Resting vs. active: a meta-analysis of the intra- and inter-specific associations between minimum, sustained, and maximum metabolic rates in vertebrates

Variation in aerobic capacity has far reaching consequences for the physiology, ecology, and evolution of vertebrates. Whether at rest or active, animals are constrained to operate within the energetic bounds determined by their minimum (minMR) and sustained or maximum metabolic rates (upperMR). MinMR and upperMR can differ considerably among individuals and species but are often presumed to be mechanistically linked to one another. Specifically, minMR is thought to reflect the idling cost of the machinery needed to support upperMR. However, previous analyses based on limited datasets have come to conflicting conclusions regarding the generality and strength of their association. Here we conduct the first comprehensive assessment of their relationship, based on a large number of published estimates of both the intra-specific (n = 176) and inter-specific (n = 41) phenotypic correlations between minMR and upperMR, estimated as either exercise-induced maximum metabolic rate (VO2max), cold-induced summit metabolic rate (Msum), or daily energy expenditure (DEE). Our meta-analysis shows that there is a general positive association between minMR and upperMR that is shared among vertebrate taxonomic classes. However, there was stronger evidence for intra-specific correlations between minMR and Msum and between minMR and DEE than there was for a correlation between minMR and VO2max across different taxa. As expected, inter-specific correlation estimates were consistently higher than intra-specific estimates across all traits and vertebrate classes. An interesting exception to this general trend was observed in mammals, which contrast with birds and exhibit no correlation between minMR and Msum. We speculate that this is due to the evolution and recruitment of brown fat as a thermogenic tissue, which illustrates how some species and lineages might circumvent this seemingly general association. We conclude that, in spite of some variability across taxa and traits, the contention that minMR and upperMR are positively correlated generally holds true both within and across vertebrate species. Ecological and comparative studies should therefore take into consideration the possibility that variation in any one of these traits might partly reflect correlated responses to selection on other metabolic parameters

High-precision determination of the critical exponents for the lambda-transition of 4He by improved high-temperature expansion

We determine the critical exponents for the XY universality class in three dimensions, which is expected to describe the $\lambda$-transition in ${}^4$He. They are obtained from the analysis of high-temperature series computed for a two-component $\lambda\phi^4$ model. The parameter $\lambda$ is fixed such that the leading corrections to scaling vanish. We obtain $\nu = 0.67166(55)$, $\gamma = 1.3179(11)$, $\alpha=-0.0150(17)$. These estimates improve previous theoretical determinations and agree with the more precise experimental results for liquid Helium.Comment: 8 pages, revte

Transfer learning for galaxy morphology from one survey to another

© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of $\sim$5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy ($\sim$ 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies ($\sim$500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.Peer reviewedFinal Accepted Versio

Framing immigration and integration: Relationships between press and parliament in the Netherlands

This article examines how the salience and framing of political issues in the press and in parliament influence each other and how this salience and framing is influenced by key events outside the media and parliamentary realms. The case focused on is the debate on immigration and integration in the Netherlands between 1995 and 2004. The empirical analyses are based on a computer-assisted content analysis of both parliamentary documents and newspaper articles. Results show bidirectional causal relationships between media and parliament. In the case of salience only long-term influence relationships are found, while framing influences follow an interesting pattern: an increase in the use of a frame in one arena leads to an increase in the other arena only if this frame has already been used regularly in the latter arena. External events have more considerable and consistent impact on issue salience and framing in both arenas. Copyright © 2007 Sage Publications

First cosmology results using SNe Ia from the dark energy survey: analysis, systematic uncertainties, and validation

International audienceWe present the analysis underpinning the measurement of cosmological parameters from 207 spectroscopically classified type Ia supernovae (SNe Ia) from the first three years of the Dark Energy Survey Supernova Program (DES-SN), spanning a redshift range of 0.01

Superluminous supernovae from the Dark Energy Survey

We present a sample of 21 hydrogen-free superluminous supernovae (SLSNe-I) and one hydrogen-rich SLSN (SLSN-II) detected during the five-year Dark Energy Survey (DES). These SNe, located in the redshift range 0.220 < z < 1.998, represent the largest homogeneously selected sample of SLSN events at high redshift. We present the observed g, r, i, z light curves for these SNe, which we interpolate using Gaussian processes. The resulting light curves are analysed to determine the luminosity function of SLSNe-I, and their evolutionary timescales. The DES SLSN-I sample significantly broadens the distribution of SLSN-I light-curve properties when combined with existing samples from the literature. We fit a magnetar model to our SLSNe, and find that this model alone is unable to replicate the behaviour of many of the bolometric light curves. We search the DES SLSN-I light curves for the presence of initial peaks prior to the main light-curve peak. Using a shock breakout model, our Monte Carlo search finds that 3 of our 14 events with pre-max data display such initial peaks. However, 10 events show no evidence for such peaks, in some cases down to an absolute magnitude of<−16, suggesting that such features are not ubiquitous to all SLSN-I events. We also identify a red pre-peak feature within the light curve of one SLSN, which is comparable to that observed within SN2018bsz

A novel framework for the local extraction of extra-axial cerebrospinal fluid from MR brain images

