A novel genetic locus for low renin hypertension: familial hyperaldosteronism type II maps to chromosome 7 (7p22)

Familial hyperaldosteronism type II (FH-II) is caused by adrenocortical hyperplasia or aldosteronoma or both and is frequently transmitted in an autosomal dominant fashion. Unlike FH type I (FI-I-I), which results from fusion of the CYP11B1 and CYP11B2 genes, hyperaldosteronism in FH-II is not glucocorticoid remediable. A large family with FH-II was used for a genome wide search and its members were evaluated by measuring the aldosterone:renin ratio. In those with an increased ratio, FH-II was confirmed by fludrocortisone suppression testing. After excluding most of the genome, genetic linkage was identified with a maximum two point lod score of 3.26 at theta =0, between FH-II in this family and the polymorphic markers D7S511, D7S517, and GATA24F03 on chromosome 7,a region that corresponds to cytogenetic band 7p22. This is the first identified locus for FH-II; its molecular elucidation may provide further insight into the aetiology of primary aldosteronism.

Minimum-order stable recursive filter design via the genetic algorithm approach

In this paper, the minimum-order stable recursive filter design problem is proposed and investigated. This problem is playing an important role in pipeline implementation sin signal processing. Here, the existence of a high-order stable recursive filter is proved theoretically, in which the upper bound for the highest order of stable filters is given. Then the minimum-order stable linear predictor is obtained via solving an optimization problem. In this paper, the popular genetic algorithm approach is adopted since it is a heuristic probabilistic optimization technique and has been widely used in engineering designs. Finally, an illustrative example is sued to show the effectiveness of the proposed algorithm.

Using stochastic dynamic programming to determine optimal fire management for Banksia ornata

1. A model of the population dynamics of Banksia ornata was developed, using stochastic dynamic programming (a state-dependent decision-making tool), to determine optimal fire management strategies that incorporate trade-offs between biodiversity conservation and fuel reduction. 2. The modelled population of B. ornata was described by its age and density, and was exposed to the risk of unplanned fires and stochastic variation in germination success. 3. For a given population in each year, three management strategies were considered: (i) lighting a prescribed fire; (ii) controlling the incidence of unplanned fire; (iii) doing nothing. 4. The optimal management strategy depended on the state of the B. ornata population, with the time since the last fire (age of the population) being the most important variable. Lighting a prescribed fire at an age of less than 30 years was only optimal when the density of seedlings after a fire was low (< 100 plants ha(-1)) or when there were benefits of maintaining a low fuel load by using more frequent fire. 5. Because the cost of management was assumed to be negligible (relative to the value of the persistence of the population), the do-nothing option was never the optimal strategy, although lighting prescribed fires had only marginal benefits when the mean interval between unplanned fires was less than 20-30 years.

Assisting decision-making in Queensland barley production through chance constrained programming

A chance constrained programming model is developed to assist Queensland barley growers make varietal and agronomic decisions in the face of changing product demands and volatile production conditions. Unsuitable or overlooked in many risk programming applications, the chance constrained programming approach nonetheless aptly captures the single-stage decision problem faced by barley growers of whether to plant lower-yielding but potentially higher-priced malting varieties, given a particular expectation of meeting malting grade standards. Different expectations greatly affect the optimal mix of malting and feed barley activities. The analysis highlights the suitability of chance constrained programming to this specific class of farm decision problem.

Modelling socially optimal land allocations for sugar cane growing in North Queensland: a linked mathematical programming and choice modelling study

A modelling framework is developed to determine the joint economic and environmental net benefits of alternative land allocation strategies. Estimates of community preferences for preservation of natural land, derived from a choice modelling study, are used as input to a model of agricultural production in an optimisation framework. The trade-offs between agricultural production and environmental protection are analysed using the sugar industry of the Herbert River district of north Queensland as an example. Spatially-differentiated resource attributes and the opportunity costs of natural land determine the optimal tradeoffs between production and conservation for a range of sugar prices.

Social structures, genetic structures and dispersal strategies in Australian rabbit (Oryctolagus cuniculus) populations

In this study, the pattern of movement of young male and female rabbits and the genetic structures present in adult male and female populations in four habitats was examined. The level of philopatry in young animals was found to vary between 18-90% for males and 32-95% for females in different populations. It was skewed, with more males dispersing than females in some but not all populations. Analysis of allozyme data using spatial autocorrelation showed that adult females from the same social group, unlike males, were significantly related in four of the five populations studied. Changes in genetic structure and rate of dispersal were measured before and during the recovery of a population that was artificially reduced in size. There were changes in the rate and distance of dispersal with density and sex. Subadults of both sexes moved further in the first year post crash (low density) than in the following years. While the level of dispersal for females was lower than that of the males for the first 3 years, thereafter (high density) both sexes showed similar, low levels of dispersal (20%). The density at which young animals switch behaviour between dispersal and philopatry differed for males and females. The level of genetic structuring in adult females was high in the precrash population, reduced in the first year post crash and undetectable in the second year. Dispersal behaviour of rabbits both affects the genetic structure of the population and changes with conditions. Over a wide range of levels of philopatry, genetic structuring is present in the adult female, but not the male population. Consequently, though genetic structuring is present, it does not lead to inbreeding. More long-distance movements are found in low-density populations, even though vacant warrens are available near birth warrens. The distances moved decreased as density increased. Calculation of the effective population size (N-e) shows that changes in dispersal distance offset changes in density, so that N-e remains constant.

Ecological interface design for pasteurizer II: A process description of semantic mapping

Ecological interface design (EID) is proving to be a promising approach to the design of interfaces for complex dynamic systems. Although the principles of EID and examples of its effective use are widely available, few readily available examples exist of how the individual displays that constitute an ecological interface are developed. This paper presents the semantic mapping process within EID in the context of prior theoretical work in this area. The semantic mapping process that was used in developing an ecological interface for the Pasteurizer II microworld is outlined, and the results of an evaluation of the ecological interface against a more conventional interface are briefly presented. Subjective reports indicate features of the ecological interface that made it particularly valuable for participants. Finally, we outline the steps of an analytic process for using EID. The findings presented here can be applied in the design of ecological interfaces or of configural displays for dynamic processes.

Genetic algorithms for design of liquid retaining structure

In this paper, genetic algorithm (GA) is applied to the optimum design of reinforced concrete liquid retaining structures, which comprise three discrete design variables, including slab thickness, reinforcement diameter and reinforcement spacing. GA, being a search technique based on the mechanics of natural genetics, couples a Darwinian survival-of-the-fittest principle with a random yet structured information exchange amongst a population of artificial chromosomes. As a first step, a penalty-based strategy is entailed to transform the constrained design problem into an unconstrained problem, which is appropriate for GA application. A numerical example is then used to demonstrate strength and capability of the GA in this domain problem. It is shown that, only after the exploration of a minute portion of the search space, near-optimal solutions are obtained at an extremely converging speed. The method can be extended to application of even more complex optimization problems in other domains.

Formal methods within a totally functional approach to programming

Taking functional programming to its extremities in search of simplicity still requires integration with other development (e.g. formal) methods. Induction is the key to deriving and verifying functional programs, but can be simplified through packaging proofs with functions, particularly folds, on data (structures). Totally Functional Programming avoids the complexities of interpretation by directly representing data (structures) as platonic combinators - the functions characteristic to the data. The link between the two simplifications is that platonic combinators are a kind of partially-applied fold, which means that platonic combinators inherit fold-theoretic properties, but with some apparent simplifications due to the platonic combinator representation. However, despite observable behaviour within functional programming that suggests that TFP is widely-applicable, significant work remains before TFP as such could be widely adopted.