We measure the local anisotropy of numerically simulated strong Alfvénic turbulence with respect to two local, physically relevant directions: along the local mean magnetic field and along the local direction of one of the fluctuating Elsasser fields. We find significant scaling anisotropy with respect to both these directions: the fluctuations are "ribbon-like" -statistically, they are elongated along both the mean magnetic field and the fluctuating field. The latter form of anisotropy is due to scale-dependent alignment of the fluctuating fields. The intermittent scalings of the nth-order conditional structure functions in the direction perpendicular to both the local mean field and the fluctuations agree well with the theory of Chandran et al. (2015), while the parallel scalings are consistent with those implied bythe critical-balance conjecture. We quantify the relationship between the perpendicular scalings and those in the fluctuation and parallel directions, and find that the scaling exponent of the perpendicular anisotropy (i.e., of the aspect ratio of the Alfvénic structures in the plane perpendicular to the mean magnetic field) depends on the amplitude of the fluctuations. This is shown to be equivalent to the anticorrelation of fluctuation amplitude and alignment at each scale. The dependence of the anisotropy on amplitude is shown to be more significant for the anisotropy between the perpendicular and fluctuation-direction scales than it is between the perpendicular and parallel scales.

A novel version of Snijders’s stochastic actor-based modeling (SABM) framework is applied to model the diffusion of first alcohol use through middle school-wide longitudinal networks of early adolescents, aged approximately 11–14 years. Models couple a standard SABM for friendship network evolution with a proportional hazard model for first alcohol use. Meta-analysis of individual models for 12 schools found significant effects for friendship selection based on the same alcohol use status, and for an increased rate of onset to first use based on exposure to already-onset peers. Onset rate was greater at higher grades and among participants who spent more unsupervised time with friends. Neither selection nor exposure effects interacted with grade, adult supervision, or gender.

The evolution of a dynamic social network and the diffusion of an innovation are jointly modelled, dependent on one another, by using an extension of a stochastic actor-oriented model developed by Snijders, which is modified so that the adoption times follow a proportional hazards model. The asymptotic behaviour of the method-of-moments estimator is examined. The model is demonstrated on a data set involving the initiation of cannabis smoking among adolescents, and a simulation study is presented.