Temperature-constrained cascade correlation networks(TCCCNs) were applied to the identification of the powder pharmaceutical samples of metronidazole based on near infrared(NIR) diffuse reflectance spectra. This work ...Temperature-constrained cascade correlation networks(TCCCNs) were applied to the identification of the powder pharmaceutical samples of metronidazole based on near infrared(NIR) diffuse reflectance spectra. This work focused on the comparison of performances of the uni-output TCCCN(Uni-TCCCN) to multi-output TCCCN(Multi-TCCCN) by using near infrared diffuse reflectance spectra of metronidazole. The TCCCN models were verified with independent prediction samples by using the "cross-validation" method. The networks were used to discriminate qualified, un-qualified and counterfeit metronidazole pharmaceutical powders. The results showed that multiple outputs network generally worked better than the single output networks. With proper network parameters the pharmaceutical powders can be classified at a rate of 100% in this work. Also, the effects of neural network parameters including number of candidate nodes, type of transfer functions(linear, sigmoid functions and temperature-constrained sigmoid function, respectively) on classification were discussed.展开更多
The paper reports the method for determination of Tartaric acid and Maleic acid by high performance liquid chromatography. Tartaric acid and Maleic acid were separated on a Shim-pack CLC ODS (150 mm×6. 0 mm id, 5...The paper reports the method for determination of Tartaric acid and Maleic acid by high performance liquid chromatography. Tartaric acid and Maleic acid were separated on a Shim-pack CLC ODS (150 mm×6. 0 mm id, 5 μm) column with 0. 01 mol/L NaH2PO4- H3PO4(pH= 2. 0) as mobile phase, and the flow rate was 0. 7 mL/min. The components detected at UV at 220 nm. The quantitative results were obtained by external standard on a method.展开更多
文摘Temperature-constrained cascade correlation networks(TCCCNs) were applied to the identification of the powder pharmaceutical samples of metronidazole based on near infrared(NIR) diffuse reflectance spectra. This work focused on the comparison of performances of the uni-output TCCCN(Uni-TCCCN) to multi-output TCCCN(Multi-TCCCN) by using near infrared diffuse reflectance spectra of metronidazole. The TCCCN models were verified with independent prediction samples by using the "cross-validation" method. The networks were used to discriminate qualified, un-qualified and counterfeit metronidazole pharmaceutical powders. The results showed that multiple outputs network generally worked better than the single output networks. With proper network parameters the pharmaceutical powders can be classified at a rate of 100% in this work. Also, the effects of neural network parameters including number of candidate nodes, type of transfer functions(linear, sigmoid functions and temperature-constrained sigmoid function, respectively) on classification were discussed.
文摘The paper reports the method for determination of Tartaric acid and Maleic acid by high performance liquid chromatography. Tartaric acid and Maleic acid were separated on a Shim-pack CLC ODS (150 mm×6. 0 mm id, 5 μm) column with 0. 01 mol/L NaH2PO4- H3PO4(pH= 2. 0) as mobile phase, and the flow rate was 0. 7 mL/min. The components detected at UV at 220 nm. The quantitative results were obtained by external standard on a method.