Instrument artifacts

Many current multidimensional methods are based on instruments that combine measurements of several luminescence variables and present a multiparameter data set. The challenge of analyzing such complex data has stimulated the application of special mathematical methods (80-85) that are made practical only with the aid of computers. It is to be expected that future analytical strategies will rely heavily on computerized pattern recognition methods (79, 86) applied to libraries of standardized multidimensional spectra, a development that will require that published luminescence spectra be routinely corrected for instrumental artifacts. Warner et al, (84) have discussed the multiparameter nature of luminescence measurements in detail and list fourteen different parameters that can be combined in various combinations for simultaneous measurement, thereby maximizing luminescence selectivity with multidimensional measurements. Table II is adapted from their paper with the inclusion of a few additional parameters. 

Capacitance and surface tension measurements have provided a wealth of data about the adsorption of ions and molecules at electrified liquid-liquid interfaces. In order to reach an understanding on the molecular level, suitable microscopic models have had to be considered. Interpretation of the capacitance measurements has been often complicated by various instrumental artifacts. Nevertheless, the results of both experimental approaches represent the reference basis for the application of other techniques of surface analysis. 

Fig. 1. Co-addition of four UVES pipeline spectra of NGC 6397/TO201432 (observing dates 2000-06-18 and 22, two spectra per night). The resulting spectrum was arbitrarily normalized at 6410 and 6690 A. As blaze residuals are not properly accounted for in the pipeline order merging, the echelle order pattern is clearly visible in the merged spectrum. With an amplitude of 2 %, these instrumental artifacts do not allow to derive Baimer-profile temperatures to better than 200-300K.

A plot of the anthracene fluorescence intensity at 425 nm as a function of the reaction time is shown in Figure 2. Again, this figure exhibits the effect of the instrumental artifact in the initial fluorescence data however, examination of the final 90% of the profile reveals that the anthracene concentration profile closely follows a first order exponential decay. Although the photosensitization reaction is bimolecular, the anthracene concentration follows a pseudo-first-order profile since the initiator is present in excess (i.e. r = = kjCA where r, Q and CA represent... 

Figure 6 is a schematic representation of a DNA histogram. The ability of the flow cytometer to rapidly count several thousand nuclei contributes to the sensitivity of this technique for DNA analysis. However, problems due to sample quality, staining, and instrumental artifacts should be recognized and minimized to insure accurate interpretation of data (B2). 

By revealing all aspects of the signal, the phase detector makes evident all instrumental artifacts which would not be observable with another type of detection. On an FFC instrument, this typically includes thermal field drifts (see Section IV.D) and field instabilities associated with the large dynamic bandwidth of the switching magnet system. 

If preparative or instrumental artifact is ruled out, the universal occurrence of red-shifted Cotton effects with a-helical character in all the membranes studied points to a common property of the proteins in biological membranes. The ORD results from lipid-free mitochondrial structural protein and erythrocyte ghost protein are consistent with assigning the red shift in these membranes to aggregated protein. It is, therefore, reasonable that similar protein-protein association may occur in all membranes. Ionic requirements for membrane stability could then reflect in part the requirements for protein-protein association. To some extent the molecular associations which stabilize membranes, therefore, may be protein-protein as well as lipid-lipid in nature. 

Lambert-Beer equation (equation 14). With the provision of a reference HO absorption spectrum, and with care to avoid local instrumental artifacts that affect the two beams differently, this design allows the removal of extraneous atmospheric absorption features without requiring assignment to known absorbing species. 

In aqueous solution, one is faced with the scattering of pure water (9), which is a strong scatterer below 200 cm-l with some broad structure around 150 cm-- -. Since water scattering is not an instrumental artifact, one does not evade this problem in going from a double to a triple monochromator or by using the iodine filter technique. The rotating divided-cell technique (10)... 

Figure 6 shows a comparison of the particle size distribution curves for samples 68-B and 8-A obtained by SEM, SFFF, and DCP, those methods directly yielding distribution information. For sample 68-B, based on the SEM number distribution, the sample is unimodal with a small shoulder on the large diameter side. The DCP number distribution curve shows the same characteristics. The SFFF number distribution curve appears to be broader and the small population of larger particles is not discernable. The shoulder on the smaller diameter side in the SFFF distribution appears to be an instrument artifact and occured in the distributions of several samples. 

One of the first things one notices about an EPR spectrum is that it is a first-derivative spectrum rather than the more typical absorption presentation. This is due to an instrumental artifact. To enhance the sensitivity of the EPR spectrometer, the magnetic field is modulated. To obtain field modulation, a small set of Helmholtz coils are place about the sample in line with the external field. These coils allow the amplitude of the external field, to change by a small amount ( 0.01 20G) at a frequency of 100 kHz (smaller frequencies can also be used, but are less sensitive). Because the spectrometer is tuned to only detect signals that change amplitude with field changes at... 

Because the normal blood-retinal barrier resists various substances, including fluorescein, the presence of fluorescein in the vitreous humor indicates a functional breakdown of this barrier. Although physiologic factors and instrument artifacts can influence vitreous fluorescence, this technique has been used to detect retinal vascular disease, especially in diabetes.The procedure has also been used to study the integrity of the blood-retinal barrier in various other diseases, including retinitis pigmentosa, optic neuritis, and essential hypertension. 

The value of a can be used in equation (17.7) to obtain an apparent CPE coefficient Qes. The resulting values pfQeff re presented in Figure 17.13. The absence of a clearly identifiable asymptote may be attributed to high-frequency instrumental artifacts. The values for the CPE confident provided in Table 17.2 represent the axxrage over the values for the 10 highest frequencies. A small reduction in the value of Qeff is evident as the immersion time increases. 

A distinction is drawn in equation (21.1) between stochastic errors that are randomly distributed about a mean value of zero, errors caused by the lack of fit of a model, and experimental bias errors that are propagated through the model. The problem of interpretation of impedance data is therefore defined to consist of two parts one of identification of experimental errors, which includes assessment of consistency with the Kramers-Kronig relations (see Chapter 22), and one of fitting (see Chapter 19), which entails model identification, selection of weighting strategies, and examination of residual errors. The error analysis provides information that can be incorporated into regression of process models. The experimental bias errors, as referred to here, may be caused by nonstationary processes or by instrumental artifacts. 

Bias errors are systematic errors that do not have a mean value of zero and that cannot be attributed to an inadequate descriptive model of the system. Bias errors can arise from instrument artifacts, parts of the measured system that are not part of the system under investigation, and nonstationary behavior of the system. Some types of bias errors lead the data to be inconsistent with the Kramers-Kronig relations. In those cases, bias errors can be identified by checking the impedance data for inconsistencies with the Kramers-Kronig relations. As some bias errors are themselves consistent with the Kramers-Kronig relations, the Kramers-Kronig relations cannot be viewed as providing a definitive tool for identification of bias errors. 

Remember 21.2 Bias errors in impedance measurements can arise from instrument artifacts, parts of the measured system that are not part of the system under investigation, and nonstationary behavior of the system. 

In principle, the Kramers-Kronig relations can be used to determine whether the impedance spectrum of a given system has been influenced by bias errors caused, for example, by instrumental artifacts or time-dependent phenomena. Although this information is critical to the analysis of impedance data, the Kramers-Kronig relations have not found widespread use in the analysis and interpretation of electrochemical impedance spectroscopy data due to difficulties with their application. The integral relations require data for frequencies ranging from zero to infinity, but the experimental frequency range is necessarily constrained by instrumental limitations or by noise attributable to the instability of the electrode. 

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