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The data for one participant (ROD) were presented in Figure 23.1. Figure 23.6 presents the data graphically for three additional subjects. Two of the participants (ROD and RIC) were representative of the participants characterized by a high negative dependence. The exaggerated sawtooth shape of this type of time series is clearly observable. Two participants (ABE and WON) were representative of the three individuals who demonstrated either a zero or low positive dependence. The time series graphs for these two participants are much smoother and more regular. Findings from this study were partially replicated in a similar study conducted in Spain (Rosel & El segui, 1994). This study of 29 smokers (9 men and 20 women) examined daily records of cigarettes smoked over a 12-week period. Virtually all of the data series (97%) were best described by autoregressive-type models, and most (75%) of these were Order 1 models; only one participant s data represented a white noise (i.e., no dependency) model. Other ndings from Rosel and El segui (1994) apparently con ict with the Velicer, Redding, et al. (1992) results. The data from the 29 smokers apparently supported the xed-effect model, with 21 participants data (73%) being described by
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Albrecht, D.R., Sah, R.L., Bhatia, S.N. (2002) Dielectrophoretic cell patterning within tissue engineering scaffolds. IEEE Proceedings of the 24th Annual International Conference of the Engineering in Medicine and Biology Society 2: 1708 1709.
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anions plus cations), rather than percentages of the separate totals of cations and anions as in the Piper plot. For certain types of groundwater, Piper and Durov diagrams do not offer suf cient discriminatory power. This is so, for instance, in the case of saline waters (Hounslow 1995). In order to differentiate between alternative sources of saline water which may be invading a freshwater aquifer, a Hounslow diagram is used (Figure 4.5a). If an individual groundwater sample is plotted on a Hounslow diagram, it is possible to infer the
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into the left ear and white noise and Stroop color words into the right ear. During the low-stress condition, the participants stayed in a quiet environment and performed just the peripheral vision task. A previous study (Andersen, 1988), which used a similar stress manipulation, found the same peripheral narrowing results for participants with high life stress as well as even greater narrowing when the experimenter moved the peripheral targets in slightly faster. The initial assessment moved the targets in as slowly as possible to eliminate any reaction time contaminate. In real-life situations, objects (e.g., people, balls) often approach from the periphery at very fast speeds, suggesting considerably greater deficits than those found in any of the laboratory studies. The Williams et al. (1991) study assessed the effects of coping resources (social support and general coping behaviors such as diet, nutrition, and time for oneself ) and daily hassles in addition to the effects of life change events. Coping resources did not affect stress reactivity directly but moderated the effects of the history of stressors. Recreational athletes with high negative life events or daily hassles, but who also had high coping resources, experienced less self-reported state anxiety during the stress condition compared to athletes with similar high stress but low coping resources. Coping resources, however, had no significant effect on peripheral narrowing. Williams and Andersen (1997) were the first to determine if, under stressful conditions, performance by athletes with high injury risk profiles leads to experiencing greater distractibility in the central field of vision. Their measures of central vision deficits included missing or delayed response to important visual cues, responding to irrelevant cues, and lowering of perceptual sensitivity (d , a ratio of missing relative cues and reporting cues not present). They found that performance in the high- compared to low-stress condition led to significant deterioration on all the perceptual variables, but athletes with high negative life event scores experienced even slower central vision reaction time and greater peripheral narrowing than athletes with low life event stress. In addition, males with low versus high social support failed twice as often to detect central cues, whereas males with high negative life events, low social support, and low coping skills had the lowest perceptual sensitivity. For females, only one significant central vision deficit occurred. Females with high versus low negative life events had twice as many failures to detect central cues, but a significant interaction indicated that this failure occurred only with the group of females who also reported lower psychological coping skills.
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