A spatial explanation for synchrony biases in perceptual grouping: Consequences for the temporal-binding hypothesis

If two images are shown in rapid sequential order, they are perceived as a single, fused image. Despite this, recent studies have revealed that fundamental perceptual processes are influenced by extremely brief temporal offsets in stimulus presentation. Some researchers have suggested that this is due to the action of a cortical temporal-binding mechanism, which would serve to keep multiple mental representations of one object distinct from those of other objects. There is now gathering evidence that these studies should be reassessed. This article describes evidence for sensitivity to fixational eye and head movements, which provides a purely spatial explanation for the earlier results. Taken in conjunction with other studies, the work serves to undermine the current body of behavioral evidence for a temporal-binding mechanism.

Likelihood-based estimation of the regression model with scrambled responses

A significant problem in the collection of responses to potentially sensitive questions, such as relating to illegal, immoral or embarrassing activities, is non-sampling error due to refusal to respond or false responses. Eichhorn & Hayre (1983) suggested the use of scrambled responses to reduce this form of bias. This paper considers a linear regression model in which the dependent variable is unobserved but for which the sum or product with a scrambling random variable of known distribution, is known. The performance of two likelihood-based estimators is investigated, namely of a Bayesian estimator achieved through a Markov chain Monte Carlo (MCMC) sampling scheme, and a classical maximum-likelihood estimator. These two estimators and an estimator suggested by Singh, Joarder & King (1996) are compared. Monte Carlo results show that the Bayesian estimator outperforms the classical estimators in almost all cases, and the relative performance of the Bayesian estimator improves as the responses become more scrambled.

On modifications to the long-term survival mixture model in the presence of competing risks

A mixture model for long-term survivors has been adopted in various fields such as biostatistics and criminology where some individuals may never experience the type of failure under study. It is directly applicable in situations where the only information available from follow-up on individuals who will never experience this type of failure is in the form of censored observations. In this paper, we consider a modification to the model so that it still applies in the case where during the follow-up period it becomes known that an individual will never experience failure from the cause of interest. Unless a model allows for this additional information, a consistent survival analysis will not be obtained. A partial maximum likelihood (ML) approach is proposed that preserves the simplicity of the long-term survival mixture model and provides consistent estimators of the quantities of interest. Some simulation experiments are performed to assess the efficiency of the partial ML approach relative to the full ML approach for survival in the presence of competing risks.

Hemichordates and deuterostome evolution: robust molecular phylogenetic support for a hemichordate plus echinoderm clade

Hemichordates were traditionally allied to the chordates, but recent molecular analyses have suggested that hemichordates are a sister group to the echinoderms, a relationship that has important consequences for the interpretation of the evolution of deuterostome body plans. However, the molecular phylogenetic analyses to date have not provided robust support for the hemichordate + echinoderm clade. We use a maximum likelihood framework, including the parametric bootstrap, to reanalyze DNA data from complete mitochondrial genomes and nuclear 18S rRNA. This approach provides the first statistically significant support for the hemichordate + echinoderm clade from molecular data. This grouping implies that the ancestral deuterostome had features that included an adult with a pharynx and a dorsal nerve cord and an indirectly developing dipleurula-like larva.

Characterisation of Australian isolates of Fusarium oxysporum f. sp cubense by DNA fingerprinting analysis

