The presence of dispersion/variability in any process is understood and its careful monitoring may furnish the performance of any process. The interquartile range (IQR) is one of the dispersion measures based on lower...The presence of dispersion/variability in any process is understood and its careful monitoring may furnish the performance of any process. The interquartile range (IQR) is one of the dispersion measures based on lower and upper quartiles. For efficient monitoring of process dispersion, we have proposed auxiliary information based Shewhart-type IQR control charts (namely IQRr and IQRp charts) based on ratio and product estimators of lower and upper quartiles under bivariate normally distributed process. We have developed the control structures of proposed charts and compared their performances with the usual IQR chart in terms of detection ability of shift in process dispersion. For the said purpose power curves are constructed to demonstrate the performance of the three IQR charts under discussion in this article. We have also provided an illustrative example to justify theory and finally closed with concluding remarks.展开更多
The characteristics of density yield curve of coal and distribution curve of products can be described with median, quartile deviation, the quartile measure of skewness and kurtosis like K. On the basis of 16 groups o...The characteristics of density yield curve of coal and distribution curve of products can be described with median, quartile deviation, the quartile measure of skewness and kurtosis like K. On the basis of 16 groups of coal density composition data and their jigging stratification data derived from the pilot jig, the regression analysis has been done for the relationship between the characteristic values of the density curve and the characteristic values of the distribution curve.The results show as follow: (1) The bigger the skewness of the density curve, the bigger the probable error (Ep) and imperfection (I ) are. (2) The bigger the median of density curve, the smaller the probable error or imperfection is. (3) The characteristic values of density curve have no influence on the kurtosis K of the distribution curve.展开更多
Cloud infrastructural resource optimization is the process of precisely selecting the allocating the correct resources either to a workload or application.When workload execution,accuracy,and cost are accurately stabi...Cloud infrastructural resource optimization is the process of precisely selecting the allocating the correct resources either to a workload or application.When workload execution,accuracy,and cost are accurately stabilized in opposition to the best possible framework in real-time,efficiency is attained.In addition,every workload or application required for the framework is characteristic and these essentials change over time.But,the existing method was failed to ensure the high Quality of Service(QoS).In order to address this issue,a Tricube Weighted Linear Regression-based Inter Quartile(TWLR-IQ)for Cloud Infrastructural Resource Optimization is introduced.A Tricube Weighted Linear Regression is presented in the proposed method to estimate the resources(i.e.,CPU,RAM,and network bandwidth utilization)based on the usage history in each cloud server.Then,Inter Quartile Range is applied to efficiently predict the overload hosts for ensuring a smooth migration.Experimental results show that our proposed method is better than the approach in Cloudsim under various performance metrics.The results clearly showed that the proposed method can reduce the energy consumption and provide a high level of commitment with ensuring the minimum number of Virtual Machine(VM)Migrations as compared to the state-of-the-art methods.展开更多
The procedure of stratified double quartile ranked set sampling （SDQRSS） method is introduced to estimate the population mean. The SDQRSS is compared with the simple random sampling （SRS）, stratified ranked set sa...The procedure of stratified double quartile ranked set sampling （SDQRSS） method is introduced to estimate the population mean. The SDQRSS is compared with the simple random sampling （SRS）, stratified ranked set sampling （SRSS） and stratified simple random sampling （SSRS）. It is shown that SDQRSS estimator is an unbiased of the population mean and more efficient than SRS, SRSS and SSRS for symmetric and asymmetric distributions. In addition, by SDQRSS we can increase the efficiency of mean estimator for specific value of the sample size.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
Previous studies have suggested that abnormal hepatobiliary system function may contribute to poor prognosis in patientswith acute coronary syndrome(ACS)and that abnormal hepatobiliary system function may be associate...Previous studies have suggested that abnormal hepatobiliary system function may contribute to poor prognosis in patientswith acute coronary syndrome(ACS)and that abnormal hepatobiliary system function may be associated with per-and polyfluoroalkyl substances(PFAS)exposure.However,there is limited evidence for this association in cardiovascular subpopulations,particularly in the ACS patients.Therefore,we performed this study to evaluate the association between plasma PFAS exposure and hepatobiliary system function biomarkers in patients with ACS.This study included 546 newly diagnosed ACS patients at the Second Hospital of Hebei Medical University,and data on 15 hepatobiliary system function biomarkers were obtained from medical records.Associations between single PFAS and hepatobiliary system function biomarkers were assessed using multiple linear regression models and restricted cubic spline model(RCS),and mixture effects were assessed using the Quantile g-computation model.The results showed that total bile acids(TBA)was negative associated with perfluorohexane sulfonic acid(PFHxS)(-7.69%,95%CI:-12.15%,-3.01%).According to the RCS model,linear associations were found between TBA and PFHxS(P for overall=0.003,P for non-linear=0.234).We also have observed the association between between PFAS congeners and liver enzyme such as aspartate aminotransferase(AST)and α-l-Fucosidase(AFU),but it was not statistically significant after correction.In addition,Our results also revealed an association between prealbumin(PA)and PFAS congeners as well as mixtures.Our findings have provided a piece of epidemiological evidence on associations between PFAS congeners or mixture,and serum hepatobiliary system function biomarkers in ACS patients,which could be a basis for subsequent mechanism studies.展开更多
文摘The presence of dispersion/variability in any process is understood and its careful monitoring may furnish the performance of any process. The interquartile range (IQR) is one of the dispersion measures based on lower and upper quartiles. For efficient monitoring of process dispersion, we have proposed auxiliary information based Shewhart-type IQR control charts (namely IQRr and IQRp charts) based on ratio and product estimators of lower and upper quartiles under bivariate normally distributed process. We have developed the control structures of proposed charts and compared their performances with the usual IQR chart in terms of detection ability of shift in process dispersion. For the said purpose power curves are constructed to demonstrate the performance of the three IQR charts under discussion in this article. We have also provided an illustrative example to justify theory and finally closed with concluding remarks.
