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Imaging Artifacts in Continuous Scanning 2D LAICP-MS Imaging due to Non-Synchronization Issues Johannes T. van Elteren, Vid Simon Šelih, Martin Šala, Stijn J. M. Van Malderen, and Frank Vanhaecke Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.7b05134 • Publication Date (Web): 28 Jan 2018 Downloaded from http://pubs.acs.org on January 29, 2018

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Analytical Chemistry

Imaging Artifacts in Continuous Scanning 2D LA-ICP-MS Imaging due to Non-Synchronization Issues Johannes T. van Elteren,*,1 Vid S. Šelih,1 Martin Šala,1 Stijn J. M. Van Malderen2 and Frank Vanhaecke2 1

Department of Analytical Chemistry, National Institute of Chemistry, Hajdrihova 19, SI-1000 Ljubljana, Slovenia Department of Chemistry, Atomic & Mass Spectrometry - A&MS research unit, Ghent University, Campus Sterre, Krijgslaan 281-S12, B-9000 Ghent, Belgium

2

ABSTRACT: Pulsed laser ablation (LA) devices in LA-ICP-MS imaging have become very advanced, delivering laser pulses with high temporal accuracy and stable energy density. However, unintentional imaging artifacts may be generated in 2D element maps when the LA repetition rate and the data acquisition parameters of ICP-MS instruments with a sequential mass spectrometer (i.e. quadrupole filter or sector-field mass spectrometer) are desynchronized. This may potentially lead to interference patterns, visible as ripples in elemental images, and thus, compromised image quality. This paper describes the background of aliasing in continuous scanning mode through simulation experiments and ways to modulate the effect. The existence of this image degradation source is demonstrated experimentally via real-life imaging of a homogeneous glass standard.

In continuous scanning LA-ICP-MS imaging, the laser fires continuously with a specific repetition rate (Hz), while the stage with the mounted sample is moving1. Image quality is invariably related to blur introduced as a result of the physical size of the laser beam and impaired transport efficiency of LAgenerated particles to the ICP-MS unit and various types of noise (Flicker and Poisson noise) as a function of the instrument’s characteristics, instrument settings and data acquisition parameters, matrix composition and elemental concentration levels2–6. In continuous scanning LA-ICP-MS, the generation of “smooth, low-noise signals is a prerequisite for accurate 2D imaging of e.g. biomedical tissues, geological samples, etc. Intuitively one would choose a “high” repetition rate and/or a “long” measurement time for smoothing of the mass flux, and thus, response. Subsequently, the scanning speed needs to be adjusted to preserve spatial resolution as much as possible. A mostly overlooked detail regarding image quality is how LA and ICP-MS are communicating, more specifically how the mass spectrometer is sampling the signal generated during the introduction of LA aerosol. In general, no specific attention is paid to an exact matching of sampling events of LA and (quadrupole) ICP-MS instruments when one reviews papers on 2D elemental imaging7. In very recent work on single pulse LA-ICP-MS imaging, it has been shown that appropriate synchronization is essential for accurate analysis, especially when using sequential (scanning) ICP-MS instruments8. To perform sequential multi-element analysis in one single pulse peak, measurement of each nuclide is inevitably associated with integration of a well-defined segment of the peak. Thus, drift of the segment of the peak sampled for each nuclide should be avoided at all cost to reduce the noise and circumvent signal aliasing artifacts to preserve image quality. An instrumental way to overcome these artifacts is by exacting synchronization protocols8 or using ICP-MS instruments that can simultaneously handle ions of different mass-to-charge ratio sampled from the ICP at a given moment in time at a sufficiently high

