Objective To evaluate the epicardial fat tissue thickness （EFTT） as a diagnostic criterion for geriatric patients with metabolic syn- drome （MetS）. Methods Sixty geriatric patients over 65 years of age were recrui...Objective To evaluate the epicardial fat tissue thickness （EFTT） as a diagnostic criterion for geriatric patients with metabolic syn- drome （MetS）. Methods Sixty geriatric patients over 65 years of age were recruited for the study. Patients were divided into two groups： Group 1 （n = 30） consisted of patients with MetS; Group 2 （n = 30） consisted of patients without MetS. Echocardiography was used to measure EFTT in all patients, and blood samples were analyzed for biochemical parameters. Results Compared to Group 2, EFTT levels of Group 1 were statistically higher （P 〈 0.05）. In a binary logistic regression analysis, EFTT levels served as the independent factor for meta- bolic syndrome 03 = 17.35, SE = 4.93, Wald = 12.36, P 〈 0.001）. Receivers operating characteristic Curve （ROC-curve） analysis revealed that EFTT predicted MetS with 96.7% sensitivity and 86.7% specificity above the level of 7.3 mm [area under the curve = 0.969; 95% con- fidence interval （CI）： 0.928-1.00]. Conclusions The present study demonstrated that serum EFTT levels were higher in geriatric patients with MetS and can therefore be used as a diagnostic criterion for MetS.展开更多
In order to improve the precision of mining subsidence prediction, a mathematical model using Support Vector Machine （SVM） was established to calculate the displacement factor. The study is based on a comprehensive ...In order to improve the precision of mining subsidence prediction, a mathematical model using Support Vector Machine （SVM） was established to calculate the displacement factor. The study is based on a comprehensive analysis of factors affecting the displacement factor, such as mechanical properties of the cover rock, the ratio of mining depth to seam thickness, dip angle of the coal seam and the thickness of loose layer. Data of 63 typical observation stations were used as a training and testing sample set. A SVM regression model of the displacement factor and the factors affecting it was established with a kernel function, an insensitive loss factor and a properly selected penalty factor. Given an accurate calculation algorithm for testing and analysis, the results show that an SVM regression model can calcu- late displacement factor precisely and reliable precision can be obtained which meets engineering requirements. The experimental results show that the method to calculation of the displacement factor, based on the SVM method, is feasible. The many factors affecting the displacement factor can be consid- ered with this method. The research provides an efficient and accurate approach for the calculation of displacement in mining subsidence orediction.展开更多
The longwall mining method is often affected by the out-of-seam dilution （OSD）. Therefore, predicting and controlling of dilution are important factors for reducing mining costs. In this study, the fuzzy set theory ...The longwall mining method is often affected by the out-of-seam dilution （OSD）. Therefore, predicting and controlling of dilution are important factors for reducing mining costs. In this study, the fuzzy set theory and multiple regression models with parameters, including variation in seam thickness, dip of seam, seam thickness, depth of seam, and hydraulic radius as inputs to the models were applied to pre- dict the OSD in the longwall coal panels. Field data obtained from Kerman and Tabas coal mines, lran were used to develop and validate the models. Three indices including coefficient of determination （R2）, root mean square error （RMSE） and variance account for （VAF） were used to evaluate the perfor- mance of the models. With 10 randomly selected datasets, for the linear, polynomial, power, exponential, and fuzzy logic models, R2, RSME and VAF are equal to （0.85, 4.4, 84.4）, （0.61, 7.5, 59.6）, （0.84, 4.5, 72.7）, （0.80, 4.1, 79.6）, and （0.97, 2.1, 95.7）, respectively. The obtained results indicate that the fuzzy logic model predictor with R2 = 0.97, RMSE = 2.1, and VAF = 95.7 performs better than the other models.展开更多
In order to improve the through-thickness homogeneity and properties of aviation aluminum alloy thick plate.The effect of heating-cooling retrogression and re-ageing on the performance of Al-8Zn-2Mg-2Cu alloy thick pl...In order to improve the through-thickness homogeneity and properties of aviation aluminum alloy thick plate.The effect of heating-cooling retrogression and re-ageing on the performance of Al-8Zn-2Mg-2Cu alloy thick plate was investigated by hardness tests, electrical conductivity tests and transmission electron microscopy(TEM) observation.Results revealed that, during retrogression heating, the fine pre-precipitates in surface layer dissolve more and the undissolved η′ or η phases are more coarsened than that of center layer. During slow cooling after retrogression,precipitates continue coarsening but with a lower rate and the secondary precipitation occurs in both layers. Finer precipitates resulting from the secondary precipitation are more in surface. However, the coarsening and secondary precipitation behaviors are restrained in both layers under quick cooling condition. The electrical conductivity and through-thickness homogeneity of precipitates increases while the hardness decreases with cooling rate decreasing. After the optimized non-isothermal retrogression and re-ageing(NRRA) including air-cooling retrogression, the throughthickness homogeneity which is evaluated by integrated retrogression effects has been improved to 94%. The tensile strength, fracture toughness and exfoliation corrosion grade of Al-8Zn-2Mg-2Cu alloy plate is 619 MPa, 24.7 MPa·m^(1/2)and EB, respectively, which indicates that the non-isothermal retrogression and re-aging(NRRA) could improve the mechanical properties and corrosion resistance with higher through-thickness homogeneity.展开更多
文摘Objective To evaluate the epicardial fat tissue thickness （EFTT） as a diagnostic criterion for geriatric patients with metabolic syn- drome （MetS）. Methods Sixty geriatric patients over 65 years of age were recruited for the study. Patients were divided into two groups： Group 1 （n = 30） consisted of patients with MetS; Group 2 （n = 30） consisted of patients without MetS. Echocardiography was used to measure EFTT in all patients, and blood samples were analyzed for biochemical parameters. Results Compared to Group 2, EFTT levels of Group 1 were statistically higher （P 〈 0.05）. In a binary logistic regression analysis, EFTT levels served as the independent factor for meta- bolic syndrome 03 = 17.35, SE = 4.93, Wald = 12.36, P 〈 0.001）. Receivers operating characteristic Curve （ROC-curve） analysis revealed that EFTT predicted MetS with 96.7% sensitivity and 86.7% specificity above the level of 7.3 mm [area under the curve = 0.969; 95% con- fidence interval （CI）： 0.928-1.00]. Conclusions The present study demonstrated that serum EFTT levels were higher in geriatric patients with MetS and can therefore be used as a diagnostic criterion for MetS.
