Estimating Two-Stage Models for Genetic Influences on Alcohol, Tobacco or Drug Use Initiation and Dependence Vulnerability in Twin and Family Data

Genetic research on risk of alcohol, tobacco or drug dependence must make allowance for the partial overlap of risk-factors for initiation of use, and risk-factors for dependence or other outcomes in users. Except in the extreme cases where genetic and environmental risk-factors for initiation and dependence overlap completely or are uncorrelated, there is no consensus about how best to estimate the magnitude of genetic or environmental correlations between Initiation and Dependence in twin and family data. We explore by computer simulation the biases to estimates of genetic and environmental parameters caused by model misspecification when Initiation can only be defined as a binary variable. For plausible simulated parameter values, the two-stage genetic models that we consider yield estimates of genetic and environmental variances for Dependence that, although biased, are not very discrepant from the true values. However, estimates of genetic (or environmental) correlations between Initiation and Dependence may be seriously biased, and may differ markedly under different two-stage models. Such estimates may have little credibility unless external data favor selection of one particular model. These problems can be avoided if Initiation can be assessed as a multiple-category variable (e.g. never versus early-onset versus later onset user), with at least two categories measurable in users at risk for dependence. Under these conditions, under certain distributional assumptions., recovery of simulated genetic and environmental correlations becomes possible, Illustrative application of the model to Australian twin data on smoking confirmed substantial heritability of smoking persistence (42%) with minimal overlap with genetic influences on initiation.

On the fast approximation of Green's functions in MPIE formulations for planar layered media

The numerical implementation of the complex image approach for the Green's function of a mixed-potential integralequation formulation is examined and is found to be limited to low values of k(0) rho (in this context k(0) rho = 2 pirho/ lambda(0), where rho is the distance between the source and the field points of the Green's function and lambda(0) is the free space wavelength). This is a clear limitation for problems of large dimension or high frequency where this limit is easily exceeded. This paper examines the various strategies and proposes a hybrid method whereby most of the above problems can be avoided. An efficient integral method that is valid for large k(0) rho is combined with the complex image method in order to take advantage of the relative merits of both schemes. It is found that a wide overlapping region exists between the two techniques allowing a very efficient and consistent approach for accurately calculating the Green's functions. In this paper, the method developed for the computation of the Green's function is used for planar structures containing both lossless and lossy media.

Complex language functions and subcortical mechanisms: evidence from Huntington's disease and patients with non-thalamic subcortical lesions

The neuropathological changes associated with Huntington's disease (HD) are most marked in the head of the caudate nucleus and, to a lesser extent, in the putamen and globus pallidus, suggesting that at least part of the language impairments found in patients with HD may result from non-thalamic subcortical (NTS) pathology. The present study aimed to test the hypothesis that a signature profile of impaired language functions is found in patients who have sustained damage to the non-thalamic subcortex, either focally induced or resulting from neurodegenerative pathology. The language abilities of a group of patients with Huntington's disease (n=13) were compared with those of an age- and education-matched group of patients with chronic NTS lesions following stroke (n=13) and a non-neurologically impaired control group (n=13). The three groups were compared on language tasks that assessed both primary and more complex language abilities. The primary language battery consisted of The Western Aphasia Battery and The Boston Naming Test, whilst the more complex cognitive-linguistic battery employed selected subtests from The Test of Language Competence-Expanded, The Test of Word Knowledge and The Word Test-Revised. On many of the tests of primary language function from the Western Aphasia Battery, both the HD and NTS participants performed in a similar manner to the control participants. The language performances of the HD participants were significantly more impaired (p<0.05 using modified Bonferroni adjustments) than the control group, however, on various lexico-semantic tasks (e. g. the Boston Naming Test and providing definitions), on both single-word and sentence-level generative tasks (e. g. category fluency and formulating sentences), and on tasks which required interpretation of ambiguous, figurative and inferential meaning. The difficulties that patients with HD experienced with tasks assessing complex language abilities were strikingly similar, both qualitatively and quantitatively, to the language profile produced by NTS participants. The results provide evidence to suggest that a signature language profile is associated with damage to the non-thalamic subcortex resulting from either focal neurological insult or a degenerative disease.

Estimating and evaluating the statistics of gapped local-alignment scores

We present a novel maximum-likelihood-based algorithm for estimating the distribution of alignment scores from the scores of unrelated sequences in a database search. Using a new method for measuring the accuracy of p-values, we show that our maximum-likelihood-based algorithm is more accurate than existing regression-based and lookup table methods. We explore a more sophisticated way of modeling and estimating the score distributions (using a two-component mixture model and expectation maximization), but conclude that this does not improve significantly over simply ignoring scores with small E-values during estimation. Finally, we measure the classification accuracy of p-values estimated in different ways and observe that inaccurate p-values can, somewhat paradoxically, lead to higher classification accuracy. We explain this paradox and argue that statistical accuracy, not classification accuracy, should be the primary criterion in comparisons of similarity search methods that return p-values that adjust for target sequence length.

