10,164 research outputs found

    How Real Are Future Events?

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    My main aim in this talk is to discuss McTaggart’s argument for the unreality of time. I will ?nd a ?aw in his argument, but ?nding the ?aw will lead us to the conclusion that although time is real, future events are not. I will begin, however, not with McTaggart, but with a version of an ancient argument for fatalism. By fatalism I do not mean the doctrine that we are fated, like Oedipus, to do something terrible at some point in the future, no matter what choices we make now, and no matter what happens in between. I mean the philosophical doctrine that we can do nothing at all to e?ect the future in any way. For most of us this will mean we are not only fated, in the ?rst sense, to do terrible things, although perhaps not as terrible as Oedipus was fated to do, but that that even the route to these terrible deeds is not in our power to alter. I adopt as a working principle that we are entitled to the distinctions we need to avoid fatalism. I will see what these are, and then maintain that they show us the way to avoid McTaggart’s argument, and that, in doing that, we will see that although there is no reason to agree with McTaggart that time is unreal, the future is, in fairly clear sense, not real

    A Declaration of the Independence of Cyberspace

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    Reusable rocket engine turbopump health monitoring system, part 3

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    Degradation mechanisms and sensor identification/selection resulted in a list of degradation modes and a list of sensors that are utilized in the diagnosis of these degradation modes. The sensor list is divided into primary and secondary indicators of the corresponding degradation modes. The signal conditioning requirements are discussed, describing the methods of producing the Space Shuttle Main Engine (SSME) post-hot-fire test data to be utilized by the Health Monitoring System. Development of the diagnostic logic and algorithms is also presented. The knowledge engineering approach, as utilized, includes the knowledge acquisition effort, characterization of the expert's problem solving strategy, conceptually defining the form of the applicable knowledge base, and rule base, and identifying an appropriate inferencing mechanism for the problem domain. The resulting logic flow graphs detail the diagnosis/prognosis procedure as followed by the experts. The nature and content of required support data and databases is also presented. The distinction between deep and shallow types of knowledge is identified. Computer coding of the Health Monitoring System is shown to follow the logical inferencing of the logic flow graphs/algorithms

    Perceptions of coach-athlete relationship are more important to coaches than athletes in predicting dyadic coping and stress appraisals: An actor-partner independence mediation model

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    Most attempts to manage stress involve at least one other person, yet coping studies in sport tend to report an athlete’s individual coping strategies. There is a limited understanding of coping involving other people, particularly within sport, despite athletes potentially spending a lot of time with other people, such as their coach. Guided by the systemic-transactional model of stress and coping among couples (Bodenmann, 1995), from relationship psychology, we assessed dyadic coping, perceptions of relationship quality, and primary stress appraisals of challenge and threat among 158 coach–athlete dyads (n D 277 participants). The athletes competed at amateur (n D 123), semiprofessional (n D 31), or professional levels (n D 4). Coaches and athletes from the same dyad completed a measure of dyadic coping, coach–athlete relationship, and stress appraisals. We tested an Actor–Partner Interdependence Mediation Model to account for the non-independence of dyadic data. These actor–partner analyses revealed differences between athletes and coaches. Although the actor effects were relatively large compared to partner effects, perceptions of relationship quality demonstrated little impact on athletes. The mediating role of relationship quality was broadly as important as dyadic coping for coaches. These findings provide an insight in to how coach–athlete dyads interact to manage stress and indicate that relationship quality is of particular importance for coaches, but less important for athletes. In order to improve perceptions of relationship quality among coaches and athletes, interventions could be developed to foster positive dyadic coping among both coaches and athletes, which may also impact upon stress appraisals of challenge and threat
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