Extreme Value Analysis of Empirical Frame Coefficients and Implications for Denoising by Soft-Thresholding

Denoising by frame thresholding is one of the most basic and efficient methods for recovering a discrete signal or image from data that are corrupted by additive Gaussian white noise. The basic idea is to select a frame of analyzing elements that separates the data in few large coefficients due to the signal and many small coefficients mainly due to the noise \epsilon_n. Removing all data coefficients being in magnitude below a certain threshold yields a reconstruction of the original signal. In order to properly balance the amount of noise to be removed and the relevant signal features to be kept, a precise understanding of the statistical properties of thresholding is important. For that purpose we derive the asymptotic distribution of max_{\omega \in \Omega_n} || for a wide class of redundant frames (\phi_\omega^n: \omega \in \Omega_n}. Based on our theoretical results we give a rationale for universal extreme value thresholding techniques yielding asymptotically sharp confidence regions and smoothness estimates corresponding to prescribed significance levels. The results cover many frames used in imaging and signal recovery applications, such as redundant wavelet systems, curvelet frames, or unions of bases. We show that `generically' a standard Gumbel law results as it is known from the case of orthonormal wavelet bases. However, for specific highly redundant frames other limiting laws may occur. We indeed verify that the translation invariant wavelet transform shows a different asymptotic behaviour.Comment: [Content: 39 pages, 4 figures] Note that in this version 4 we have slightely changed the title of the paper and we have rewritten parts of the introduction. Except for corrected typos the other parts of the paper are the same as the original versions

Amino acid sequence and distribution of mRNA encoding a major skeletal muscle laminin binding protein: an extracellular matrix-associated protein with an unusual COOH-terminal polyaspartate domain.

Two cDNAs encoding an abundant chicken muscle extracellular matrix (ECM)-associated laminin-binding protein (LBP) have been isolated and sequenced. The predicted primary amino acid sequence includes a probable signal peptide and a site for N-linked glycosylation, but lacks a hydrophobic segment long enough to span the membrane. The COOH terminus consists of an unusual repeat of 33 consecutive aspartate residues. Comparison with other sequences indicates that this protein is different from previously described LBPs and ECM receptors. RNA blot analysis of LBP gene expression showed that LBP mRNA was abundant in skeletal and heart muscle, but barely detectable in other tissues. Blots of chicken genomic DNA suggest that a single gene encodes this LBP. The amino acid sequence and mRNA distribution are consistent with the biochemical characterization described by Hall and co-workers (Hall, D. E., K. A. Frazer, B. C. Hahn, and L. F. Reichardt. 1988. J. Cell Biol. 107:687-697). These analyses indicate that LBP is an abundant ECM-associated muscle protein with an unusually high negative charge that interacts with both membranes and laminin, and has properties of a peripheral, not integral membrane protein. Taken together, our studies show that muscle LBP is a secreted, peripheral membrane protein with an unusual polyaspartate domain. Its laminin and membrane binding properties suggest that it may help mediate muscle cell interactions with the extracellular matrix. We propose the name "aspartactin" for this LBP

An ontology enhanced parallel SVM for scalable spam filter training

This is the post-print version of the final paper published in Neurocomputing. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.Spam, under a variety of shapes and forms, continues to inflict increased damage. Varying approaches including Support Vector Machine (SVM) techniques have been proposed for spam filter training and classification. However, SVM training is a computationally intensive process. This paper presents a MapReduce based parallel SVM algorithm for scalable spam filter training. By distributing, processing and optimizing the subsets of the training data across multiple participating computer nodes, the parallel SVM reduces the training time significantly. Ontology semantics are employed to minimize the impact of accuracy degradation when distributing the training data among a number of SVM classifiers. Experimental results show that ontology based augmentation improves the accuracy level of the parallel SVM beyond the original sequential counterpart

Widespread association between the ericoid mycorrhizal fungus Rhizoscyphus ericae and a leafy liverwort in the maritime and sub-Antarctic

