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Hardy and Riehl (1988) found that injured athletes overall had significantly higher NLE than noninjured athletes, but injured female athletes reported higher scores on TLE compared to uninjured females Both TLE and NLE significantly predicted injury across sports, but analyses within sports indicated injured softball players reported higher TLE, baseball players higher NLE, and track athletes higher object loss (eg, loss of a significant other through death, divorce, separation) compared to equivalent uninjured players Except for track, none of the stress measures predicted injuries in the specific sports In track, both TLE and object loss predicted injuries These findings led Hardy and Riehl to conclude that the life stress injury relationship is influenced by both the athlete s sex and the sport Hardy, O Connor, and Geisler s (1990) study of Division I soccer players supported the conclusion that gender affects the relationship between life stress and injury.

The reason gender would affect the stress-injury relationship, however, is unclear The preceding differences aside, almost all studies that assessed life events found at least some significant relationship between life stress and injury This almost universal finding is itself compelling, but even more so considering it occurred across sports and competitive levels (youth to elite level) and with diverse measures of life stress and definitions of injury Researchers used eight questionnaires to assess life stress, and the criteria for injury varied from requiring treatment from an athletic trainer but no need to reduce practice time or modify activity (eg, Blackwell & McCullagh, 1990), to time loss requiring missing more than a week of practice (eg, Coddington & Troxell, 1980) These different operational definitions make it impossible to determine relative injury risk across sports and competitive levels and across positive versus negative stressors.

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Diverse operational definitions also contribute to the difficulty in determining the effect of life stress on severity of injury Approximately two-thirds of the studies found some relationship between life stress and injury severity (eg, Blackwell & McCullagh, 1990; Hanson et al, 1992; Hardy et al, 1990; Hardy & Riehl, 1988; Kerr & Minden, 1988; Meyer, 1995; Petrie, 1992, 1993b), and one third found no effect (eg, Cryan & Alles, 1983; Hardy, Richman, & Rosenfeld, 1991; Lavallee & Flint, 1996; Lysens, Vanden Auweele, & Ostyn, 1986; Williams, Tonymon, & Wadsworth, 1986), although that relationship would be expected to share substantial variance with injury occurrence These studies did not control for injury incidence when looking at relationships between life events and injury severity (usually measured by dura-.

Thurstone (1928) and Guttman (1947) independently desired to construct opinion-attitude scales that manifest characteristics of physical measurement This led them to the notion of unidimensionality, whereby persons are classified in an unequivocal order However, their desire was not met, particularly because the models they used were insufficient to validate the concepts they introduced Despite several inconsistencies, Thurstone and Guttman.

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Illustrated TCP/IP by Matthew G. Naugle Wiley Computer Publishing, John Wiley & Sons, Inc. ISBN: 0471196568 Pub Date: 11/01/98

Table 34.1 Hypothetical Data for Real and Recalled Anxiety State in 10 Athletes Anxiety State Athlete 1 2 3 4 5 6 7 8 9 10 Mean SD Real 45 57 61 33 42 54 27 37 58 70 48.4 13.75 t = 9.00 (p 0.00) Recalled 50 62 66 38 47 59 32 42 63 70 52.9 12.94

Now that you ve seen several freeware and commercial products that implement stego and understand the techniques they use, you get to create your own. You ll explore all three types of techniques: insertion, substitution, and generation. You ll see that the number of approaches to stego you might come up with is limited only by your creativity. For this section I concentrated on the functionality, not fancy GUIs. Elaborate GUIs may look nice, but they make it harder to compile code on different platforms.

minimum requirements on upgrading network protocols and infrastructure. These solutions will target the manner in which the content is managed (in terms of storage, value-added services, search, distribution, consistency, adaptation, digital rights management, and charging) and delivered to enhance performance (latency, reliability, ef ciency) and usability. In a nutshell, the development of future mobile networks will be driven, in large part, by content and Web-based services, and user experience. These are essentially the topics that are covered in this book.

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