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SNP pro le, 175, 178 SNP scan, genome-wide, 95 Social differentiation, 251, 252, 263 Social groups, genetic research and, 194 199 Social mandates, pharmacy responses to, 213 223 Social practice, changing, 262 263 Software tools, proprietary, 122 Sparteine, 141 Squamous cell carcinomas, 145 Standard of care doctrine, 187, 326 Start-ups, small, 130 Statement on Bene t Sharing, 74 Statins, 91 Statistical design, 54 Stereotypes, health-provider, 276 277 Sterilization experiments, 199 Stevens-Johnson syndrome (SJS), 93 STI-571, 154 Stigmatization, disease-based, 75 77 Strict liability, 190, 191, 326 327 Structural Genomics Project, 41 Studies, federally funded, 280. See also Research Study participation, treatment development based on, 8 Study populations, describing, 149 Subscriber agreements, 122 Succinylcholine, 60, 165, 168 Survey Questionnaire, General Population, 337 348 Susceptibility alleles, 52 Susceptibility genes, 44, 86 Susceptibility testing, 181, 306 307 Suter, Sonia, 17 Suxamethonium, 89, 139 140 Syphilis study, 68 Systems approach to risk reduction, 188 Targeted therapeutics, assessing the use of, 107 108 Task Force on Genetic Testing, 179 Taxol, 127 Tay-Sachs disease, 76, 279 testing associated with, 195 196, 307 Technological change, policy implications of, 236 237

Figure G.1 illustrates available power gain. The input power pin is the power that the source delivers to a load that is matched to that source. The output power pout is the power the module delivers to a load that is matched to its output impedance when the module is driven by the source. The source impedance must be speci ed. (This term has also been used for what we are calling maximum available power gain (Jay, ed. 1977.) Available gains can be multiplied to give the available gain of a cascade, as in Eq. (2.1), even though the variables [Eq. (2.2)] may not actually exist in the cascade. The intermediate variables uj are powers that would be delivered to a matched load, whether such a load is present or not. This means that the available gain of a module depends on the output impedance of the preceding module and cannot be de ned without that information. The same module will have different available gains in different cascades.

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Just as an organization becomes more complex, a technology plan for a larger, more mature organization is similarly more complex. A good plan for such an organization should include:

There are three benefits of applying the Thread-Safe Interface pattern: Increased robustness This pattern ensures that self-deadlock does not occur due to intracomponent method calls Enhanced performance This pattern ensures that locks are not acquired or released unnecessarily Simplification of software Separating the locking and functionality concerns can help to simplify both aspects However, there are also four liabilities when applying the Thread-Safe Interface pattern: Additional indirection and extra methods Each interface method requires at least one implementation method, which increases the footprint of the component and may also add an extra level of methodcall indirection for each invocation One way to minimize this overhead is to inline the interface and/or implementation methods Potential deadlock By itself, the Thread-Safe Interface pattern does not resolve the problem of self-deadlock completely.

fourth, and fth packages With his rst package, Stokes varied the algorithm, the convergence tolerance, starting values, and so on This is something that every user should do with every nonlinear estimation Suppose that a user has done this and identi ed a possible solution How might he verify the solution McCullough and Vinod (2004) recommend four steps: 1 Examine the gradient Is ||g|| 0|| 2 Inspect the sequence of function values Does it exhibit the expected rate of convergence 3 Analyze the Hessian Is it positive semide nite Is it ill conditioned 4 Pro le the objective function Is the function approximately quadratic Gill et al (1981, p 313) note that if the rst three conditions hold, very probably a solution has been found, regardless of whether the program has declared convergence.

For example, consider a client that calls an interface method on component A, which then delegates to an implementation method that calls an interface method on another component B If the implementation of component B's method calls back on an interface method of component A, deadlock will occur when trying to reacquire the lock that was acquired by the first call in this chain Potential for misuse Object-oriented programming languages, such as C++ and Java, support class-level rather than object-level access control As a result, an object can bypass the public interface to call a private method on another object of the same class, thus bypassing that object's lock Therefore, programmer's should be careful to avoid invoking private methods on any object of their class other than themselves Potential overhead The Thread-Safe Interface pattern prevents multiple components from sharing the same lock.

The fourth step justi es the use of the usual t-statistics for coef cients reported by most packages These t-statistics are Wald statistics and, as such, are predicated on the assumption that the objective function, in this case the sum-of-squares function, is approximately quadratic in the vicinity of the minimum If the function is not approximately quadratic, the Wald statistic is invalid and other methods are more appropriate (eg, likelihood ratio intervals); this topic is addressed in detail in Section 86 The easy way to determine whether the objective function is approximately quadratic is to pro le the objective function Each of these four steps is discussed in turn 851 Step 1: Examine the Gradient At the solution, each component of the gradient should be zero.

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