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Characterization of integrated noises driving bacterial degradation kinetics in the water environment by Fourier transform algorithm

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Abstract

Integrated noises are used in this study for tackling uncertainties in the dynamic energy budget model (DEB) to study bacterial degradation kinetics in water environment. According to the Fourier transform algorithm, the R2 coefficients in the regression equation are greater than 0.9 and more than 80 % of the data are close to true ones, indicating that the transform algorithm is satisfactory in identifying intensity (B) and correlation time (τ) of noises existing in the DEB model. The major findings include: (1) bacterial cells are not suitable for survival under certain integrated-noises scenarios (intensity B is more than 10−2 or constant time τ is greater than 100); (2) the conversion value is closer to the true value when the estimate sample is greater; (3) a well-identified running number (around 400 times in this study) is helpful in improving the estimation accuracy; (4) the larger the true values of B and τ, the lower the estimation accuracy. In addition, more efforts are still desired for noises characterization, for example, the reorganization of integrated noises and correlation among noises.

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Acknowledgments

This research was supported by the China National Funds for Excellent Young Scientists (51222906), National Natural Science Foundation of China (41271540), the Program for New Century Excellent Talents in University of China (NCET-13-0791), and Fundamental Research Funds for the Central Universities.

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Dong, H., He, L. & Lu, H. Characterization of integrated noises driving bacterial degradation kinetics in the water environment by Fourier transform algorithm. Stoch Environ Res Risk Assess 30, 343–351 (2016). https://doi.org/10.1007/s00477-015-1114-5

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