426 research outputs found

    Evaluation of Detector Array Designs for Optical Communication Between Unmanned Underwater Vehicle

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    The communication interface is essential for unmanned underwater vehicles (UUVs) to interact with each other or with a stationary target, such as docking station. In this paper, we investigate different optical array designs using a simulator. In addition to the hardware characteristics (e.g., sensitivity of the detectors and noise sources), the environmental conditions affecting the light field underwater were also taken into account. The simulator product is an image of the light field sensed by the detector array. The simulator product provides a signature that allows the UUV to track its position and orientation with respect to a light source. A variety of motion types (i.e., translation in the x, y, z directions including rotation about these axes) were analytically tested and evaluated for different array designs. The results from the simulator are to be validated against empirical measurements conducted in the water tank facilities in the Ocean Engineering Laboratory at the University of New Hampshire. Preliminary results suggest that unique image signatures can be obtained for the relative translational and rotational motion between two platforms

    Pothead or pot smoker? a taxometric investigation of cannabis dependence

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    BACKGROUND: Taxometric methods were used to discern the latent structure of cannabis dependence. Such methods help determine if a construct is categorical or dimensional. Taxometric analyses (MAXEIG and MAMBAC) were conducted on data from 1,474 cannabis-using respondents to the 2001–2002 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Respondents answered questions assessing DSM-IV criteria for cannabis dependence. RESULTS: Both taxometric methods provided support for a dimensional structure of cannabis dependence. CONCLUSION: Although the MAMBAC results were not entirely unequivocal, the majority of evidence favored a dimensional structure of cannabis dependence

    Discovering study-specific gene regulatory networks

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    This article has been made available through the Brunel Open Access Publishing Fund.Microarrays are commonly used in biology because of their ability to simultaneously measure thousands of genes under different conditions. Due to their structure, typically containing a high amount of variables but far fewer samples, scalable network analysis techniques are often employed. In particular, consensus approaches have been recently used that combine multiple microarray studies in order to find networks that are more robust. The purpose of this paper, however, is to combine multiple microarray studies to automatically identify subnetworks that are distinctive to specific experimental conditions rather than common to them all. To better understand key regulatory mechanisms and how they change under different conditions, we derive unique networks from multiple independent networks built using glasso which goes beyond standard correlations. This involves calculating cluster prediction accuracies to detect the most predictive genes for a specific set of conditions. We differentiate between accuracies calculated using cross-validation within a selected cluster of studies (the intra prediction accuracy) and those calculated on a set of independent studies belonging to different study clusters (inter prediction accuracy). Finally, we compare our method's results to related state-of-the art techniques. We explore how the proposed pipeline performs on both synthetic data and real data (wheat and Fusarium). Our results show that subnetworks can be identified reliably that are specific to subsets of studies and that these networks reflect key mechanisms that are fundamental to the experimental conditions in each of those subsets

    Looking Beyond Lambda with the Union Supernova Compilation

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    The recent robust and homogeneous analysis of the world's supernova distance-redshift data, together with cosmic microwave background and baryon acoustic oscillation data, provides a powerful tool for constraining cosmological models. Here we examine particular classes of scalar field, modified gravity, and phenomenological models to assess whether they are consistent with observations even when their behavior deviates from the cosmological constant Lambda. Some models have tension with the data, while others survive only by approaching the cosmological constant, and a couple are statistically favored over LCDM. Dark energy described by two equation of state parameters has considerable phase space to avoid Lambda and next generation data will be required to constrain such physics.Comment: 32 pages, 19 figure

    Constraining dust and color variations of high-z SNe using NICMOS on Hubble Space Telescope

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    We present data from the Supernova Cosmology Project for five high redshift Type Ia supernovae (SNe Ia) that were obtained using the NICMOS infrared camera on the Hubble Space Telescope. We add two SNe from this sample to a rest-frame I-band Hubble diagram, doubling the number of high redshift supernovae on this diagram. This I-band Hubble diagram is consistent with a flat universe (Omega_Matter, Omega_Lambda= 0.29, 0.71). A homogeneous distribution of large grain dust in the intergalactic medium (replenishing dust) is incompatible with the data and is excluded at the 5 sigma confidence level, if the SN host galaxy reddening is corrected assuming R_V=1.75. We use both optical and infrared observations to compare photometric properties of distant SNe Ia with those of nearby objects. We find generally good agreement with the expected color evolution for all SNe except the highest redshift SN in our sample (SN 1997ek at z=0.863) which shows a peculiar color behavior. We also present spectra obtained from ground based telescopes for type identification and determination of redshift.Comment: 30 pages, 10 figures; accepted for publication in ApJ; v2: revised to match the version in the journa

    A case-control study of determinants for high and low dental caries prevalence in Nevada youth

