Parametric accelerated failure time models with random effects and an application to kidney transplant survival

Accelerated failure time models with a shared random component are described, and are used to evaluate the effect of explanatory factors and different transplant centres on survival times following kidney transplantation. Different combinations of the distribution of the random effects and baseline hazard function are considered and the fit of such models to the transplant data is critically assessed. A mixture model that combines short- and long-term components of a hazard function is then developed, which provides a more flexible model for the hazard function. The model can incorporate different explanatory variables and random effects in each component. The model is straightforward to fit using standard statistical software, and is shown to be a good fit to the transplant data. Copyright (C) 2004 John Wiley Sons, Ltd.

Rooting cuttings of Syringa vulgaris cv. Charles Joly and Corylus avellana cv. Aurea: the influence of stock plant pruning and shoot growth

The relationship between shoot growth and rooting was examined in two, 'difficult-to root' amenity trees, Syringa vulgaris L. cv. Charles Joly and Corylus avellana L. cv. Aurea. A range of treatments reflecting severity of pruning was imposed on field-grown stock prior to bud break. To minimise variation due to the numbers of buds that developed under different treatments, bud number was restricted to 30 per plant. Leafy cuttings were harvested at different stages of the active growth phase of each species. With Syringa, rooting decreased with later harvests, but loss of rooting potential was delayed in cuttings collected from the most severe pruning treatment. Rooting potential was associated with the extent of post-excision shoot growth on the cutting but regression analyses indicated that this relationship could not entirely explain the loss of rooting with time, nor the effects due to pruning. Similarly, in Corylus rooting was promoted by severe pruning, but the relationship between apical growth on the cutting and rooting was weaker than in Syringa, and only at the last harvest did growth play a critical role in determining rooting. Another unusual factor of the last harvest of Corylus was a bimodal distribution of roots per cutting, with very few rooted cuttings having less than five roots. This implies that, for this harvest at least, the potential of an individual cutting to root is probably not limited by the number of potential rooting sites.

Preventive maintenance models with random maintenance quality

In real-world environments it is usually difficult to specify the quality of a preventive maintenance (PM) action precisely. This uncertainty makes it problematic to optimise maintenance policy.-This problem is tackled in this paper by assuming that the-quality of a PM action is a random variable following a probability distribution. Two frequently studied PM models, a failure rate PM model and an age reduction PM model, are investigated. The optimal PM policies are presented and optimised. Numerical examples are also given.

Noncompetitive plasma biokinetics of deuterium-labeled natural and synthetic alpha-tocopherol in healthy men with an apoE4 genotype

Previous studies comparing the biokinetics of deuterated natural (RRR) and synthetic (all-rac) α-tocopherol (vitamin E) used a simultaneous ingestion or competitive uptake approach and reported relative bioavailability ratios close to 2:1, higher than the accepted biopotency ratio of 1.36:1. The aim of the current study was to compare the biokinetics of deuterated natural and synthetic vitamin E using a noncompetitive uptake model both before and after vitamin E supplementation in a distinct population. Healthy men (n = 10) carrying the apolipoprotein (apo)E4 genotype completed a randomized crossover study, comprised of two 4-wk treatments with 400 mg/d (RRR-α-tocopheryl and all-rac-α-tocopheryl acetate) with a 12-wk washout period between treatments. Before and after each treatment period, the subjects consumed a capsule containing 150 mg deuterated α-tocopheryl acetate in either the PRR or all-rac form depending on their treatment regimen. Blood was obtained up to 48 h after ingestion, and tocopherols analyzed by LC/MS. After deuterated all-rac administration, plasma deuterated tocopherol maximum concentrations and area under the concentration vs. time curves (AUC) were lower than those following RRR administration. The RRR:all-rac ratios determined from the deuterated biokinetic profiles (maximum concentration; C-max) and AUCs were 1.35:1 &PLUSMN; 0.17 and 1.33:1 &PLUSMN; 0.18, respectively. The 4-wk supplementation with either PRR or all-rac significantly increased plasma a-tocopherol concentrations (P < 0.001), but decreased the plasma response to newly absorbed deuterated RRR or all-rac α-tocopherol. Using a noncompetitive uptake approach, the relative bioavailability of natural to synthetic vitamin E in apoE4 males was close to the currently accepted biopotency ratio of 1.36:1.