sampling rate such as, e.g., ICP-TOF-MS9. Triggering an acquisition segment in the data acquisition hardware at a set delay after the laser firing trigger may aid in further improving accuracy through spot-resolved, single-pixel synchronization10. When focusing on continuous scanning LA-ICP-MS imaging using quadrupole-based instruments, synchronization is seemingly less important than for single pulse analysis, but as will be shown, the effects can still be detrimental to the image quality. Modeling experiments were carried out to identify the scale of the influence of non-synchronization, and imaging experiments on a homogeneous glass standard have provided evidence for the validity of this image degradation concept and the value of hardware synchronization. EXPERIMENTAL AND MODELING The LA-ICP-MS instrument comprised a laser ablation system (193 nm ArF*; Analyte G2, Teledyne Photon Machines Inc., Bozeman, MT) with 2-volume ablation cell (HelEx II; He carrier gas flow rate, cup = 0.5 L min-1, cell = 0.3 L min-1). The LA unit was interfaced with a quadrupole ICP-MS instrument (Agilent 7900, Agilent Technologies, Santa Clara, CA); Ar makeup gas was added before the ICP torch (0.8 L min-1) and MS operation was in time-resolved mode, measuring one mass channel per detector cycle, monitoring the signals for 159Tb (dwell time: 10 ms for all conditions) and 165 Ho (dwell times: 61, 86, 96 and 111 ms); this resulted in total acquisition times of 75, 100, 110 and 125 ms (in all cases 4 ms per detector cycle were lost due to quadrupole DAQ dead time). Experiments were run on a multi-element homogeneous glass standard (NIST SRM 612), containing 37.3 ± 1.1 µg g-1 of Tb and 38.3 ± 0.8 µg g-1 of Ho (uncertainties are given as 95 % confidence limits; GeoRem preferred values by the Max Plank Institute of Chemistry, http://georem.mpchmainz.gwdg.de), using the following LA conditions: fluence,

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4.82 J cm-2; beam diameter, 80 µm (square mask); scanning speed, 80 µm s-1; repetition rate, 20 Hz. For this particular LAICP-MS setup, the FW0.01M single pulse response (full width at 1 % of the maximum) was ca. 0.5 s. Modeling of the image noise for various synchronized and non-synchronized LA and ICP-MS conditions was performed in GNU Octave 4.0.01711; further data and image processing was performed in Origin 8.1 (Originlab Corporation, Northampton, MA) and ImageJ 1.51n12. RESULTS AND DISCUSSION Synchronous and Non-Synchronous Sampling Events. In LA-ICP-MS analysis, two sampling events take place at two distinct sampling frequencies (f [Hz]), viz. (spatial) LA sampling according to the repetition rate (fLA) and subsequent (signal) sampling by the sequential scanning mass spectrometer (fICP-MS). The mass spectrometer is able to sample several mass channels sequentially in one mass sweep cycle, whose duration is expressed as the acquisition time AT (= 1/fMS [s]); AT equals the sum of the dwell times DTi, plus data acquisition (DAQ) dead time (consisting of quadrupole transition and settling times), for each of the individual elements i. In general, the DAQ dead time is considerably lower than AT, hence DTi ≅ AT when one element is monitored, and DTi < AT when more elements are monitored. Figure 1 illustrates the two critical LA-ICP-MS analysis conditions, viz. one where fLA = fMS (synchronous sampling) and the other one where fLA ≠ fMS (non-synchronous sampling). In the Supporting Information, SI-1, we can see how a mismatch of LA and ICP-MS sampling frequencies may lead to introduction of serious aliasing effects, hereafter called non-synchronization sampling noise, upon scanning of homogeneous matrices, whereas for the matched case the aliasing effect can be modulated to a great extent, and the noise sources reduced to white and detector noise sources, characterized by Flicker and Poisson noise, respectively.

