We study the problem of selecting a subset of k random variables to observe that will yield the best linear prediction of another variable of interest, given the pairwise correlations between the observation variables and the predictor variable. Under approximation preserving reductions, this problem is also equivalent to the "sparse approximation" problem of approximating signals concisely.We propose and analyze exact and approximation algorithms for several special cases of practical interest. We give an FPTAS when the covariance matrix has constant bandwidth, and exact algorithms when the associated covariance graph, consisting of edges for pairs of variables with non-zero correlation, forms a tree or has a large (known) independent set. Furthermore, we give an exact algorithm when the variables can be embedded into a line such that the covariance decreases exponentially in the distance, and a constant-factor approximation when the variables have no "conditional suppressor variables".Much of our reasoning is based on perturbation results for the R 2 multiple correlation measure, frequently used as a measure for "goodness-of-fit statistics". It lies at the core of our FPTAS, and also allows us to extend exact algorithms to approximation algorithms when the matrix "nearly" falls into one of the above classes. We also use perturbation analysis to prove approximation guarantees for the widely used "Forward Regression" heuristic when the observation variables are nearly independent.

Rare-earth activated upconversion nanoparticles (UCNPs) are receiving renewed attention for use in bioimaging due to their exceptional photostability and low cytotoxicity. Often, these nanoparticles are attached to plasmonic nanostructures to enhance their photoluminescence (PL) emission. However, current wet-chemistry techniques suffer from large inhomogeneity and thus low enhancement is achieved. In this paper, we report lithographically fabricated metal-insulator-metal (MIM) nanostructures that show over 1000-fold enhancement of their PL. We demonstrate the potential for bioimaging applications by dispersing the MIMs into water and imaging bladder cancer cells with them. To our knowledge, our results represent one and two orders of magnitude improvement, respectively, over the best lithographically fabricated structures and colloidal systems in the literature. The large enhancement will allow for bioimaging and therapeutics using lower particle densities or lower excitation power densities, thus increasing the sensitivity and efficacy of such procedures while decreasing potential side effects.

Our opinions and judgments are increasingly shaped by what we read on social media -whether they be tweets and posts in social networks, blog posts, or review boards. These opinions could be about topics such as consumer products, politics, life style, or celebrities. Understanding how users in a network update opinions based on their neighbor's opinions, as well as what global opinion structure is implied when users iteratively update opinions, is important in the context of viral marketing and information dissemination, as well as targeting messages to users in the network.In this paper, we consider the problem of modeling how users update opinions based on their neighbors' opinions. We perform a set of online user studies based on the celebrated conformity experiments of Asch [1]. Our experiments are carefully crafted to derive quantitative insights into developing a model for opinion updates (as opposed to deriving psychological insights). We show that existing and widely studied theoretical models do not explain the entire gamut of experimental observations we make. This leads us to posit a new, nuanced model that we term the BiasedVoterModel. We present preliminary theoretical and simulation results on the convergence and structure of opinions in the entire network when users iteratively update their respective opinions according to the BiasedVoterModel. We show that consensus and polarization of opinions arise naturally in this model under easy to interpret initial conditions on the network.

Expression of trpB and trpA of the Escherichia coli tryptophan operon is shown to be "translationally coupled", i.e., efficient translation of the t coding region is dependent on prior translation of the trpB coding region and termination of translation at the trpB stop codon.. To examine the dependence of trpA expression on the ribosome binding site sequence in the distal segment of t, deletions were produced that replaced this tpB sequence. Analysis of trpA expression in these deletion mutants establ4ished that the ribosome binding site sequence is required for efficient translation of the trp A segment of trp riRNA. A modest effect of translation over the trpA ri osorme binding site on independent initiation at that site was also served.trpD-trpC and galT-galK gene pairs of E. coli the stop and start codons of © I R L Press Limited, Oxford, England.

