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To test whether changes in discomfort tolerance were mediated by activation of the endorphin system, half the participants in each condition received 10 mg of naloxone, a drug that inhibits the effect of opiates and, therefore, increases the sensation of pain The other half received 10 mg of a saline solution Results suggested that those who received cognitive training strengthened their self-efficacy to withstand and reduce pain The cognitive training and naloxone group, when compared to the group receiving cognitive training and saline, was less able to tolerate discomfort However, the cognitive group that received the naloxone was still able to increase discomfort tolerance to some degree This suggests a nonopioid component in cognitive pain control (Bandura et al, 1987) In conclusion, self-efficacy can be altered, but its effectiveness is accurately assessed only under task-specific conditions..

In the original paper of Ziv and Lempel [603], the authors described the basic LZ77 algorithm and proved that it compressed any string as well as any nite-state compressor acting on that string However, they did not prove that this algorithm achieved asymptotic optimality (ie, that the compression ratio converged to the entropy for an ergodic source) This result was proved by Wyner and Ziv [591] The proof relies on a simple lemma due to Kac: the average length of time that you need to wait to see a particular symbol is the reciprocal of the probability of a symbol Thus, we are likely to see the high-probability strings within the window and encode these strings ef ciently The strings that we do not nd within the window have low probability, so that asymptotically, they do not in uence the compression achieved.

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Perhaps [this] rationale for learning [behavioral] psychotherapy will also have to include some method for the assessment of behavior. In order to discover the behavioral de ciencies, the required changes in the reinforcing system [the individual s emotional-motivational characteristics], the circumstances in which stimulus control is absent, and so on, evaluational techniques in these respects may have to be devised. Certainly, no two individuals will be alike in these various characteristics, and it may be necessary to determine such facts for the individual prior to beginning the learning program of treatment. Such assessment might take a form similar to some of the psychological tests already in use. . . . [H]owever, . . . a general learning rationale for behavior disorders and treatment will suggest techniques of assessment. (Staats, 1963, pp. 508 509)

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Instead of proving the optimality of the practical version of LZ77, we will present a simpler proof for a different version of the algorithm, which, though not practical, captures some of the basic ideas This algorithm assumes that both the sender and receiver have access to the in nite past of the string, and represents a string of length n by pointing to the last time it occurred in the past We assume that we have a stationary and ergodic process de ned for time from to , and that both the encoder and decoder have access to , X 2 , X 1 , the in nite past of the sequence Then to encode X0 , X1 , , Xn 1 (a block of length n), we nd the last time we have seen these n symbols in the past Let Rn (X0 , X1 , .

protocols in ad hoc and sensor networks Computer Communications (Elsevier), forthcoming Johnson Kuruvila, Amiya Nayak, and Ivan Stojmenovic Hop count optimal position based packet routing algorithms for ad hoc wireless networks with a realistic physical layer In Proceedings of the 1st IEEE International Conference on Mobile Ad-hoc and Sensor Systems (MASS), Fort Lauderdale, Florida, October 2004 Johnson Kuruvila, Amiya Nayak, and Ivan Stojmenovic Greedy localized routing for maximizing probability of delivery in wireless ad hoc networks with a realistic physical layer In CD Proceedings of the 1st International Workshop on AlgorithmS for Wireless And mobile Networks (A-SWAN), Personal, Sensor, Ad-hoc, and Cellular Workshop (at MobiQuitous), Boston, Massachusetts, August 2004 Ivan Stojmenovic, Amiya Nayak, and Johnson Kuruvila Design guidelines for routing protocols in ad hoc and sensor networks with a realistic physical layer IEEE Communications Magazine (Ad Hoc and Sensor Networks Series), 43(3):101 106, March 2005 T Nadeem and A Agrawala.

, Xn 1 ) = max{j < 0 : (X j , X j +1 X j +n 1 ) = (X0 , , Xn 1 )} (1360).

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