The life history legacy of evolutionary body size change in carnivores

We estimate the body sizes of direct ancestors of extant carnivores, and examine selected aspects of life history as a function not only of species' current size, but also of recent changes in size. Carnivore species that have undergone marked recent evolutionary size change show life history characteristics typically associated with species closer to the ancestral body size. Thus, phyletic giants tend to mature earlier and have larger litters of smaller offspring at shorter intervals than do species of the same body size that are not phyletic giants. Phyletic dwarfs, by contrast, have slower life histories than nondwarf species of the same body size. We discuss two possible mechanisms for the legacy of recent size change: lag (in which life history variables cannot evolve as quickly as body size, leading to species having the 'wrong' life history for their body size) and body size optimization (in which life history and hence body size evolve in response to changes in energy availability); at present, we cannot distinguish between these alternatives. Our finding that recent body size changes help explain residual variation around life history allometries shows that a more dynamic view of character change enables comparative studies to make more precise predictions about species traits in the context of their evolutionary background.

Orphan worms and, homeless parasites enhance bilaterian diversity

Microscopic endoparasites belonging to the Phylum Myxozoa provide a striking example of how much there is still to be learned about the diversity of the Metazoa. Recent research on myxozoans has provided new insights into evolution within the Bilateria, revealing unparalleled levels of morphological simplification associated with parasitism, a home for an orphan worm, and a hypothesis of the endosymbiotic origin(s) for extrusible intracellular organelles in myxozoans and cnidarians. In addition, discovery of the source of a devastating disease of salmonid fish has enabled researchers to identify two ancient clades within the Myxozoa, and has exposed new mysteries concerning myxozoan life-cycle evolution and evolutionary diversification. This plethora of new insights exemplifies the fundamental value of studying obscure organisms.

Modulation of the microbial ecology of the human colon by probiotics, prebiotics and synbiotics to enhance human health: an overview of enabling science and potential applications

The application of probiotics and prebiotics to the manipulation of the microbial ecology of the human colon has recently seen many scientific advances. The sequencing of probiotic genomes is providing a wealth of new information on the biology of these microorganisms. In addition, we are learning more about the interactions of probiotics with human cells and with pathogenic bacteria. An alternative means of modulating the colonic microbial community is by the use of prebiotic oligosaccharides. Increasing knowledge of the metabolism of prebiotics by probiotics is allowing us to consider specifically targeting such dietary intervention tools at specific populatiori groups and specific disease states. (c) 2005 Federation of European Microbiological Societies. Published by Elsevier B.V. All rights reserved.

Human evolution, nutritional ecology and prebiotics in ancient diet

Modern studies of prebiotic non digestible carbohydrates continue to expand and demonstrate their colonic and systemic benefits. However, virtually nothing is known of their use among ancient populations. In this paper we discuss evidence for prebiotic use in the archaeological record from select areas of the world. It is suggested that members of our genus Homo would have had sufficient ecological opportunity to include prebiotic-bearing plants in diet as early as ~ 2 million years ago, but that significant dietary intake would not have taken place until the advent of technological advances that characterized the Upper Paleolithic of ~40,000 years ago. Throughout human evolution, hominid populations that diversified their diet to include prebiotic-bearing plants would have had a selective advantage over competitors.

A technique for evaluation of interactive evolutionary systems

Very large scale scheduling and planning tasks cannot be effectively addressed by fully automated schedule optimisation systems, since many key factors which govern 'fitness' in such cases are unformalisable. This raises the question of an interactive (or collaborative) approach, where fitness is assigned by the expert user. Though well-researched in the domains of interactively evolved art and music, this method is as yet rarely used in logistics. This paper concerns a difficulty shared by all interactive evolutionary systems (IESs), but especially those used for logistics or design problems. The difficulty is that objective evaluation of IESs is severely hampered by the need for expert humans in the loop. This makes it effectively impossible to, for example, determine with statistical confidence any ranking among a decent number of configurations for the parameters and strategy choices. We make headway into this difficulty with an Automated Tester (AT) for such systems. The AT replaces the human in experiments, and has parameters controlling its decision-making accuracy (modelling human error) and a built-in notion of a target solution which may typically be at odds with the solution which is optimal in terms of formalisable fitness. Using the AT, plausible evaluations of alternative designs for the IES can be done, allowing for (and examining the effects of) different levels of user error. We describe such an AT for evaluating an IES for very large scale planning.

RBF equalizer design using directional evolutionary multi-objective optimization

Whilst radial basis function (RBF) equalizers have been employed to combat the linear and nonlinear distortions in modern communication systems, most of them do not take into account the equalizer's generalization capability. In this paper, it is firstly proposed that the. model's generalization capability can be improved by treating the modelling problem as a multi-objective optimization (MOO) problem, with each objective based on one of several training sets. Then, as a modelling application, a new RBF equalizer learning scheme is introduced based on the directional evolutionary MOO (EMOO). Directional EMOO improves the computational efficiency of conventional EMOO, which has been widely applied in solving MOO problems, by explicitly making use of the directional information. Computer simulation demonstrates that the new scheme can be used to derive RBF equalizers with good performance not only on explaining the training samples but on predicting the unseen samples.

A hybridised evolutionary algorithm for multi-criterion minimum spanning tree problems

A hybridised and Knowledge-based Evolutionary Algorithm (KEA) is applied to the multi-criterion minimum spanning tree problems. Hybridisation is used across its three phases. In the first phase a deterministic single objective optimization algorithm finds the extreme points of the Pareto front. In the second phase a K-best approach finds the first neighbours of the extreme points, which serve as an elitist parent population to an evolutionary algorithm in the third phase. A knowledge-based mutation operator is applied in each generation to reproduce individuals that are at least as good as the unique parent. The advantages of KEA over previous algorithms include its speed (making it applicable to large real-world problems), its scalability to more than two criteria, and its ability to find both the supported and unsupported optimal solutions.