Do harvest refuges buffer kangaroos against evolutionary responses to selective harvesting?

There is a wealth of literature documenting a directional change of body size in heavily harvested populations. Most of this work concentrates on aquatic systems, but terrestrial populations are equally at risk. This paper explores the capacity of harvest refuges to counteract potential effects of size-selective harvesting on the allele frequency,of populations. We constructed a stochastic, individual-based model parameterized with data on red kangaroos. Because we do not know which part of individual growth would change in the course of natural selection, we explored the effects of two alternative models of individual growth in which alleles affect either the growth rate or the maximum size. The model results show that size-selective harvesting can result in significantly smaller kangaroos for a given age when the entire population is subject to harvesting. In contrast, in scenarios that include dispersal from harvest refuges, the initial allele frequency remains virtually unchanged.

Home-range sizes and bower visitation patterns of immature male Satin Bowerbirds (Ptilonorhynchus violaceus)

Adult male Satin Bowerbirds build and decorate stick bowers to which they attract females for matings; females choose among males based on these complex bowers, decorations placed at these bowers, and displays consisting of vocalisations and posturing. Male Satin Bowerbirds undergo an extended period of delayed morphological maturation during which they retain female-like plumage and are assumed to learn adult male behavioural traits. Little is known, however, of how immature males acquire the ability to display and build and decorate bowers, except that they observe the displays of adult males at adults' bowers, and practise their own displays at both adults' and 'practice' bowers. We present data on the home ranges and movement patterns of six immature males, acquired through radio-tracking at the Bunya Mountains in south-east Queensland. Home-range size averaged 13.67 +/- 3.38 ha and immature males visited only some of the bowers located in their home ranges. On average, they visited 2.33 +/- 0.52 adults' bowers and 4.00 +/- 2.00 practice bowers.

Determination of domain sizes in blends of poly(ethylene) and poly(styrene) formed in the presence of supercritical carbon dioxide

Well-mixed blends of poly(ethylene) and poly(styrene) have been synthesized using supercritical carbon dioxide as a solvent. The morphology of the blends has been conclusively characterized using differential scanning calorimetry (DSC), small-angle X-ray scattering (SAXS), Raman microprobe microscopy, and C-13 solid-state cross-polarization magic angle spinning NMR (C-13 CPMAS NMR). DSC measurements demonstrate that poly(styrene) in the blends resides solely in the amorphous regions of the poly(ethylene) matrix; however, corroborative evidence from the SAXS experiments shows that poly(styrene) resides within the interlamellar spaces. The existence of nanometer-sized domains of poly(styrene) was shown within a blend of poly(styrene) and poly(ethylene) when formed in supercritical carbon dioxide using Raman microprobe microscopy and C-13 CPMAS NMR spectroscopy coupled with a spin diffusion model. This contrasts with blends formed at ambient pressure in the absence of solvent, in which domains of poly(styrene) in the micrometer size range are formed. This apparent improved miscibility of the two components was attributed to better penetration of the monomer prior to polymerization and increased swelling of the polymer substrate by the supercritical carbon dioxide solvent.

Application of the cross-entropy method to the buffer allocation problem in a simulation-based environment

The buffer allocation problem (BAP) is a well-known difficult problem in the design of production lines. We present a stochastic algorithm for solving the BAP, based on the cross-entropy method, a new paradigm for stochastic optimization. The algorithm involves the following iterative steps: (a) the generation of buffer allocations according to a certain random mechanism, followed by (b) the modification of this mechanism on the basis of cross-entropy minimization. Through various numerical experiments we demonstrate the efficiency of the proposed algorithm and show that the method can quickly generate (near-)optimal buffer allocations for fairly large production lines.

Estimating buffer overflows in three stages using cross-entropy

In this paper we propose a fast adaptive Importance Sampling method for the efficient simulation of buffer overflow probabilities in queueing networks. The method comprises three stages. First we estimate the minimum Cross-Entropy tilting parameter for a small buffer level; next, we use this as a starting value for the estimation of the optimal tilting parameter for the actual (large) buffer level; finally, the tilting parameter just found is used to estimate the overflow probability of interest. We recognize three distinct properties of the method which together explain why the method works well; we conjecture that they hold for quite general queueing networks. Numerical results support this conjecture and demonstrate the high efficiency of the proposed algorithm.