基金the Research and Innovation Program for College and University Graduate Students in Jiangsu Province (No.CX10B_141Z)the National Natural Science Foundation of China (No.41071273) for support of this project
文摘In order to improve the precision of mining subsidence prediction, a mathematical model using Support Vector Machine （SVM） was established to calculate the displacement factor. The study is based on a comprehensive analysis of factors affecting the displacement factor, such as mechanical properties of the cover rock, the ratio of mining depth to seam thickness, dip angle of the coal seam and the thickness of loose layer. Data of 63 typical observation stations were used as a training and testing sample set. A SVM regression model of the displacement factor and the factors affecting it was established with a kernel function, an insensitive loss factor and a properly selected penalty factor. Given an accurate calculation algorithm for testing and analysis, the results show that an SVM regression model can calcu- late displacement factor precisely and reliable precision can be obtained which meets engineering requirements. The experimental results show that the method to calculation of the displacement factor, based on the SVM method, is feasible. The many factors affecting the displacement factor can be consid- ered with this method. The research provides an efficient and accurate approach for the calculation of displacement in mining subsidence orediction.
文摘The longwall mining method is often affected by the out-of-seam dilution （OSD）. Therefore, predicting and controlling of dilution are important factors for reducing mining costs. In this study, the fuzzy set theory and multiple regression models with parameters, including variation in seam thickness, dip of seam, seam thickness, depth of seam, and hydraulic radius as inputs to the models were applied to pre- dict the OSD in the longwall coal panels. Field data obtained from Kerman and Tabas coal mines, lran were used to develop and validate the models. Three indices including coefficient of determination （R2）, root mean square error （RMSE） and variance account for （VAF） were used to evaluate the perfor- mance of the models. With 10 randomly selected datasets, for the linear, polynomial, power, exponential, and fuzzy logic models, R2, RSME and VAF are equal to （0.85, 4.4, 84.4）, （0.61, 7.5, 59.6）, （0.84, 4.5, 72.7）, （0.80, 4.1, 79.6）, and （0.97, 2.1, 95.7）, respectively. The obtained results indicate that the fuzzy logic model predictor with R2 = 0.97, RMSE = 2.1, and VAF = 95.7 performs better than the other models.
基金Project(51801082) supported by National Natural Science Foundation of ChinaProjects(GY2021003, GY2021020)supported by the Key Research and Development Program of Zhenjiang City,China+1 种基金Project(KYCX21_3453) supported by Graduate Research and Innovation Projects in Jiangsu Province,ChinaProject(202110289002Z) supported by Undergraduate Innovation and Entrepreneurship Training Program of Jiangsu Province,China。
文摘In order to improve the through-thickness homogeneity and properties of aviation aluminum alloy thick plate.The effect of heating-cooling retrogression and re-ageing on the performance of Al-8Zn-2Mg-2Cu alloy thick plate was investigated by hardness tests, electrical conductivity tests and transmission electron microscopy(TEM) observation.Results revealed that, during retrogression heating, the fine pre-precipitates in surface layer dissolve more and the undissolved η′ or η phases are more coarsened than that of center layer. During slow cooling after retrogression,precipitates continue coarsening but with a lower rate and the secondary precipitation occurs in both layers. Finer precipitates resulting from the secondary precipitation are more in surface. However, the coarsening and secondary precipitation behaviors are restrained in both layers under quick cooling condition. The electrical conductivity and through-thickness homogeneity of precipitates increases while the hardness decreases with cooling rate decreasing. After the optimized non-isothermal retrogression and re-ageing(NRRA) including air-cooling retrogression, the throughthickness homogeneity which is evaluated by integrated retrogression effects has been improved to 94%. The tensile strength, fracture toughness and exfoliation corrosion grade of Al-8Zn-2Mg-2Cu alloy plate is 619 MPa, 24.7 MPa·m^(1/2)and EB, respectively, which indicates that the non-isothermal retrogression and re-aging(NRRA) could improve the mechanical properties and corrosion resistance with higher through-thickness homogeneity.
