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American social science, including what was to take form as social psychology, stepped onto a platform built of a sturdy scienti c rationality and a curiously optimistic anticipation of scienti cally guided social control As J W Sprowls re ected in 1930, American politics, philanthropy, industry, jurisprudence, education, and religion have demanded a science of control and prediction of human behavior, not required by similar but less dynamic institutional counterparts in other countries (p 380) The new understandings of human nature as complex, amoral, and not entirely rational, however, could have yielded other intellectual renderings Many European scholars constructed quite different theories, self-consciously re ecting upon the complexities of the unconscious and the implications of nonlinear causality and refusing to set aside two challenging but fundamental manifestations of human sociality: language and culture They.

Staub (1974) found that an aggregate dispositional measure, a prosocial orientation index (combining measures of feelings of personal responsibility, social responsibility, moral reasoning, prosocial values, and a low level of Machiavellianism), was a reasonably good predictor of helping across several different measures Rushton (1980) reanalyzed previous research (notably, the classic studies by Hartshorne and May in the late 1920s) by computing aggregate measures of prosocial behavior and found far better evidence of cross-situation consistency than had analyses based on individual measures Other researchers pointed to the greater predictive potential of dispositional factors for the higher cost, nonspontaneous, longer term helping that occurs in the natural stream of behavior outside the psychological laboratory For example, Oliner and Oliner (1988) conducted a major study using interviews and questionnaires to identify predictors of acting to rescue Jews in Nazi Europe.

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Independent of the physical-layer model being used (eg, the combined Friis and two-ray ground model used in ref [45] or the log normal shadowing model used in ref [41], protocols dealing with physical-layer impact require nodes to estimate the probability of receiving a bit or a packet based on either signal strength, distance between nodes, or merely by deriving statistics from a number of bits or packets recently sent between two nodes The basic property of each of realistic physical modeling is a rapidly decreasing packet reception probability For example, in the shadowing model used in ref [41], the packet reception probability p(x) depends on the probability of receiving a bit successfully, the length of the packet, and the distance x between two nodes Suppose R can be determined in that way, so that the packet error rate at distance R is 05.

Then the function p(x) may have approximately the following values: p(0) 1, p(0:1R) % 1, p(0:5R) % 0:9, p(R) 0:5, p(1:5R) % 0:25, and p(2R) 0 The given values are only an illustration, but give a suf cient intuition on how to design physical layer aware routing schemes Kuruvila et al [42,43] described geographic routing schemes that are amenable to any realistic physical-layer model (which follows the basic properties of the wireless medium) and consider two basic medium access-layer approaches, with xed and variable packet lengths, while cases both with and without acknowledgments are being considered The described methods assume that all nodes use the same transmission power for sending messages, and, in most cases, optimize the expected (packet or bit) hop count on a route.

They claimed evidence for the predictive power of three dispositional factors: (a) a proclivity to feel empathy for those in need, (b) sensitivity to normative pressure from social groups, and (c) adherence to inclusive, universal moral principles such as justice or care Presumably, better prediction is possible outside the laboratory because the more re ective decision process involved in planned (nonspontaneous) helping permits more chance for personal values, attitudes, and dispositions to come into play Still other researchers argued that it was an oversimpli cation to expect a personality variable to relate to helping in all situations Many pointed to the greater success of predicting prosocial behavior using disposition-situation interactions (eg, Romer, Gruder, & Lizzardo, 1986) For example, self-con dence and independence seem to correlate with helping in emergency situations, especially dangerous ones, but not in response to a request to contribute to the United Way (Wilson, 1976).

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