Abstract

Using the Levenberg–Marquardt nonlinear optimization algorithm and a series of Lorentzian line shapes, the fluorescence emission spectra from BG (Bacillus globigii) bacteria can be accurately modeled. This method allows data from both laboratory and field sources to model the return signal from biological aerosols using a typical LIF (lidar induced fluorescence) system. The variables found through this procedure match individual fluorescence components within the biological material and therefore have a physically meaningful interpretation. The use of this method also removes the need to calculate phase angles needed in autoregressive all-pole models.

© 2007 Optical Society of America

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References

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  1. R. M. Measures, Laser Remote Sensing: Fundamentals and Applications (Krieger, 1984).
  2. D. M. Bates and D. G. Watts, Nonlinear Regression and Its Applications (Wiley, 1988).
    [CrossRef]
  3. H. B. Nielsen, "Immoptibox: A Matlab Toolbox for Optimization and Data Fitting," retrieved 09 May 2005, www2.imm.dtu.dk/hbn/immoptibox.
  4. K. K. Ong and S. D. Christesen, "Biological fluorescence database," in Proceedings of The Fifth Joint Conference on Standoff Detection for Chemical and Biological Defense (U.S. Army, 2001).
    [PubMed]
  5. J. A. Huwaldt, "Plotdigitizer," retrieved 28 December 2004, http://plotdigitizer.sourceforge.net.
  6. J. R. Lakowicz, Principles of Fluorescence Spectroscopy (Plenum, 1999).

Other

R. M. Measures, Laser Remote Sensing: Fundamentals and Applications (Krieger, 1984).

D. M. Bates and D. G. Watts, Nonlinear Regression and Its Applications (Wiley, 1988).
[CrossRef]

H. B. Nielsen, "Immoptibox: A Matlab Toolbox for Optimization and Data Fitting," retrieved 09 May 2005, www2.imm.dtu.dk/hbn/immoptibox.

K. K. Ong and S. D. Christesen, "Biological fluorescence database," in Proceedings of The Fifth Joint Conference on Standoff Detection for Chemical and Biological Defense (U.S. Army, 2001).
[PubMed]

J. A. Huwaldt, "Plotdigitizer," retrieved 28 December 2004, http://plotdigitizer.sourceforge.net.

J. R. Lakowicz, Principles of Fluorescence Spectroscopy (Plenum, 1999).

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Figures (7)

Fig. 1
Fig. 1

BG emission spectra at 270   nm in washed and unwashed states.

Fig. 2
Fig. 2

BG emission spectra at 350   nm in washed and unwashed states.

Fig. 3
Fig. 3

(Color online) Best fit of washed BG at 270   nm using the Marquardt method.

Fig. 4
Fig. 4

(Color online) Fitting washed BG at 350   nm .

Fig. 5
Fig. 5

(Color online) Fitting unwashed BG at 350   nm .

Fig. 6
Fig. 6

(Color online) Fitting lidar data of aerosolized BG at 270   nm .

Fig. 7
Fig. 7

Single shot emission spectra of various cellular components at 266   nm .

Tables (4)

Tables Icon

Table 1 Best Fit Variables for Washed BG at 270 nm

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Table 2 Variables for One Term Fit for Aerosol BG Lidar Data

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Table 3 Best Fit Variables for Washed BG at 350 nm

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Table 4 Best Fit Variables for Unwashed BG at 350 nm

Equations (24)

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E ( λ , R ) = E L K 0 ( λ ) T ( R ) ξ ( R ) A 0 R 2 N ( R ) σ F ( λ L , λ ) 4 π c τ d 2 .
λ L
K 0 ( λ )
σ F ( λ L , λ ) = σ A ( λ L ) Q F F ( λ ) ,
F ( λ )
( λ ) = i = 1 n A i ( λ λ 0 i ) 2 + β i .
A i
λ 0 i
β i
( a , b )
g ( x ) ( , ) = ln ( λ a b λ ) ,
f ( λ ) ( a , b ) = a + e x b 1 + e x .
270   nm
350   nm
λ 0
270   nm
350   nm
270   nm
350   nm
270   nm
350   nm
350   nm
270   nm
266   nm

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