References—continued minimum data

Two UV detectors are also available from Laboratory Data Control, the UV Monitor and the Duo Monitor. The UV Monitor (Fig.3.45) consists of an optical unit anda control unit. The optical unit contains the UV source (low-pressure mercury lamp), sample, reference cells and photodetector. The control unit is connected by cable to the optical unit and may be located at a distance of up to 25 ft. The dual quartz flow cells (path-length, 10 mm diameter, 1 mm) each have a capacity of 8 (i 1. Double-beam linear-absorbance measurements may be made at either 254 nm or 280 nm. The absorbance ranges vary from 0.01 to 0.64 optical density units full scale (ODFS). The minimum detectable absorbance (equivalent to the noise) is 0.001 optical density units (OD). The drift of the photometer is usually less than 0.002 OD/h. With this system, it is possible to monitor continuously and quantitatively the absorbance at 254 or 280 nm of one liquid stream or the differential absorbance between two streams. The absorbance readout is linear and is directly related to the concentration in accordance with Beer s law. In the 280 nm mode, the 254-nm light is converted by a phosphor into a band with a maximum at 280 nm. This light is then passed to a photodetector which is sensitized for a response at 280 nm. The Duo Monitor (Fig.3.46) is a dual-wavelength continuous-flow detector with which effluents can be monitored simultaneously at 254 nm and 280 nm. The system consists of two modules, and the principle of operation is based on a modification of the 280-nm conversion kit for the UV Monitor. Light of 254-nm wavelength from a low-pressure mercury lamp is partially converted by the phosphor into a band at 280 nm. 

Adopting the unsupervised option initially, the first two variables to be selected are those with the lowest pairwise correlation. The next variable selected has the smallest multiple squared correlation with those first two variables. This process is continued until the preset maximum level of multicolinearity (determined by the squared multiple correlation coefficient) is reached. Whitley et al. refer to this procedure as unsupervised forward selection (UFS). UFS can also be performed with a minimum variance criterion where only variables with variance above this minimum will be selected. These two criteria can be used by scientists simultaneously. With supervised variable selection, only those variables having a sufficiently high correlation with the response are considered for what effectively is UFS on this reduced set of variables. We will term this latter process, supervised forward selection (SFS). To see how these options work and to examine the effect they have on the model produced, we performed PLS on the data with both UFS and SFS configured to run with a range of response variable correlations (Table 8). 

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