The quantification of cerebrospinal fluid (CSF) in the human brain has shown to play an important role in early postnatal brain developmental. Extr a-axial fluid (EA-CSF), which is characterized by the CSF in the subarachnoid space, is promising in the early detection of children at risk for neurodevelopmental disorders. Currently, though, there is no tool to extract local EA-CSF measurements in a way that is suitable for localized analysis. In this paper, we propose a novel framework for the localized, cortical surface based analysis of EA-CSF. In our proposed processing, we combine probabilistic brain tissue segmentation, cortical surface reconstruction as well as streamline based local EA-CSF quantification. For streamline computation, we employ the vector field generated by solving a Laplacian partial differential equation (PDE) between the cortical surface and the outer CSF hull. To achieve sub-voxel accuracy while minimizing numerical errors, fourth-order Runge-Kutta (RK4) integration was used to generate the streamlines. Finally, the local EA-CSF is computed by integrating the CSF probability along the generated streamlines. The proposed local EA-CSF extraction tool was used to study the early postnatal brain development in typically developing infants. The results show that the proposed localized EA-CSF extraction pipeline can produce statistically significant regions that are not observed in previous global approach

Measurement of the splashback feature around SZ-selected Galaxy clusters with DES, SPT, and ACT

We present a detection of the splashback feature around galaxy clusters selected using the Sunyaev–Zel’dovich (SZ) signal. Recent measurements of the splashback feature around optically selected galaxy clusters have found that the splashback radius, rsp, is smaller than predicted by N-body simulations. A possible explanation for this discrepancy is that rsp inferred from the observed radial distribution of galaxies is affected by selection effects related to the optical cluster-finding algorithms. We test this possibility by measuring the splashback feature in clusters selected via the SZ effect in data from the South Pole Telescope SZ survey and the Atacama Cosmology Telescope Polarimeter survey. The measurement is accomplished by correlating these cluster samples with galaxies detected in the Dark Energy Survey Year 3 data. The SZ observable used to select clusters in this analysis is expected to have a tighter correlation with halo mass and to be more immune to projection effects and aperture-induced biases, potentially ameliorating causes of systematic error for optically selected clusters. We find that the measured rsp for SZ-selected clusters is consistent with the expectations from simulations, although the small number of SZ-selected clusters makes a precise comparison difficult. In agreement with previous work, when using optically selected redMaPPer clusters with similar mass and redshift distributions, rsp is ∼2σ smaller than in the simulations. These results motivate detailed investigations of selection biases in optically selected cluster catalogues and exploration of the splashback feature around larger samples of SZ-selected clusters. Additionally, we investigate trends in the galaxy profile and splashback feature as a function of galaxy colour, finding that blue galaxies have profiles close to a power law with no discernible splashback feature, which is consistent with them being on their first infall into the cluster

Heavy quarkonium: progress, puzzles, and opportunities

A golden age for heavy quarkonium physics dawned a decade ago, initiated by the confluence of exciting advances in quantum chromodynamics (QCD) and an explosion of related experimental activity. The early years of this period were chronicled in the Quarkonium Working Group (QWG) CERN Yellow Report (YR) in 2004, which presented a comprehensive review of the status of the field at that time and provided specific recommendations for further progress. However, the broad spectrum of subsequent breakthroughs, surprises, and continuing puzzles could only be partially anticipated. Since the release of the YR, the BESII program concluded only to give birth to BESIII; the $B$-factories and CLEO-c flourished; quarkonium production and polarization measurements at HERA and the Tevatron matured; and heavy-ion collisions at RHIC have opened a window on the deconfinement regime. All these experiments leave legacies of quality, precision, and unsolved mysteries for quarkonium physics, and therefore beg for continuing investigations. The plethora of newly-found quarkonium-like states unleashed a flood of theoretical investigations into new forms of matter such as quark-gluon hybrids, mesonic molecules, and tetraquarks. Measurements of the spectroscopy, decays, production, and in-medium behavior of c\bar{c}, b\bar{b}, and b\bar{c} bound states have been shown to validate some theoretical approaches to QCD and highlight lack of quantitative success for others. The intriguing details of quarkonium suppression in heavy-ion collisions that have emerged from RHIC have elevated the importance of separating hot- and cold-nuclear-matter effects in quark-gluon plasma studies. This review systematically addresses all these matters and concludes by prioritizing directions for ongoing and future efforts.Comment: 182 pages, 112 figures. Editors: N. Brambilla, S. Eidelman, B. K. Heltsley, R. Vogt. Section Coordinators: G. T. Bodwin, E. Eichten, A. D. Frawley, A. B. Meyer, R. E. Mitchell, V. Papadimitriou, P. Petreczky, A. A. Petrov, P. Robbe, A. Vair

Altered Cognitive Function in Men Treated for Prostate Cancer with LHRH Analogues and Cyproterone Acetate: A Randomised Controlled Trial

Objective. Luteinising hormone releasing hormone (LHRH) analogues have been associated with memory impairments in women using these drugs for gynaecological conditions. This is the first systematic investigation of the cognitive effects of LHRH analogues in male patients. Methods. 82 men with non-localised prostate cancer were randomly assigned to receive continuous leuprorelin (LHRH analogue), goserelin (LHRH analogue), cyproterone acetate (steroidal antiandrogen) or close clinical monitoring. These patients underwent cognitive assessments at baseline and before commencement of treatment (77) then 6 months later (65). Results. Compared with baseline assessments, men administered androgen suppression monotherapy performed worse in 2/12 tests of attention and memory. 24/50 men randomised to active treatment and assessed 6 months later demonstrated clinically significant decline in one or more cognitive tests but not one patient randomised to close monitoring showed a decline in any test performance. Conclusion. Pharmacological androgen suppression monotherapy for prostate cancer may be associated with impaired memory, attention and executive functions