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Normalized signal intensity calculation

Simulations of the experimental signal were performed using Equation 1 without adjustable parameters. The spectrum of the pulse and the absorption spectrum of HPTS were measured experimentally. An examination of the molecular structure of HPTS shows that it has no center of symmetry. Since parity restrictions may be relaxed in this case, the similarity between one-photon and two-photon absorption spectra is expected. The spectral phase

phase mask was the same used for the simulations. Both experimental and theoretical data were normalized such that the signal intensity is unity and the background observed is zero. The experimental data (dots) generally agree with the calculated response (continuous line) of the dyes in all pH environments (see Fig. 2). [Pg.98]

When the REMPI signal intensities are measured rotating the X/2 plate by 90°, 7 and I are obtained with the probe laser polarization parallel and perpendicular to the surface normal, respectively. The so-called polarization Rv can be calculated by... [Pg.321]

Normalization is a very important step, as it aims to reduce experimental variance. Normalization is most often performed by dividing each spectrum by a normalization factor (Figure 2G). The most popular normalization factor is calculated as the total ion count (TIC), which is the sum of all ion intensities in a spectrum. Several studies discovered that in MSI the assumptions for TIC applicability hold true only for very homogeneous tissues. In heterogeneous samples, more robust normalization factors based on the median or the TIC with exclusion of very localized mass signals have been proposed (35-37). [Pg.170]

Ion etching). They are utilized to determine the composition of specimens as a function of depth. The units along the abscissa are normally sputter time. Sputter time can be converted to depth If the sputter rate of the material Is known. The units along the ordinate are normally Auger signal Intensities or calculated atomic concentrations. [Pg.121]

Some scanners (such as the PerkinElmer ScanArray instrument) adjust the laser settings based on a pre-scan of the slide these types of scanners generally calculate the correct settings so adjustments are not normally required. However, it is still useful to check the signal intensities of the control spots as the automatic detection settings based on the pre-scan may be incorrect. [Pg.149]

Telomerase activity is typically measured using the Telomeric Repeat Amplification Protocol (TRAP) assay. In the TRAP assay, products of the telomerase reaction are quantified following their PCR amplification [20, 21], The assay is exquisitely sensitive and incorporates an internal standard (ITAS) with which to normalize signals for differences in PCR efficiency. Telomerase activity is calculated as the ratio of the intensity of the telomeric products to that of the ITAS. With this assay, telomerase activity can be measured in a wide range of specimens, from tissue biopsies to cell pellets [22]. High throughput assays have been developed to adapt the telomerase assay to the clinical environment. Many of these new assays take advantage of fluorophores that alleviate the use of radioisotopes and facilitate the quantification of PCR products. [Pg.192]

RMA Quantile normalization—raw intensity values are preprocessed to create equally distributed data between chips accounts for experimentally observed patterns for probe behavior. Only uses perfect match (PM) probes in signal calculation Irizarry et al. (2003)... [Pg.514]

Finally, the SNR is just that - the signal intensity divided by the nearby average noise value. The only trick here is to define exactly how the average noise value is calculated. Although there are many methods available, the most widely accepted calculation is to use the root-mean-square of the noise, neglecting noise spikes - provided that they do not interfere with the real sample peaks. Normally, it is very easy to identify noise spikes because almost aU real ions have an isotopic peak distribution. [Pg.53]

Characterization of a sample usually starts after a pre-ablation pass, which removes surface contamination, and following a short period to allow the sample to reach the ICP torch. Signal intensities for the analytes of interest are monitored, as in normal ICP-MS applications, and the resulting data saved to a file on the ICP-MS computer. Because calibration, discussed further below, requires ablation of a series of solid, multielement reference standards, it is generally impossible to have the ICP-MS software calculate standard curves and elemental concentrations. Thus, raw signal intensities are usually downloaded and processed off-line. [Pg.831]

Figure 15.13. Simulated ESI-MS dispersion profiles, representing the signal intensity of selected analytes at the end of a laminar flow tube under different conditions, (a) Dispersion profile expected far a single analyte in the absence of diffusion, that is, D = 0. (b) Dispersion profiles expected for a macromolecule (D= 1 x 10 m /s, solid curve), and a small molecule (D= 10 x 10 m /s, dashed curve). It is assumed that the two analytes do not interact in solution, (c) Dispersion profiles as in panel b, but under the assumption of tight noncovalent binding between the two analytes. Under these conditions the profiles measured for the two species will be identical (for the purpose of presentation, one of the profiles has been slightly shifted). Parameters used Tube length / = 3 m, tube radius R = 129.1 pm, flow rate = 5 pL/min (corresponding to max = 3.18 X 10 m/s). The dispersion profile in panel a has been calculated based on Eq. (19) in Ref. 110 all the other j ofiles have been calculated based on Eq. (17) from the same reference. For simplicity, all dispersion profiles have been normalized to unity. (Reproduced with permission from Ref. 112. Copyright 2003 Elsevier.)... Figure 15.13. Simulated ESI-MS dispersion profiles, representing the signal intensity of selected analytes at the end of a laminar flow tube under different conditions, (a) Dispersion profile expected far a single analyte in the absence of diffusion, that is, D = 0. (b) Dispersion profiles expected for a macromolecule (D= 1 x 10 m /s, solid curve), and a small molecule (D= 10 x 10 m /s, dashed curve). It is assumed that the two analytes do not interact in solution, (c) Dispersion profiles as in panel b, but under the assumption of tight noncovalent binding between the two analytes. Under these conditions the profiles measured for the two species will be identical (for the purpose of presentation, one of the profiles has been slightly shifted). Parameters used Tube length / = 3 m, tube radius R = 129.1 pm, flow rate = 5 pL/min (corresponding to max = 3.18 X 10 m/s). The dispersion profile in panel a has been calculated based on Eq. (19) in Ref. 110 all the other j ofiles have been calculated based on Eq. (17) from the same reference. For simplicity, all dispersion profiles have been normalized to unity. (Reproduced with permission from Ref. 112. Copyright 2003 Elsevier.)...
The fitted and calculated vibrational frequencies and normal mode composition factors corresponding to the 17 most important NIS bands are presented in Table 5.9. It is evident that the vibrational peaks in the calculated NIS spectrum are typically 0-30 cm lower than to the experimental values. In the calculated NIS spectra, there are two small peaks at 635 and 716 cm (Fig. 5.14b) that are not visible in the experimental spectrum. According to the normal mode calculations these are Fe-N-N and Fe-O-C deformation vibrations. Small admixtures of Fe-N and Fe-O stretching modes account for the calculated nonzero normal mode composition factors. Although the calculated relative intensities are slightly above detection limit dictated by the signal-to-noise ratio, they are determined by values of pea which are very small (0.028 and 0.026 for the peaks at 635 and 716 cm ). They must be considered to be within the uncertainties of the theoretical... [Pg.190]


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