From Midden to Sieve: The Impact of Differential Recovery and Quantification Techniques on Interpretations of Shellfish Remains in Australian Coastal Archaeology

Experimental mechanical sieving methods are applied to samples of shellfish remains from three sites in southeast Queensland, Seven Mile Creek Mound, Sandstone Point and One-Tree, to test the efficacy of various recovery and quantification procedures commonly applied to shellfish assemblages in Australia. There has been considerable debate regarding the most appropriate sieve sizes and quantification methods that should be applied in the recovery of vertebrate faunal remains. Few studies, however, have addressed the impact of recovery and quantification methods on the interpretation of invertebrates, specifically shellfish remains. In this study, five shellfish taxa representing four bivalves (Anadara trapezia, Trichomya hirsutus, Saccostrea glomerata, Donax deltoides) and one gastropod (Pyrazus ebeninus) common in eastern Australian midden assemblages are sieved through 10mm, 6.3mm and 3.15mm mesh. Results are quantified using MNI, NISP and weight. Analyses indicate that different structural properties and pre- and postdepositional factors affect recovery rates. Fragile taxa (T. hirsutus) or those with foliated structure (S. glomerata) tend to be overrepresented by NISP measures in smaller sieve fractions, while more robust taxa (A. trapezia and P. ebeninus) tend to be overrepresented by weight measures. Results demonstrate that for all quantification methods tested a 3mm sieve should be used on all sites to allow for regional comparability and to effectively collect all available information about the shellfish remains.

Thermal effects in the evolution of initially layered mantle material

A simplified model for anisotropic mantle convection based on a novel class of rheologies, originally developed for folding instabilities in multilayered rock (MUHLHAUS et al., 2002), is extended ¨ through the introduction of a thermal anisotropy dependent on the local layering. To examine the effect of the thermal anisotropy on the evolution of mantle material, a parallel implementation of this model was undertaken using the Escript modelling toolkit and the Finley finite-element computational kernel (DAVIES et al., 2004). For the cases studied, there appears too little if any effect. For comparative purposes, the effects of anisotropic shear viscosity and the introduced thermal anisotropy are also presented. These results contribute to the characterization of viscous anisotropic mantle convection subject to variation in thermal conductivities and shear viscosities.

Evolution of Wolbachia pipientis transmission dynamics in insects

Wolbachia pipientis is an intracellular bacterial parasite of arthropods that enhances its transmission by manipulating host reproduction, most commonly by inducing cytoplasmic incompatibility. The discovery of isolates with modified cytoplasmic incompatibility phenotypes and others with novel virulence properties is an indication of the potential breadth of evolutionary strategies employed by Wolbachia.

Sampling phylogenetic tree space with the generalized Gibbs sampler

The generalized Gibbs sampler (GGS) is a recently developed Markov chain Monte Carlo (MCMC) technique that enables Gibbs-like sampling of state spaces that lack a convenient representation in terms of a fixed coordinate system. This paper describes a new sampler, called the tree sampler, which uses the GGS to sample from a state space consisting of phylogenetic trees. The tree sampler is useful for a wide range of phylogenetic applications, including Bayesian, maximum likelihood, and maximum parsimony methods. A fast new algorithm to search for a maximum parsimony phylogeny is presented, using the tree sampler in the context of simulated annealing. The mathematics underlying the algorithm is explained and its time complexity is analyzed. The method is tested on two large data sets consisting of 123 sequences and 500 sequences, respectively. The new algorithm is shown to compare very favorably in terms of speed and accuracy to the program DNAPARS from the PHYLIP package.

Periodic or Bounded Solutions of Carathéodory Systems of Ordinary Differential Equations

In this paper we extend the guiding function approach to show that there are periodic or bounded solutions for first order systems of ordinary differential equations of the form x1 =f(t,x), a.e. epsilon[a,b], where f satisfies the Caratheodory conditions. Our results generalize recent ones of Mawhin and Ward.

Fast evolution strategies

Evolution strategies are a class of general optimisation algorithms which are applicable to functions that are multimodal, nondifferentiable, or even discontinuous. Although recombination operators have been introduced into evolution strategies, the primary search operator is still mutation. Classical evolution strategies rely on Gaussian mutations. A new mutation operator based on the Cauchy distribution is proposed in this paper. It is shown empirically that the new evolution strategy based on Cauchy mutation outperforms the classical evolution strategy on most of the 23 benchmark problems tested in this paper. The paper also shows empirically that changing the order of mutating the objective variables and mutating the strategy parameters does not alter the previous conclusion significantly, and that Cauchy mutations with different scaling parameters still outperform the Gaussian mutation with self-adaptation. However, the advantage of Cauchy mutations disappears when recombination is used in evolution strategies. It is argued that the search step size plays an important role in determining evolution strategies' performance. The large step size of recombination plays a similar role as Cauchy mutation.

An improved seeded region growing algorithm

Recently Adams and Bischof (1994) proposed a novel region growing algorithm for segmenting intensity images. The inputs to the algorithm are the intensity image and a set of seeds - individual points or connected components - that identify the individual regions to be segmented. The algorithm grows these seed regions until all of the image pixels have been assimilated. Unfortunately the algorithm is inherently dependent on the order of pixel processing. This means, for example, that raster order processing and anti-raster order processing do not, in general, lead to the same tessellation. In this paper we propose an improved seeded region growing algorithm that retains the advantages of the Adams and Bischof algorithm fast execution, robust segmentation, and no tuning parameters - but is pixel order independent. (C) 1997 Elsevier Science B.V.

Evolution of a mate recognition system after hybridization between two Drosophila species

I investigated the genetic relationship between male and female components of the mate recognition system and how this relationship influenced the subsequent evolution of the two traits, in a series of replicate populations of interspecific hybrids. Thirty populations of hybrids between Drosophila serrata and Drosophila birchii were established and maintained for 24 generations. At the fifth generation after hybridization, the mating success of hybrid individuals with the D. serrata parent was determined. The genetic correlation between male and female components of the male recognition system, as a consequence of pleiotropy or tight physical linkage, was found to be significant but low (r = 0.388). This result suggested that pleiotropy may play only a minor role in the evolution of mate recognition in this system. At the twenty-fourth generation after hybridization, the mating success of the hybrids was again determined. The evolution of male and female components was investigated by analyzing the direction of evolution of each hybrid line with respect to its initial position in relation to the genetic regression. Male and female components appeared to converge on a single equilibrium point, rather than evolving along trajectories with slope equal to the genetic regression, toward a line of equilibria.

Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.