Temporal precision of interceptive action: differential effects of target size and speed

The duration of movements made to intercept moving targets decreases and movement speed increases when interception requires greater temporal precision. Changes in target size and target speed can have the same effect on required temporal precision, but the response to these changes differs: changes in target speed elicit larger changes in response speed. A possible explanation is that people attempt to strike the target in a central zone that does not vary much with variation in physical target size: the effective size of the target is relatively constant over changes in physical size. Three experiments are reported that test this idea. Participants performed two tasks: (1) strike a moving target with a bat moved perpendicular to the path of the target; (2) press on a force transducer when the target was in a location where it could be struck by the bat. Target speed was varied and target size held constant in experiment 1. Target speed and size were co-varied in experiment 2, keeping the required temporal precision constant. Target size was varied and target speed held constant in experiment 3 to give the same temporal precision as experiment 1. Duration of hitting movements decreased and maximum movement speed increased with increases in target speed and/or temporal precision requirements in all experiments. The effects were largest in experiment 1 and smallest in experiment 3. Analysis of a measure of effective target size (standard deviation of strike locations on the target) failed to support the hypothesis that performance differences could be explained in terms of effective size rather than actual physical size. In the pressing task, participants produced greater peak forces and shorter force pulses when the temporal precision required was greater, showing that the response to increasing temporal precision generalizes to different responses. It is concluded that target size and target speed have independent effects on performance.

Epidemiological analysis of electroconvulsive therapy in Victoria, Australia

Objective: To determine the population-based utilization rate of electroconvulsive therapy (ECT) in Victoria between 1998-1999, to examine the characteristics of the ECT treated group, and to identify patient factors independently associated with differential rates of ECT treatment. Method: Electroconvulsive therapy is reported under statute in Victoria, Australia. Crude, age-adjusted and age-sex specific utilization rates were calculated using this statutory data for the 1998-1999 financial year and estimated mid-year populations from the Australian Bureau of Statistics. Descriptive characteristics of those treated with ECT were derived from the statutory data. Patient factors associated with an increased likelihood of ECT in the public sector were explored with logistic regression analysis, using non-ECT treated mental health patients from the Victorian Psychiatric Case Register as the reference population. Results: The crude treated-person and age-adjusted rates for the State (both public and private sectors) were 39.9 and 44.0 persons per 100 000 resident population per annum, respectively. The crude and age-adjusted administration rates were 330.3 and 362.6 ECT administrations per 100 000 resident population per annum, respectively. Age-sex specific rates varied by age and sex, with rates generally increasing with age and female sex. Overall, 62.8% of the treated group were women, 32.9% aged over 64, and 75.2% had depression. Diagnosis, age and sex each independently predicted ECT in the public sector, with diagnosis the most important factor, followed by age then sex. Conclusions: Despite decades of use, the appropriate rate of ECT utilization is still unclear. Further research should be directed at exploring the factors, including provider variables, determining ECT treatment.

Tissue-specific gene expression in soybean (Glycine max) detected by cDNA microarray analysis

We have constructed cDNA microarrays for soybean (Glycine max L. Merrill), containing approximately 4,100 Unigene ESTs derived from axenic roots, to evaluate their application and utility for functional genomics of organ differentiation in legumes. We assessed microarray technology by conducting studies to evaluate the accuracy of microarray data and have found them to be both reliable and reproducible in repeat hybridisations. Several ESTs showed high levels (>50 fold) of differential expression in either root or shoot tissue of soybean. A small number of physiologically interesting, and differentially expressed sequences found by microarray analysis were verified by both quantitative real-time RT-PCR and Northern blot analysis. There was a linear correlation (r(2) = 0.99, over 5 orders of magnitude) between microarray and quantitative real-time RT-PCR data. Microarray analysis of soybean has enormous potential not only for the discovery of new genes involved in tissue differentiation and function, but also to study the expression of previously characterised genes, gene networks and gene interactions in wild-type, mutant or transgenic; plants.

Latent class and genetic analysis does not support migraine with aura and migraine without aura as separate entities

