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The disruptive effects of noise on sleep can be of concern in communities exposed to aircraft overflights during nighttime hours Over the past two decades, many investigations of noise-induced sleep disruption have been conducted worldwide The functional relationship most often evaluated has been the probability of a sleep disruption created by a single noise intrusion of a given sound level Four major research review studies [10, 32, 37, 46] all support the same general finding that increased sound exposure level (SEL) results in higher probabilities of sleep disruption Currently, however, there are no guidelines or acceptability criteria for assessing the cumulative impact of many aircraft noise intrusions of various SELs over the course of a nighttime sleeping period The aforementioned reviews provide some insight as to why such guidelines and criteria have not been forthcoming Data acquisition methodologies, the treatment of mitigating variables, and the choice of both dose and disruption metrics are far from standardized, even for studies limited to short-term, transient noise events similar to those produced by aircraft overflights

Despite all of this variability, first order dose-response curves have been developed which attempt to relate the probability of an arousal, either a sleep stage change or an actual awakening, to the sound exposure level of a single noise event [11, 26] At the present time caution should be exercised in drawing inferences from such curves Among other things, the preponderance of underlying data generally represents laboratory listening conditions Thus the curves could be expected to better predict reaction to new and unfamiliar sounds rather than older, more familiar ones When compared with in-laboratory studies, the limited data available from in-home investigations using familiar sound sources suggests that arousal probabilities may be on the order of only one-eighth those observed from unfamiliar sources In addition to these adaptation issues, uncertainty still remains on important questions such as the cumulative effects of multiple noise intrusions, the effects of noise on falling asleep as opposed to awakening, and the extent to which sleep deprivation represents a quantifiable physiological problem

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Our two queries are functionally equivalent and therefore return the same cells The second query uses the Except set operator whereas the first one uses the minus sign (-), which means Except Except is covered elsewhere in the book In effect, it has subtracted the United Kingdom from the list of all the countries in the Sales Territory dimension

Social survey data have long made it clear that individual reactions to noise vary widely for a given 24-h average sound level As a group, however, the aggregate response of people to factors such as speech and sleep interference and desire for an acceptable environment is predictable and relates well to measures of cumulative noise exposure such as DNL Figure 14-5 shows the most widely recognized

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0 40 50 60 70 80 90 Day-Night Average Sound Level (decibels)

FIGURE 14-5 Percentage of people highly annoyed as a function of day-night average sound level (Adapted from Schultz, Journal of the Acoustical Society of America [49] )

The Where clause in MDX bears little resemblance to an SQL Where clause The nearest you can get to an SQL Where is an MDX Filter function Before we try it, let s get some dimension attribute members, some measures, and a few cells

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