Radiochemistry-based techniques will be an important complement to x-ray implosion diagnostics. Simulations demonstrate the value of alpha-induced or deuteron-induced reactions as a direct measurement of static mix contamination in DT-filled ignition capsules. In this proceedings we examine to what extent neutron-induced reactions might be highly correlated with the energetically down-scattered neutron fraction which is, in turn, related to the critical quantity of fuel areal density, {rho}R. Although alpha and deuteron reactions are highly suppressed in HT/D-filled capsules, neutron-induced reactions produce robust abundances and 2% measurements of the relevant radiological ratios is achievable. We conclude that radiochemical data are strongly correlated with the down-scattered fraction and fuel areal density. Unknown physics, primarily uncertainties in the direct T-T fusion neutron cross section and, to a lesser extent, various radiochemical production cross sections are important but calibration shots can be used to reduce these errors. The primary advantage of radiochemistry remains - it is the only technique that samples down-scattered neutrons from the entire capsule during the burn. In particular radiochemistry correlated with other diagnostics can be used to minimize experimental uncertainties and thus maximize gain.

We study the universality of the transverse momentum dependent parton distributions at small-x, by comparing the initial/final state interaction effects in dijet-correlation in pA collisions with that in deep inelastic lepton nucleus scattering. We demonstrate the non-universality by an explicit calculation in a particular model where the multiple gauge boson exchange contributions are summed up to all orders. We furthercomment on the implications of our results on the theoretical interpretation of di-hadron correlation in dA collisions in terms of the saturation phenomena in deep inelastic lepton nucleus scattering.

CgWind is a high-fidelity large eddy simulation (LES) tool designed to meet the modeling needs of wind turbine and wind park engineers. This tool combines several advanced computational technologies in order to model accurately the complex and dynamic nature of wind energy applications. The composite grid approach provides high-quality structured grids for the efficient implementation of high-order accurate discretizations of the incompressible Navier-Stokes equations. Composite grids also provide a natural mechanism for modeling bodies in relative motion and complex geometry. Advanced algorithms such as matrix-free multigrid, compact discretizations and approximate factorization will allow CgWind to perform highly resolved calculations efficiently on a wide class of computing resources. Also in development are nonlinear LES subgrid-scale models required to simulate the many interacting scales present in large wind turbine applications. This paper outlines our approach, the current status of CgWind and future development plans.

Despite recent advances in named entity extraction technologies, state-of-the-art extraction tools achieve insufficient accuracy rates for practical use in many operational settings. However, they are not generally prone to the same types of error, suggesting that substantial improvements may be achieved via appropriate combinations of existing tools, provided their behavior can be accurately characterized and quantified. In this paper, we present an inference methodology for the aggregation of named entity extraction technologies that is founded upon a black-box analysis of their respective error processes. This method has been shown to produce statistically significant improvements in extraction relative to standard performance metrics and to mitigate the weak performance of entity extractors operating under suboptimal conditions. Moreover, this approach provides a framework for quantifying uncertainty and has demonstrated the ability to reconstruct the truth when majority voting fails.