Identification of tissue-specific microRNAs from mouse

MicroRNAs (miRNAs) are a new class of noncoding RNAs, which are encoded as short inverted repeats in the genomes of invertebrates and vertebrates [1, 2]. It is believed that miRNAs are modulators of target mRNA translation and stability, although most target mRNAs remain to be identified. Here we describe the identification of 34 novel miRNAs by tissue- specific cloning of approximately 21-nucleotide RNAs from mouse. Almost all identified miRNAs are conserved in the human genome and are also frequently found in nonmammalian vertebrate genomes, such as pufferfish. In heart, liver, or brain, it is found that a single, tissue-specifically expressed miRNA dominates the population of expressed miRNAs and suggests a role for these miRNAs in tissue specification or cell lineage decisions. Finally, a miRNA was identified that appears to be the fruitfly and mammalian ortholog of C. elegans lin-4 stRNA

Cost Effectiveness of Sampling and Testing Programs

DTFH61-82-C-00015This report documents studies aimed at providing a means of establishing priorities among quality control tests and of optimizing sampling frequencies for each test, based on the effects of material properties measured on the performance of the pavements. Appropriate procedures were developed and are discussed in the report, including critical considerations and limitations due to lack of suitable stochastic models to predict performance and contractor response to changes in testing frequency. These procedures are embodied in computer program "COSTOP1", which was developed to assist state highway agencies in determining the optimum test frequency for a single test or the optimum test program for multiple tests to produce the greatest return for every dollar spent on testing. COSTOP1 is general and modular so that the testing programs for all paving construction and materials can be evaluated, and new models and differing repair strategies may be easily defined and input. Preliminary results based on limited models indicate that higher frequencies of testing than commonly used would be cost effective, decreasing the equivalent annual pavement costs by much more than the additional testing costs

Multipliers for p-Bessel sequences in Banach spaces

Multipliers have been recently introduced as operators for Bessel sequences and frames in Hilbert spaces. These operators are defined by a fixed multiplication pattern (the symbol) which is inserted between the analysis and synthesis operators. In this paper, we will generalize the concept of Bessel multipliers for p-Bessel and p-Riesz sequences in Banach spaces. It will be shown that bounded symbols lead to bounded operators. Symbols converging to zero induce compact operators. Furthermore, we will give sufficient conditions for multipliers to be nuclear operators. Finally, we will show the continuous dependency of the multipliers on their parameters.Comment: 17 page

Atoms of all channels, unite! Average case analysis of multi-channel sparse recovery using greedy algorithms

This paper provides new results on computing simultaneous sparse approximations of multichannel signals over redundant dictionaries using two greedy algorithms. The first one, p-thresholding, selects the S atoms that have the largest $p$-correlation while the second one, p-simultaneous matching pursuit (p-SOMP), is a generalisation of an algorithm studied by Tropp. We first provide exact recovery conditions as well as worst case analyses of all algorithms. The results, expressed using the standard cumulative coherence, are very reminiscent of the single channel case and, in particular, impose stringent restrictions on the dictionary. We unlock the situation by performing an average case analysis of both algorithms. First, we set up a general probabilistic signal model in which the coefficients of the atoms are drawn at random from the standard gaussian distribution. Second, we show that under this model, and with mild conditions on the coherence, the probability that p-thresholding and p-SOMP fail to recover the correct components is overwhelmingly small and gets smaller as the number of channels increases. Furthermore, we analyse the influence of selecting the set of correct atoms at random. We show that, if the dictionary satisfies a uniform uncertainty principle, the probability that simultaneous OMP fails to recover any sufficiently sparse set of atoms gets increasingly smaller as the number of channels increases

Aminoacid zwitterions in solution : Geometric, energetic, and vibrational analysis using density functional theory-continuum model calculations

Glycine and alanine aminoacids chemistry in solution is explored using a hybrid three parameters density functional (B3PW91) together with a continuum model. Geometries, energies, and vibrational spectra of glycine and alanine zwitterions are studied at the B3PW91/6-31+G∗∗ level and the results compared with those obtained at the HF and MP2/6-31+G∗∗ levels. Solvents effects are incorporated by means of an ellipsoidal cavity model with a multipolar expansion (up to sixth order) of the solute’s electrostatic potential. Our results confirm the validity of the B3PW91 functional for studying aminoacid chemistry in solution. Taking into account the more favorable scaling behavior of density functional techniques with respect to correlated ab initio methods these studies could be extended to larger [email protected] ; [email protected]

Estimation in high dimensions: a geometric perspective

This tutorial provides an exposition of a flexible geometric framework for high dimensional estimation problems with constraints. The tutorial develops geometric intuition about high dimensional sets, justifies it with some results of asymptotic convex geometry, and demonstrates connections between geometric results and estimation problems. The theory is illustrated with applications to sparse recovery, matrix completion, quantization, linear and logistic regression and generalized linear models.Comment: 56 pages, 9 figures. Multiple minor change