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Barkate, M L, G R Acuff, L M Lucia, and D S Hale 1993 Hot water decontamination of beef carcasses for reduction of initial bacterial numbers Meat Science 35(3):397 401 Barkocy-Gallagher, G A, T M Arthur, M RiveraBetancourt, X Nou, S D Shackelford, T L Wheeler, and M Koohmaraie 2003 Seasonal prevalence of shiga toxin-producing Escherichia coli, including O157:h7 and non-O157 serotypes, and salmonella in commercial beef processing plants Journal of Food Protection 66(11):1978 1986 Bauermeister, L J, J W J Bowers, J C Townsend, and S R McKee 2008 Validating the ef cacy of peracetic acid mixture as an antimicrobial in poultry chillers Journal of Food Protection 71(6):1119 1122 Bell, M F, R T Marshall, and M E Anderson 1986 Microbiological and sensory tests of beef treated with acetic and formic acids Journal of Food Protection 49(3):207 210 Bell, R G 1997.

Distribution and sources of microbial contamination on beef carcasses Journal of Applied Microbiology 82(3):292 300 Berry, E D, and C N Cutter 2000 Effects of acid adaptation of Escherichia coli O157:H7 on ef cacy of acetic acid spray washes to decontaminate beef carcass tissue Applied and Environmental Microbiology 66(4):1493 1498 Biss, M E, and S C Hathaway 1995 Microbiological and visible contamination of lamb carcasses according to preslaughter presentation status: Implications for HACCP Journal of Food Protection 58(7):776 783 Bolton, D J, A M Doherty, and J J Sheridan 2001 Beef HACCP: intervention and non intervention systems International Journal of Food Microbiology 66:119 129 Bolton, D J, R A Pearce, J J Sheridan, I S Blair, D A McDowell, and D Harrington 2002 Washing and chilling as critical control points in pork slaughter hazard analysis and critical control point (HACCP) systems.

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For example, compare the frequency amplitude plots of FP1 and FP2 in Figure 106 However, it is clear that this is not the case for patient 2 It can be thus concluded that strong similarities in the range 0 to 13 Hz (particularly in channel FP1 and FP2) indicate that the patient will not succumb to brain death 10541 EEG Phase Analysis using EMD It is clear that if similarities exist between speci c frequency ranges (8 to 13 Hz) among different EEG channels (FP1 and FP2), then this is an indication that the patient will not succumb to brain death For this reason, it is proposed to extract relevant channel features using EMD and to compare these features using complex extensions of the algorithm.

Journal of Applied Microbiology 92(5):893 902 Bosilevac, J M, T M Arthur, T L Wheeler, S D Shackelford, M Rossman, J O Reagan, and M Koohmaraie 2004a Prevalence of Escherichia coli O157 and levels of aerobic bacteria and Enterobacteriaceae are reduced when hides are washed and treated with cetylpyridinium chloride at a commercial beef processing plant Journal of Food Protection 67(4):646 650 Bosilevac, J M, T L Wheeler, M Rivera-Betancourt, X Nou, T M Arthur, S D Shackelford, M P Kent, D Jaroni, M S Osborn, M Rossman, J O Reagan, and M Koohmaraie 2004b Protocol for evaluating the ef cacy of cetylpyridinium chloride as a beef hide intervention Journal of Food Protection 67(2):303 309 Bosilevac, J M, X Nou, G A Barkocy-Gallagher, T M Arthur, and M Koohmaraie 2006 Treatments using hot water instead of lactic acid reduce levels of aerobic bacteria and Enterobacteriaceae and reduce.

1 2

Easterbrook, J. A., 292 Eaves, L., 312, 313 Eaves, L. J., 63, 72, 76 Ebert, M. H., 104 Ebmeier, K. P., 89 Ebstein, R. P., 77, 78, 93, 101 Edelbroek, P., 96 Edelman, R. J., 342 Edelstein, W., 540 Edleson, J. L., 576 Edwards, A. L., 180, 335 Edwards, C., 38 Edwards, C. P., 36 Edwards, J. A., 273 Edwards, K., 173, 276, 353, 354, 493, 494 495 Eelen, P., 362 Efran, M. G., 391 Egan, S. K., 577 Egeland, B., 576 Eggert, M., 78 Eich, E., 292 Eisenberg, N., 465, 471, 474, 476 Eisenberger, R., 393, 394 Ekelund, J., 101 Ekman, P., 46, 190, 193, 286, 288 Ekstrom, R. D., 96 Eldredge, N., 7 Eley, T., 72, 73 Elkashef, A., 95 Elkin, R. A., 354, 367, 368 Ellemers, N., 485, 496, 526, 529 Ellenberger, H., 119 Elliot, A. J., 341, 354, 367, 517 Elliot, F. A., 103 Elliot, S. J., 426 Elliott, E. S., 186 Ellis, A., 176, 177 Ellis, A. L., 401 Ellsworth, P., 394, 456 Ellsworth, P. C., 276, 293 Elmore-Yalch, R., 360 Elms, A. C., 366 Elsass, P., 579 Elster, J., 543, 548, 554, 559 Elwood, P. C., 104 Ely, R. J., 410 Ember, C. R., 571 Ember, M., 571 Emde, R. N., 118, 124, 129 Emdl, W., 130 Emel, J., 426 Emmons, R. A., 124, 180, 186, 334 Emswiller, T., 392 Engelstad, F., 548 Engestroem, Y., 44 Engle, R. W., 362 English, E., 345 Enloe, C., 577 Ennis, R., 307 Enrenreich, B., 345 Epstein, A., 178 179 Epstein, S., 129, 159, 160, 161, 162, 166, 167, 169, 170, 171, 172, 173, 174, 175, 176, 177, 181, 199, 560 Erber, R., 339 Erdelyi, M. H., 120, 126, 129, 266

The EEG data from channel FP1 and FP2 for each patient were decomposed into their IMFs and their instantaneous amplitude and frequencies were calculated Features within the desired frequency range were retained by [17], fusing instantaneous amplitudes that corresponded to instantaneous frequencies within 8 to 13 Hz All other.

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