28,878 research outputs found

    Variance of spectral entropy (VSE): an SNR estimator for speech enhancement in hearing aids

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    In everyday situations an individual can encounter a variety of acoustic environments. For an individual with a hearing aid following speech in different types of background noise can often present a challenge. For this reason, estimating the signal-to-noise ratio (SNR) is a key factor to consider in hearing-aid design. The ability to adjust a noise reduction algorithm according to the SNR could provide the flexibility required to improve speech intelligibility in varying levels of background noise. However, most of the current high-accuracy SNR estimation methods are relatively complex and may inhibit the performance of hearing aids. This study investigates the advantages of incorporating a spectral entropy method to estimate SNR for speech enhancement in hearing aids; in particular a variance of spectral entropy (VSE) measure. The VSE approach avoids some of the complex computational steps of traditional statistical-model based SNR estimation methods by only measuring the spectral entropy among frequency channels of interest within the hearing aid. For this study, the SNR was estimated using the spectral entropy method in different types of noise. The variance of the spectral entropy in a hearing-aid model with 10 peripheral frequency channels was used to measure the SNR. By measuring the variance of the spectral entropy at input SNR levels between -10 dB to 20 dB, the relationship function between the SNR and the VSE was estimated. The VSE for the speech-in-noise was measured at temporal intervals of 1.5s. The VSE method demonstrates a more reliable performance in different types of background noise, in particular for low-number of speakers babble noise when compared to the US National Institute of Standards and Technology (NIST) or Waveform Amplitude Distribution Analysis (WADA) methods. The VSE method may also reduce additional computational steps (reducing system delays) making it more appropriate for implementation in hearing aids where system delays should be minimized as much as possible

    Subclinical myocardial disease by cardiac magnetic resonance imaging and spectroscopy in healthy HIV/Hepatitis C virus-coinfected persons.

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    Objective The contribution of hepatitis C virus (HCV) infection to the risk of heart failure in human immunodeficiency virus (HIV)-coinfected persons is unknown. The objective was to characterize cardiac function and morphology in HIV-treated coinfected persons. Methods In a cross-sectional study, HIV-infected patients virologically suppressed on antiretroviral therapy without known cardiovascular disease or diabetes mellitus underwent cardiac magnetic resonance imaging and spectroscopy for measures of cardiac function, myocardial fibrosis, and steatosis. Results The study included 18 male patients with a median age of 44 years. Of these, 10 had untreated HCV coinfection and eight had HIV monoinfection. Global systolic and diastolic function in the cohort were normal, and median myocardial fat content was 0.48% (interquartile range 0.35-1.54). Left ventricular (LV) mass index and LV mass/volume ratio were significantly greater in the HIV/HCV-coinfected group compared with the HIV-monoinfected group. In the HIV-monoinfected group, there was more myocardial fibrosis as measured by extracellular volume fraction. Conclusions There were differences between HIV/HCV-coinfected and HIV-monoinfected patients in cardiac structure and morphology. Larger studies are needed to examine whether HIV and HCV independently contribute to mechanisms of heart failure