Latent class and genetic analyses were used to identify subgroups of migraine sufferers in a community sample of 6,265 Australian twins (55% female) aged 25-36 who had completed an interview based on International Headache Society UHS) criteria. Consistent with prevalence rates from other population-based studies, 703 (20%) female and 250 (9%) male twins satisfied the IHS criteria for migraine without aura (MO), and of these, 432 (13%) female and 166 (6%) male twins satisfied the criteria for migraine with aura (MA) as indicated by visual symptoms. Latent class analysis (LCA) of IHS symptoms identified three major symptomatic classes, representing 1) a mild form of recurrent nonmigrainous headache, 2) a moderately severe form of migraine, typically without visual aura symptoms (although 40% of individuals in this class were positive for aura), and 3) a severe form of migraine typically with visual aura symptoms (although 24% of individuals were negative for aura). Using the LCA classification, many more individuals were considered affected to some degree than when using IHS criteria (35% vs. 13%). Furthermore, genetic model fitting indicated a greater genetic contribution to migraine using the LCA classification (heritability, h(2) =0.40; 95% CI, 0.29-0.46) compared with the IHS classification (h(2)=0.36; 95% CI, 0.22-0.42). Exploratory latent class modeling, fitting up to 10 classes, did not identify classes corresponding to either the IHS MO or MA classification. Our data indicate the existence of a continuum of severity, with MA more severe but not etiologically distinct from MO. In searching for predisposing genes, we should therefore expect to find some genes that may underlie all major recurrent headache subtypes, with modifying genetic or environmental factors that may lead to differential expression of the liability for migraine. (C) 2004 Wiley-Liss, Inc.

Non-linear analysis of the thermo-electro-mechanical behaviour of shear deformable FGM plates with piezoelectric actuators

This paper investigates the non-linear bending behaviour of functionally graded plates that are bonded with piezoelectric actuator layers and subjected to transverse loads and a temperature gradient based on Reddy's higher-order shear deformation plate theory. The von Karman-type geometric non-linearity, piezoelectric and thermal effects are included in mathematical formulations. The temperature change is due to a steady-state heat conduction through the plate thickness. The material properties are assumed to be graded in the thickness direction according to a power-law distribution in terms of the volume fractions of the constituents. The plate is clamped at two opposite edges, while the remaining edges can be free, simply supported or clamped. Differential quadrature approximation in the X-axis is employed to convert the partial differential governing equations and the associated boundary conditions into a set of ordinary differential equations. By choosing the appropriate functions as the displacement and stress functions on each nodal line and then applying the Galerkin procedure, a system of non-linear algebraic equations is obtained, from which the non-linear bending response of the plate is determined through a Picard iteration scheme. Numerical results for zirconia/aluminium rectangular plates are given in dimensionless graphical form. The effects of the applied actuator voltage, the volume fraction exponent, the temperature gradient, as well as the characteristics of the boundary conditions are also studied in detail. Copyright (C) 2004 John Wiley Sons, Ltd.

Differential expression of N-methyl-D-aspartate receptor NR2 isoforms in Alzheimer's disease

We have previously shown that the expression of NMDA receptor NR1 subunit mRNA splice variants in Alzheimer's disease (AD) brain varies according to regional susceptibility to pathological damage. Here we investigated the expression of the modulatory NR2 subunits of the NMDA receptor using quantitative RT-PCR to assay all NR2 isoforms. Significantly lower expression of NR2A and NR2B transcripts was found in susceptible regions of AD brain, whereas expression of NR2C and NR2D transcripts did not differ from that in controls. Western blot analysis confirmed a lower expression of the NR2A and NR2B isoforms at the protein level. The results suggest that NR2 subunit composition may modulate NMDA receptor-mediated excitotoxicity. NMDA receptor dysfunction might give rise to the regionally selective pattern of neuronal loss that is characteristic of AD.

Adaptive stepsize based on control theory for stochastic differential equations

The numerical solution of stochastic differential equations (SDEs) has been focussed recently on the development of numerical methods with good stability and order properties. These numerical implementations have been made with fixed stepsize, but there are many situations when a fixed stepsize is not appropriate. In the numerical solution of ordinary differential equations, much work has been carried out on developing robust implementation techniques using variable stepsize. It has been necessary, in the deterministic case, to consider the best choice for an initial stepsize, as well as developing effective strategies for stepsize control-the same, of course, must be carried out in the stochastic case. In this paper, proportional integral (PI) control is applied to a variable stepsize implementation of an embedded pair of stochastic Runge-Kutta methods used to obtain numerical solutions of nonstiff SDEs. For stiff SDEs, the embedded pair of the balanced Milstein and balanced implicit method is implemented in variable stepsize mode using a predictive controller for the stepsize change. The extension of these stepsize controllers from a digital filter theory point of view via PI with derivative (PID) control will also be implemented. The implementations show the improvement in efficiency that can be attained when using these control theory approaches compared with the regular stepsize change strategy. (C) 2004 Elsevier B.V. All rights reserved.

Numerical simulation of stochastic ordinary differential equations in biomathematical modelling

In this work we discuss the effects of white and coloured noise perturbations on the parameters of a mathematical model of bacteriophage infection introduced by Beretta and Kuang in [Math. Biosc. 149 (1998) 57]. We numerically simulate the strong solutions of the resulting systems of stochastic ordinary differential equations (SDEs), with respect to the global error, by means of numerical methods of both Euler-Taylor expansion and stochastic Runge-Kutta type. (C) 2003 IMACS. Published by Elsevier B.V. All rights reserved.

