Molecular dynamics simulation of helium–argon gas mixture under various wall conditions

As computational capabilities increase, molecular dynamics (MD) simulations become important tools of simulating reality. These simulations are especially useful for compressible gas mixture problems. In this study, binary diffusion of helium and argon was examined using a hard-sphere MD simulation method. For the sake of computational speed, low spacing ratios were chosen. Binary mass diffusion of gases in two equally sized halves of a box was simulated for identical initial kinetic energies and number densities. It has been noted that a purely mass diffusion mechanism of different gases is not physically possible. The resultant gas mixtures of several diffusion simulations were used as initial conditions for combined heat transfer – Couette flow, and heating and cooling experiments. The results showed the interesting behaviour of the mixture, which was subjected to various wall conditions. Energy of heavier molecules is found to be more sensitive to the wall velocities and less sensitive to the wall temperatures than lighter molecules. Diffusion, heat transfer, viscosity and heat capacity coefficients are deduced as well.     

Adsorption of Binary Mixtures in a Zeolite Micropore

Abstract

We investigate the selective adsorption of xenon, argon, and methane in zeolite NaA by applying the grand canonical ensemble Monte Carlo simulation technique to an adsorbed binary mixture and to two reference systems: i) an adsorbed single component system and ii) a bulk mixture. We define and calculate selectivities and excess densities due to i) mixing and ii) adsorption in terms of differences between the binary adsorbed system and these reference systems. We observe that xenon selectively adsorbs in both xenon-argon and xenon-methane mixtures at low chemical potential (low pressure) due to its greater energetic interaction with the zeolite. However, a reversal in selectivity occurs at higher chemical potential in both of these mixtures. This is due in large part to the greater efficiency in which the smaller component “packs” in the pore as compared to the bulk. We show that the crossover in selectivity occurs at a lower chemical potential for a mixture where one component can occupy regions of the porespace inaccessible to the other. We suggest that this crossover in selectivity may be a general feature of microporous adsorption.     

International Society of Chronobiology: Membership Information

Most variables of interest in laboratory medicine show predictable changes with several frequencies in the span of time investigated. The waveform of such nonsinusoidal rhythms can be well described by the use of multiple components rhythmometry, a method that allows fitting a linear model with several cosine functions. The method, originally described for analysis of longitudinal time series, is here extended to allow analysis of hybrid data (time series sampled from a group of subjects, each represented by an individual series). Given k individual series, we can fit the same linear model with m different frequencies (harmonics or not from one fundamental period) to each series. This fit will provide estimations for 2m + 1 parameters, namely, the amplitude and acrophase of each component, as well as the rhythm-adjusted mean. Assuming that the set of parameters obtained for each individual is a random sample from a multivariate normal population, the corresponding population parameter estimates can be based on the means of estimates obtained from individuals in the sample. Their confidence intervals depend on the variability among individual parameter estimates. The vari-ance-covariance matrix can then be estimated on the basis of the sample covariances. Confidence intervals for the rhythm-adjusted mean, as well as for the amplitude-acrophase pair, of each component can then be computed using the estimated covariance matrix. The p-values for testing the zero-amplitude assumption for each component, as well as for the global model, can finally be derived using those confidence intervals and the t and F distributions. The method, validated by a simulation study and illustrated by an example of modeling the circadian variation of heart rate, represents a new step in the development of statistical procedures in chronobiology.     

Effect of increasing GnRH and PGF2α dose during Double-Ovsynch on ovulatory response,luteal regression,and fertility of lactating dairy cows

Ovsynch-type synchronization of ovulation protocols have suboptimal synchronization rates due to reduced ovulation to the first GnRH treatment and inadequate luteolysis to the prostaglandin F_2α (PGF_2α) treatment before timed artificial insemination (TAI). Our objective was to determine whether increasing the dose of the first GnRH or the PGF_2α treatment during the Breeding-Ovsynch portion of Double-Ovsynch could improve the rates of ovulation and luteolysis and therefore increase pregnancies per artificial insemination (P/AI). In experiment 1, cows were randomly assigned to a two-by-two factorial design to receive either a low (L) or high (H) doses of GnRH (Gonadorelin; 100 vs. 200 μg) and a PGF_2α analogue (cloprostenol; 500 vs. 750 μg) resulting in the following treatments: LL (n = 263), HL (n = 277), LH (n = 270), and HH (n = 274). Transrectal ultrasonography and serum progesterone (P4) were used to assess ovulation to GnRH1, GnRH2, and luteal regression after PGF_2α during Breeding-Ovsynch in a subgroup of cows (n = 651 at each evaluation). Pregnancy status was assessed 29, 39, and 74 days after TAI. In experiment 2, cows were randomly assigned to LL (n = 220) or HH (n = 226) treatment as described for experiment 1. For experiment 1, ovulation to GnRH1 was greater (P = 0.01) for cows receiving H versus L GnRH (66.6% [217/326] vs. 57.5% [187/325]) treatment, but only for cows with elevated P4 at GnRH1. Cows that ovulated to GnRH1 had increased (P < 0.001) fertility compared with cows that did not ovulate (52.2% vs. 38.5%); however, no effect of higher dose of GnRH on fertility was detected. The greater PGF_2α dose increased luteal regression primarily in multiparous cows (P = 0.03) and tended to increase fertility (P = 0.05) only at the pregnancy diagnosis 39 days after TAI. Overall, P/AI was 47.0% at 29 days and 39.7% at 74 days after TAI; P/AI did not differ (P = 0.10) among treatments at 74 days (LL, 34.6%; HL, 40.8%; LH, 42.2%; HH, 40.9%) and was greater (P < 0.001) for primiparous cows than for multiparous cows (46.1% vs. 33.8%). For experiment 2, P/AI did not differ (P = 0.21) between H versus L treatments (44.2% [100/226] vs. 40.5% [89/220]). Thus, despite an increase in ovulatory response to GnRH1 and luteal regression to PGF_2α, there were only marginal effects of increasing dose of GnRH or PGF_2α on fertility to TAI after Double-Ovsynch.     

