Why do some individuals pick up arms as opposed to others who live under the same conditions? Environmental and group theories fail to differentiate between these individuals. In response, we apply the cognitive mapping approach and model violence as decisions based on chains of beliefs about various types of factors, including state aggression, access to violent groups, religion, and personal characteristics. Based on a double-paired comparison, data are constructed from ethnographic interviews with Muslim and non-Muslim individuals engaging in violent and nonviolent activity in authoritarian and democratic states—Egypt and Germany. The analysis develops a computational model formalizing the cognitive maps into Bayesian networks. In 477,604 runs, the model (1) identifies the beliefs connected to decisions, (2) traces inference chains antecedent to decisions, and (3) explores counterfactuals. This suggests that both violent and nonviolent activities are responses to state aggression, and not to Islam, group access, or personal characteristics.

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Geant4 is a large-scale particle physics package that facilitates every aspect of particle transport simulation. This includes, but is not limited to, geometry description, material definition, tracking of particles passing through and interacting with matter, storage of event data, and visualization. As more detailed and complex simulations are required in different application domains, there is much interest in adapting the code for parallel and multi-core architectures. Parallelism can be achieved by tracking many particles at the same time. The complexity in the context of a GPU/CUDA adaptation is the highly serialized nature of the Geant4 package and the presence of large lookup tables that guide the simulation. This work presents G4CU, a CUDA implementation of the core Geant4 algorithm adapted for dose calculations in radiation therapy. For these applications the geometry is a block of voxels and the physics is limited to low energy electromagnetic physics. These features allow efficient tracking of many particles in parallel on the GPU. Experiments with radiotherapy simulations in G4CU demonstrate about 40 times speedups over Geant4.

Much research examines the state-dissident nexus by large-n studies and rational choice theories. This article contributes an analysis of dissident reasoning through a computational evaluation of ethnographic interviews. The analysis shows that dissident decision-making is based on tit-for-tat deliberations: Dissidents choose violent means primarily in response to violent repression, and nonviolent means in response to nonviolent repression. Ordinary citizens not participating in dissent consider positive state behavior or safety concerns instead. Consistent with arguments that state-dissident interactions are reciprocal, these findings reveal unexpected cognitive similarities between political dissent and cooperation, which is often associated with tit-for-tat deliberations. They also show the importance of state repression compared with other motivators of dissent, including perceived relative deprivation and social contagion. The findings identify heuristic patterns of reasoning which suggest that dissidents may be more open to change and, ultimately, cooperation with state authorities than what is argued by repressive states.

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