New RGD-peptide amphiphile mixtures containing a negatively charged diluent

Here, we studied the self-assembly of two peptide amphiphiles, C16-Gly-Gly-Gly-Arg-Gly- Asp (PA 1: C16-GGG-RGD) and C16-Gly-Gly-Gly-Arg-Gly-Asp-Ser (PA 2: C16-GGG-RGDS).We showed that PA 1 and PA 2 self-assemble into nanotapes with an internal bilayer structure. C16 chains were highly interdigitated within the nanotape cores, while the peptide blocks formed water-exposed b-sheets too. PA 1 nanotapes were characterized by one spacing distribution, corresponding to a more regular internal structure than that of PA 2 nanotapes, which presented two different spacing distributions. We showed that it is possible to obtain homogeneous nanotapes in water by co-assembling PA 1 or PA 2 with the negatively charged diluent C16-Glu-Thr-Thr-Glu- Ser (PA 3: C16-ETTES). The homogeneous tapes formed by PA 1–PA 3 or PA 2–PA 3 mixtures presented a structure similar to that observed for the corresponding pure PA 1 or PA 2 nanotapes. The mixed nanotapes, which were able to form a stabilized matrix containing homogeneously distributed cell adhesive RGD groups, represent promising materials for designing new cell adhesion substrates.

The spacing of orographic rainbands triggered by small-scale topography

A combination of idealized numerical simulations and analytical theory is used to investigate the spacing between convective orographic rainbands over the Coastal Range of western Oregon. The simulations, which are idealized from an observed banded precipitation event over the Coastal Range, indicate that the atmospheric response to conditionally unstable flow over the mountain ridge depends strongly on the subridge-scale topographic forcing on the windward side of the ridge. When this small-scale terrain contains only a single scale (l) of terrain variability, the band spacing is identical to l, but when a spectrum of terrain scales are simultaneously present, the band spacing ranges between 5 and 10 km, a value that is consistent with observations. Based on the simulations, an inviscid linear model is developed to provide a physical basis for understanding the scale selection of the rainbands. This analytical model, which captures the transition from lee waves upstream of the orographic cloud to moist convection within it, reveals that the spacing of orographic rainbands depends on both the projection of lee-wave energy onto the unstable cap cloud and the growth rate of unstable perturbations within the cloud. The linear model is used in tandem with numerical simulations to determine the sensitivity of the band spacing to a number of environmental and terrain-related parameters.

Quasi-biennial oscillation and tracer distributions in a coupled chemistry-climate model

[ 1] We have used a fully coupled chemistry-climate model (CCM), which generates its own wind and temperature quasi-biennial oscillation (QBO), to study the effect of coupling on the QBO and to examine the QBO signals in stratospheric trace gases, particularly ozone. Radiative coupling of the interactive chemistry to the underlying general circulation model tends to prolong the QBO period and to increase the QBO amplitude in the equatorial zonal wind in the lower and middle stratosphere. The model ozone QBO agrees well with Stratospheric Aerosol and Gas Experiment II and Total Ozone Mapping Spectrometer satellite observations in terms of vertical and latitudinal structure. The model captures the ozone QBO phase change near 28 km over the equator and the column phase change near +/- 15 degrees latitude. Diagnosis of the model chemical terms shows that variations in NOx are the main chemical driver of the O-3 QBO around 35 km, i.e., above the O-3 phase change.

Modeling distributions of immediate memory effects: No strategies needed?

Many models of immediate memory predict the presence or absence of various effects, but none have been tested to see whether they predict an appropriate distribution of effect sizes. The authors show that the feature model (J. S. Nairne, 1990) produces appropriate distributions of effect sizes for both the phonological confusion effect and the word-length effect. The model produces the appropriate number of reversals, when participants are more accurate with similar items or long items, and also correctly predicts that participants performing less well overall demonstrate smaller and less reliable phonological similarity and word-length effects and are more likely to show reversals. These patterns appear within the model without the need to assume a change in encoding or rehearsal strategy or the deployment of a different storage buffer. The implications of these results and the wider applicability of the distributionmodeling approach are discussed.

Asymptotic normality in mixtures of power series distributions

The problem of estimating the individual probabilities of a discrete distribution is considered. The true distribution of the independent observations is a mixture of a family of power series distributions. First, we ensure identifiability of the mixing distribution assuming mild conditions. Next, the mixing distribution is estimated by non-parametric maximum likelihood and an estimator for individual probabilities is obtained from the corresponding marginal mixture density. We establish asymptotic normality for the estimator of individual probabilities by showing that, under certain conditions, the difference between this estimator and the empirical proportions is asymptotically negligible. Our framework includes Poisson, negative binomial and logarithmic series as well as binomial mixture models. Simulations highlight the benefit in achieving normality when using the proposed marginal mixture density approach instead of the empirical one, especially for small sample sizes and/or when interest is in the tail areas. A real data example is given to illustrate the use of the methodology.

A parametric model for the interval censored survival times of Acacia mangium plantation in a spacing trial

Survival times for the Acacia mangium plantation in the Segaliud Lokan Project, Sabah, East Malaysia were analysed based on 20 permanent sample plots (PSPs) established in 1988 as a spacing experiment. The PSPs were established following a complete randomized block design with five levels of spacing randomly assigned to units within four blocks at different sites. The survival times of trees in years are of interest. Since the inventories were only conducted annually, the actual survival time for each tree was not observed. Hence, the data set comprises censored survival times. Initial analysis of the survival of the Acacia mangium plantation suggested there is block by spacing interaction; a Weibull model gives a reasonable fit to the replicate survival times within each PSP; but a standard Weibull regression model is inappropriate because the shape parameter differs between PSPs. In this paper we investigate the form of the non-constant Weibull shape parameter. Parsimonious models for the Weibull survival times have been derived using maximum likelihood methods. The factor selection for the parameters is based on a backward elimination procedure. The models are compared using likelihood ratio statistics. The results suggest that both Weibull parameters depend on spacing and block.