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Here s how to use the Page Setup dialog box: n Printer/Plotter Choose a printer or plotter from the drop-down list For more information, see Specifying plot settings later in this chapter n Paper size Choose a paper size from the drop-down list n Plot area By default, the plot is set to the layout However, you can choose to plot the current display, the drawing extents, a named view, or a window that you specify; the options available depend on whether you re on the Model tab or a layout tab n Plot offset You can move the plot from the lower-left corner Specify the X and Y offset in inches If you aren t plotting the layout, but rather some smaller area, check the Center the Plot check box to center the plot on the paper n Plot scale Set the scale from the drop-down list.

Once in a while, installing a new program can wreak havoc with your entire computer, causing it to freeze, crash, or not operate normally. If so, do the following:

wavemeter to characterize a source in 256 wavelength bands with seven or fewer measurements. The source in this case is a slit or pinhole; the goal is to identify the wavelength of the source in logd N measurements. The collimator and frontend grating map the source onto the spectral encoding mask such that each color channel occupies a different transverse column; for instance, if the source power spectrum is S(l), then the power spectrum illuminating the mask is f (x, y) S(x al). Section 9.2 describes how a dispersive spectrograph implements this transformation. For the present purposes it is suf cient to note that if the mask transmission t(x, y) is described by one of the codes of Fig. 7.21, then the spectral density on the plane immediately after the mask can be represented discretely as tij f j , where f j % S(l jD=a) is the signal in the jth spectral channel. Optical components following the mask decollimate the light to focus on an output slit, which in this case is occupied by a detector array distributed along the y axis. The effect of the backend optics is to sum the spectral channels transmitted by the mask along the rows such P that the measured irradiance on the ith detector is gi j tij f j .

of acute symptomatic states, crises of all sorts, and overall level of functioning. Many personality disordered patients can be perfectly appropriate with clinic staff, waiters and waitresses, and others they encounter in daily living situations. Some can maintain employment or even attend university and complete advanced degrees. There is considerable evidence that personality disorder symptomology fluctuates, and that is good news for psychotherapists. If it were otherwise, there would be little sense in treating clients with personality disorder. Therapeutic strategies for personality disorder take advantage of stable periods and work toward containment and reestablishing more adaptive functioning during times of dysregulation. The interpersonal approach developed here accounts for this fluctuating severity in terms of interpersonal learning associated with developmentally salient motives and regulatory metagoals. That is, while symptoms of personality disordered patients fluctuate and they exhibit transient capacity for adaptive functioning, when it becomes necessary for them to regulate their sense of self (e.g., cohesion, esteem, identity), their emotions, or the behavior of others, this is when we often see an increase in severity of symptomology. This is because such regulatory metagoals are likely to be associated with core motives and the internalized patterns of relating associated with their achievement or frustration. When such metagoals and motives are evoked or thwarted, activation of internalized relations that guide perception of new input and expression of interpersonal behavior dominate the individual s functioning (i.e., parataxic distortion). In healthy personalities, only a small number of interpersonal situations require significant regulatory effort, but in personality disordered individuals, many more interpersonal situations appear to elicit anxiety and self-esteem threat.

where the bk are the logistic regression estimates, and 2 /3 is, by assumption, the underlying error variance for the logistic regression model. Because the logistic regression coef cients are estimates of the betas in Y = k X k + , the numerator is a consistent estimator of the variance of the conditional mean of the Y and the denominator is a consis2 tent estimator of the marginal variance of Y . RMZ is there2 fore a consistent estimator of P . A consistent estimator of is , de ned as =1