T. Nguyen — Page 2 | Searcharxiv

arXiv2013

Confidence-constrained joint sparsity recovery under the Poisson noise model

Our work is focused on the joint sparsity recovery problem where the common sparsity pattern is corrupted by Poisson noise. We formulate the confidence-constrained optimization problem in both least squares (LS) and maximum likelihood (ML) frameworks and study the conditions for perfect reconstruction of the original row sparsity and row sparsity pattern. However, the confidence-constrained optimization problem is non-convex. Using convex relaxation, an alternative convex reformulation of the problem is proposed. We evaluate the performance of the proposed approach using simulation results on synthetic data and show the effectiveness of proposed row sparsity and row sparsity pattern recovery framework.

stat.ML↗

arXiv2009

Non-perturbative QCD Modeling and Meson Physics

Using a ladder-rainbow kernel previously established for light quark hadron physics, we explore the extension to masses and electroweak decay constants of ground state pseudoscalar and vector quarkonia and heavy-light mesons in the c- and b-quark regions. We make a systematic study of the effectiveness of a constituent mass concept as a replacement for a heavy quark dressed propagator for such states. The difference between vector and axial vector current correlators is explored within the same model to provide an estimate of the four quark chiral condensate and the leading distance scale for the onset of non-perturbative phenomena in QCD.

nucl-th↗

arXiv2007

Cell-to-Cell stochastic fluctuations in apoptotic signaling can decide between life and death

Apoptosis, or genetically programmed cell death, is a crucial cellular process that maintains the balance between life and death in cells. The precise molecular mechanism of apoptosis signaling and how these two pathways are differentially activated under distinct apoptotic stimuli is poorly understood. We developed a Monte Carlo-based stochastic simulation model that can characterize distinct signaling behaviors in the two major pathways of apoptotic signaling using a novel probability distribution-based approach. Specifically, we show that for a weak death signal, such as low levels of death ligand Fas (CD95) binding or under stress conditions, the type 2 mitochondrial pathway dominates apoptotic signaling. Our results also show signaling in the type 2 pathway is stochastic, where the population average over many cells does not capture the cell-to-cell fluctuations in the time course (~1 - 10 hours) of downstream caspase-3 activation. On the contrary, the probability distribution of caspase-3 activation for the mitochondrial pathway shows a distinct bimodal behavior that can be used to characterize the stochastic signaling in type 2 apoptosis. Interestingly, such stochastic fluctuations in apoptosis signaling happen even in the presence of large numbers of signaling molecules. In a fluctuating environment, such stochasticity in the timecourse of caspase-3 activation may be an adaptive mechanism for allowing a competing survival signal to win over a weak death trigger before the critical cell fate decision is made and thus minimizes the risk of pathologies.

q-bio.MN↗