• Citations Per Year
Learn More
Many real applications can be formulated as nonlinear minimization problems with a single linear equality constraint and box constraints. We are interested in solving problems where the number of variables is so huge that basic operations, such as the updating of the gradient or the evaluation of the objective function, are very time consuming. Thus, for(More)
Post-transcriptional gene regulation is a fundamental step for coordinating cellular response in a variety of processes. RNA-binding proteins (RBPs) and microRNAs (miRNAs) are the most important factors responsible for this regulation. Here we report that different components of the miR-200 family are involved in c-Jun mRNA regulation with the opposite(More)
In the array of water Cherenkov detectors of the Pierre Auger Observatory, 4800 large photomultiplier tubes (PMTs) will be used. Before being deployed, each PMT is evaluated to check that various parameters, such as the linearity, dark noise, and gain, fall within a specified range. The large scale test system, designed and constructed for this purpose, is(More)
In this paper we consider the problem of minimizing a nonlinear function using partial derivative knowledge. Namely, the objective function is such that its derivatives with respect to a pre-specified block of variables cannot be computed. To solve the problem we propose a block decomposition method that takes advantage of both derivative-free and(More)
  • 1