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ing sampling frequencies of fLA and fMS, we assumed a homogeneous matrix and used previously developed mathematical modeling approaches4,13,14. Laser pulses were modeled assuming an exponential decay profile with a nominal width of FW0.01M as a result of aerosol washout from the LA cell and transfer to the ICP-MS unit. This exponential model is a simplification of the actual decay profile and may amplify the effect of non-synchronization; other models15 that may show less spectral aliasing issues do exist, although our model findings have been experimentally confirmed for a glass matrix (see Figure 5). It is obvious that “smooth” signals can only be obtained under certain conditions, but intuitively, we would choose a “high” fLA and a “low” fMS (= “high” AT); for lower FW0.01M values we would choose higher and lower frequencies, respectively. Figure 2 shows how the LA-ICP-MS output can be simulated for virtual line scanning based on superimposition of laser pulses in the LA sampling process, leading to higher, more compressed signals with lower relative noise levels at higher repetition rates (Figure 2A), followed by MS sampling of the superimposed LA signals, effectively implying integration of AT·fLA LA signal pulses when DTi ≅ AT (Figure 2B) or fractional integration of 0.1·AT·fLA LA signal pulses when DTi = 0.1·AT (Figure 2C). It can be seen that MS sampling leads to oscillating signals with varying periodicity and amplitude. This implies that in LA-ICP-MS imaging, the levels of non-synchronization noise may vary considerably with fLA, AT and DTi. Under synchronized sampling frequencies, when AT is a positive integer (ℤ+) of 1/fLA, this type of aliasing can be modulated to an extent where it is not visible any longer in the signal as will be shown in detail below. Table 1. Conditions used for simulation of the LA-ICP-MS output for a homogeneous matrix assuming a concentrationrelated pixel intensity of 100,000 cps; conditions A-E are associated with AT = DTi (i.e. one element), whereas conditions F-J are associated with AT > DTi (i.e. more elements).

Condition

FW0.01M (s)

fLA (Hz)

AT (ms)

DTi (ms)

Conc. (cpp*)

q

A

0.5

20

75

75

7,500

0.05

B

0.5

20

90

90

9,000

0.05

C

0.5

20

100

100

10,000

0.05

D

0.5

20

110

110

11,000

0.05

E

0.5

20

125

125

12,500

0.05

F

0.5

20

75

10

1,000

0.05

G

0.5

20

90

10

1,000

0.05

H

0.5

20

100

10

1,000

0.05

I

0.5

20

110

10

1,000

0.05

J

0.5

20

125

10

1,000

0.05

*, counts per pixel

Figure 1. Sampling of LA-generated signal profile (blue) and ICP-MS signal (red) illustrated for synchronous (A) and nonsynchronous (B) conditions, with AT the acquisition time and DTi the dwell time for element i. Simulation of Non-Synchronization Sampling Noise. To be able to simulate the non-synchronization noise upon vary-

In Figure 3, using an extended range of values compared to Figures 2B and C, for dwell times DTi ≅ AT and DTi = 0.1·AT, and fLA values of 10, 20 and 40 Hz, the levels of non-synchronization noise in the LA-ICP-MS profiles, expressed as the relative standard deviation RSDns in the LAICP-MS profile for a homogeneous matrix, are plotted as a function of the acquisition time AT. The effect of synchronization of the LA and MS sampling events becomes immediately evident from the appearance of RSDns minima (nulls) in the graphs, i.e. where AT = ℤ+/fLA.


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Figure 2. Simulation of the LA sampling profile for three different fLA values (A), the MS sampling profiles after LA sampling for three AT=DTi values (B), and the MS sampling profiles for three DTi=10⋅AT values (C); FW0.01M was assumed to be 0.5 s. The traces in B and C are color-coded, similar to A, i.e. blue = 40 Hz, red = 20 Hz, and green = 10 Hz, whereas the style/weight of the traces relates to the AT and DTi values. It should be noted that the oscillations generated are merely the result of sampling and not related to Flicker or Poisson noise. tal noise. Selecting e.g. AT ≅ DTi = 110 ms (Figure 3A), the levels of non-synchronization noise are ca. 2.3, 1.2 and 0.4 % at 10, 20 and 40 Hz, respectively. More pronounced nonsynchronization noise is generated when more mass channels are measured with shorter dwell times per mass channel; for AT = 10·DTi = 110 ms (Figure 3B) the levels of nonsynchronization noise increase to ca. 25, 12 and 4.0 % at 10, 20 and 40 Hz, respectively. Thus, under unfavorable conditions, the RSDns levels may become very substantial, leading to interference patterns, depending on the amount of aliasing introduced during the LA-ICP-MS experiment. Although the results in Figure 3 are derived for an FW0.01M value of 0.5 s, any value can be chosen when at the same time the other figure attributes are changed as well (see the Supporting Information, SI-2).