Evaluation of line-transect sampling for estimating koala abundance in the Pine Rivers Shire, south-east Queensland

Distance sampling using line transects has not been previously used or tested for estimating koala abundance. In July 2001, a pilot survey was conducted to compare the use of line transects with strip transects for estimating koala abundance. Both methods provided a similar estimate of density. On the basis of the results of the pilot survey, the distribution and abundance of koalas in the Pine Rivers Shire, south-east Queensland, was determined using line-transect sampling. In total, 134 lines (length 64 km) were used to sample bushland areas. Eighty-two independent koalas were sighted. Analysis of the frequency distribution of sighting distances using the software program DISTANCE enabled a global detection function to be estimated for survey sites in bushland areas across the Shire. Abundance in urban parts of the Shire was estimated from densities obtained from total counts at eight urban sites that ranged from 26 to 51 ha in size. Koala abundance in the Pine Rivers Shire was estimated at 4584 (95% confidence interval, 4040-5247). Line-transect sampling is a useful method for estimating koala abundance provided experienced koala observers are used when conducting surveys.

Is maximizing resilience compatible with established ecological goal functions?

Cropp and Gabric [Ecosystem adaptation: do ecosystems maximise resilience? Ecology. In press] used a simple phytoplanktonzooplankton-nutrient model and a genetic algorithm to determine the parameter values that would maximize the value of certain goal functions. These goal functions were to maximize biomass, maximize flux, maximize flux to biomass ratio, and maximize resilience. It was found that maximizing goal functions maximized resilience. The objective of this study was to investigate whether the Cropp and Gabric [Ecosystem adaptation: do ecosystems maximise resilience? Ecology. In press] result was indicative of a general ecosystem principle, or peculiar to the model and parameter ranges used. This study successfully replicated the Cropp and Gabric [Ecosystem adaptation: do ecosystems maximise resilience? Ecology. In press] experiment for a number of different model types, however, a different interpretation of the results is made. A new metric, concordance, was devised to describe the agreement between goal functions. It was found that resilience has the highest concordance of all goal functions trialled. for most model types. This implies that resilience offers a compromise between the established ecological goal functions. The parameter value range used is found to affect the parameter versus goal function relationships. Local maxima and minima affected the relationship between parameters and goal functions, and between goal functions. (C) 2003 Elsevier B.V. All rights reserved.

A practical method of estimating energy expenditure during tennis play

This study aimed to develop a practical method of estimating energy expenditure (EE) during tennis. Twenty-four elite female tennis players first completed a tennis-specific graded test in which five different intensity levels were applied randomly. Each intensity level was intended to simulate a game of singles tennis and comprised six 14 s periods of activity alternated with 20 s of active rest. Oxygen consumption (VO2) and heart rate (HR) were measured continuously and each player's rate of perceived exertion (RPE) was recorded at the end of each intensity level. Rate of energy expenditure (EEVO2) during the test was calculated using the sum of VO2 during play and the 'O-2 debt' during recovery, divided by the duration of the activity. There were significant individual linear relationships between EEVO2 and RPE, EEVO2 and HR, (rgreater than or equal to0.89 rgreater than or equal to0.93; p

Unsaturated diffusivity functions for concrete derived from NMR images

Deterioration of concrete or reinforcing steel through excessive contaminant concentration is often the result of repeated wetting and drying cycles. At each cycle, the absorption of water carries new contaminants into the unsaturated concrete. Nuclear Magnetic Resonance (NMR) is used with large concrete samples to observe the shape of the wetting profile during a simple one-dimensional wetting process. The absorption of water by dry concrete is modelled by a nonlinear diffusion equation with the unsaturated hydraulic diffusivity being a strongly nonlinear function of the moisture content. Exponential and power functions are used for the hydraulic diffusivity and corresponding solutions of the diffusion equation adequately predict the shape of the experimental wetting profile. The shape parameters, describing the wetting profile, vary little between different blends and are relatively insensitive to subsequent re-wetting experiments allowing universal parameters to be suggested for these concretes.

