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MacMillan, J., 273, 274, 276, 278 MacPherson, K., 495 MacRae, P. G., 492, 494, 497, 500 Mactavish, J., 603, 849, 851 Madden, D. J., 496, 499 Madden, P. A., 316, 863 Maddison, R., 145, 148, 150, 151, 385, 391, 395, 426, 524 Maddock, J. E., 551 Maddux, J. E., 147, 150, 800, 803 Madrigal, R., 696 Maehr, M., 3, 4, 5, 20, 21, 22, 23, 24, 130, 567, 675 Magai, C., 651 Magdol, L., 353 Mageau, G., 62, 65, 67, 68, 69, 70, 75 Magill, R. A., 185, 252, 438 Magill-Evans, J., 846 Maguire, E. A., 473 Maguire, P., 581 Magyar, T. M., 418, 664, 671, 672, 673, 801, 802, 807, 808, 810, 814, 816 Maher, K. E., 580 Maher, P., 562 Mahoney, L., 567 Mahoney, M. J., 43, 48, 49 Maia, J. A. R., 513 Maida, D. M., 356 Maier, K. S., 811 Mainwaring, L., 410, 417, 418 Makeig, S., 101 Malatesta, C. Z., 652 Malenchuk, O., 829 Malik, P. B., 724 Malina, R. M., 184, 360, 654 Mallett, C. J., 298 Malley, M., 496 Malliou, P., 415, 416, 417 Malo, S., 408, 409, 410, 413, 417 Malone, L. A., 722 Malone, S. C., 586, 587 Maloney, T. L., 663 Maltby, J., 523 Mamassis, G., 299 Mand, C., 674 Mandell, A. J., 859, 866, 869, 870 Mandler, G., 32 Mangum, M., 564 Mangweth, B., 361 Maniar, S. D., 316 Mann, B. J., 321 Mann, B. L., 122 Mann, C. A., 105 Mann, L., 357 Mann, T., 369, 553, 655 Manne, S. L., 582 Mannell, R. C., 66 Manning, T., 69 Manore, M. M., 354, 355, 360, 371 Manson, J. E., 495 Manstead, A. S. R., 152 Mant, M. J., 590, 591

From (12.8), to guarantee the QoS of link i (i.e., a nonnegative MSIi), the summation of all the DMSIji over j should be bounded. From the linear constraint, we de ne the amount of resources for link i as the MSImax . The i DMSIji in Eq. (12.8) represents the amount of resources consumed by link j from the perspective of link i, and the MSIi is the amount of available resources at link i. 12.5.2 Slot Selection and Power/Rate Allocation

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with ai = 1/4, i = 1, . . . , 4, so that composite W represented the mean of the four (standardized) variables. The conceptual de nition of composite W is block group size, a natural and straightforward concept. It is unlikely that all block groups have exactly the same size and therefore that, differences in block group size may account for part of the variability in the other variables. We might expect large block groups tending to have large values for all four variables, and small block groups tending to have small values for all four variables. The analyst should seek out support in the research or business literature for the conceptual de nition of the composite. The evidence for the existence and relevance of the user-de ned composite should be clear and convincing. For example, for composite W, the analyst may cite the study from the National Academy of Sciences by Hope et al. [11], which states that block groups in urban areas average 5.3 square kilometers in size, whereas block groups outside urban areas averaged 168 square kilometers in size. Since we may not presume that block groups inside and outside urban areas have exactly similar characteristics, this may mean that block group size could conceivably be associated with differences in block group characteristics, including median housing value, the response variable. Further, the analyst could cite the U.S. Census Bureau s notice in the Federal Register [12] that population density was much lower for block groups whose size was greater than 2 square miles. Hence, block group size may be considered a real and relevant concept to be used in further analysis downstream.

meat industry in the production of cooked sausages and cooked cured meat products. Food Control 14:323 332. Mortimore, S. 2001. How to make HACCP really work in practice. Food Control 12:209 215. Mortimore, S., and C. Wallace. 1997. HACCP: A Practical Approach. London: Chapman & Hall. N rrung, B., and S. Buncic. 2008. Microbial safety of meat in the European Union. Meat Science 78:14 24. Oiye, S. O., and N. M. Muroki. 2002. Use of spices in foods. Journal of Food Technology in Africa 7:33 44. Pan American Health Organization (PAHO). 2008. Strategic Plan 2008 2012. Of cial Document No. 328. A PAHO Planning Series Document. Pearce, R. A., D. J. Bolton, J. J. Sheridan, D. A. McDowell, I. S. Blair, and D. Harrison. 2004. Studies to determine the critical control points in pork slaughter hazard analysis and critical control point systems. International Journal of Food Microbiology 90:331 339. Raken, M. D. 2000. Handbook of Meat Product Technology. Ames, Iowa: Blackwell Science. Raspor, P. 2008. Total food chain safety: How good practices can contribute. Trends in Food Science & Technology 19:405 412. Roy, S. L., A. S. Lopez, and P. M. Schantz. 2003. Trichinellosis surveillance United States 1997 2001. Morbidity and Mortality Weekly Report 52:SS6, 1 12. Scott, B. S., A. E. Wilcock, and V. Kanetkar. 2009. A survey of structured continuous improvement programs in the Canadian food sector. Food Control 20(3):209 217.

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