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Score images

The data array Xmyriyqy which may be preprocessed by standardisation and transformation, is decomposed in a set of three-way products of score images, T, loading vectors, p, and the residual, Emytlyq ... [Pg.281]

Figure 8.5 Adulterated pharmaceutical blister pack containing a single rogue tablet (A) Visible image showing that visually the tablets are virtually indistinguishable and (B) NIR PCA score image highlighting the single tablet that has a different chemical signature. Figure 8.5 Adulterated pharmaceutical blister pack containing a single rogue tablet (A) Visible image showing that visually the tablets are virtually indistinguishable and (B) NIR PCA score image highlighting the single tablet that has a different chemical signature.
Figure 8.6 Contraceptive contained in the original package, demonstrating high-throughput classification possibilities. (A) Visible image (B) description of sample positioning and (C) NIR PCA score image showing contrast between the placebo and the active-containing tablets. Figure 8.6 Contraceptive contained in the original package, demonstrating high-throughput classification possibilities. (A) Visible image (B) description of sample positioning and (C) NIR PCA score image showing contrast between the placebo and the active-containing tablets.
A partial least square type two (PLS 2) analysis was employed, based on a library of the three API pure components. Applying the model in classification mode to the sample data set results in PLS score images that show the spatial distribution of the three API components. [Pg.268]

The PLS scores images for acetaminophen, aspirin and caffeine highlighting high concentration areas for each chemical components are shown in Figure 8.11A-C. Contrast in these score images is based on the... [Pg.268]

Figure 8.11 An OTC analgesic tablet (Excedrin) with three APIs. Spatial distribution of each API was obtained using PLS analysis. (A-C) PLS score images of acetaminophen, aspirin, and caffeine, respectively and (D-F) single-pixel microspectra (solid line) compared to pure component acetaminophen, aspirin, and caffeine spectra (dashed line), respectively. Figure 8.11 An OTC analgesic tablet (Excedrin) with three APIs. Spatial distribution of each API was obtained using PLS analysis. (A-C) PLS score images of acetaminophen, aspirin, and caffeine, respectively and (D-F) single-pixel microspectra (solid line) compared to pure component acetaminophen, aspirin, and caffeine spectra (dashed line), respectively.
Figure 8.12 Histograms of PLS score images. (A) acetaminophen (B) aspirin and (C) caffeine. Figure 8.12 Histograms of PLS score images. (A) acetaminophen (B) aspirin and (C) caffeine.
Figure 8.15 (A-F) hiistogram representations of the PLS score images showing the statistical distributions of the API class. Heterogeneity In the blend Is Indicated by deviations from a normal distribution and can be expressed as percent standard deviation (%SD), calculated by dividing the standard deviation by the mean. Figure 8.15 (A-F) hiistogram representations of the PLS score images showing the statistical distributions of the API class. Heterogeneity In the blend Is Indicated by deviations from a normal distribution and can be expressed as percent standard deviation (%SD), calculated by dividing the standard deviation by the mean.
For a statistical analysis to adequately characterize the distribution of a component, the data should first be processed to obtain the optimum selectivity for that component. In this application the PLS model produces a score image that effectively separates the spectral response of the API from the excipients. Even though there is very little observable contrast in the images of the well blended samples, the results from the poorly blended samples convey conhdence that the method is effective at tracking the API distribution. [Pg.275]

Figure 8.16 Analysis of selected areas of the best laboratory blend (Tablet E) and the commercial blend (tablet F). (a) Truncated PLS score imaged for the API component (depicted as white) from the central region of the tablets showing that on a local scale, the blending in both samples is uniform and (b) histograms and resulting %SD of the distribution from the truncated images. Note that both examples display nearly normal distributions. Figure 8.16 Analysis of selected areas of the best laboratory blend (Tablet E) and the commercial blend (tablet F). (a) Truncated PLS score imaged for the API component (depicted as white) from the central region of the tablets showing that on a local scale, the blending in both samples is uniform and (b) histograms and resulting %SD of the distribution from the truncated images. Note that both examples display nearly normal distributions.
FIGURE 8 Self-calibrating image comparison for counterfeit identification score images. White higher score. Black lower score. [Pg.420]

FIGURE 15 PCA score images PC2 magnesium stearate PC3 API PC4 Avicel PCI poloxamer, not discriminant and not displayed (white higher absorbance, black lower absorbance). [Pg.425]

Fig. 14.2. Factors and score images of a 275 pm x 140 pm region of mature canine trabecular bone strut, (a) PC>4 3 and (b) phenylalanine. Each pixel is 1.4pm x 1.4 pm. Reprinted with permission from [26]... Fig. 14.2. Factors and score images of a 275 pm x 140 pm region of mature canine trabecular bone strut, (a) PC>4 3 and (b) phenylalanine. Each pixel is 1.4pm x 1.4 pm. Reprinted with permission from [26]...
Finally, a similar approach was undertaken to evaluate the origin of factor 3 in Fig. 15.3c whose score image reveals several small-localized pockets in the epidermis. The loading from factor 3 (Fig. 15.3b) depicts one broad feature at 1090cm 1 not present in the other factor loadings. Based on both the position of this particular band and the spatial distribution of the factor score, the band probably arises from a phosphodiester mode of DNA [30, 31] present in the nuclei of keratinocytes or other cells. An additional feature at 780 cm 1 in both spectra and factors (not shown) arises from cytosine in DNA [32] and is consistent with this interpretation. [Pg.372]


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See also in sourсe #XX -- [ Pg.256 ]

See also in sourсe #XX -- [ Pg.256 ]




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