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, the les containing the data structure and content) that they access Typically, the DDBE will consist of one or more coordinating server instances (providing services across the entire DDBE) and a set of DBEs that combine to make the DDBE work We call each of these DBEs a Sub-DBE (S-DBE), because they combine to form the DDBE in a way that is similar to how subsystems combine to form a system Each S-DBE is a DBE in its own right, which means that each of them is also subject to categorization too using this taxonomy in particular, each S-DBE can be either a centralized DBE or another distributed DBE Most S-DBEs are centralized environments, especially for traditional architectures such as the ones we will discuss in 12.

In this book, we are mostly interested in DDBEs and really only consider the CDBEs when we want to evaluate some type of DDBE or examine the S-DBE inside a larger DDBE..

Figure 2-3. The organization chart for a small, limited-service lodging property includes only minimal staf ng. Several duties have been combined under various positions.

Command bar controls have an Execute method. When invoked, this method runs the internal procedure assigned to a built-in control. For example, executing the following instruction is equivalent to clicking the Sort Ascending button on the Standard toolbar:

1. Wireline fair queueing algorithms such as WFQ [4] or PGPS [18], in which the rate of change of the virtual time (dV/dt) is explicitly simulated. Simulating the virtual time explicitly can be computationally expensive. Idealized wireless fair queueing (IWFQ) [10] uses WFQ or WF2Q [1] to compute its error-free service. 2. Wireline fair queueing algorithms such as start-time fair queueing (STFQ) [8], in which the virtual time is not explicitly simulated. In STFQ, for example, the virtual time is set to the start tag of the packet that is currently being served. Channel-condition-independent fair-queueing (CIF-Q) [16] uses STFQ to compute its error free service. 3. A variation of fluid fair queueing that allows for a decoupling of delay and rate in the scheduler. This is achieved by allocating a rate weight ri and a delay weight i for each flow i, and modifying the tagging mechanism described in Section 8.2.2 as follows: S( p k) = max{V(A[p k)], S( p k 1) + Lk 1/ri} i i i i F( p k) = S( p k) + Lk/ i i i

forms of therapy for speci c disorders (e.g., Borkovec & Ruscio, 2001). Psychosocial interventions also include both prevention and treatment (see, e.g., Christensen & Heavey, 1999, for reviews of both prevention and treatment in the area of marital relations). Social psychologists have evaluated interventions that are designed to improve a wide array of social problems. These include prejudice (Aronson, Blaney, Stephan, Sikes, & Snapp, 1978), the transmission of sexually transmitted diseases (e.g., Alstead et al., 1999), and binge drinking among college students (e.g., Schroeder & Prentice, 1998). Whatever their specialty area, when psychologists evaluate a program or policy, the question of impact of the intervention s effects is often at center stage. Examples abound. Does a particular type of training increase employee s performance Does preschool increase children s subsequent academic performance Do certain types of cooperative learning arrangements in schools reduce racial prejudice Does a speci c form of cognitive-behavioral therapy alleviate generalized anxiety disorder It appears that causal questions usually are central in evaluations of the kinds of interventions that are of interest to psychologists. Given the importance of causal questions, a major focus of this chapter is on key methods for estimating the effects of policies and programs in the context of evaluation.

For instance, sense of mastery and self-efficacy have been suggested as possible mechanisms for the exercise-mood relationship (Landers & Arent, 2001; Mutrie, 2000) As people exercise and their sense of mastery and confidence in exercising and dealing with their environment increases, they may become less depressed and anxious Additionally, exercise (and related mastery experiences) may function to increase selfesteem and self-concept, particularly for physical attributes (Sonstroem, 1998), thus influencing depressive or anxious symptomatology Although this may be the case, most of the studies examining this have been correlational in nature The lack of experimental studies examining changes in selfefficacy, mastery, and self-esteem brought about by exercise training, and its effects on anxiety, depression, and positive mood, limit these psychological hypotheses as viable mechanisms These variables may be more relevant to exercise adherence than they are to the relationship between exercise and positive mood state.