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The RadioButton component lets you add groups of radio buttons to your Flash document. The groupName parameter logically groups radio button instances together and prevents more than one radio button in the same group from being selected at the same time. RadioButton parameters You can set the following parameters for each radio button instance in your Flash document using the Parameters tab on the Property inspector or the Component Parameters panel.
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3.2. Overview of Cell Sources The cells used thus far to engineer cartilage have varied with respect to donor age (embryonic, neonatal, immature, or adult), differentiation state (precursor or phenotypically mature), and method of preparation (selection, expansion, gene transfer). The sources of chondrogenic cells have included bovine chondrocytes [See, e.g., Buschmann et al., 1992; Freed et al., 1998; Pei et al., 2002b], rabbit chondrocytes [See, e.g., Fedewa et al., 1998], equine chondrocytes [See, e.g., Heath, 2000; Litzke et al., 2004], embryonic chick limb bud cells [See, e.g., Elder et al., 2000], human chondrocytes [See, e.g., Sittinger et al., 1994] and mesenchymal stem cells derived from bone marrow [Meinel et al., 2004a]. The choice of cell type can affect in vitro culture requirements (e.g., medium supplements, structure, and degradation rate of scaffold) and in vivo function (e.g., potential for integration) of engineered cartilage constructs. Articular chondrocytes are phenotypically stable if cultured under appropriate conditions (e.g., up to 7 8 months in vitro [Hauselmann et al., 1994; Freed et al., 1997]) and can be used to engineer mechanically functional cartilaginous constructs [Buschmann et al., 1995; Freed et al., 1997; Vunjak-Novakovic et al., 1999; Obradovic et al., 2001; Schaefer et al., 2002]. However, adult chondrocytes are not easily harvested; cells from younger donors tend to be more responsive to environmental stimuli [(See, e.g., Heath, 2000]), and cell expansion responds to growth factors [Martin et al., 1999, 2001b; Pei et al., 2002a]. Articular chondrocytes are obtained by enzymatic digestion of full-thickness articular cartilage harvested from 2- to 4-week-old bovine calves [Freed et al., 1993] or 2- to 8month old New Zealand White rabbits [Freed et al., 1994a]. For both sources, the cell yield is 3 5 107 cells per gram of wet tissue. Primary chondrocytes can be directly seeded onto scaffolds, or rst ampli ed by subculture in the chondrocyte medium (See below) supplemented with 5 ng/ml of broblast growth factor FGF-2 [Martin et al., 1999]. Expanding chondrocytes undergo approximately 10 doublings, in two passages. During monolayer culture, chondrocytes can be transfected, for example, by human insulin-like growth factor I [Madry and Trippel, 2000]. Precursor cells from the bone marrow are relatively easier to harvest and expand in culture, remain metabolically active in older donors [Haynesworth et al., 1998],
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5.7 COMPARISON BETWEEN WORKLOAD OF WIRELINE WEB AND MOBILE WEB We now compare and contrast the workload between wireline and wireless users. 5.7.1 Comparison in Web Content
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In Section B.3 we discussed the laws of adding and subtracting exponents. From these laws we can derive the laws of logarithms. Let us say that the generalized base of a logarithm is a, which is positive, and that x and y are real numbers. Here we mean they are not imaginary numbers (i.e., based on the square root of 1). Note that a can be any positive number. However, we concentrate on a 10, that is, on logarithms to the base 10. The scienti c calculator should be used to obtain the logarithm by using the log button. There will also probably be an ln button. This button is used to obtain logarithms to the natural base, where a 2.71828183+. Law 1. The logarithm of the product of two numbers equals the sum of the logarithms of the factors. That is: loga xy loga x + loga y.
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Thus, the standard error of the difference is .2704 = .52, making the CI for the difference t1y t2y (1.96) (standard error of the difference) = .2 1.02, which is very wide because of the small sample size. The estimated covariance and variances are also the basis of an inferential method in a type of ordinal multiple regression, to which we now turn. Ordinal Multiple Regression In addition to the situations just discussed, ordinal correlation can be extended to the multivariate case in a type of ordinal multiple regression (OMR; Cliff, 1994, 1996b). OMR has some advantages over the traditional least squares multiple regression (LSMR). OMR is based on ordinal operations, and its results address the ordinal questions that researchers often pose in multiple regression. Both the descriptive and inferential results of OMR are invariant under monotonic transformation. OMR can be more powerful than LSMR when predictor correlations are moderate to high, and when LSMR assumptions are violated. LSMR is a method in which the information of a set of predictors (X j ) is combined to optimally predict the scores on a response variable, Y. A weighted combination of predictors is formed, Yi = bi X ij , which minimizes a loss function based on the sum of squared residuals, (Yi Yi ) 2 , thereby maximizing the sample multiple correlation. The highly speci c mathematics of LSMR means that the relationships between the predictors and the response can be expressed in very explicit, unit-based terms. For example, it is common to interpret an unstandardized regression weight as the predicted increase in Y for a one-unit increase in predictor X j holding all other predictors constant (Howell, 1997, p. 516). The other predictors are actually held constant only in the case of strict multivariate normality, or when the predictors have xed values as in ANOVA. In more common situations, the condition satis ed is that the contribution of X j is uncorrelated with the contributions of all other predictors. Furthermore, raw scores can be composed (or decomposed) from proportions of predictors (and constants). Suppose that Yi = b1 X i1 + b2 X i2 + b0 + ei , where b1 = .8 and b2 = .4. This means that the ith response score is .8 of X 1 , plus .4 of X 2 , plus a constant and a leftover. It is rare that research questions are consistent with the highly speci c nature of LSMR. Rather, most research questions are vague, along the lines of Given a set of predictors, can we predict who will be high and who will be low on the response This type of question is ordinal in nature and is perhaps best answered with a corresponding ordinal method. OMR is based on ordinal operations that provide results consistent with these ordinal questions commonly asked in multiple regression.
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The application calls endGrab from its applicationWillTerminate override, just before it quits. The endGrab function cleans up by performing several tasks: Releases the NSTimer that calls SGIdle. Calls SGStop to turn off Recording, which is the process QuickTime is using to get video from the camera. Calls CDSequenceEnd to stop the decompression sequences. Shuts down the sequence grabber component by calling CloseComponent. Releases the gWorld object and its memory.
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The European authorities in charge of the frequency allocations devoted to Galileo have worked within the ITU frame. The allocations of the WRC held in 1997 in the L2 and L1 bands are respectively shown in Figs 3.2 and 3.3 (note that the future L5 was already planned). The Galileo program had to nd a way to be
Current major theories of personality disorder vary in terms of their assessment of DSM Axis II. Benjamin s (1996a, 1996b) interpersonal theory based on Structural Analysis of Social Behavior (SASB) and Beck s cognitive theory (Beck & Freedman, 1990; Pretzer & Beck, 1996) both generally accept the DSM classification. Contemporary psychodynamic theories (e.g., Kernberg, 1984, 1996; McWilliams, 1994) and neurobiological theories (e.g., Depue, 1996; Paris, 2000) tend to ignore DSM classification in favor of current or future alternatives. Millon s (1990) evolutionary theory tends to parallel the DSM (Millon & Davis, 1996), although he is clear about DSM s limitations (Millon, 2000). Almost all of the recent practical-empirical literature concludes that the DSM system needs revision, although suggestions differ in terms of whether to focus revisions on the structure of the DSM (e.g., Axis I versus Axis II distinctions, categorical versus dimensional versus prototypal classification) or to focus revisions on the nature and scope of diagnostic criteria, or both.
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