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We present a distributed proximal-gradient method for optimizing the average of convex functions, each of which is the private local objective of an agent in a network with time-varying topology. The local objectives have distinct differentiable components, but they share a common nondifferentiable component, which has a favorable structure suitable for(More)
Hsp104, a protein disaggregase from yeast, can be engineered and potentiated to counter TDP-43, FUS, or α-synuclein misfolding and toxicity implicated in neurodegenerative disease. Here, we reveal that extraordinarily disparate mutations potentiate Hsp104. Remarkably, diverse single missense mutations at 20 different positions interspersed throughout the(More)
In chronic infections, pathogens are often in the presence of other microbial species. For example, Pseudomonas aeruginosa is a common and detrimental lung pathogen in individuals with cystic fibrosis (CF) and co-infections with Candida albicans are common. Here, we show that P. aeruginosa biofilm formation and phenazine production were strongly influenced(More)
Memory systems play a key role in the performance of FPGA applications. As FPGA deployments move towards design entry points that are more serial, memory latency has become a serious design consideration. For these applications, memory network optimization is essential in improving performance. In this paper, we examine the automatic, program-optimized(More)
Antimicrobial peptides are an important component of the molecular arsenal employed by hosts against bacteria. Many bacteria in turn possess pathways that provide protection against these compounds. In Escherichia coli and related bacteria, the PhoQ/PhoP signalling system is a key regulator of this antimicrobial peptide defence. Here we show that treating(More)
We study a simulation optimization approach for the online-retail inventory replenishment problem, where the goal is to minimize the total operational cost among a class of parametrized replenishment policies. We model the problem as an infinite-horizon average-cost dynamic program with discrete states and controls, which can be difficult to solve due to(More)
This paper presents several approaches for efficient imaging on the atomic force microscope (AFM) using boundary tracking. In addition to the refinement and generalization of existing algorithms such as those of Andersson [1][2] and Chen [3] , a new multi-point model is proposed. In this model, variables are calculated according to a set of consecutive(More)
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