An investigation into the numerical prediction of boundary layer transition using the K.Y. Chien turbulence model

Assessments were made of the simulation capabilities of transition models developed at the University of Minnesota, as applied to the Launder-Sharma and Lam-Bremhorst two-equation turbulence models, and at The University of Texas at Austin, as applied to the K. Y. Chien two-equation turbulence model. A major shortcoming in the use of the basic K. Y. Chien turbulence model for low-Reynolds number flows was identified. The problem with the Chien model involved premature start of natural transition and a damped response as the simulation moved to fully turbulent flow at the end of transition. This is in contrast to the other two-equation turbulence models at comparable freestream turbulence conditions. The damping of the transition response of the Chien turbulence model leads to an inaccurate estimate of the start and end of transition for freestream turbulence levels greater than 1.0 percent and to difficulty in calculating proper model constants for the transition model

Development of electromagnetic cascades in the atmosphere including the Landau-Pomeranchuk-Migdal effect

Numerical solutions have been obtained for the one-dimensional atmospheric electromagnetic cascade diffusion equations, including the Landau-Pomeranchuk-Migdal and screening effects. Spectra produced by primary gamma rays of various energies are given at a number of deths in the atmosphere

Local Chemical Environments and the Phonon Partial Densities of States of 57Fe in 57Fe3Al

Inelastic nuclear resonant scattering spectra were measured on alloys of Fe3Al that were chemically disordered, partially ordered, and D03 ordered. The features in the phonon partial density of states of 57Fe were found to change systematically with chemical short-range order in the alloy. Changes in the phonon partial density of states were modeled successfully by assigning vibrational spectra to 57Fe atoms in different first-nearest-neighbor chemical environments

Seasonal changes in microbial dissolved organic sulfur transformations in coastal waters

The marine trace gas dimethylsulfide (DMS) is the single most important biogenic source of atmospheric sulfur, accounting for up to 80% of global biogenic sulfur emissions. Approximately 300 million tons of DMS are produced annually, but the majority is degraded by microbes in seawater. The DMS precursor dimethylsulfoniopropionate (DMSP) and oxidation product dimethylsulphoxide (DMSO) are also important organic sulfur reservoirs. However, the marine sinks of dissolved DMSO remain unknown. We used a novel combination of stable and radiotracers to determine seasonal changes in multiple dissolved organic sulfur transformation rates to ascertain whether microbial uptake of dissolved DMSO was a significant loss pathway. Surface concentrations of DMS ranged from 0.5 to 17.0 nM with biological consumption rates between 2.4 and 40.8 nM·d−1. DMS produced from the reduction of DMSO was not a significant process. Surface concentrations of total DMSO ranged from 2.3 to 102 nM with biological consumption of dissolved DMSO between 2.9 and 111 nM·d−1. Comparisons between 14C2-DMSO assimilation and dissimilation rates suggest that the majority of dissolved DMSO was respired (>94%). Radiotracer microbial consumption rates suggest that dissimilation of dissolved DMSO to CO2 can be a significant loss pathway in coastal waters, illustrating the significance of bacteria in controlling organic sulfur seawater concentrations

Two-sample Bayesian Nonparametric Hypothesis Testing

In this article we describe Bayesian nonparametric procedures for two-sample hypothesis testing. Namely, given two sets of samples $\mathbf{y}^{\scriptscriptstyle(1)}\;$\stackrel{\scriptscriptstyle{iid}}{\s im}$\;F^{\scriptscriptstyle(1)}$ and $\mathbf{y}^{\scriptscriptstyle(2 )}\;$\stackrel{\scriptscriptstyle{iid}}{\sim}$\;F^{\scriptscriptstyle( 2)}$, with $F^{\scriptscriptstyle(1)},F^{\scriptscriptstyle(2)}$ unknown, we wish to evaluate the evidence for the null hypothesis $H_0:F^{\scriptscriptstyle(1)}\equiv F^{\scriptscriptstyle(2)}$ versus the alternative $H_1:F^{\scriptscriptstyle(1)}\neq F^{\scriptscriptstyle(2)}$. Our method is based upon a nonparametric P\'{o}lya tree prior centered either subjectively or using an empirical procedure. We show that the P\'{o}lya tree prior leads to an analytic expression for the marginal likelihood under the two hypotheses and hence an explicit measure of the probability of the null $\mathrm{Pr}(H_0|\{\mathbf {y}^{\scriptscriptstyle(1)},\mathbf{y}^{\scriptscriptstyle(2)}\}\mathbf{)}$.Comment: Published at http://dx.doi.org/10.1214/14-BA914 in the Bayesian Analysis (http://projecteuclid.org/euclid.ba) by the International Society of Bayesian Analysis (http://bayesian.org/