A recent study identified a fungal isolate from the Antarctic leafy liverwort Cephaloziella varians as the ericoid mycorrhizal associate Rhizoscyphus ericae. However, nothing is known about the wider Antarctic distribution of R. ericae in C. varians, and inoculation experiments confirming the ability of the fungus to form coils in the liverwort are lacking. Using direct isolation and baiting with Vaccinium macrocarpon seedlings, fungi were isolated from C. varians sampled from eight sites across a 1875-km transect through sub- and maritime Antarctica. The ability of an isolate to form coils in aseptically grown C. varians was also tested. Fungi with 98–99% sequence identity to R. ericae internal transcribed spacer (ITS) region and partial large subunit ribosomal (r)DNA sequences were frequently isolated from C. varians at all sites sampled. The EF4/Fung5 primer set did not amplify small subunit rDNA from three of five R. ericae isolates, probably accounting for the reported absence of the fungus from C. varians in a previous study. Rhizoscyphus ericae was found to colonize aseptically-grown C. varians intracellularly, forming hyphal coils. This study shows that the association between R. ericae and C. varians is apparently widespread in Antarctica, and confirms that R. ericae is at least in part responsible for the formation of the coils observed in rhizoids of field-collected C. varians

Volume Fractions of the Kinematic "Near-Critical" Sets of the Quantum Ensemble Control Landscape

An estimate is derived for the volume fraction of a subset $C_{\epsilon}^{P} = \{U : ||grad J(U)|\leq {\epsilon}\}\subset\mathrm{U}(N)$ in the neighborhood of the critical set $C^{P}\simeq\mathrm{U}(\mathbf{n})P\mathrm{U}(\mathbf{m})$ of the kinematic quantum ensemble control landscape J(U) = Tr(U\rho U' O), where $U$ represents the unitary time evolution operator, {\rho} is the initial density matrix of the ensemble, and O is an observable operator. This estimate is based on the Hilbert-Schmidt geometry for the unitary group and a first-order approximation of $||grad J(U)||^2$. An upper bound on these near-critical volumes is conjectured and supported by numerical simulation, leading to an asymptotic analysis as the dimension $N$ of the quantum system rises in which the volume fractions of these "near-critical" sets decrease to zero as $N$ increases. This result helps explain the apparent lack of influence exerted by the many saddles of $J$ over the gradient flow.Comment: 27 pages, 1 figur

Role of PTP1B in POMC neurons during chronic high fat diet: Sex differences in regulation of liver lipids and glucose tolerance

Protein tyrosine phosphatase 1B (PTP1B) is a negative regulator of leptin receptor signalling and may contribute to leptin resistance in diet-induced obesity. Although PTP1B inhibition has been suggested as a potential weight loss therapy, the role of specific neuronal PTP1B signalling in cardiovascular and metabolic regulation and the importance of sex differences in this regulation are still unclear. In this study, we investigated the impact of pro-opiomelanocortin (POMC) neuronal PTP1B deficiency in cardiometabolic regulation in male and female mice fed a high fat diet (HFD). Compared to control mice (PTP1Bflox/flox), male and female mice deficient in POMC neuronal PTP1B (PTP1Bflox/flox/POMC-Cre) had attenuated body weight gain (Male: -18%; Female: -16%) and fat mass (Male: -33%; Female: -29%) in response to HFD. Glucose tolerance was improved by 40% and liver lipid accumulation was reduced by 40% in PTP1Bflox/flox/POMC-Cre males but not in females. Compared to control mice, deficiency of POMC neuronal PTP1B did not alter mean arterial pressure (MAP) in male or female mice (Male: 112±1 vs. 112±1 mmHg in controls; Female: 106±3 vs. 109±3 mmHg in controls). Deficiency of POMC neuronal PTP1B also did not alter MAP response to acute stress in male or female compared to control mice (Male: Δ32±0 vs. Δ29±4 mmHg; Female: Δ22±2 vs. Δ27±4 mmHg). These data demonstrate that POMC-specific PTP1B deficiency improved glucose tolerance and attenuated diet-induced fatty liver only in male mice, attenuated weight gain in males and females, but did not enhance the MAP and HR responses to a HFD or to acute stress

gEM/GANN: a multivariate computational strategy for auto-characterizing relationships between cellular and clinical phenotypes and predicting disease progression time using high-dimensional flow cytometry data