Figure 3. Simulation of non-synchronization sampling noise (RSDns) for AT=DTi (A) and AT=10⋅DTi (B) as a function of different fLA values; FW0.01M was assumed to be 0.5 s. The higher the fLA, the less the aliasing effect impacts the overall response, due to signal smoothing and sampling of the mass channel across multiple peak profiles. For this reason, the conditions for synchronization also relax when the oscillatory component becomes negligible relative to the instrumen-

Generic Measurement Noise and Interference Patterns. Pure measurement noise can be related to the pixel intensity A [counts] in an image, assuming Flicker and Poisson noise. Flicker noise (expressed as the relative standard deviation RSDF [counts]) is the result of fluctuations in the primary laser output, fluctuation in the plasma source and the detector dark noise, and is proportional to the pixel intensity (q·A, with q a factor between 0 and 1), whereas counting statistics in the detector leads to Poisson noise (expressed as the relative standard deviation RSDP [counts]) that is related to the square root of the pixel intensity (√A). For non-synchronized LA and ICP-MS sampling frequencies, non-synchronization noise (RSDns) needs to be taken into account as well. In single line scans, non-synchronization noise effects may not be directly visible, but in 2D images they may show up as interference patterns when the Flicker and Poisson noise are not too high, as the human visual system (HVS) is highly adapted to extract structural information from an image16.



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Figure 4. Visualization of 2D interference patterns as a function of various LA-ICP-MS conditions (A-J) as specified in Table 1, and noise levels extracted from the images (see Eq. 1). Conditions with synchronized sampling frequencies are denoted by *. The following equation shows how noise can be calculated for a pixel intensity A, yielding the total pixel noise (expressed as the relative standard deviation RSDT = 100·SDT/A): RSDT2 = RSDF2 + RSDP2 + RSDns2 = 10,000⋅q2 + 10,000/A + RSDns2

(1)

Realistic values for q vary in general between 0.05 and 0.15 (5 % < RSDF < 15 %), whereas A values critically determine the level of measurement noise for low counts numbers (< 100, i.e. RSDP > 10 %). Gaussian (normal) distributed Flicker noise is added to an image, whereas Poisson noise is applied upon LA-ICP-MS imaging of a homogeneous matrix; unintentional noise appears as a result of non-synchronized LA and ICP-MS sampling frequencies. In the simulation, count numbers are based on a pixel intensity of 100,000 cps and only associated with the LA sampling frequency (fLA), MS sampling frequency (fMS), dwell time (DTi) and FW0.01M value. Under realistic experimental conditions, also the element concentration, ablation rate and density are determining the count number, whereas the scanning speed influences the step size in the scan direction and as such, the actual lateral resolution in the final image. To evaluate in how far interference patterns may become visible as a result of non-synchronization in the presence of Flicker and Poisson noise, a homogeneous matrix was virtually ablated under fixed conditions for beam size and scanning speed, and assuming a FW0.01M value of 0.5 s. Table 1 lists the ten different conditions (A - J) selected for modeling, five in which DTi ≅ AT (A – E) and five in which DTi < AT (F – J), including synchronous (C* and H*) and non-synchronous (A, B, D, E, F, G, I, J) LA and MS sampling events, and assuming a homogeneous concentration associated with 100,000 cps pixel-1. Figure 4 shows the modeled imaging output for all ten conditions; it can be seen that only under truly synchronized conditions (C* and H*), the interference effect as a result of signal aliasing is modulated to an extent that it becomes statistically insignificant. All other conditions develop