Numerical methods for strong solutions of stochastic differential equations: an overview

This paper gives a review of recent progress in the design of numerical methods for computing the trajectories (sample paths) of solutions to stochastic differential equations. We give a brief survey of the area focusing on a number of application areas where approximations to strong solutions are important, with a particular focus on computational biology applications, and give the necessary analytical tools for understanding some of the important concepts associated with stochastic processes. We present the stochastic Taylor series expansion as the fundamental mechanism for constructing effective numerical methods, give general results that relate local and global order of convergence and mention the Magnus expansion as a mechanism for designing methods that preserve the underlying structure of the problem. We also present various classes of explicit and implicit methods for strong solutions, based on the underlying structure of the problem. Finally, we discuss implementation issues relating to maintaining the Brownian path, efficient simulation of stochastic integrals and variable-step-size implementations based on various types of control.

Miscibility and phase separation in blends of phenolphthalein poly(aryl ether ketone) and poly(ethylene oxide): a differential scanning calorimetric study

Miscibility and phase separation in the blends of phenolphthalein poly(aryl ether ketone) (PPAEK) and poly(ethylene oxide) (PEO) were investigated by means of differential scanning calorimetry (DSC). The PPAEK/PEO blends prepared by solution casting from N,N-dimethylformamide (DMF) displayed single composition-dependent glass transition temperatures (T-g), intermediate between those of the pure components, suggesting that the blend system is miscible in the amorphous state at all compositions. All the blends underwent phase separation at higher temperatures and the system exhibited a lower critical solution temperature (LCST) behavior. A step-heating thermal analysis was designed to determine the phase boundaries with DSC. The significant changes in the thermal properties of blends were utilized to judge the mixing status for the blends and the phase diagram was thus established. (C) 2004 Elsevier B.V. All rights reserved.

A genetic estimation algorithm for parameters of stochastic ordinary differential equations

A generic method for the estimation of parameters for Stochastic Ordinary Differential Equations (SODEs) is introduced and developed. This algorithm, called the GePERs method, utilises a genetic optimisation algorithm to minimise a stochastic objective function based on the Kolmogorov-Smirnov statistic. Numerical simulations are utilised to form the KS statistic. Further, the examination of some of the factors that improve the precision of the estimates is conducted. This method is used to estimate parameters of diffusion equations and jump-diffusion equations. It is also applied to the problem of model selection for the Queensland electricity market. (C) 2003 Elsevier B.V. All rights reserved.

Wheat grain cooking process as investigated by modulated temperature differential scanning calorimetry

The thermal properties of soft and hard wheat grains, cooked in a steam pressure cooker, as a function of cooking temperature and time were investigated by modulated temperature differential scanning calorimetry (MTDSC). Four cooking temperatures (110, 120, 130 and 140 degrees C) and six cooking times (20, 40, 60, 80, 100 and 120 min) for each temperature were studied. It was found that typical non-reversible heat flow thermograms of cooked and uncooked wheat grains consisted of two endothermic baseline shifts localised around 40-50 degrees C and then 60-70 degrees C. The second peaks of non-reversible heat flow thermograms (60-70 degrees C) were associated with starch gelatinisation. The degree of gelatinisation was quantified based on these peaks. In this study, starch was completely gelatinised within 60-80 min for cooking temperatures at 110-120 degrees C and within 20 min for cooking temperatures at 130-140 degrees C. MTDSC detected reversible endothermic baseline shifts in most samples, localised broadly around 48-67 degrees C with changes in heat capacity ranging from 0.02 to 0.06 J/g per degrees C. These reversible endothermic baseline shifts are related to the glass transition, which occurs during starch gelatinisation. Data on the specific heat capacity of the cooked wheat samples are provided. (C) 2005 Elsevier Ltd. All rights reserved.

An experimental and finite element poroelastic creep response analysis of an intervertebral hydrogel disc model in axial compression

A hydrogel intervertebral disc (lVD) model consisting of an inner nucleus core and an outer anulus ring was manufactured from 30 and 35% by weight Poly(vinyl alcohol) hydrogel (PVA-H) concentrations and subjected to axial compression in between saturated porous endplates at 200 N for 11 h, 30 min. Repeat experiments (n = 4) on different samples (N = 2) show good reproducibility of fluid loss and axial deformation. An axisymmetric nonlinear poroelastic finite element model with variable permeability was developed using commercial finite element software to compare axial deformation and predicted fluid loss with experimental data. The FE predictions indicate differential fluid loss similar to that of biological IVDs, with the nucleus losing more water than the anulus, and there is overall good agreement between experimental and finite element predicted fluid loss. The stress distribution pattern indicates important similarities with the biological lVD that includes stress transference from the nucleus to the anulus upon sustained loading and renders it suitable as a model that can be used in future studies to better understand the role of fluid and stress in biological IVDs. (C) 2005 Springer Science + Business Media, Inc.