r-modes in Relativistic Superfluid Stars

We discuss the modal properties of the $r$-modes of relativistic superfluid neutron stars, taking account of the entrainment effects between superfluids. In this paper, the neutron stars are assumed to be filled with neutron and proton superfluids and the strength of the entrainment effects between the superfluids are represented by a single parameter $\eta$. We find that the basic properties of the $r$-modes in a relativistic superfluid star are very similar to those found for a Newtonian superfluid star. The $r$-modes of a relativistic superfluid star are split into two families, ordinary fluid-like $r$-modes ($r^o$-mode) and superfluid-like $r$-modes ($r^s$-mode). The two superfluids counter-move for the $r^s$-modes, while they co-move for the $r^o$-modes. For the $r^o$-modes, the quantity $\kappa\equiv\sigma/\Omega+m$ is almost independent of the entrainment parameter $\eta$, where $m$ and $\sigma$ are the azimuthal wave number and the oscillation frequency observed by an inertial observer at spatial infinity, respectively. For the $r^s$-modes, on the other hand, $\kappa$ almost linearly increases with increasing $\eta$. It is also found that the radiation driven instability due to the $r^s$-modes is much weaker than that of the $r^o$-modes because the matter current associated with the axial parity perturbations almost completely vanishes.Comment: 14 pages, 4 figures. To appear in Physical Review

Observational constraints on the curvaton model of inflation

Simple curvaton models can generate a mixture of of correlated primordial adiabatic and isocurvature perturbations. The baryon and cold dark matter isocurvature modes differ only by an observationally null mode in which the two perturbations almost exactly compensate, and therefore have proportional effects at linear order. We discuss the CMB anisotropy in general mixed models, and give a simple approximate analytic result for the large scale CMB anisotropy. Working numerically we use the latest WMAP observations and a variety of other data to constrain the curvaton model. We find that models with an isocurvature contribution are not favored relative to simple purely adiabatic models. However a significant primordial totally correlated baryon isocurvature perturbation is not ruled out. Certain classes of curvaton model are thereby ruled out, other classes predict enough non-Gaussianity to be detectable by the Planck satellite. In the appendices we review the relevant equations in the covariant formulation and give series solutions for the radiation dominated era.Comment: Minor changes and corrections to match version accepted by PR

Database of diazotrophs in global ocean: abundance, biomass and nitrogen fixation rates

Marine N2 fixing microorganisms, termed diazotrophs, are a key functional group in marine pelagic ecosystems. The biological fixation of dinitrogen (N2) to bioavailable nitrogen provides an important new source of nitrogen for pelagic marine ecosystems and influences primary productivity and organic matter export to the deep ocean. As one of a series of efforts to collect biomass and rates specific to different phytoplankton functional groups, we have constructed a database on diazotrophic organisms in the global pelagic upper ocean by compiling about 12 000 direct field measurements of cyanobacterial diazotroph abundances (based on microscopic cell counts or qPCR assays targeting the nifH genes) and N2 fixation rates. Biomass conversion factors are estimated based on cell sizes to convert abundance data to diazotrophic biomass. The database is limited spatially, lacking large regions of the ocean especially in the Indian Ocean. The data are approximately log-normal distributed, and large variances exist in most sub-databases with non-zero values differing 5 to 8 orders of magnitude. Reporting the geometric mean and the range of one geometric standard error below and above the geometric mean, the pelagic N2 fixation rate in the global ocean is estimated to be 62 (52–73) Tg N yr?1 and the pelagic diazotrophic biomass in the global ocean is estimated to be 2.1 (1.4–3.1) Tg C from cell counts and to 89 (43–150) Tg C from nifH-based abundances. Reporting the arithmetic mean and one standard error instead, these three global estimates are 140 ± 9.2 Tg N yr?1, 18 ± 1.8 Tg C and 590 ± 70 Tg C, respectively. Uncertainties related to biomass conversion factors can change the estimate of geometric mean pelagic diazotrophic biomass in the global ocean by about ±70%. It was recently established that the most commonly applied method used to measure N2 fixation has underestimated the true rates. As a result, one can expect that future rate measurements will shift the mean N2 fixation rate upward and may result in significantly higher estimates for the global N2 fixation. The evolving database can nevertheless be used to study spatial and temporal distributions and variations of marine N2 fixation, to validate geochemical estimates and to parameterize and validate biogeochemical models, keeping in mind that future rate measurements may rise in the future. The database is stored in PANGAEA (doi:10.1594/PANGAEA.774851)

A consensus protocol for functional connectivity analysis in the rat brain

Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows for comparisons with data modalities collected under invasive or terminal procedures. Currently, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. Here we introduce StandardRat, a consensus rat functional magnetic resonance imaging acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired from rats across 46 centers. We developed a reproducible pipeline for analyzing rat data acquired with diverse protocols and determined experimental and processing parameters associated with the robust detection of functional connectivity across centers. We show that the standardized protocol enhances biologically plausible functional connectivity patterns relative to previous acquisitions. The protocol and processing pipeline described here is openly shared with the neuroimaging community to promote interoperability and cooperation toward tackling the most important challenges in neuroscience