    Levosimendan for the prevention of acute organ dysfunction in sepsis

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    BACKGROUND Levosimendan is a calcium-sensitizing drug with inotropic and other properties that may improve outcomes in patients with sepsis. METHODS We conducted a double-blind, randomized clinical trial to investigate whether levosimendan reduces the severity of organ dysfunction in adults with sepsis. Patients were randomly assigned to receive a blinded infusion of levosimendan (at a dose of 0.05 to 0.2 μg per kilogram of body weight per minute) for 24 hours or placebo in addition to standard care. The primary outcome was the mean daily Sequential Organ Failure Assessment (SOFA) score in the intensive care unit up to day 28 (scores for each of five systems range from 0 to 4, with higher scores indicating more severe dysfunction; maximum score, 20). Secondary outcomes included 28-day mortality, time to weaning from mechanical ventilation, and adverse events. RESULTS The trial recruited 516 patients; 259 were assigned to receive levosimendan and 257 to receive placebo. There was no significant difference in the mean (±SD) SOFA score between the levosimendan group and the placebo group (6.68±3.96 vs. 6.06±3.89; mean difference, 0.61; 95% confidence interval [CI], −0.07 to 1.29; P=0.053). Mortality at 28 days was 34.5% in the levosimendan group and 30.9% in the placebo group (absolute difference, 3.6 percentage points; 95% CI, −4.5 to 11.7; P=0.43). Among patients requiring ventilation at baseline, those in the levosimendan group were less likely than those in the placebo group to be successfully weaned from mechanical ventilation over the period of 28 days (hazard ratio, 0.77; 95% CI, 0.60 to 0.97; P=0.03). More patients in the levosimendan group than in the placebo group had supraventricular tachyarrhythmia (3.1% vs. 0.4%; absolute difference, 2.7 percentage points; 95% CI, 0.1 to 5.3; P=0.04). CONCLUSIONS The addition of levosimendan to standard treatment in adults with sepsis was not associated with less severe organ dysfunction or lower mortality. Levosimendan was associated with a lower likelihood of successful weaning from mechanical ventilation and a higher risk of supraventricular tachyarrhythmia. (Funded by the NIHR Efficacy and Mechanism Evaluation Programme and others; LeoPARDS Current Controlled Trials number, ISRCTN12776039.

    A Cost-Effective Random Testing Method for Programs with Non-Numeric Inputs

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    MCL-CAw: A refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure

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    Abstract Background The reconstruction of protein complexes from the physical interactome of organisms serves as a building block towards understanding the higher level organization of the cell. Over the past few years, several independent high-throughput experiments have helped to catalogue enormous amount of physical protein interaction data from organisms such as yeast. However, these individual datasets show lack of correlation with each other and also contain substantial number of false positives (noise). Over these years, several affinity scoring schemes have also been devised to improve the qualities of these datasets. Therefore, the challenge now is to detect meaningful as well as novel complexes from protein interaction (PPI) networks derived by combining datasets from multiple sources and by making use of these affinity scoring schemes. In the attempt towards tackling this challenge, the Markov Clustering algorithm (MCL) has proved to be a popular and reasonably successful method, mainly due to its scalability, robustness, and ability to work on scored (weighted) networks. However, MCL produces many noisy clusters, which either do not match known complexes or have additional proteins that reduce the accuracies of correctly predicted complexes. Results Inspired by recent experimental observations by Gavin and colleagues on the modularity structure in yeast complexes and the distinctive properties of "core" and "attachment" proteins, we develop a core-attachment based refinement method coupled to MCL for reconstruction of yeast complexes from scored (weighted) PPI networks. We combine physical interactions from two recent "pull-down" experiments to generate an unscored PPI network. We then score this network using available affinity scoring schemes to generate multiple scored PPI networks. The evaluation of our method (called MCL-CAw) on these networks shows that: (i) MCL-CAw derives larger number of yeast complexes and with better accuracies than MCL, particularly in the presence of natural noise; (ii) Affinity scoring can effectively reduce the impact of noise on MCL-CAw and thereby improve the quality (precision and recall) of its predicted complexes; (iii) MCL-CAw responds well to most available scoring schemes. We discuss several instances where MCL-CAw was successful in deriving meaningful complexes, and where it missed a few proteins or whole complexes due to affinity scoring of the networks. We compare MCL-CAw with several recent complex detection algorithms on unscored and scored networks, and assess the relative performance of the algorithms on these networks. Further, we study the impact of augmenting physical datasets with computationally inferred interactions for complex detection. Finally, we analyse the essentiality of proteins within predicted complexes to understand a possible correlation between protein essentiality and their ability to form complexes. Conclusions We demonstrate that core-attachment based refinement in MCL-CAw improves the predictions of MCL on yeast PPI networks. We show that affinity scoring improves the performance of MCL-CAw.http://deepblue.lib.umich.edu/bitstream/2027.42/78256/1/1471-2105-11-504.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/2/1471-2105-11-504-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/3/1471-2105-11-504-S2.ZIPhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/4/1471-2105-11-504.pdfPeer Reviewe

