1.2 Machine failure A system is composed of 5 components, each of which is either working or broken. Consider an experiment that consists of observing the status of each component, and let the outcome of the experiment be given by the vector (x1, x2, x3, x4, x5), where xi = 1 if component i works and 0 if component i is broken. 1. How many outcomes are in the sample space of this experiment? 2....

Neoplastic transformation is a complex process that results from multiple changes in gene activities. Probably most of these are mutational, i.e. alterations in the genomic structure of DNA, but others may be due to adaptive changes wherein genes are expressed that are inappropriate to a stage of development or differentiation. In this commentary neoplastic development is discussed in the conte...

The performance of the domain based local pair-natural orbital coupled-cluster (DLPNO-CCSD(T)) method has been tested to reproduce the experimental gas phase ligand dissociation enthalpy in a series of Cu(+), Ag(+), and Au(+) complexes. For 33 Cu(+)-noncovalent ligand dissociation enthalpies, all-electron calculations with the same method result in MUE below 2.2 kcal/mol, although a MSE of 1.4 ...

Antitumor activities have been described in selol, a hydrophobic mixture of molecules containing selenium in their structure, and also in maghemite magnetic nanoparticles (MNPs). Both selol and MNPs were co-encapsulated within poly(lactic-co-glycolic acid) (PLGA) nanocapsules for therapeutic purposes. The PLGA-nanocapsules loaded with MNPs and selol were labeled MSE-NC and characterized by tran...

PURPOSE Regularizing parallel magnetic resonance imaging (MRI) reconstruction significantly improves image quality but requires tuning parameter selection. We propose a Monte Carlo method for automatic parameter selection based on Stein's unbiased risk estimate that minimizes the multichannel k-space mean squared error (MSE). We automatically tune parameters for image reconstruction methods tha...

In this paper, new classes of lower bounds on the outage error probability and on the mean-square-error (MSE) in Bayesian parameter estimation are proposed. The minima of the h-outage error probability and the MSE are obtained by the generalized maximum a-posteriori probability and the minimum MSE (MMSE) estimators, respectively. However, computation of these estimators and their corresponding ...

Purpose: Regularizing parallel magnetic resonance imaging (MRI) reconstruction significantly improves image quality but requires tuning parameter selection. We propose a Monte Carlo method for automatic parameter selection based on Stein’s unbiased risk estimate that minimizes the multichannel k-space mean squared error (MSE). We automatically tune parameters for image reconstruction methods th...