Random number generation as an index of controlled processing

Random number generation (RNG) is a functionally complex process that is highly controlled and therefore dependent on Baddeley's central executive. This study addresses this issue by investigating whether key predictions from this framework are compatible with empirical data. In Experiment 1, the effect of increasing task demands by increasing the rate of the paced generation was comprehensively examined. As expected, faster rates affected performance negatively because central resources were increasingly depleted. Next, the effects of participants' exposure were manipulated in Experiment 2 by providing increasing amounts of practice on the task. There was no improvement over 10 practice trials, suggesting that the high level of strategic control required by the task was constant and not amenable to any automatization gain with repeated exposure. Together, the results demonstrate that RNG performance is a highly controlled and demanding process sensitive to additional demands on central resources (Experiment 1) and is unaffected by repeated performance or practice (Experiment 2). These features render the easily administered RNG task an ideal and robust index of executive function that is highly suitable for repeated clinical use.

Simulating global properties of electroencephalograms with minimal random neural networks

The human electroencephalogram (EEG) is globally characterized by a 1/f power spectrum superimposed with certain peaks, whereby the "alpha peak" in a frequency range of 8-14 Hz is the most prominent one for relaxed states of wakefulness. We present simulations of a minimal dynamical network model of leaky integrator neurons attached to the nodes of an evolving directed and weighted random graph (an Erdos-Renyi graph). We derive a model of the dendritic field potential (DFP) for the neurons leading to a simulated EEG that describes the global activity of the network. Depending on the network size, we find an oscillatory transition of the simulated EEG when the network reaches a critical connectivity. This transition, indicated by a suitably defined order parameter, is reflected by a sudden change of the network's topology when super-cycles are formed from merging isolated loops. After the oscillatory transition, the power spectra of simulated EEG time series exhibit a 1/f continuum superimposed with certain peaks. (c) 2007 Elsevier B.V. All rights reserved.

Towards the automatic reconstruction of dendritic trees using particle filters

The 3D reconstruction of a Golgi-stained dendritic tree from a serial stack of images captured with a transmitted light bright-field microscope is investigated. Modifications to the bootstrap filter are discussed such that the tree structure may be estimated recursively as a series of connected segments. The tracking performance of the bootstrap particle filter is compared against Differential Evolution, an evolutionary global optimisation method, both in terms of robustness and accuracy. It is found that the particle filtering approach is significantly more robust and accurate for the data considered.

Examining random number generators used in stochastic iteration algorithms

This paper investigates random number generators in stochastic iteration algorithms that require infinite uniform sequences. We take a simple model of the general transport equation and solve it with the application of a linear congruential generator, the Mersenne twister, the mother-of-all generators, and a true random number generator based on quantum effects. With this simple model we show that for reasonably contractive operators the theoretically not infinite-uniform sequences perform also well. Finally, we demonstrate the power of stochastic iteration for the solution of the light transport problem.

Enhancing change detection in low-quality surveillance footage using markov random fields

Urban surveillance footage can be of poor quality, partly due to the low quality of the camera and partly due to harsh lighting and heavily reflective scenes. For some computer surveillance tasks very simple change detection is adequate, but sometimes a more detailed change detection mask is desirable, eg, for accurately tracking identity when faced with multiple interacting individuals and in pose-based behaviour recognition. We present a novel technique for enhancing a low-quality change detection into a better segmentation using an image combing estimator in an MRF based model.

Trees outside forests and rural livelihoods: a study of Chitwan District, Nepal

Trees outside forests (TOF) in Nepal’s Terai have significantly increased over the past decade. The Chitwan District was one of the focus districts in the Terai Community Forestry Development Project that promoted a tree seedling distribution program. This paper examines the current position of tree integration on farmland and its contribution to livelihoods of rural households in this district. Interviews with local key informants, government and non-government agencies and woodbased industries, as well as an in-depth study of 32 households were used to describe the constraints faced by the households in management of trees on farmland. Most households cited disease, poor growth, lack of preferred tree species, lack of technical support, an uncertain tree market, and lack of financial support as constraints. Despite the important role of trees in subsistence and marketbased rural livelihood diversification, and the consequent reduction in pressure on national forests from on-farm trees, current government policies and practices fail to recognise the value of these trees. It is argued that there is substantial potential for improving on-farm trees to enhance rural livelihoods. A responsive service mechanism centred on tree growing households would help the management of tree resources on the farmland.

Neural networks for identification of nonlinear systems under random piecewise polynomial disturbances

The problem of identification of a nonlinear dynamic system is considered. A two-layer neural network is used for the solution of the problem. Systems disturbed with unmeasurable noise are considered, although it is known that the disturbance is a random piecewise polynomial process. Absorption polynomials and nonquadratic loss functions are used to reduce the effect of this disturbance on the estimates of the optimal memory of the neural-network model.