone sensitivity and dyslipidemia in patients with T2DM.METHODS In this cross-sectional study,thyroid hormone sensitivity indices,the thyroid feedback quantile-based index(TFQI),the thyroid-stimulating hormone index(TSHI),the thyrotrophic T4 resistance index(TT4RI),and the free triiodothyronine(FT3)/free thyroxine(FT4)ratio were calculated.Logistic regression analysis was performed to determine the associations between those composite indices and non-HDL-C levels.Random forest variable importance and Shapley Additive Explanations(SHAP)summary plots were used to identify the strength and direction of the association between hyper-non-HDL-C and its major predictor.RESULTS Among the 994 participants,389(39.13%)had high non-HDL-C levels.Logistic regression analysis revealed that the risk of hyper-non-HDL-C was positively correlated with the TFQI(OR:1.584;95%CI:1.088-2.304;P=0.016),TSHI(OR:1.238;95%CI:1.034-1.482;P=0.02),and TT4RI(OR:1.075;95%CI:1.006-1.149;P=0.032)but was not significantly correlated with the FT3/FT4 ratio.The relationships between composite indices of the thyroid system and non-HDL-C levels differed according to sex.An increased risk of hyper-non-HDL-C was associated with elevated TSHI levels in men(OR:1.331;95%CI:1.003-1.766;P=0.048)but elevated TFQI levels in women(OR:2.337;95%CI:1.4-3.901;P=0.001).Among the analyzed variables,the average SHAP values were highest for TSHI,followed by TT4RI.CONCLUSION Impaired sensitivity to thyroid hormones was associated with high non-HDL-C levels in patients with T2DM.展开更多
基金supported by the National Key R&D Program of China(No.2021YFB1715000)the National Natural Science Foundation of China(No.52375073)。
文摘The Reliability-Based Design Optimization(RBDO)of complex engineering structures considering uncertainties has problems of being high-dimensional,highly nonlinear,and timeconsuming,which requires a significant amount of sampling simulation computation.In this paper,a basis-adaptive Polynomial Chaos(PC)-Kriging surrogate model is proposed,in order to relieve the computational burden and enhance the predictive accuracy of a metamodel.The active learning basis-adaptive PC-Kriging model is combined with a quantile-based RBDO framework.Finally,five engineering cases have been implemented,including a benchmark RBDO problem,three high-dimensional explicit problems,and a high-dimensional implicit problem.Compared with Support Vector Regression(SVR),Kriging,and polynomial chaos expansion models,results show that the proposed basis-adaptive PC-Kriging model is more accurate and efficient for RBDO problems of complex engineering structures.
基金supported by the National Natural Science Foundation of China(No.U22A20358)Zhejiang Provincial Program for the Cultivation of High-Level Innovative Health Talents(No.2020-18).
文摘Metal may affect maternal immune function,but few epidemiological studies have reported the associations between multiple-metal exposure and maternal immunoglobulin(Ig)levels.Based on the Hangzhou Birth Cohort Study,1059 participants were included,and eleven metals in whole blood samples and serum IgA,IgG,IgE and IgM levels were measured.Linear regression,quantile-based g-computation(QGC),and Bayesian kernel machine regression(BKMR)models were used to evaluate the associations.Compared with the first tertile of metal levels,arsenic(As)was negatively associated with IgE(β=-0.25,95%confidence interval(CI)=-0.48 to-0.02).Moreover,significant associations of manganese(Mn)with IgA,IgG and IgM were demonstrated(β=0.10,95%CI=0.04 to 0.18;β=0.07,95%CI=0.03 to 0.12;β=0.10,95%CI=0.03 to 0.18,respectively).Cadmium(Cd)were associated with higher levels of IgM.QGC models showed the positive association of the metalmixtures with IgA and IgG,with Mn playing amajor role.Mn and Cd had positive contributions to IgM,while As had negative contributions to IgE.In the BKMR models,the latent continuous outcomes of IgA and IgG showed a significant increase when all the metals were at their 60th percentile or above compared to those at their 50th percentile.Therefore,exposure to metals was associated with maternal Igs,and mainly showed that Mn was associated with increased levels of IgA,IgG and IgM,and As was associated with low IgE levels.
基金Supported by the Xuanwu Hospital Capital Medical University Science Program for Fostering Young Scholars,No.YC20220113the Pilot Project for Public,No.Beijing Medical Research 2021-8.
文摘BACKGROUND Dyslipidemia and type 2 diabetes mellitus(T2DM)are chronic conditions with substantial public health implications.Effective management of lipid metabolism in patients with T2DM is critical.However,there has been insufficient attention given to the relationship between thyroid hormone sensitivity and dyslipidemia in the T2DM population,particularly concerning non-high-density lipoprotein cholesterol(non-HDL-C).AIM To clarify the association between thyroid hormone sensitivity and dyslipidemia in patients with T2DM.METHODS In this cross-sectional study,thyroid hormone sensitivity indices,the thyroid feedback quantile-based index(TFQI),the thyroid-stimulating hormone index(TSHI),the thyrotrophic T4 resistance index(TT4RI),and the free triiodothyronine(FT3)/free thyroxine(FT4)ratio were calculated.Logistic regression analysis was performed to determine the associations between those composite indices and non-HDL-C levels.Random forest variable importance and Shapley Additive Explanations(SHAP)summary plots were used to identify the strength and direction of the association between hyper-non-HDL-C and its major predictor.RESULTS Among the 994 participants,389(39.13%)had high non-HDL-C levels.Logistic regression analysis revealed that the risk of hyper-non-HDL-C was positively correlated with the TFQI(OR:1.584;95%CI:1.088-2.304;P=0.016),TSHI(OR:1.238;95%CI:1.034-1.482;P=0.02),and TT4RI(OR:1.075;95%CI:1.006-1.149;P=0.032)but was not significantly correlated with the FT3/FT4 ratio.The relationships between composite indices of the thyroid system and non-HDL-C levels differed according to sex.An increased risk of hyper-non-HDL-C was associated with elevated TSHI levels in men(OR:1.331;95%CI:1.003-1.766;P=0.048)but elevated TFQI levels in women(OR:2.337;95%CI:1.4-3.901;P=0.001).Among the analyzed variables,the average SHAP values were highest for TSHI,followed by TT4RI.CONCLUSION Impaired sensitivity to thyroid hormones was associated with high non-HDL-C levels in patients with T2DM.