Mapping the royal road and other hierarchical functions

In this paper we present a technique for visualising hierarchical and symmetric, multimodal fitness functions that have been investigated in the evolutionary computation literature. The focus of this technique is on landscapes in moderate-dimensional, binary spaces (i.e., fitness functions defined over {0, 1}(n), for n less than or equal to 16). The visualisation approach involves an unfolding of the hyperspace into a two-dimensional graph, whose layout represents the topology of the space using a recursive relationship, and whose shading defines the shape of the cost surface defined on the space. Using this technique we present case-study explorations of three fitness functions: royal road, hierarchical-if-and-only-if (H-IFF), and hierarchically decomposable functions (HDF). The visualisation approach provides an insight into the properties of these functions, particularly with respect to the size and shape of the basins of attraction around each of the local optima.

Estimating Local Part Thickness in Midplane Meshes for Finite Element Analysis

Within the development of motor vehicles, crash safety (e.g. occupant protection, pedestrian protection, low speed damageability), is one of the most important attributes. In order to be able to fulfill the increased requirements in the framework of shorter cycle times and rising pressure to reduce costs, car manufacturers keep intensifying the use of virtual development tools such as those in the domain of Computer Aided Engineering (CAE). For crash simulations, the explicit finite element method (FEM) is applied. The accuracy of the simulation process is highly dependent on the accuracy of the simulation model, including the midplane mesh. One of the roughest approximations typically made is the actual part thickness which, in reality, can vary locally. However, almost always a constant thickness value is defined throughout the entire part due to complexity reasons. On the other hand, for precise fracture analysis within FEM, the correct thickness consideration is one key enabler. Thus, availability of per element thickness information, which does not exist explicitly in the FEM model, can significantly contribute to an improved crash simulation quality, especially regarding fracture prediction. Even though the thickness is not explicitly available from the FEM model, it can be inferred from the original CAD geometric model through geometric calculations. This paper proposes and compares two thickness estimation algorithms based on ray tracing and nearest neighbour 3D range searches. A systematic quantitative analysis of the accuracy of both algorithms is presented, as well as a thorough identification of particular geometric arrangements under which their accuracy can be compared. These results enable the identification of each technique’s weaknesses and hint towards a new, integrated, approach to the problem that linearly combines the estimates produced by each algorithm.

Health education: the role and functions of the specialist and the generalist

Education for health is a process in which all public health and medical care personnel are involved. People learn both formally (planned learning experiences) and informally (unplanned learning experiences). Since the patient, the client, the consummer and the community expect public health and medical care personnel to assist them with health and disease issues and problems, the response of the professional "educates" the customer whether the professional intends to educate or not. Therefore, it is incumbent on all public health and medical care professionals to understand their educational functions and their role in health education. It is also important that the role of the specialist in education be clear. The specialist, as to all other specialists, has an in-depth knowledge of his area of expertise, i.e., the teaching/learning process; s/he may function as a consultant to others to enhance the educational potential of their role or s/he may work with a team or with communities or groups of patients. Specific competencies and knowledge are required of the health education specialist; and there is a body of learning and social change theory which provides a frame of reference for planning, implementing and evaluating educational programs. Working with others to enhance their potential to learn and to make informed decisions about health/disease issues is the hallmark of the health education specialist.

Equilibrium self-assembly of colloids with distinct interaction sites: Thermodynamics, percolation, and cluster distribution functions

We calculate the equilibrium thermodynamic properties, percolation threshold, and cluster distribution functions for a model of associating colloids, which consists of hard spherical particles having on their surfaces three short-ranged attractive sites (sticky spots) of two different types, A and B. The thermodynamic properties are calculated using Wertheim's perturbation theory of associating fluids. This also allows us to find the onset of self-assembly, which can be quantified by the maxima of the specific heat at constant volume. The percolation threshold is derived, under the no-loop assumption, for the correlated bond model: In all cases it is two percolated phases that become identical at a critical point, when one exists. Finally, the cluster size distributions are calculated by mapping the model onto an effective model, characterized by a-state-dependent-functionality (f) over bar and unique bonding probability (p) over bar. The mapping is based on the asymptotic limit of the cluster distributions functions of the generic model and the effective parameters are defined through the requirement that the equilibrium cluster distributions of the true and effective models have the same number-averaged and weight-averaged sizes at all densities and temperatures. We also study the model numerically in the case where BB interactions are missing. In this limit, AB bonds either provide branching between A-chains (Y-junctions) if epsilon(AB)/epsilon(AA) is small, or drive the formation of a hyperbranched polymer if epsilon(AB)/epsilon(AA) is large. We find that the theoretical predictions describe quite accurately the numerical data, especially in the region where Y-junctions are present. There is fairly good agreement between theoretical and numerical results both for the thermodynamic (number of bonds and phase coexistence) and the connectivity properties of the model (cluster size distributions and percolation locus).