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AbstractLanthanide-based upconversion materials convert low energy infrared photons into high energy visible photons. These materials are of interest in a myriad of applications such as solar energy harvesting, color displays and photocatalysis. Upconversion nanoparticles (UCNPs) are also of interest in biological applications as bioimaging and therapeutic agents. However, the intrinsic conversion efficiency of UCNPs remains low for most applications. In this review, we survey the recent work done in increasing the upconversion emission by changing the local electric field experienced by the UCNPs using photonic nanostructures. We review both the underlying theory behind this photonic manipulation as well as experimental demonstrations of enhancement. We discuss the recent developments in the more common plasmonic designs as well as the emerging field of dielectric nanostructures. We find that improvements in design and fabrication of these nanostructures in the last few years have led to reported enhancements of over three orders of magnitude. This large enhancement has been achieved in not only nanostructures on films but also in nanostructures that can be dispersed into solution which is especially relevant for biological applications.

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Partially purified Met-tRNAf binding factor, eIF-2, was phosphorylated by using heme-regulated inhibitor (HRI). Phosphorylated eIF-2 was freed from HRI by phosphocellulose column chromatography. Analysis by isoelectric focusing showed 100% phosphorylation of the 38,000-dalton subunit of eIF-2. Both eIF-2 and eIF-2(P) formed ternary complexes with Met-tRNAf and GTP with almost the same efficiency, and in both cases the ternary complex formation was drastically inhibited by prior addition of Mg2+. However, whereas the ternary complexes formed with eIF-2 could be stimulated by Co-eIF-2C at 1 mM Mg2+ and dissociated by Co-eIF-2B at 5 mM Mg2+, the ternary complexes formed with eIF-2(P) were unresponsive to both Co-eIF-2B and Co-eIF-2C. Also under conditions of eIF-2 phosphorylation, HRI drastically inhibited AUG-dependent Met-tRNAf binding to 40S ribosomes.However, HRI (in the presence of ATP) had no effect on the joining of preformed Met-tRNAfr40S-AUG complex to the 60S ribosomal subunit to form Met-tRNAfr80S*AUG complex. These studies suggest that HRI inhibits protein synthesis initiation by phosphorylation of the 38,000-dalton subunit of eIF-2. HRIphosphorylated eIF-2 does not interact with at least two other protein factors, Co-eIF-2B and Co-eIF-2C, and is thus inactive in protein synthesis initiation. During heme deficiency, protein synthesis in reticulocyte lysates is inhibited due to activation of a latent protein synthesis inhibitor, heme-regulated inhibitor (HRI) (7-9). HRI is a protein kinase that specifically phosphorylates the 38,000-dalton subunit of Met-tRNAf binding factor, eIF-2 (10-14). HRI also inhibits the following partial initiation reactions and in each case, the inhibition requires ATP: (i) Co-eIF-2B-promoted dissociation of Met-tRNAf-eIF-2-GTP complex at high Mg2+ and low temperature (0°C) (TDF activity) (3, 15, 16); (fi) CoeIF-2C stimulation of ternary complex formation at 1 mM Mg2+ (5,[16][17][18]; and (iii) Met-tRNAf binding to 40S ribosomes (15,16,19). Based on these results, it has been proposed that HRI phosphorylation causes conformational modification of eIF-2 and that phosphorylated eIF-2 [eIF-2(P)] does not interact with two factors, Co-eIF-2B and Co-eIF-2C, and is inactive in peptide chain intiation. However, these studies do not conclusively establish the precise role of eIF-2(P) in the inhibition process and the possibility that the phosphorylation of other components such as HRI, Co-eIF-2B, and Co-eIF-2C also is involved in this inhibition has not been ruled out. Moreover, Trachsel and Staehelin (20) used prephosphorylated eIF-2 (HRI catalyzed) and observed that both eIF-2(P) and eIF-2 were equally active in all the partial initiation reactions studied including Met-tRNAf binding to 40S ribosomes. Also, the possibility that HRI can inhibit more than one step in peptide chain initiation has been indicated (21).To clearly establish the mechanism of HRI inhibition of peptide chain initiation and the precise role of HRI-phosphorylated eIF-2 in this inhibition process, we prep...