Scale-dependent non-Gaussianity probes inflationary physics

We calculate the scale dependence of the bispectrum and trispectrum in (quasi) local models of non-Gaussian primordial density perturbations, and characterize this scale dependence in terms of new observable parameters. They can help to discriminate between models of inflation, since they are sensitive to properties of the inflationary physics that are not probed by the standard observables. We find consistency relations between these parameters in certain classes of models. We apply our results to a scenario of modulated reheating, showing that the scale dependence of non-Gaussianity can be significant. We also discuss the scale dependence of the bispectrum and trispectrum, in cases where one varies the shape as well as the overall scale of the figure under consideration. We conclude providing a formulation of the curvature perturbation in real space, which generalises the standard local form by dropping the assumption that f_NL and g_NL are constants.Comment: 27 pages, 2 figures. v2: Minor changes to match the published versio

Can induced gravity isotropize Bianchi I, V, or IX Universes?

We analyze if Bianchi I, V, and IX models in the Induced Gravity (IG) theory can evolve to a Friedmann--Roberson--Walker (FRW) expansion due to the non--minimal coupling of gravity and the scalar field. The analytical results that we found for the Brans-Dicke (BD) theory are now applied to the IG theory which has $\omega \ll 1$ ($\omega$ being the square ratio of the Higgs to Planck mass) in a cosmological era in which the IG--potential is not significant. We find that the isotropization mechanism crucially depends on the value of $\omega$. Its smallness also permits inflationary solutions. For the Bianch V model inflation due to the Higgs potential takes place afterwads, and subsequently the spontaneous symmetry breaking (SSB) ends with an effective FRW evolution. The ordinary tests of successful cosmology are well satisfied.Comment: 24 pages, 5 figures, to be published in Phys. Rev. D1

Stein's method on Wiener chaos

We combine Malliavin calculus with Stein's method, in order to derive explicit bounds in the Gaussian and Gamma approximations of random variables in a fixed Wiener chaos of a general Gaussian process. We also prove results concerning random variables admitting a possibly infinite Wiener chaotic decomposition. Our approach generalizes, refines and unifies the central and non-central limit theorems for multiple Wiener-It\^o integrals recently proved (in several papers, from 2005 to 2007) by Nourdin, Nualart, Ortiz-Latorre, Peccati and Tudor. We apply our techniques to prove Berry-Ess\'een bounds in the Breuer-Major CLT for subordinated functionals of fractional Brownian motion. By using the well-known Mehler's formula for Ornstein-Uhlenbeck semigroups, we also recover a technical result recently proved by Chatterjee, concerning the Gaussian approximation of functionals of finite-dimensional Gaussian vectors.Comment: 39 pages; Two sections added; To appear in PTR

Antibacterial Resistance Leadership Group 2.0: Back to Business

In December 2019, the Antibacterial Resistance Leadership Group (ARLG) was awarded funding for another 7-year cycle to support a clinical research network on antibacterial resistance. ARLG 2.0 has 3 overarching research priorities: infections caused by antibiotic-resistant (AR) gram-negative bacteria, infections caused by AR gram-positive bacteria, and diagnostic tests to optimize use of antibiotics. To support the next generation of AR researchers, the ARLG offers 3 mentoring opportunities: the ARLG Fellowship, Early Stage Investigator seed grants, and the Trialists in Training Program. The purpose of this article is to update the scientific community on the progress made in the original funding period and to encourage submission of clinical research that addresses 1 or more of the research priority areas of ARLG 2.0