Infrared spectra of crystalline and glassy silicates and application to interstellar dust

The infrared spectra of crystalline minerals predicted in theoretical condensation sequences do not match the astronomical observations. Since the astronomical spectra are a closer match to glassy silicates, the authors undertook a study to measure the infrared spectra of glassy silicates that have compositions similar to silicate minerals predicted in theoretical condensation sequences. The data should support observations aimed at elucidating condensation chemistry in dust forming regions. The authors measured the mass absorption coefficients, from 2.5 to 25 microns, of ground samples of olivine, diopside, and serpentine and also smoke samples that were prepared from these minerals. The smoke samples prepared in this way are predominantly glassy with nearly the same composition as the parent minerals. The crystalline samples consisted of pure olivine ((Fe(0.1)Mg(0.9))(2)SiO(4)), serpentine, diopside. Sample purity was confirmed by x ray diffraction. Each mineral was ground for 10 hours and a measured mass of the powder was mixed with KBr powder for absorption measurements using the method of Borghesi et a. (1985). The smoke samples were prepared from the same samples used for grinding by vaporizing the minerals using pulsed laser radiation in air. The smoke samples formed by condensation of the resulting vapor. The smoke settled onto infrared transparent KRS-5 substrates and onto a quartz crystal microbalance used to obtain mass measurements. A description of the preparation method is given in Stephens (1980). The glassy diopside showed only diffuse electron diffraction peaks and hence was nearly amorphous, while the serpentine smoke showed a weak diffraction pattern corresponding to MgO. The smoke from olivine showed a weak diffraction pattern corresponding to Fe2O3 and/or Fe3O4. The mass absorption coefficients, from 2.5 to 25 microns, of crystalline diopside, olivine, and serpentine and their corresponding smoke samples are shown in figures

Recurrence interval analysis of high-frequency financial returns and its application to risk estimation

We investigate the probability distributions of the recurrence intervals $\tau$ between consecutive 1-min returns above a positive threshold $q>0$ or below a negative threshold $q<0$ of two indices and 20 individual stocks in China's stock market. The distributions of recurrence intervals for positive and negative thresholds are symmetric, and display power-law tails tested by three goodness-of-fit measures including the Kolmogorov-Smirnov (KS) statistic, the weighted KS statistic and the Cram\'er-von Mises criterion. Both long-term and shot-term memory effects are observed in the recurrence intervals for positive and negative thresholds $q$. We further apply the recurrence interval analysis to the risk estimation for the Chinese stock markets based on the probability $W_q(\Delta{t},t)$, Value-at-Risk (VaR) analysis and VaR analysis conditioned on preceding recurrence intervals.Comment: 17 pages, 10 figures, 1 tabl

Letters between A. E. Grantham and William Kerr\u27s secretary.

Letters concerning a position in agronomy at Utah Agricultural College

Prey selection by an apex predator : the importance of sampling uncertainty.

The impact of predation on prey populations has long been a focus of ecologists, but a firm understanding of the factors influencing prey selection, a key predictor of that impact, remains elusive. High levels of variability observed in prey selection may reflect true differences in the ecology of different communities but might also reflect a failure to deal adequately with uncertainties in the underlying data. Indeed, our review showed that less than 10% of studies of European wolf predation accounted for sampling uncertainty. Here, we relate annual variability in wolf diet to prey availability and examine temporal patterns in prey selection; in particular, we identify how considering uncertainty alters conclusions regarding prey selection. Over nine years, we collected 1,974 wolf scats and conducted drive censuses of ungulates in Alpe di Catenaia, Italy. We bootstrapped scat and census data within years to construct confidence intervals around estimates of prey use, availability and selection. Wolf diet was dominated by boar (61.5±3.90 [SE] % of biomass eaten) and roe deer (33.7±3.61%). Temporal patterns of prey densities revealed that the proportion of roe deer in wolf diet peaked when boar densities were low, not when roe deer densities were highest. Considering only the two dominant prey types, Manly's standardized selection index using all data across years indicated selection for boar (mean = 0.73±0.023). However, sampling error resulted in wide confidence intervals around estimates of prey selection. Thus, despite considerable variation in yearly estimates, confidence intervals for all years overlapped. Failing to consider such uncertainty could lead erroneously to the assumption of differences in prey selection among years. This study highlights the importance of considering temporal variation in relative prey availability and accounting for sampling uncertainty when interpreting the results of dietary studies