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    <p>Abstract</p> <p>Background</p> <p>The main purpose of this study was to compare the 30% of Nevada Youth who presented with the highest Decayed Missing and Filled Teeth (DMFT) index to a cohort who were caries free and to national NHANES data. Secondly, to explore the factors associated with higher caries prevalence in those with the highest DMFT scores compared to the caries-free group.</p> <p>Methods</p> <p>Over 4000 adolescents between ages 12 and 19 (Case Group: N = 2124; Control Group: N = 2045) received oral health screenings conducted in public/private middle and high schools in Nevada in 2008/2009 academic year. Caries prevalence was computed (Untreated decay scores [D-Score] and DMFT scores) for the 30% of Nevada Youth who presented with the highest DMFT score (case group) and compared to the control group (caries-free) and to national averages. Bivariate and multivariate logistic regression was used to analyze the relationship between selected variables and caries prevalence.</p> <p>Results</p> <p>A majority of the sample was non-Hispanic (62%), non-smokers (80%), and had dental insurance (70%). With the exception of gender, significant differences in mean D-scores were found in seven of the eight variables. All variables produced significant differences between the case and control groups in mean DMFT Scores. With the exception of smoking status, there were significant differences in seven of the eight variables in the bivariate logistic regression. All of the independent variables remained in the multivariate logistic regression model contributing significantly to over 40% of the variation in the increased DMFT status. The strongest predictors for the high DMFT status were racial background, age, fluoridated community, and applied sealants respectively. Gender, second hand smoke, insurance status, and tobacco use were significant, but to a lesser extent.</p> <p>Conclusions</p> <p>Findings from this study will aid in creating educational programs and other primary and secondary interventions to help promote oral health for Nevada youth, especially focusing on the subgroup that presents with the highest mean DMFT scores.</p

    Lattice Boltzmann simulations of soft matter systems

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    This article concerns numerical simulations of the dynamics of particles immersed in a continuum solvent. As prototypical systems, we consider colloidal dispersions of spherical particles and solutions of uncharged polymers. After a brief explanation of the concept of hydrodynamic interactions, we give a general overview over the various simulation methods that have been developed to cope with the resulting computational problems. We then focus on the approach we have developed, which couples a system of particles to a lattice Boltzmann model representing the solvent degrees of freedom. The standard D3Q19 lattice Boltzmann model is derived and explained in depth, followed by a detailed discussion of complementary methods for the coupling of solvent and solute. Colloidal dispersions are best described in terms of extended particles with appropriate boundary conditions at the surfaces, while particles with internal degrees of freedom are easier to simulate as an arrangement of mass points with frictional coupling to the solvent. In both cases, particular care has been taken to simulate thermal fluctuations in a consistent way. The usefulness of this methodology is illustrated by studies from our own research, where the dynamics of colloidal and polymeric systems has been investigated in both equilibrium and nonequilibrium situations.Comment: Review article, submitted to Advances in Polymer Science. 16 figures, 76 page

    Four theorems on the psychometric function

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    In a 2-alternative forced-choice (2AFC) discrimination task, observers choose which of two stimuli has the higher value. The psychometric function for this task gives the probability of a correct response for a given stimulus difference, Δx. This paper proves four theorems about the psychometric function. Assuming the observer applies a transducer and adds noise, Theorem 1 derives a convenient general expression for the psychometric function. Discrimination data are often fitted with a Weibull function. Theorem 2 proves that the Weibull "slope" parameter, β, can be approximated by [Formula: see text], where [Formula: see text] is the β of the Weibull function that fits best to the cumulative noise distribution, and [Formula: see text] depends on the transducer. We derive general expressions for [Formula: see text] and [Formula: see text], from which we derive expressions for specific cases. One case that follows naturally from our general analysis is Pelli's finding that, when [Formula: see text], [Formula: see text]. We also consider two limiting cases. Theorem 3 proves that, as sensitivity improves, 2AFC performance will usually approach that for a linear transducer, whatever the actual transducer; we show that this does not apply at signal levels where the transducer gradient is zero, which explains why it does not apply to contrast detection. Theorem 4 proves that, when the exponent of a power-function transducer approaches zero, 2AFC performance approaches that of a logarithmic transducer. We show that the power-function exponents of 0.4-0.5 fitted to suprathreshold contrast discrimination data are close enough to zero for the fitted psychometric function to be practically indistinguishable from that of a log transducer. Finally, Weibull β reflects the shape of the noise distribution, and we used our results to assess the recent claim that internal noise has higher kurtosis than a Gaussian. Our analysis of β for contrast discrimination suggests that, if internal noise is stimulus-independent, it has lower kurtosis than a Gaussian

    Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

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    Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

    Characterization of the linkage disequilibrium structure and identification of tagging-SNPs in five DNA repair genes

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    BACKGROUND: Characterization of the linkage disequilibrium (LD) structure of candidate genes is the basis for an effective association study of complex diseases such as cancer. In this study, we report the LD and haplotype architecture and tagging-single nucleotide polymorphisms (tSNPs) for five DNA repair genes: ATM, MRE11A, XRCC4, NBS1 and RAD50. METHODS: The genes ATM, MRE11A, and XRCC4 were characterized using a panel of 94 unrelated female subjects (47 breast cancer cases, 47 controls) obtained from high-risk breast cancer families. A similar LD structure and tSNP analysis was performed for NBS1 and RAD50, using publicly available genotyping data. We studied a total of 61 SNPs at an average marker density of 10 kb. Using a matrix decomposition algorithm, based on principal component analysis, we captured >90% of the intragenetic variation for each gene. RESULTS: Our results revealed that three of the five genes did not conform to a haplotype block structure (MRE11A, RAD50 and XRCC4). Instead, the data fit a more flexible LD group paradigm, where SNPs in high LD are not required to be contiguous. Traditional haplotype blocks assume recombination is the only dynamic at work. For ATM, MRE11A and XRCC4 we repeated the analysis in cases and controls separately to determine whether LD structure was consistent across breast cancer cases and controls. No substantial difference in LD structures was found. CONCLUSION: This study suggests that appropriate SNP selection for an association study involving candidate genes should allow for both mutation and recombination, which shape the population-level genomic structure. Furthermore, LD structure characterization in either breast cancer cases or controls appears to be sufficient for future cancer studies utilizing these genes
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