Effect of vegetation on density thresholds of adult desert locust gregarization from survey data in Mauritania

In the desert locust, Schistocerca gregaria (Forskål) (Orthoptera: Acrididae), the threshold density inducing the gregarization phenomenon has never been determined under natural conditions. The influence of environmental factors on this phenomenon has been studied mostly in controlled environments. Based on data collected during several years by the survey teams of the National Center for Locust Control in Mauritania, we analyzed the influence of locust density, vegetation cover, and vegetation status on the probability of observing gregarious locusts. We assumed that a probability to observe gregarious locusts of 0.5 corresponded to the density threshold of gregarization. The results showed in detail the change in the threshold of gregarization according to the cover and status of the vegetation. Low cover and dry vegetation led to a low density threshold of gregarization probably due to high probability of individuals to touch each other. Dense and green vegetation favored a high threshold of gregarization probably due to a dispersion of the individuals and a low probability of individual encounters. These findings should help the management of locusts and decision making during control operations.     

EXAMINING THE FULL EFFECTS OF LANDSCAPE HETEROGENEITY ON SPATIAL GENETIC VARIATION: A MULTIPLE MATRIX REGRESSION APPROACH FOR QUANTIFYING GEOGRAPHIC AND ECOLOGICAL ISOLATION

Understanding the effects of landscape heterogeneity on spatial genetic variation is a primary goal of landscape genetics. Ecological and geographic variables can contribute to genetic structure through geographic isolation, in which geographic barriers and distances restrict gene flow, and ecological isolation, in which gene flow among populations inhabiting different environments is limited by selection against dispersers moving between them. Although methods have been developed to study geographic isolation in detail, ecological isolation has received much less attention, partly because disentangling the effects of these mechanisms is inherently difficult. Here, I describe a novel approach for quantifying the effects of geographic and ecological isolation using multiple matrix regression with randomization. I explored the parameter space over which this method is effective using a series of individual‐based simulations and found that it accurately describes the effects of geographic and ecological isolation over a wide range of conditions. I also applied this method to a set of real‐world datasets to show that ecological isolation is an often overlooked but important contributor to patterns of spatial genetic variation and to demonstrate how this analysis can provide new insights into how landscapes contribute to the evolution of genetic variation in nature.     

A plant‐traits approach to assessing the success of alien weed species in irrigated Mediterranean orchards

In addition to their impact on natural habitats, invasive alien plants can have a significant negative effect on agricultural systems and cause economic losses. Flood‐irrigated orchards in the Mediterranean Basin are vulnerable to the invasion of alien weeds, primarily because of the traditional management practices used in the orchards, which are characterized by high soil moisture during the dry summer period, nutrient availability and high levels of disturbance. This study sought to determine whether their biological traits can explain the success of alien weed species. To answer this question, 408 floristic relevés were conducted in 136 flood‐irrigated orchards on the Plains of Lleida (Catalonia, NE of Spain). Richness and cover of native and alien weeds were compared. Furthermore, a set of biological traits were compared between successful and non‐successful weeds for the whole data and separately between native and alien weeds using logistic regression and classification trees. In flood‐irrigated orchards, alien species covered most of their area, even though the richness of alien species was lower than that of the native species. The most important species were C4 species with seeds dispersed by water, and on the other hand, rosulate and caespitose‐reptant hemicryptophytes with long flowering period. Most of these traits fitted with those of the invasive alien weeds, which were mostly C4 species with seeds dispersed by water. Perennial life form characterized successful native weeds. In this study, we discuss how the traditional management of flood irrigation in fruit‐tree orchards favours invasive alien weeds that have specific traits, acting as a reservoir for the spread of alien weeds into other crops and surrounding riparian habitats. We also propose changing management practices in order to avoid the selection of alien weeds and to promote native species.     

Testing for size and allometric differences in fossil hominin body mass estimation

Body size reconstructions of fossil hominins allow us to infer many things about their evolution and lifestyle, including diet, metabolic requirements, locomotion, and brain/body size relationships. The importance of these implications compels anthropologists to attempt body mass estimation from fragmentary fossil hominin specimens. Most calculations require a known “calibration” sample usually composed of modern humans or other extant apes. Caution must be taken in these analyses, as estimates are sensitive to overall size and allometric differences between the fossil hominin and the reference sample. Am J Phys Anthropol 151:215–229, 2013. © 2013 Wiley Periodicals, Inc.