Drop Generation Using Cross-Flow in Rigid Body Rotation

Inspired by crossflow membrane droplet generation and microfluidic droplet generation, I propose an easy method to generate monodisperse drops using cross-flow caused by rigid body rotation. In this approach, a dispersed phase (DP) liquid was injected through a stationary vertical needle into an immiscible continuous phase (CP) liquid which was in rigid body rotation. A DP drop growing at the end of the needle experienced fluid dynamic forces from the horizontal CP flow, and it was detached from the needle when it had grown to a certain size. This study investigated the relationship between the resultant size of drops and the controllable experimental factors including the flow velocity of the CP at the needle end and the flow rate of the DP through the needle. Advisor: Sangjin Ry

Strong CMB Constraint On P-Wave Annihilating Dark Matter

We consider a dark sector consisting of dark matter that is a Dirac fermion and a scalar mediator. This model has been extensively studied in the past. If the scalar couples to the dark matter in a parity conserving manner then dark matter annihilation to two mediators is dominated by the P-wave channel and hence is suppressed at very low momentum. The indirect detection constraint from the anisotropy of the Cosmic Microwave Background is usually thought to be absent in the model because of this suppression. In this letter we show that dark matter annihilation to bound states occurs through the S-wave and hence there is a constraint on the parameter space of the model from the Cosmic Microwave Background.Comment: 5 pages, 3 figure

Robust regularized singular value decomposition with application to mortality data

We develop a robust regularized singular value decomposition (RobRSVD) method for analyzing two-way functional data. The research is motivated by the application of modeling human mortality as a smooth two-way function of age group and year. The RobRSVD is formulated as a penalized loss minimization problem where a robust loss function is used to measure the reconstruction error of a low-rank matrix approximation of the data, and an appropriately defined two-way roughness penalty function is used to ensure smoothness along each of the two functional domains. By viewing the minimization problem as two conditional regularized robust regressions, we develop a fast iterative reweighted least squares algorithm to implement the method. Our implementation naturally incorporates missing values. Furthermore, our formulation allows rigorous derivation of leave-one-row/column-out cross-validation and generalized cross-validation criteria, which enable computationally efficient data-driven penalty parameter selection. The advantages of the new robust method over nonrobust ones are shown via extensive simulation studies and the mortality rate application.Comment: Published in at http://dx.doi.org/10.1214/13-AOAS649 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Right-Handed Quark Mixings in Minimal Left-Right Symmetric Model with General CP Violation

We present a systematic approach to solve analytically for the right-handed quark mixings in the minimal left-right symmetric model which generally has both explicit and spontaneous CP violations. The leading-order result has the same hierarchical structure as the left-handed CKM mixing, but with additional CP phases originating from a spontaneous CP-violating phase in the Higgs vev. We explore the phenomenology entailed by the new right-handed mixing matrix, particularly the bounds on the mass of $W_R$ and the CP phase of the Higgs vev.Comment: 8 pages, one postscript figure include