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Optical sectioning of confocal systems is commonly used to measure, for example, cells in biological applications and transparent coatings in the semiconductor industry In cases like these, a different de nition of vertical resolution is used, a de nition that applies to the measurable optical thickness (Sheppard and Gu, 1992; Sheppard et al, 1994) This de nition of axial vertical resolution is based on the vertical two-point resolution of the signal where the width of the axial signal determines the resolution, in this case the minimal measurable optical thickness The vertical resolution of optical slicing can reach down to 15 mm for high NA objectives and is much larger than the vertical resolution related to the measurable step height Figure 1521 shows example of axial responses for transparent layer.

the details for the medium and evaluate the sources, landing pages, and ads involved perhaps there is a site that performs really well and some that perform abysmally. Use drill-down analysis and comparison to determine the winners and losers, then prune out the losers while rewarding the winners. Overall performance for display traf c should begin with total traf c generated (visits). Traf c volume should be considered in light of the volume of impressions (which isn t available in Google Analytics you ll need to conduct visits-to-impressions analysis outside of Google Analytics) and the cost for that exposure. If you spent $10,000 to drive 1 million impressions and received only 1,000 visits, that equates to a cost per visit of $10, which is pretty high. Of course, compare that in the light of the cost of traf c from other mediums before making nal conclusions on this top-line analysis.

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Much research has gone into improving vertical resolution mainly through the application of annular lters in the pupil (Sheppard and Gu, 1991; Martinez-Corral et al, 1995) to narrow the width of PSF in both directions as registered by a nite size detector In order to enhance optical-sectioning capacity, some methods apply symmetrical defocusing of the point source and point (Sheppard and Hamilton, 1984; Ho and Shao, 1991; Kimura and Wilson, 1993) Axial appodization was.

The TEMs support a range of applications requiring ultra-high-resolution down to sub- ngstrom levels. TEMs utilize very thin (0.5 m or less) samples illuminated by an electron beam. Images are recorded by detecting the electrons that pass through the sample (similar to what happens with the light in a slide projector). These electrons pass through a system of electromagnetic lenses and are focused as an enlarged image on a uorescent screen, a photographic lm or a digital camera. Magni cations of more than 1 million times are attainable. The technology uses an electron beam monochromator to improve the resolution of a Cs-corrected electron microscope; the 0.1-nm resolution is not far o the theoretical limit of about 0.07 nm [469]. F.1.7 Energy Dispersive X-Ray Spectrometry (EDS)

not followed. Both the developers and the architect had the static analyzer installed and appropriately con gured. To further assess and improve the quality of the code base, the architect con gured the static analyzer to check whether the code complied with coding standards that have been shown to signi cantly improve code reliability, security, performance, and maintainability. Sample rules included: Reliability Rules:

Figure 14-5

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one iteration to the next, even as the parameter estimate is rapidly increasing in magnitude So to avoid the false appearance of convergence, it is essential that convergence be evaluated by looking at changes in the parameter estimate across iterations rather than changes in the log-likelihood The explanation is a bit more complicated with the SAS GENMOD procedure, however SAS documentation is quite explicit that the criterion is based on parameter estimates, not on the log-likelihood (SAS Institute 1999) But GENMOD uses a modi ed Newton Raphson algorithm that performs a line search at each step to stabilize its convergence properties In most cases this improves the rate of convergence However, if the likelihood cannot be improved along the current Newton step, the algorithm returns the current parameter values as the updated values and therefore determines that the convergence criterion has been met (G Johnston 2002 personal communication).

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