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Recent data has indirectly shown that the process of apoptosis may play a role in postmortem proteolysis and meat tenderization (Herrera-Mendez et al. 2006; Ouali et al. 2006). In living organisms, apoptosis, or programmed cell death, is a complex mechanism by which cells can be eliminated without damaging surrounding cells (Kerr et al. 1972; Fidzianska et al. 1991). Apoptosis is initiated and regulated by either the target cell or the central nervous system, and is mediated by the caspase enzyme system. As a result of the slaughter process, the muscle tissue will be deprived of oxygen and nutrients due to the loss of the blood supply. The hypothesis is that under these anoxic conditions, the muscle cells will have no alternative but to initiate apoptosis, which through the caspase system would induce a series of biochemical and structural changes important in the tenderization process. Thus, the traditional model of the conversion of muscle to meat would include a phase corresponding to the initiation of cell death in addition to the phases of rigor mortis development and aging tenderization (Ouali et al. 2006). The apoptotic process would then occur until muscle conditions (pH, ionic strength, energy availability) would be unfavorable for enzyme activity (Ouali et al. 2006). Direct evidence to support this emerging hypothesis is still lacking, however.

1 A Mainwaring, J Polastre, R Szewczyk, D Culler, and J Anderson Wireless sensor networks for habitat monitoring In Proceedings of the 1st ACM International Workshop on Wireless Sensor Networks and Applications (WSNA 02), Atlanta, Georgia, September 2002 2 F Zhao, J Shin, and J Reich, Information-driven dynamic sensor collaboration for tracking applications, IEEE Signal Processing Magazine, 19:68 77, March 2002 3 S S Intille Designing a home of the future IEEE Pervasive Computing, 1(2):80 81, April June 2002 4 I A Essa Ubiquitous sensing for smart and aware environments IEEE Personal Communications, 7(5):47 49, October 2000 5 P Bonnet, J Gehrke, and P Seshadri Querying the physical world IEEE Personal Communications, 7:10 15, October 2000 6 D Estrin, R Govindan, J Heidemann, and S Kumar Next century challenges: Scalable coordination in sensor networks.

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3, we will show how graph labelings can be useful in finding algorithms for channel assignment problems with demands greater than 1 We will now proceed with a formal definition of the model described, and a review of other relevant models 511 Graph Models The definitions and notations used in this chapter are consistent with those introduced in the previous chapter [28] For a general background on graph theory, the reader is referred to [8] A constrained graph G = (V, E, c0, , ck) is a graph G = (V, E) and positive integer parameters c0, , ck, c0 c1 ck called its constraints The constraints represent the prescribed channel spacing for pairs of channels assigned to the same node or to different nodes More precisely, ci represents the constraint between nodes at graph distance i from each other.

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In Proceedings of the 5th Annual International Conference on Mobile Computing and Networks (MobiCom 99), August 1999 7 D Estrin, L Girod, G Pottie, and M Srivastava Instrumenting the world with wireless sensor networks In Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP), Salt Lake City, Utah, May 2001 8 B Krishnamachari, D Estrin, and S Wicker Modelling data-centric routing in wireless sensor networks In Proceedings of INFOCOM 2002, New York, June 2002 9 S Madden, M J Franklin, and J M Hellerstein, and W Hong The design of an acquisitional query processor for sensor networks In Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data, pages 491 502, San Diego, California, June 2003 10 X Li, Y J Kim, R Govindan, and W Hong Multi-dimensional range queries in sensor networks.

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