The dramatic increase in the complexity of flow cytometric datasets requires the development of new computational based approaches that can maximize the amount of information derived and overcome the limitations of traditional gating strategies. Herein, we present a multivariate computational analysis of the HIV-infected flow cytometry datasets that were provided as part of the FlowCAP-IV Challenge using unsupervised and supervised learning techniques. Out of 383 samples (stimulated and unstimulated), 191 samples were used as a training set (34 individuals whose disease did not progress, and 157 individuals whose disease did progress). Using the results from the training set, the participants in the Challenge were then asked to predict the condition and progression time of the remaining individuals (45 ‘non-progressors’ and 147 ‘progressors’). To achieve this, we first scaled down data resolution. We then excluded doublet cells from the analysis using Expectation Maximization approaches. We then standardized all samples into histograms and used Genetic Algorithm-Neural Network to extract feature sets from the datasets, the reliability of which were examined using WEKA-implemented classifiers. The selected feature set resulted in a high sensitivity and specificity for the discrimination of progressors and non-progressors in the training set (average True Positive Rate = 1.00 and average False Positive Rate = 0.033). The capacity of the feature set to predict real-time survival time was better when using data from the ‘unstimulated’ training set (r = 0.825). The p-values and 95% confidence interval logrank ratios between actual and predicted survival time in the test set were 0.682 and 0.9542±0.24 for the unstimulated dataset, and 0.4451 and 0.9173±0.23 for the stimulated dataset. Our analytic strategy has demonstrated a promising capacity to extract useful information from complex flow cytometry datasets, despite a significance imbalance and variation between the training and test sets

Who Watches the Watchmen? An Appraisal of Benchmarks for Multiple Sequence Alignment

Multiple sequence alignment (MSA) is a fundamental and ubiquitous technique in bioinformatics used to infer related residues among biological sequences. Thus alignment accuracy is crucial to a vast range of analyses, often in ways difficult to assess in those analyses. To compare the performance of different aligners and help detect systematic errors in alignments, a number of benchmarking strategies have been pursued. Here we present an overview of the main strategies--based on simulation, consistency, protein structure, and phylogeny--and discuss their different advantages and associated risks. We outline a set of desirable characteristics for effective benchmarking, and evaluate each strategy in light of them. We conclude that there is currently no universally applicable means of benchmarking MSA, and that developers and users of alignment tools should base their choice of benchmark depending on the context of application--with a keen awareness of the assumptions underlying each benchmarking strategy.Comment: Revie

Quark Mass Textures and sin 2 beta

Recent precise measurements of sin 2 beta from the B-factories (BABAR and BELLE) and a better known strange quark mass from lattice QCD make precision tests of predictive texture models possible. The models tested include those hierarchical N-zero textures classified by Ramond, Roberts and Ross, as well as any other hierarchical matrix Ansatz with non-zero 12 = 21 and vanishing 11 and 13 elements. We calculate the maximally allowed value for sin 2 beta in these models and show that all the aforementioned models with vanishing 11 and 13 elements are ruled out at the 3 sigma level. While at present sin 2 beta and |Vub/Vcb| are equally good for testing N-zero texture models, in the near future the former will surpass the latter in constraining power.Comment: 1+20 pages, 2 figures, JHEP3 clas

EK Eridani: the tip of the iceberg of giants which have evolved from magnetic Ap stars

We observe the slowly-rotating, active, single giant, EK Eri, to study and infer the nature of its magnetic field directly. We used the spectropolarimeter NARVAL at the Telescope Bernard Lyot, Pic du Midi Observatory, and the Least Square Deconvolution method to create high signal-to-noise ratio Stokes V profiles. We fitted the Stokes V profiles with a model of the large-scale magnetic field. We studied the classical activity indicators, the CaII H and K lines, the CaII infrared triplet, and H\alpha line. We detected the Stokes V signal of EK Eri securely and measured the longitudinal magnetic field Bl for seven individual dates spanning 60% of the rotational period. The measured longitudinal magnetic field of EK Eri reached about 100 G and was as strong as fields observed in RSCVn or FK Com type stars: this was found to be extraordinary when compared with the weak fields observed at the surfaces of slowly-rotating MS stars or any single red giant previously observed with NARVAL. From our modeling, we infer that the mean surface magnetic field is about 270 G, and that the large scale magnetic field is dominated by a poloidal component. This is compatible with expectations for the descendant of a strongly magnetic Ap star.Comment: 8 pages, 6 figures. Accepted for publication in A&