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Image brightness (photon flux per area per unit time) is also determined by the NA and is of great practical importance for confocal microscopy Since the amount of light reaching the photomultiplier tube is usually small, we are frequently forced to operate the confocal system at high electronic gain, which tends to produce noisy images The gain can be reduced and the image quality improved by providing a brighter diffraction spot at the pinhole with a high-NA objective Since image brightness is proportional to NA4/Mag2 (s 4 and 6), you should select the lowest magnification commensurate with the resolution requirements, and within that constraint, choose the highest available NA For these reasons, a well-corrected plan-neofluorite or planapochromatic objective of 60 100 magnification is ideal for the examination of cellular details.



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In addition to the confocal pinhole, the objective lens plays an equally important role in determining the depth of field in the specimen and the depth of focus in the image, and therefore the thickness of a confocal image The thickness d of the focal plane along the z-axis in the specimen is defined as /NA2 and is determined by the wavelength and the numerical aperture NA of the objective lens ( 6) Since in epi-illumination mode the objective focuses the laser spot on the specimen, high-NA lenses reduce the thickness dimension of the diffraction spot for laser excitation and reduce the focal plane thickness at the exit pinhole Reducing the size of the pinhole diaphragm limits the thickness of the confocal optical section, but only to the limit set by the microscope optics Therefore, the combination of high-NA lenses and small pinhole apertures generates the thinnest optical sections.

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generally indicating a higher transmission data rate. There is a crossover point around ECR 3/4 when it is bene cial to employ 16QAM with strong coding rather than using QPSK with reduced coding. The results presented in Figure 7.2 are for the single HS-PDSCH case showing the basic modulation and coding performance without link adaptation. Link adaptation selects the modulation and coding scheme so that throughput and delay are optimized for the instantaneous SINR. Figure 7.3 shows the required SINR as a function of the data rate for the rst transmission when link adaptation is included.

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Suppose that we intend to evaluate the accuracy of a clustering algorithm A on a set of objects S relative to a collection of classes on S that forms a partition of S. In other words, we wish to determine the extent to which the clustering produced by A coincides with the partition determined by the classes. If the set S is large, the evaluation can be performed by extracting a random sample T from S, applying A to T , and then comparing the clustering partition of T computed by A and the partition of T into the preexisting classes. Let = {C1 , . . . , Cm } be the clustering partition of T and let = {K1 , . . . , Kn } be the partition of T of classes. The evaluation is helped by n m matrix Q, where qij = |Ci Kj | named the confusion matrix. We can use distances associated with the generalized entropy, d ( , ), to evaluate the distinction between these partitions. This was already observed by Rand [11], who proposed as a measure the cardinality of the symmetric difference of the sets of pairs of objects that belong to the equivalences that correspond to the two partitions. Frequently, one uses the conditional entropy

Amerine, M.A. & Roessler, E.B. (1983) Wines: Their Sensory Evaluation. San Francisco: WH Freeman. Amerine, M.A. & Singleton, V.L. (1977). Wine: An Introduction, 2nd edn. Berkeley: University of California. Amerine, M.A., Berg, H.W., Kunkee, R.E., Ough, C.S., Singleton, V.L. & Webb, A.D. (1980) The Technology of Wine Making, 4th edn. Westport, CT: AVI. Boulton, R.B., Singleton, V.L., Bisson, L.F. & Kunkee, R.E. (1996) The Principles and Practices of Winemaking. New York: Aspen. Dutruc-Rosset, G. (2000) The state of vitiviniculture in the world and the statistical information in 1998. Bulletin de l Of ce International de la Vigne et du Vin, 73, 1 94. Fleet, H., ed. (1993) Wine Microbiology and Biotechnology. Chur: Harwood. Jackson, R.S. (2000) Wine Science: Principles, Practice, Perception, 2nd edn. San Diego: Academic Press. Waterhouse, A.L. & Ebeler, S., eds (1998) Chemistry of Wine Flavor. ACS Symposium Series No. 714. Washington, DC: American Chemical Society.

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