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. 2012 Feb 15;17(2):1929-38.
doi: 10.3390/molecules17021929.

An adaptive single-well stochastic resonance algorithm applied to trace analysis of clenbuterol in human urine

Wei Wang  1 , Suyun Xiang, Shaofei Xie, Bingren Xiang
Affiliations

An adaptive single-well stochastic resonance algorithm applied to trace analysis of clenbuterol in human urine

Wei Wang et al. Molecules. .

Abstract

Based on the theory of stochastic resonance, an adaptive single-well stochastic resonance (ASSR) coupled with genetic algorithm was developed to enhance the signal-to-noise ratio of weak chromatographic signals. In conventional stochastic resonance algorithm, there are two or more parameters needed to be optimized and the proper parameters values were obtained by a universal searching within a given range. In the developed ASSR, the optimization of system parameter was simplified and automatic implemented. The ASSR was applied to the trace analysis of clenbuterol in human urine and it helped to significantly improve the limit of detection and limit of quantification of clenbuterol. Good linearity, precision and accuracy of the proposed method ensure that it could be an effective tool for trace analysis and the improvement of detective sensibility of current detectors.

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Figures

Figure 1
Figure 1
A typical single-well potential.
Figure 2
Figure 2
Chromatogram of urine spiked with clenbuterol at 0.025 ng/mL. (a) Full length of the chromatogram. (b) Especially enlarged chromatogram of clenbuterol. (c) The peak of clenbuterol obtained by ASSR with b = 0.0574.
Figure 3
Figure 3
Chromatograms of clebuterol in urine samples of calibration curve. (a) The raw chromatograms of clenbuterol. (b) The chromatograms of clenbuterol obtained by ASSR with b = 0.0574. From left to right, the concentrations of clenbuterol are 0.2, 0.5, 1.0, 2.0, 5.0, 10.0 and 20.0 ng/mL, respectively.
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