文摘The characteristics of density yield curve of coal and distribution curve of products can be described with median, quartile deviation, the quartile measure of skewness and kurtosis like K. On the basis of 16 groups of coal density composition data and their jigging stratification data derived from the pilot jig, the regression analysis has been done for the relationship between the characteristic values of the density curve and the characteristic values of the distribution curve.The results show as follow: (1) The bigger the skewness of the density curve, the bigger the probable error (Ep) and imperfection (I ) are. (2) The bigger the median of density curve, the smaller the probable error or imperfection is. (3) The characteristic values of density curve have no influence on the kurtosis K of the distribution curve.
文摘Cloud infrastructural resource optimization is the process of precisely selecting the allocating the correct resources either to a workload or application.When workload execution,accuracy,and cost are accurately stabilized in opposition to the best possible framework in real-time,efficiency is attained.In addition,every workload or application required for the framework is characteristic and these essentials change over time.But,the existing method was failed to ensure the high Quality of Service(QoS).In order to address this issue,a Tricube Weighted Linear Regression-based Inter Quartile(TWLR-IQ)for Cloud Infrastructural Resource Optimization is introduced.A Tricube Weighted Linear Regression is presented in the proposed method to estimate the resources(i.e.,CPU,RAM,and network bandwidth utilization)based on the usage history in each cloud server.Then,Inter Quartile Range is applied to efficiently predict the overload hosts for ensuring a smooth migration.Experimental results show that our proposed method is better than the approach in Cloudsim under various performance metrics.The results clearly showed that the proposed method can reduce the energy consumption and provide a high level of commitment with ensuring the minimum number of Virtual Machine(VM)Migrations as compared to the state-of-the-art methods.
文摘The procedure of stratified double quartile ranked set sampling （SDQRSS） method is introduced to estimate the population mean. The SDQRSS is compared with the simple random sampling （SRS）, stratified ranked set sampling （SRSS） and stratified simple random sampling （SSRS）. It is shown that SDQRSS estimator is an unbiased of the population mean and more efficient than SRS, SRSS and SSRS for symmetric and asymmetric distributions. In addition, by SDQRSS we can increase the efficiency of mean estimator for specific value of the sample size.
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 National Natural Science Foundation of China(No.21976050)the Science and Technology Program of Hebei Province(No.21377779D)+3 种基金the Natural Science Foundation of Hebei Province(No.B2020206008)China Postdoctoral Science Foundation(Nos.2023M730317 and 2023T160066)the Fundamental Research Funds for the Central Universities(No.3332023042)the Open Project of Hebei Key Laboratory of Environment and Human Health(No.202301).
文摘Previous studies have suggested that abnormal hepatobiliary system function may contribute to poor prognosis in patientswith acute coronary syndrome(ACS)and that abnormal hepatobiliary system function may be associated with per-and polyfluoroalkyl substances(PFAS)exposure.However,there is limited evidence for this association in cardiovascular subpopulations,particularly in the ACS patients.Therefore,we performed this study to evaluate the association between plasma PFAS exposure and hepatobiliary system function biomarkers in patients with ACS.This study included 546 newly diagnosed ACS patients at the Second Hospital of Hebei Medical University,and data on 15 hepatobiliary system function biomarkers were obtained from medical records.Associations between single PFAS and hepatobiliary system function biomarkers were assessed using multiple linear regression models and restricted cubic spline model(RCS),and mixture effects were assessed using the Quantile g-computation model.The results showed that total bile acids(TBA)was negative associated with perfluorohexane sulfonic acid(PFHxS)(-7.69%,95%CI:-12.15%,-3.01%).According to the RCS model,linear associations were found between TBA and PFHxS(P for overall=0.003,P for non-linear=0.234).We also have observed the association between between PFAS congeners and liver enzyme such as aspartate aminotransferase(AST)and α-l-Fucosidase(AFU),but it was not statistically significant after correction.In addition,Our results also revealed an association between prealbumin(PA)and PFAS congeners as well as mixtures.Our findings have provided a piece of epidemiological evidence on associations between PFAS congeners or mixture,and serum hepatobiliary system function biomarkers in ACS patients,which could be a basis for subsequent mechanism studies.
