Social information can be acquired either directly or indirectly from cues inadvertently produced by individuals with similar interests and requirements (''inadvertent social information,'' ISI). These inadvertent cues provide ''public information'' that other individuals can use to guide their behavior. We show here that female mice use olfactory ISI to determine their choice of, and responses to, males and that the use of this ISI involves the gene for oxytocin (OT). Female mice (OT wild type and CF-1 strain) displayed a significant interest in, and choice of, the odors of uninfected males of varying sexual status that were associated with the odors of an another estrous female. This recognition of, and choices for, specific, individual male odors was evident 24 h later. Female mice also distinguished between males subclinically infected with the gastrointestinal nematode parasite, Heligimosomoides polygyrus, and nonparasitized males, displaying aversive responses (analgesia, increased corticosterone) to, and avoidance of, the odors of infected males. The presence of the odors of another estrous female with that of the infected male, which are indicative of potential mate interests, attenuated these aversive responses and resulted in a choice for the odors of infected male. OT genedeficient (knockout) females were impaired in their use of this ISI to modulate their responses to either uninfected males of differing sexual states or infected males. These findings suggest that OT genes are necessary for the processing of inadvertent social information and likely the integration of both direct and indirect social information.
Some properties of the geometric process are studied along with those of a related process which we propose to call the ␣-series process. It is shown that the expected number of counts at an arbitrary time does not exist for the decreasing geometric process. The decreasing version of the ␣-series process does have a finite expected number of counts, under certain conditions. This process also has the same advantages of tractability as the geometric process; it exhibits some properties which may make it a useful complement to the increasing geometric process. In addition, it may be fit to observed data as easily as the geometric process. Applications in reliability and stochastic scheduling are considered in order to demonstrate the versatility of the alternative model.
We consider a stochastic fire growth model, with the aim of predicting the behaviour of large forest fires. Such a model can describe not only average growth, but also the variability of the growth. Implementing such a model in a computing environment allows one to obtain probability contour plots, burn size distributions, and distributions of time to specified events. Such a model also allows the incorporation of a stochastic spotting mechanism.
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