The Time Domain Spectroscopic Survey: Variable Selection and Anticipated Results

We present the selection algorithm and anticipated results for the Time Domain Spectroscopic Survey (TDSS). TDSS is an Sloan Digital Sky Survey (SDSS)-IV Extended Baryon Oscillation Spectroscopic Survey (eBOSS) subproject that will provide initial identification spectra of approximately 220,000 luminosity-variable objects (variable stars and active galactic nuclei across 7500 deg2 selected from a combination of SDSS and multi-epoch Pan-STARRS1 photometry. TDSS will be the largest spectroscopic survey to explicitly target variable objects, avoiding pre-selection on the basis of colors or detailed modeling of specific variability characteristics. Kernel Density Estimate analysis of our target population performed on SDSS Stripe 82 data suggests our target sample will be 95% pure (meaning 95% of objects we select have genuine luminosity variability of a few magnitudes or more). Our final spectroscopic sample will contain roughly 135,000 quasars and 85,000 stellar variables, approximately 4000 of which will be RR Lyrae stars which may be used as outer Milky Way probes. The variability-selected quasar population has a smoother redshift distribution than a color-selected sample, and variability measurements similar to those we develop here may be used to make more uniform quasar samples in large surveys. The stellar variable targets are distributed fairly uniformly across color space, indicating that TDSS will obtain spectra for a wide variety of stellar variables including pulsating variables, stars with significant chromospheric activity, cataclysmic variables, and eclipsing binaries. TDSS will serve as a pathfinder mission to identify and characterize the multitude of variable objects that will be detected photometrically in even larger variability surveys such as Large Synoptic Survey Telescope

Sequential, Multiple-Assignment, Randomized Trials for COMparing Personalized Antibiotic StrategieS (SMART-COMPASS)

Patient management is not based on a single decision. Rather, it is dynamic: Based on a sequence of decisions, with therapeutic adjustments made over time. Adjustments are personalized: Tailored to individual patients as new information becomes available. However, strategies allowing for such adjustments are infrequently studied. Traditional antibiotic trials are often nonpragmatic, comparing drugs for definitive therapy when drug susceptibilities are known. COMparing Personalized Antibiotic StrategieS (COMPASS) is a trial design that compares strategies consistent with clinical practice. Strategies are decision rules that guide empiric and definitive therapy decisions. Sequential, multiple-assignment, randomized (SMART) COMPASS allows evaluation when there are multiple, definitive therapy options. SMART COMPASS is pragmatic, mirroring clinical, antibiotic-treatment decision-making and addressing the most relevant issue for treating patients: Identification of the patient-management strategy that optimizes the ultimate patient outcomes. SMART COMPASS is valuable in the setting of antibiotic resistance, when therapeutic adjustments may be necessary due to resistance

The interrelation between temperature regimes and fish size in juvenile Atlantic cod (Gadus morhua): effects on growth and feed conversion efficiency

The present paper describes the growth properties of juvenile Atlantic cod (Gadus morhua) reared at 7, 10, 13 and 16 °C, and a group reared under “temperature steps” i.e. with temperature reduced successively from 16 to 13 and 10 °C. Growth rate and feed conversion efficiency of juvenile Atlantic cod were significantly influenced by the interaction of temperature and fish size. Overall growth was highest in the 13 °C and the T-step groups but for different reasons, as the fish at 13 °C had 10% higher overall feeding intake compared to the T-step group, whereas the T-step had 8% higher feeding efficiency. After termination of the laboratory study the fish were reared in sea pens at ambient conditions for 17 months. The groups performed differently when reared at ambient conditions in the sea as the T-step group was 11.6, 11.5, 5.3 and 7.5% larger than 7, 10, 13 and 16 °C, respectively in June 2005. Optimal temperature for growth and feed conversion efficiency decreased with size, indicating an ontogenetic reduction in optimum temperature for growth with increasing size. The results suggest an optimum temperature for growth of juvenile Atlantic cod in the size range 5–50 g dropping from 14.7 °C for 5–10 g juvenile to 12.4 °C for 40–50 g juvenile. Moreover, a broader parabolic regression curve between growth, feed conversion efficiency and temperature as size increases, indicate increased temperature tolerance with size. The study confirms that juvenile cod exhibits ontogenetic variation in temperature optimum, which might partly explain different spatial distribution of juvenile and adult cod in ocean waters. Our study also indicates a physiological mechanism that might be linked to cod migrations as cod may maximize their feeding efficiency by active thermoregulation

Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias