On a Moving Boundary Problem of Transitional Ballistics

A major problem which arises in computer simulation of the firing of a gun weapon is the development of numerical schemes which effectively account for the physics of projectile motion. The chief difficulty is that away from the projectile the calculation is ordinarily accomplished on a fixed numerical grid, whereas due to projectile movement some cells of the grid near the projectile undergo volume changes as the calculation proceeds. A local finite volume scheme is developed which accounts for the expansion or compression of cells fore-and-aft of the projectile. Through the process of numerical experiment, the effectiveness of the scheme is assessed, with quite good results. The rapid discharge of propellant gas from a gun weapon produces a strong shock wave which propagates into the environment, while other interacting shocks form within the developing plume. For this reason, strong interest in the determination of shock capturing algorithms which can be used away from the projectile arises. In this respect, a theoretical weak derivative form (WDF) is derived for linear hyperbolic systems of conservation laws. The virtue of the WDF approach is that it indicates how to difference in the presence of a flow discontinuity, without differencing across the discontinuity. This differencing produces a robust shock capturing scheme whose extension to the nonlinear case is apparent. The WDF shock capturing scheme so obtained is shown to be equivalent to a flux-splitting scheme studied by P. L. Roe, thus leading to a better understanding of the schemes of Godunov and Roe, as well as upwind differencing in general. Roe\u27s scheme is investigated in detail. Three views of the scheme are obtained, one of which is new. Harten\u27s second-order accurate extension of Roe\u27s method is then used in simulating the flow around a typical weapon\u27s configuration. These numerical results reinforce the belief that the local finite volume scheme effectively accounts for projectile motion

Modeling Between-Study Heterogeneity for Improved Replicability in Gene Signature Selection and Clinical Prediction

In the genomic era, the identification of gene signatures associated with disease is of significant interest. Such signatures are often used to predict clinical outcomes in new patients and aid clinical decision-making. However, recent studies have shown that gene signatures are often not replicable. This occurrence has practical implications regarding the generalizability and clinical applicability of such signatures. To improve replicability, we introduce a novel approach to select gene signatures from multiple datasets whose effects are consistently non-zero and account for between-study heterogeneity. We build our model upon some rank-based quantities, facilitating integration over different genomic datasets. A high dimensional penalized Generalized Linear Mixed Model (pGLMM) is used to select gene signatures and address data heterogeneity. We compare our method to some commonly used strategies that select gene signatures ignoring between-study heterogeneity. We provide asymptotic results justifying the performance of our method and demonstrate its advantage in the presence of heterogeneity through thorough simulation studies. Lastly, we motivate our method through a case study subtyping pancreatic cancer patients from four gene expression studies

Humans and Technology: Forms of Conjoined Agency in Organizations

Organizations are increasingly deploying technologies that have the ability to parse through large amounts of data, acquire skills and knowledge, and operate autonomously. These technologies diverge from prior technologies in their capacity to exercise intentionality over protocol development or action selection in the practice of organizational routines, thereby affecting organizations in new and distinct ways. In this article, we categorize four forms of conjoined agency between humans and technologies: (1) conjoined agency with assisting technologies, (2) conjoined agency with arresting technologies, (3) conjoined agency with augmenting technologies, and (4) conjoined agency with automating technologies. We then theorize on the different ways in which these forms of conjoined agency impact a routine’s change at a particular moment in time as well as a routine’s responsiveness to feedback over time. In doing so, we elaborate on how organizations may evolve in varied and diverse ways based on the form(s) of conjoined agency they deploy in their organizational design choices