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As already mentioned, environmental factors rather than population-level genetic change must explain the steady climb in BMI over the last 30 years, which has been seen in many populations (see 2). Environmental factors include numerous societal and other changes that tend to encourage overconsumption of food and/or decrease energy expenditure, primarily through reduced physical activity. As discussed below, assortative mating that is, the tendency of obese people to select obese partners may have augmented the effects of obesogenic environmental factors. The importance of social contacts in facilitating the spread of obesity has been highlighted by recent data from the Framingham Heart Study. The changing pattern of obesity was mapped within neighbourhoods over several years. Obesity developed in clusters and appeared to spread within social networks, especially among groups of individuals who are linked by friendship and family ties with the chances of close friends and family members of an obese person also becoming obese increasing by 40 60% (see Figure 8.8). By contrast, immediate neighbours were unaffected, arguing against local environmental in uences. This implies that social contacts are important in propagating obesogenic behaviours. The relative importance of decreased physical activity versus increased food intake has been much discussed; both may contribute to the spread of obesity, to degrees that vary with time and between populations. Numerous methodological dif culties have clouded this issue.
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This section describes tra c management in the 2G-SGSN and, more speci cally, active queue management techniques that may be implemented in that element (see [11] for more details). In addition to playing a central role in, say, session, mobility and charging management procedures, the 2G-SGSN acts as a bu er for the radio access network. That is, the 2G-SGSN shall temporarily hold downlink packets (instead of forwarding them immediately) if the BSC is not able to receive them due to, say, lack of own-bu er space. The main bene t of this approach is to avoid placing too high memory requirements at the BSC. This ow control procedure between the 2G-SGSN and the BSC is speci ed in 3GPP [3] and [12] (see Figure 6.6). There are three di erent ow control levels. The rst is the BSSGP virtual connection (BVC) ow control, which refers to the cell level. In case the available bu er space in the BSC reserved for a particular BVC drops below a certain threshold, the BSC will signal the 2G-SGSN to reduce its sending rate for the tra c accessing that BVC. The second level is MS-speci c ow control. Again, if the available memory in the BSC reserved for a particular MS gets too low, the 2G-SGSN will reduce the sending rate for that particular
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, where wn = 0, 1, . . . and A is a positive scalar. The Poisson probability function describes the probability of a counting result w, and is, therefore, a discrete stochastic variable. It can be shown that Ew, = A , (3.37)
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84. Wood, R. (1999), How to validate analytical methods, Trends Anal. Chem., 18, 624 632. 85. Waters Corporation (2004), Validation Guidelines: Terminology and De nitions, available: 86. Hibbert, D. B. (1999), Method validation of modern analytical techniques, Accred. Qual. Assur., 4, 352 356. 87. Fleming, J., Neidhart, B., Albus, H., and Wegscheider, W. (1996), Glossary of analytical terms (III), Accred. Qual. Assur., 1, 135. 88. Krull, I. S., and Swartz, M. (1999), Analytical method development and validation for the academic researcher, Anal. Lett., 32, 1067 1080. 89. Quevauviller, Ph. (2004), Traceability of environmental chemical measurements, Trends Anal. Chem., 23, 171 176. 90. Holcombe, G., Lawn, R., and Sargent, M. (2004), Improvements in ef ciency of production and traceability for certi cation of reference materials, Accred. Qual. Assur., 9, 198 204. 91. Lauwaars, M., and Anklam, E. (2004), Method validation and reference materials, Accred. Qual. Assur., 9, 253 258. 92. Fleming, J., Albus, H., Neidhart, B., and Wegschieder, W. (1996), Glossary of analytical terms (IV), Accred. Qual. Assur., 1, 191. 93. Thompson, M., Ellison, S. L. R., Fajgelj, A., Willets, P., and Wood, R. (1999), Harmonised guidelines for the use of recovery information in analytical measurement, Pure Appl. Chem., 71, 337 348. 94. Vessman, J. (1996), Selectivity or speci city Validation of analytical methods from the perspective of an analytical chemist in the pharmaceutical industry, J. Pharm. Biomed. Anal., 14, 867 869. 95. Analytical Methods Committee (1987), Recommendations for the de nition, estimation and use of the detection limit, Analyst, 112, 199 204. 96. Fleming, J., Albus, H., Neidhart, B., and Wegschieder, W. (1997) Glossary of analytical terms (VII), Accred. Qual. Assur., 2, 51 52. 97. Huber, W. (2003), Basic calculations about the limit of detection and its optimal determination, Accred. Qual. Assur., 8, 213 217. 98. Kuselman, I., and Sherman, F. (1999), Assessment of limits of detection and quanti cation using calculation of uncertainty in a new method for water determination, Accred. Qual. Assur., 4, 124 128. 99. European Commission (EC), Council directive 96/23/EC of April, 29 1996, on measures to monitor certain substances and residues thereof in live animals and animal products and repealing directives 85/258/EEC and 86/469/EEC and decisions 89/187/EEC and 91/664/EEC, Off. J. Eur. Commun., L125, 0010 0032, 23.05.1996. 100. European Commission (EC), Commission decision 2003/181/EC amending decision 2002/657/EC as regards the setting of minimum required performance limits (MRPLs) for certain residues in food of animal origin, Off. J. Eur. Commun., L 71/17, 0017 0018, 15.3.2003. 101. Antignac, J.-P., Le Bizec, B., Monteau, F., and Andre, F. (2003), Validation of analytical methods based on mass spectrometric detection according to the 2002/657/EC European decision: Guideline and application, Anal. Chim. Acta, 483, 325 334. 102. De Wasch, K., De Brabander, H. F., Courtheyn, D., Van Hoof, N., Poelmans, S., and Noppe, H. (2003), The commission decision 2002/657/EC: Disscussion on some new analytical aspects. EURO FOOD CHEM XII, in Strategies on Safe Food, Proceedings, Vol. 1, Brugge, Belgium, Sept. 24 26, 2003, pp. 45 48.
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WSs with Ethernet connection. Conventional network protocols often use default parameters that are only suitable for small le transfer. Changing some parameters in the protocol may speed up the transfer rates, for example, enlarging the TCP window size and the image buffer size. Operational Environment Methods in the speci c category are based on the operational environment. Methods of correction may involve changing the operational procedure in the radiology department. Consider two examples: CR images stacked up at the CR readers and CT/MR images stacked up at the scanners. Most CR applications are for portable examinations and are mostly performed in early morning. An obvious method of correction is to rearrange the portable examination schedule at the wards. CT/MR images stacked up at the scanners can be caused by a design fault in the communication protocol at the scanners. There are two methods of correction. First,
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Embed or Extract The embed or extract process time is mainly determined by the correlation of adjacent pixels of each image in an image set in accord with the concept of the LDSERS algorithm. For images with high correlation among adjacent pixels, the process time to embed or extract is short. For a comprehensive performance of the 3-D LDSERS, see Zhou et al. (2003).
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