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With relevance to quality assurance in the meat sector, there is a wealth of of cial regulations, guidelines (e.g., the Code of Hygienic Practice for Meat issued by the Codex Alimentarius Commission [2005]), standards (e.g., ISO norms 9001 and 22000), and speci cations developed by industrial and retail organizations as the driving force (e.g., Codes for Good Hygienic Practice, noti ed and registered with the European Commission according to article 8 of Regulation [EC] 852/2004; standards benchmarked by the Global Food Safety Initiative). Most of these documents focus on meat safety and specify, among other things, that the processor must implement and maintain a system of foodsafety assurance. However, the purpose of many regulations and standards is also to protect the consumer from being misled (in particular, by inadequate labeling on weight, composition, shelf life, nutritive value, origin, and production method) and to ensure fair competition. Obviously, it does not make sense that a meat processor installs different systems to assure safety, traceability, compliance with other standards, and sensory quality. Rather, the documents for controlling a given process step should cover all criteria of product quality. For information on the implementation and maintenance of HACCP in meat processing, the reader is referred to of cial documents (e.g., the Generic HACCP models issued by the U.S. Food Safety and Inspection Service [USDA-FSIS 1999a]) or the relevant literature (Brown 2000a, b; Sheridan 2000;

especially informative to current approaches to clinical treatment of infectious disease and cancer, by suggesting that psychosocial interventions can promote lower susceptibility and increased resistance (Andersen, Kiecolt-Glaser, & Glaser, 1994; Glaser, Rabin, Chesney, Cohen, & Natelson, 1999) One of the rst studies used an academic examination paradigm to investigate acute stress, social support, and immune response to hepatitis B vaccination (Glaser, Kiecolt-Glaser, Bonneau, Malarkey, & Hughes, 1992) Although no differences in seroconversion rates were found when comparing subjects on social support, social support was positively associated with the immune response to the vaccine as measured by total antibody titers and T cell responses to the vaccine antigen Similarly, subjects with low social integration (less diverse social roles) were three times more likely to develop clinical symptoms of cold when infected with a cold virus compared to subjects with high social integration (Cohen, Doyle, Skoner, Rabin, & Gwaltney, 1997).

Mataix-Oltra, On movement-based mobility tracking strategy An enhanced version, IEEE Communications Letters, 2, 2, 45 47, 1998 14 EIA/TIA, Cellular Radio-Telecommunications Intersystems Operations (Revision C), Technical Report IS 41, EIA/TIA, 1995 15 G Fan and J Zhang, Virtual cellular networks for non-uniformly distributed base stations, in Proceedings of the 30th Annual International Conference on Parallel Processing, Valencia, Spain, September 2001..

A large number of studies on social support have involved HIV-positive individuals who had not yet progressed to AIDS (asymptomatic) Given the positive bene ts of social support on immune function, perhaps HIV-positive individuals with high social support would show a slower decline in immune competence associated with progression to AIDS Although initial studies indicated negative ndings (Goodkin, Blaney, et al, 1992; Perry, Fishman, Jacobsberg, & Frances, 1992), later studies found increased social participation and decreased loneliness to be associated with higher CD4+ counts (Persson, Gullberg, Hanson, Moestrup, & Ostergren, 1994; Straits-Troester et al, 1994) Moreover, low perceived emotional support was associated with a more rapid decline in CD4+ cells (Theorell et al, 1995) Social Support-Immune Pathways Considerable evidence suggests that social support contributes positively to immune function.

The pathways through which social relationships can in uence immune competence appear to be through primarily stress-buffering effects (Esterling, Kiecolt-Glaser, et al, 1994; Esterling et al, 1996; Goodkin, Blaney, et al, 1992; Kang et al, 1998; Kiecolt-Glaser et al, 1991; Theorell et al, 1990), although ample evidence suggests that immunological regulation is promoted by the mere presence of supportive others (S Cohen et al, 1997; Levy et al, 1990; Linn et al, 1988; Persson et al, 1994; Theorell et al, 1995; Thomas et al, 1985) The magnitude of these effects appears to be small (r 21), as shown in a meta-analysis of the literature up to 1995 (Uchino, Cacioppo, & Kiecolt-Glaser, 1996) However, these effects may have clinical relevance because social.

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AODV and DSR have been well studied for their routing capabilities, but their energy characteristics had not been studied until now. Both protocols are deemed on-demand protocols since they discover and maintain routes only when needed. All network nodes participate equally in the routing process. These two protocols differ in that AODV is destination-oriented, based on the Bellman Ford algorithm, and uses distance vector routing information. DSR is a topology-oriented source routing protocol that uses aggressive caching of network-wide topology information. More details on how these protocols work can be found in the respective references listed earlier. Energy Cost Equations Feeney [7] presents the energy calculations for various routing operations. In general, there is a fixed channel-acquisition cost and an incremental cost proportional to the size of the packet: cost = m size + b where m denotes the packet size multiplicative factor and b the fixed channel acquisition cost. The fixed cost relates to acquiring the channel, for example, as part of the medium access control procedure. The variable cost depends on the packet size, distance, receiver sensitivity, and so on. The total cost is the sum of all the costs incurred by the source and destination nodes. Traffic is classified as broadcast traffic and point-to-point. For broadcast traffic, the sender listens briefly to the channel and sends data if the channel is clear. If the channel is not clear, the sender waits and retries later. Fixed channel-access costs and incremental payload costs combined in the previous equation result in a new cost equation: cost = msend size + bsend + (mrecv size + brecv)