This paper developed a sensitive and efficient analytical method for triclocarban (TCC), triclosan (TCS) and Methyl-triclosan (MTCS) determination in environmental water, which involves enrichment by using silicon dio...This paper developed a sensitive and efficient analytical method for triclocarban (TCC), triclosan (TCS) and Methyl-triclosan (MTCS) determination in environmental water, which involves enrichment by using silicon dioxide/polystyrene composite microspheres solid-phase extraction and detection with HPLC-ESI-MS. The influence of several operational parameters, including the eluant and its volume, the flow rate and acidity of water sample were investigated and optimized. Under the optimum conditions, the limits of detection were 1.0 ng/L, 2.5 and 4.5 ng/L for TCC, TCS, and MTCS, respectively. The linearity of the method was observed in the range of 5-2000 ng/L, with correlation coefficients (r2) >.99. The spiked recoveries of TCC, TCS and MTCS in water sampleswereachieved in the range of 89.5% -96.8% with RSD below 5.7%. The proposed method has been successfully applied to analyze real water samples and satisfactory results were achieved.展开更多
The paper establishes a theorem of data perturbation analysis for the support vector classifier dual problem, from which the data perturbation analysis of the corresponding primary problem may be performed through sta...The paper establishes a theorem of data perturbation analysis for the support vector classifier dual problem, from which the data perturbation analysis of the corresponding primary problem may be performed through standard results. This theorem derives the partial derivatives of the optimal solution and its corresponding optimal decision function with respect to data parameters, and provides the basis of quantitative analysis of the influence of data errors on the optimal solution and its corresponding optimal decision function. The theorem provides the foundation for analyzing the stability and sensitivity of the support vector classifier.展开更多
文摘This paper developed a sensitive and efficient analytical method for triclocarban (TCC), triclosan (TCS) and Methyl-triclosan (MTCS) determination in environmental water, which involves enrichment by using silicon dioxide/polystyrene composite microspheres solid-phase extraction and detection with HPLC-ESI-MS. The influence of several operational parameters, including the eluant and its volume, the flow rate and acidity of water sample were investigated and optimized. Under the optimum conditions, the limits of detection were 1.0 ng/L, 2.5 and 4.5 ng/L for TCC, TCS, and MTCS, respectively. The linearity of the method was observed in the range of 5-2000 ng/L, with correlation coefficients (r2) >.99. The spiked recoveries of TCC, TCS and MTCS in water sampleswereachieved in the range of 89.5% -96.8% with RSD below 5.7%. The proposed method has been successfully applied to analyze real water samples and satisfactory results were achieved.
文摘The paper establishes a theorem of data perturbation analysis for the support vector classifier dual problem, from which the data perturbation analysis of the corresponding primary problem may be performed through standard results. This theorem derives the partial derivatives of the optimal solution and its corresponding optimal decision function with respect to data parameters, and provides the basis of quantitative analysis of the influence of data errors on the optimal solution and its corresponding optimal decision function. The theorem provides the foundation for analyzing the stability and sensitivity of the support vector classifier.
