733 research outputs found

    High resolution study of the spatial distributions of abyssal fishes by autonomous underwater vehicle

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    On abyssal plains, demersal fish are believed to play an important role in transferring energy across the seafloor and between the pelagic and benthic realms. However, little is known about their spatial distributions, making it difficult to quantify their ecological significance. To address this, we employed an autonomous underwater vehicle to conduct an exceptionally large photographic survey of fish distributions on the Porcupine Abyssal Plain (NE Atlantic, 4850?m water depth) encompassing two spatial scales (1–10?km2) on and adjacent to a small abyssal hill (240?m elevation). The spatial distributions of the total fish fauna and that of the two dominant morphotypes (Coryphaenoides sp. 1 and C. profundicolus) appeared to be random, a result contrary to common expectation but consistent with previous predictions for these fishes. We estimated total fish density on the abyssal plain to be 723 individuals km?2 (95% CI: 601–844). This estimate is higher, and likely more precise, than prior estimates from trawl catch and baited camera techniques (152 and 188 individuals km?2 respectively). We detected no significant difference in fish density between abyssal hill and plain, nor did we detect any evidence for the existence of fish aggregations at any spatial scale assessed

    Handling misclassified stratification variables in the analysis of randomised trials with continuous outcomes

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    Many trials use stratified randomisation, where participants are randomised within strata defined by one or more baseline covariates. While it is important to adjust for stratification variables in the analysis, the appropriate method of adjustment is unclear when stratification variables are affected by misclassification and hence some participants are randomised in the incorrect stratum. We conducted a simulation study to compare methods of adjusting for stratification variables affected by misclassification in the analysis of continuous outcomes when all or only some stratification errors are discovered, and when the treatment effect or treatment-by-covariate interaction effect is of interest. The data were analysed using linear regression with no adjustment, adjustment for the strata used to perform the randomisation (randomisation strata), adjustment for the strata if all errors are corrected (true strata), and adjustment for the strata after some errors are discovered and corrected (updated strata). The unadjusted model performed poorly in all settings. Adjusting for the true strata was optimal, while the relative performance of adjusting for the randomisation strata or the updated strata varied depending on the setting. As the true strata are unlikely to be known with certainty in practice, we recommend using the updated strata for adjustment and performing subgroup analyses, provided the discovery of errors is unlikely to depend on treatment group, as expected in blinded trials. Greater transparency is needed in the reporting of stratification errors and how they were addressed in the analysis.Lisa N. Yelland, Jennie Louise, Brennan C. Kahan, Tim P. Morris, Katherine J. Lee, Thomas R. Sulliva

    Semigroups of distributions with linear Jacobi parameters

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    We show that a convolution semigroup of measures has Jacobi parameters polynomial in the convolution parameter tt if and only if the measures come from the Meixner class. Moreover, we prove the parallel result, in a more explicit way, for the free convolution and the free Meixner class. We then construct the class of measures satisfying the same property for the two-state free convolution. This class of two-state free convolution semigroups has not been considered explicitly before. We show that it also has Meixner-type properties. Specifically, it contains the analogs of the normal, Poisson, and binomial distributions, has a Laha-Lukacs-type characterization, and is related to the q=0q=0 case of quadratic harnesses.Comment: v3: the article is merged back together with arXiv:1003.4025. A significant revision following suggestions by the referee. 2 pdf figure

    Endothelial function and insulin sensitivity during acute non-esterified fatty acid elevation: effects of fat composition and gender

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    Background and Aims: We have reported that adverse effects on flow-mediated dilation of an acute elevation of non-esterified fatty acids rich in saturated fat (SFA) are reversed following addition of long-chain (LC) n-3 polyunsaturated fatty acids (PUFA), and hypothesised that these effects may be mediated through alterations in insulin signalling pathways. In a subgroup, we explored the effects of raised NEFA enriched with SFA, with or without LC n-3 PUFA, on whole body insulin sensitivity (SI) and responsiveness of the endothelium to insulin infusion. Methods and Results: Thirty adults (mean age 27.8 y, BMI 23.2 kg/m2) consumed oral fat loads on separate occasions with continuous heparin infusion to elevate NEFA between 60-390 min. For the final 150 min, a hyperinsulinaemic-euglycaemic clamp was performed, whilst FMD and circulating markers of endothelial function were measured at baseline, pre-clamp (240 min) and post-clamp (390 min). NEFA elevation during the SFA-rich drinks was associated with impaired FMD (P=0.027) whilst SFA+LC n-3 PUFA improved FMD at 240 min (P=0.003). In males, insulin infusion attenuated the increase in FMD with SFA+LC n-3 PUFA (P=0.049), with SI 10% greater with SFA+LC n-3 PUFA than SFA (P=0.041). Conclusion: This study provides evidence that NEFA composition during acute elevation influences both FMD and SI, with some indication of a difference by gender. However our findings are not consistent with the hypothesis that the effects of fatty acids on endothelial function and SI operate through a common pathway. Trial registered at clinicaltrials.gov, NCT01351324

    Hippocampus, Amygdala and Basal Ganglia Based Navigation Control

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    In this paper we present a novel robot navigation system aimed at testing hypotheses about the roles of key brain areas in foraging behavior of rats. The key components of the control network are: 1. a Hippocampus inspired module for spatial localization based on associations between sensory inputs and places; 2. an Amygdala inspired module for the association of values with places and sensory stimuli; 3. a Basal Ganglia inspired module for the selection of actions based on the evaluated sensory inputs. By implementing this Hippocampus-Amygdala-Basal Ganglia based control network with a simulated rat embodiment we intend to test not only our understanding of the individual brain areas but especially the interaction between them. Understanding the neural circuits that allows rats to efficiently forage for food will also help to improve the ability of robots to autonomously evaluate and select navigation targets

    Measurement of (anti)deuteron and (anti)proton production in DIS at HERA

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    The first observation of (anti)deuterons in deep inelastic scattering at HERA has been made with the ZEUS detector at a centre-of-mass energy of 300--318 GeV using an integrated luminosity of 120 pb-1. The measurement was performed in the central rapidity region for transverse momentum per unit of mass in the range 0.3<p_T/M<0.7. The particle rates have been extracted and interpreted in terms of the coalescence model. The (anti)deuteron production yield is smaller than the (anti)proton yield by approximately three orders of magnitude, consistent with the world measurements.Comment: 26 pages, 9 figures, 5 tables, submitted to Nucl. Phys.

    An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

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    For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

    Search for direct production of charginos and neutralinos in events with three leptons and missing transverse momentum in √s = 7 TeV pp collisions with the ATLAS detector

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    A search for the direct production of charginos and neutralinos in final states with three electrons or muons and missing transverse momentum is presented. The analysis is based on 4.7 fb−1 of proton–proton collision data delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with Standard Model expectations in three signal regions that are either depleted or enriched in Z-boson decays. Upper limits at 95% confidence level are set in R-parity conserving phenomenological minimal supersymmetric models and in simplified models, significantly extending previous results
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