Aim To establish a method for determination of Ginkgo biloba L, its extractand preparations with HPLC fingerprints, so as to control the quality of the preparations. MethodsHPLC-DAD method was used to determine the co...Aim To establish a method for determination of Ginkgo biloba L, its extractand preparations with HPLC fingerprints, so as to control the quality of the preparations. MethodsHPLC-DAD method was used to determine the constituents in preparations. Diamonsil? C_(18) (200mm X 4.6 mm, 5 μm) was used as analytical column, and acetonitrile/KH_2PO_4 was used as mobilephase with gradient elu-tion. The column temperature was at 24 ℃. The HPLC profile of chemicalconstituents of control sample and preparations were analyzed using similarity software. Results Thefingerprints of different preparations from different companies were slightly different because ofthe different preparing procedures. Mean while, the fingerprints of different batches of the samepreparation from the same company were similar to each other and the technology of each preparationwas stable. Conclusion This method is accurate, reproducible , simple, and can be used as ananalytical method for the routine quality control of Ginkgo biloba preparations.展开更多
Back-Propagation (BP) neural network and its modified algorithm are introduced. Two series of BP neural network models have been established to predict yarn properties and to deduce wool fiber qualities. The results f...Back-Propagation (BP) neural network and its modified algorithm are introduced. Two series of BP neural network models have been established to predict yarn properties and to deduce wool fiber qualities. The results from these two series of models have been compared with the measured values respectively, proving that the accuracy in both the prediction model and the deduction model is high. The experimental results and the corresponding analysis show that the BP neural network is an efficient technique for the quality prediction and has wide prospect in the application of worsted yarn production system.展开更多
文摘Aim To establish a method for determination of Ginkgo biloba L, its extractand preparations with HPLC fingerprints, so as to control the quality of the preparations. MethodsHPLC-DAD method was used to determine the constituents in preparations. Diamonsil? C_(18) (200mm X 4.6 mm, 5 μm) was used as analytical column, and acetonitrile/KH_2PO_4 was used as mobilephase with gradient elu-tion. The column temperature was at 24 ℃. The HPLC profile of chemicalconstituents of control sample and preparations were analyzed using similarity software. Results Thefingerprints of different preparations from different companies were slightly different because ofthe different preparing procedures. Mean while, the fingerprints of different batches of the samepreparation from the same company were similar to each other and the technology of each preparationwas stable. Conclusion This method is accurate, reproducible , simple, and can be used as ananalytical method for the routine quality control of Ginkgo biloba preparations.
文摘Back-Propagation (BP) neural network and its modified algorithm are introduced. Two series of BP neural network models have been established to predict yarn properties and to deduce wool fiber qualities. The results from these two series of models have been compared with the measured values respectively, proving that the accuracy in both the prediction model and the deduction model is high. The experimental results and the corresponding analysis show that the BP neural network is an efficient technique for the quality prediction and has wide prospect in the application of worsted yarn production system.
