Browsing by Author "Xu, Boyang"
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Item Modeling and simulations of wave-ice interactions(University of Delaware, 2022) Xu, BoyangThe problem of wave-ice interactions in the marginal ice zone is investigated. Two principal mechanisms: scattering by ice floes and dissipative processes, may cause the wave spectrum attenuation. These two mechanisms are studied both theoretically and numerically. ☐ First, a two-layer poroelastic model for linear gravity waves propagating in ice-covered seas is considered. Numerical solutions of the corresponding dispersion relation are obtained. Extensive tests against both laboratory experiments and field observations are performed to assess this model's ability at describing wave attenuation in various types of sea ice. A detailed comparison with other existing viscoelastic theories is also presented. For this poroelastic system, the range of estimated rheological parameters, such as shear modulus and kinematic viscosity, turns out to be relatively narrow in orders of magnitude over all the cases considered. Instead of monotonically increasing with frequencies, the measured apparent attenuation rate from the Arctic Ocean peaks at an intermediate frequency. This model is able to reasonably reproduce the "roll-over" of attenuation rate as a function of frequency. ☐ Second, phase-resolved numerical simulations are performed to investigate the scattering process from a nonlinear and time-dependent viewpoint. Spatial distributions of ice floes can be directly specified in the numerical model. Various wave regimes and floe configurations are considered in the absence of dissipative effects. The attenuation rate is obtained by computing the wave spectrum and least-squares fitting for each set of parameter values. Comparison with field data suggests that our numerical results can also capture the roll-over effect. Nonlinear interactions are shown to play an important role in the roll-over development.Item Traditional social learning predicts cyber deviance? Exploring the offending versatility thesis in social learning theory(Behavioral Sciences & the Law, 2024-05-20) Zhou, You; Liu, Weidi; Lee, Claire; Xu, Boyang; Sun, IvanSocial learning theory has been widely implemented to understand cyber deviance. Nevertheless, the antecedent scholarship homogenously nested in the perspective of offending specification, leaving the offending versatility thesis unattained. The lack of such studies may undermine the capability of comprehensively understanding the social learning patterns of online offending. Using a sample of 3741 Chinese college students, this study estimated an array of binary logistic regressions to compare the effects of traditional and online social learning in four types of online offending (online sexual harassment, cyberbullying, hacking, and digital piracy). The results suggest that offending versatility and offending specification co-exist in the social learning process of cyber deviance, while offending specification explains a marginally greater variance. Besides, online learning variables act as potential mediators in the relationships between traditional learning and cyber deviance. Furthermore, traditional social learning shows greater predictive power in cyber-enabled crimes than in cyber-dependent crimes. Our study provides fresh empirical evidence for the non-exclusive association between offending versatility and offending specification in the social learning process of cyber deviance.