non-synchronization noise although this is not always discriminated as interference patterns within the image by an average observer. Refined mathematical tools, such as fast Fourier transforms-based frequency discrimination have a higher detection power. Non-synchronization noise extracted from the images in Figure 4 (see inserted table), using Eq. 1, imply that for conditions where AT ≅ DTi this noise is relatively low and appears to not create artifacts that would change how the elemental distribution is interpreted. However, for more elements where AT > DTi, this noise might become the major source of noise that will show up as ripples in images. Especially for conditions G and I, clear interference patterns emerge; for conditions F and J, the calculated RSDns levels are similar to G and I but less distinct as interference patterns. Experimental Confirmation of Interferences Patterns and Retrieval of Non-Synchronization Noise. Simulation infers that interference patterns may develop under nonsynchronized LA and MS conditions, but a proof-of-concept implies that this has to be confirmed by experiments, in this case using a quadrupole ICP-MS unit that sequentially scans the mass spectrum upon imaging of a homogeneous glass standard. In Figure 5, the experimental LA-ICP-MS output for four conditions (20 line scans per condition) is visualized for acquisition times AT of 75 ms, 100 ms, 110 ms and 125 ms and corresponding dwell times DTTb|DTHo of 10|61 ms, 10|86 ms, 10|96 ms and 10|111 ms (in all instances 4 ms of DAQ dead time added to the dwell times DTi makes up the AT). From the synchronous case (AT = 100 ms), and using Eq. 1, we calculated the Flicker and Poisson noise for Tb|Ho to be 2.8|1.6 % and 1.5|0.51 %, respectively, independent of the conditions chosen (Tb|Ho concentrations were associated with 470,000|450,000 cps pixel-1). Non-synchronization noise is absent at AT = 100 ms, but has a magnitude of 8.8|2.3 %, 9.6|0.92 % and 7.0|0.61 % for Tb|Ho at AT = 75 ms, 110 ms and 125 ms, respectively. The experimental images for Tb in Figure 5 look remarkably similar to the modeled output in Figure 4 for the cases F, H*, I and J, proving that this non-synchronization sampling concept is valid and may negatively influence the image quality.

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Figure 5. Experimental LA-ICP-MS output for imaging of 159Tb and 165Ho in NIST SRM 612 at four different conditions: AT = 75 ms, 100 ms, 110 ms and 125 ms, and DTTb|DTHo = 10|61 ms, 10|86 ms, 10|96 ms and 10|111 ms, respectively. Color coding was similar to Figure 4. For Ho only faint interference patterns are evident, which is in accordance with theory, which assumes that when DTi approaches AT, the non-synchronization noise decreases. Additional artifacts in Figure 5 can be observed from the “wavy” patterns, especially visible at AT =110 ms for Tb, due to unprecise triggering of the ICP-MS unit at the start of the line scans. Although the laser pulsing repeatability is very high, unprecise triggering or activation of the measurement run may lead to erratic interference patterns that we have observed on many occasions in routine LA-ICP-MS imaging when LA and ICP-MS sampling frequencies are not synchronized. It should be noted that even with trigger synchronization, there may still be drift of the peak profile as a result of the unpredictable fluid dynamic trajectory the particles follow, while jitter on the electronics may occur when low-level hardware is not configured for this specific purpose. Table 2. Selection of a limited number of LA and ICP-MS conditions for generic smoothing (RSDns < 2.5 %) of LA-ICPMS signals in continuous scanning mode for one (AT=DTi) and ten (AT=10⋅DTi) elements and two FW0.01M values. FW0.01M (s)

fLA (Hz)

AT=DTi (s)

AT=10⋅DTi (s)

0.1

10 Hz 20 Hz 40 Hz

> 1.6 >0.50 >0.125

>11 >2.2 >0.4

0.5

10 Hz 20 Hz 40 Hz

>0.40 >0.045 >0.018

>2.7 >0.40 >0.15

From a practical point-of-view one would like to synchronize the LA repetition rate and the acquisition time very precisely via AT·fLA = ℤ+. However, since trigger, drift and jitter irregularities may lead to desynchronization, one should still ascertain that a “smoothed” signal is generated by optimizing the AT⋅fLA term. Since selection of AT and fLA values is highly dependent on the interface between LA and ICP-MS, characterized by the FW0.01M, they have to be chosen very carefully so as to alleviate potential interference patterns when LA

