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4. On the Fit tab, in the Text Placement section, choose Over Dimension Line, with Leader. 5. In the Fine Tuning section, check Draw Dim Line Between Ext Lines. Architectural dimensions customarily place a line between the extension lines, even if the text cannot fit. 6. Because the drawing s scale is 1 4"=1', or 1:48, type 48 in the Use Overall Scale Of text box. 7. Click OK. Click Close to return to your drawing. 8. Save your drawing. You can finally see the dimension! It should look like Figure 15-23. Keep this drawing open if you re continuing on to the next exercise.

Binge eating is characterized by eating, within a discrete time-period, more food than most others would consume in similar circumstances, this being accompanied by a sense of loss of control over eating (American Psychiatric Association, 1994). Many individuals also report losing control over eating even when they have not consumed an objectively large amount of food; such episodes are termed subjective (as opposed to objective) binge eating. Studies analysing recorded food intake have found that obese binge eaters report binge eating episodes that vary greatly in caloric content, ranging from a few hundred calories up to several thousand calories. A typical binge recorded by a patient using a food diary is shown in Figure 20.1.

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entrance side to a shunting activity. The order of assignments is de ned by the tryall statements. These few statements are all that we have de ned in the implementation of the search strategy. The assignment of routes has not as yet been based on domain speci c knowledge. The internal mechanism handles the checking and propagation of the constraints as well as backtracking and the assignment of values to variables that are not included in the domain-speci c search strategy.

Use the Query Wizard to build a query that displays the data shown in Figure 15-28. Be sure to sort the results by time and then by show name.

Measure the distance from A to B. Using the probable speed through the water, calculate the estimated time taken to

Figure 12.2 One of the chromatic adaptation factors F plotted as a function of the adapting chromaticity for a variety of adapting luminance levels. This function illustrates how adaptation becomes less complete (F departs from 1.0) as the purity of the adapting stimulus increases (h departs from 1.0) and the luminance level decreases

Jane walked into the board meeting confident and proud. As the director of development for a regional Midwestern symphony orchestra, she had a strong relationship with the board, and she enjoyed the challenging assignments they gave her. A year ago, she completed a five-month project to roll out the symphony s first Web site one of the board s major initiatives. Although Web traffic was slow at first, over time she and the board came to regard the project as a success: hundreds of visitors came to the site each month, and she had received a good deal of positive feedback on the online program guide.

Comparison of Models To compare the predictions of both models ( rst- and zero-order kinetics), Table 33 and Figure 6 have been prepared. As expected, both predictions give quite similar results. The rst-order model gives slightly better results, suggesting that the degradation is actually of rst order. Both predictions yield similar results because degradation reactions are quite slow and therefore the time frame of these measurements is very small compared, say, to the half-life of the degradation (or the time it takes for the assay to reach the value of 50% LC). Although the discussion of half-life calculation is beyond the scope of this handbook, suf ce it to say that based on the results of Examples 6 and 7, the half-life for rst-order kinetics is about 23 years and for zero-order kinetics (probably less accurate) is 17 years. These values are about 40 times the time frame used in the accelerated (short-term) tests of 6 months (0.5 year). Thus, any kinetic model will work reasonably well. 7.2.4.4 Preliminary Shelf Life Calculation from Stressed Data

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