    Graphene-based photovoltaic cells for near-field thermal energy conversion

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    Thermophotovoltaic devices are energy-conversion systems generating an electric current from the thermal photons radiated by a hot body. In far field, the efficiency of these systems is limited by the thermodynamic Schockley-Queisser limit corresponding to the case where the source is a black body. On the other hand, in near field, the heat flux which can be transferred to a photovoltaic cell can be several orders of magnitude larger because of the contribution of evanescent photons. This is particularly true when the source supports surface polaritons. Unfortunately, in the infrared where these systems operate, the mismatch between the surface-mode frequency and the semiconductor gap reduces drastically the potential of this technology. Here we show that graphene-based hybrid photovoltaic cells can significantly enhance the generated power paving the way to a promising technology for an intensive production of electricity from waste heat.Comment: 5 pages, 4 figure

    Evaluation of Phage Display Discovered Peptides as Ligands for Prostate-Specific Membrane Antigen (PSMA)

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    The aim of this study was to identify potential ligands of PSMA suitable for further development as novel PSMA-targeted peptides using phage display technology. The human PSMA protein was immobilized as a target followed by incubation with a 15-mer phage display random peptide library. After one round of prescreening and two rounds of screening, high-stringency screening at the third round of panning was performed to identify the highest affinity binders. Phages which had a specific binding activity to PSMA in human prostate cancer cells were isolated and the DNA corresponding to the 15-mers were sequenced to provide three consensus sequences: GDHSPFT, SHFSVGS and EVPRLSLLAVFL as well as other sequences that did not display consensus. Two of the peptide sequences deduced from DNA sequencing of binding phages, SHSFSVGSGDHSPFT and GRFLTGGTGRLLRIS were labeled with 5-carboxyfluorescein and shown to bind and co-internalize with PSMA on human prostate cancer cells by fluorescence microscopy. The high stringency requirements yielded peptides with affinities KD∼1 μM or greater which are suitable starting points for affinity maturation. While these values were less than anticipated, the high stringency did yield peptide sequences that apparently bound to different surfaces on PSMA. These peptide sequences could be the basis for further development of peptides for prostate cancer tumor imaging and therapy. © 2013 Shen et al

    Control and Characterization of Individual Grains and Grain Boundaries in Graphene Grown by Chemical Vapor Deposition

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    The strong interest in graphene has motivated the scalable production of high quality graphene and graphene devices. Since large-scale graphene films synthesized to date are typically polycrystalline, it is important to characterize and control grain boundaries, generally believed to degrade graphene quality. Here we study single-crystal graphene grains synthesized by ambient CVD on polycrystalline Cu, and show how individual boundaries between coalescing grains affect graphene's electronic properties. The graphene grains show no definite epitaxial relationship with the Cu substrate, and can cross Cu grain boundaries. The edges of these grains are found to be predominantly parallel to zigzag directions. We show that grain boundaries give a significant Raman "D" peak, impede electrical transport, and induce prominent weak localization indicative of intervalley scattering in graphene. Finally, we demonstrate an approach using pre-patterned growth seeds to control graphene nucleation, opening a route towards scalable fabrication of single-crystal graphene devices without grain boundaries.Comment: New version with additional data. Accepted by Nature Material

    Small RNA Profile in Moso Bamboo Root and Leaf Obtained by High Definition Adapters

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    Moso bamboo (Phyllostachy heterocycla cv. pubescens L.) is an economically important fast-growing tree. In order to gain better understanding of gene expression regulation in this important species we used next generation sequencing to profile small RNAs in leaf and roots of young seedlings. Since standard kits to produce cDNA of small RNAs are biased for certain small RNAs, we used High Definition adapters that reduce ligation bias. We identified and experimentally validated five new microRNAs and a few other small non-coding RNAs that were not microRNAs. The biological implication of microRNA expression levels and targets of microRNAs are discussed
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