and ICP-MS get desynchronized. Generic smoothing (RSDns < 2.5 %), even for completely non-synchronized LA and ICPMS conditions where AT·fLA = ℤ+0.5, can be achieved by selecting the simulated AT and fLA values given in Table 2 (for one and ten elements and FW0.01M values of 0.1 and 0.5 s). From Table 2 it can be deduced that for signal smoothing in “faster” cells (FW0.01M = 0.1 s), the AT.fLA term needs to be on average four times higher than for “slower” cells (FW0.01M = 0.5 s), implying higher repetition rates and/or longer acquisition times. Table 2 also clearly shows that measurement of one element can be achieved under much more relaxed conditions than measurement of ten elements, evident from acquisition times that are on average a factor six lower for identical repetition rates. CONCLUSIONS This work has shown that non-synchronization noise (RSDns) in continuous scanning LA-ICP-MS imaging, as a result of mismatching sampling LA (fLA) and MS (fMS) sampling frequencies, may result in serious loss of elemental image quality for quadrupole ICP-MS instruments. The MS sampling frequency fMS is inversely related to the acquisition time AT, during which several nuclides i can be sequentially measured in one mass sweep cycle. Only when synchronizing fLA and fMS, i.e. when AT = ℤ+/fLA (with ℤ+ a positive integer), this non-synchronization sampling effect may be modulated. For measurement of more elements during the acquisition time, i.e. AT > DTi, non-synchronization noise becomes more pronounced at lower DTi/AT ratios. Whether or not this type of noise is visible in images as interference/aliasing patterns depends entirely on measurement noise associated with Flicker and Poisson noise and the trigger precision and repeatability. Nevertheless, non-synchronization will always lead to higher noise levels in the image. ASSOCIATED CONTENT Supporting Information AUTHOR INFORMATION Corresponding Author *E-mail: [email protected].



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Notes The authors declare no competing financial interest. ACKNOWLEDGMENTS This bilateral research project (N1-0060) was financed by the Research Foundation Flanders (FWO) and the Slovenian Research Agency (ARRS). Stijn J. M. Van Malderen is a postdoctoral fellow of the FWO (application number 12S5718N). REFERENCES (1) Bussweiler, Y.; Borovinskaya, O.; Tanner, M. Spectroscopy 2017, 32 (5), 14–20. (2) de Pessoa, G. S.; Capelo-Martinez, J. L.; FdezRiverola, F.; Lopez-Fernandez, H.; Glez-Pena, D.; ReboiroJato, M.; Arruda, M. A. Z. J. Anal. At. Spectrom. 2016, 31, 832–840. (3) Vaculovič, T.; Warchilová, T.; Čadková, Z.; Száková, J.; Tlustoš, P.; Otruba, V.; Kanický, V. Appl. Surf. Sci. 2015, 351, 296–302. (4) van Elteren, J. T.; Izmer, A.; Šelih, V. S.; Vanhaecke, F. Anal. Chem. 2016, 88, 7413–7420. (5) Bonta, M.; Limbeck, A.; Quarles Jr, C. D.; Oropeza, D.; Russo, R. E.; Gonzalez, J. J. J. Anal. At. Spectrom. 2015, 30 (8), 1809–1815. (6) Kertesz, V.; Cahill, J. F.; Van Berkel, G. J. Rapid Commun. Mass Spectrom. 2016, 30 (7), 927–932. (7) Becker, J. S.; Matusch, A.; Wu, B. Anal. Chim. Acta 2014, 835, 1–18. (8) Van Malderen, S. J. M.; van Elteren, J. T.; Šelih, V. S.; Vanhaecke, F. Spectrochim. Acta - Part B At. Spectrosc. 2017, accepted. (9) Gundlach-Graham, A.; Günther, D. Anal. Bioanal. Chem. 2016, 408 (11), 2687–2695. (10) Bussweiler, Y.; Borovinskaya, O.; Tanner, M. 2017, pp 14–20. (11) Eaton, J. W.; Bateman, D.; Hauberg, S.; Wehbring, R. GNU Octave Manual; Network Theory Limited, 2015. (12) Schneider, C. A.; Rasband, W. S.; Eliceiri, K. W. Nat. Methods 2012, 9 (7), 671–675. (13) Triglav, J.; van Elteren, J. T.; Šelih, V. S. Anal. Chem. 2010, 82 (19), 8153–8160. (14) van Elteren, J. T.; Vanhaecke, F. J. Anal. At. Spectrom. 2016, 31, 1998–2004. (15) Van Malderen, S. J. M.; Managh, A. J.; Sharp, B. L.; Vanhaecke, F. J. Anal. At. Spectrom. 2016, 31, 423–439. (16) Smith, S. W. The Scientist and Engineer’s Guide to Digital Signal Processing, 2nd ed.; California Technical Publishing, San Diego, California, 1999.


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