Genetic variation among Australian isolates of the fungus Fusarium oxysporum f. sp. cubense (Foc), which causes Fusarium wilt in banana, was examined using DNA amplification fingerprinting (DAF). Ninety-four isolates which represented Races 1, 2, 3, and 4, and vegetative compatibility groups (VCGs) 0120, 0124, 0125, 0128, 0129, 01211, 01213/16, and 01220 were analysed. The genetic relatedness among isolates within each VCG, and between the 8 different VCGs of Foc present in Australia was determined. The DNA fingerprint patterns were VCG-specific, with each VCG representing a unique genotype. The genetic similarity among isolates within each VCG ranged from 97% to 100%. Among the different VCGs of Foc, 3 major clusters were distinguished which corresponded with race. All Race 1 and 2 isolates (VCGs 0124, 0125, 0128, and 01220) were closely related and clustered together, the Race 3 isolates from Heliconia clustered separately, and all Race 4 isolates (VCGs 0120, 0129, 01211, and 01213/16) clustered together. Fifteen isolates from Alstonville, NSW, were characterised because although they were classified as Race 2 based on their recovery from cooking banana cultivars, they belonged in VCG 0124, which had previously contained only Race 1 isolates. The occurrence of more than one race within a VCG means that vegetative compatibility grouping cannot be used to assign pathotype to pathogenic race as previously thought. It was possible to distinguish the Race 1 and Race 2 isolates within VCG 0124 using DNA fingerprinting, as each race produced a unique DNA fingerprint pattern. Among the Australian isolates, DNA fingerprinting analysis identified 9 different VCGs and genotypes of Foc.

Modelling the Distribution of Ischaemic Stroke-Specific Survival Time Using an EM-based Mixture Approach with Random Effects Adjustment

A two-component survival mixture model is proposed to analyse a set of ischaemic stroke-specific mortality data. The survival experience of stroke patients after index stroke may be described by a subpopulation of patients in the acute condition and another subpopulation of patients in the chronic phase. To adjust for the inherent correlation of observations due to random hospital effects, a mixture model of two survival functions with random effects is formulated. Assuming a Weibull hazard in both components, an EM algorithm is developed for the estimation of fixed effect parameters and variance components. A simulation study is conducted to assess the performance of the two-component survival mixture model estimators. Simulation results confirm the applicability of the proposed model in a small sample setting. Copyright (C) 2004 John Wiley Sons, Ltd.

ANNA: A new prediction method for bioassessment programs

1. Cluster analysis of reference sites with similar biota is the initial step in creating River Invertebrate Prediction and Classification System (RIVPACS) and similar river bioassessment models such as Australian River Assessment System (AUSRIVAS). This paper describes and tests an alternative prediction method, Assessment by Nearest Neighbour Analysis (ANNA), based on the same philosophy as RIVPACS and AUSRIVAS but without the grouping step that some people view as artificial. 2. The steps in creating ANNA models are: (i) weighting the predictor variables using a multivariate approach analogous to principal axis correlations, (ii) calculating the weighted Euclidian distance from a test site to the reference sites based on the environmental predictors, (iii) predicting the faunal composition based on the nearest reference sites and (iv) calculating an observed/expected (O/E) analogous to RIVPACS/AUSRIVAS. 3. The paper compares AUSRIVAS and ANNA models on 17 datasets representing a variety of habitats and seasons. First, it examines each model's regressions for Observed versus Expected number of taxa, including the r(2), intercept and slope. Second, the two models' assessments of 79 test sites in New Zealand are compared. Third, the models are compared on test and presumed reference sites along a known trace metal gradient. Fourth, ANNA models are evaluated for western Australia, a geographically distinct region of Australia. The comparisons demonstrate that ANNA and AUSRIVAS are generally equivalent in performance, although ANNA turns out to be potentially more robust for the O versus E regressions and is potentially more accurate on the trace metal gradient sites. 4. The ANNA method is recommended for use in bioassessment of rivers, at least for corroborating the results of the well established AUSRIVAS- and RIVPACS-type models, if not to replace them.

Achieving the millennium development goals for health - Cost effectiveness analysis of strategies for. maternal and neonatal health in developing countries

Objective To determine the costs and benefits of interventions for maternal and newborn health to assess the appropriateness of current strategies and guide future plans to attain the millennium development goals. Design Cost effectiveness analysis. Setting Two regions classified by the World Health Organization according to their epidemiological grouping: Afr-E, those countries in sub-Saharan Africa with very high adult and high child mortality, and Sear-D, comprising countries in South East Asia with high adult and high child mortality. Data sources Effectiveness data from several sources, including trials, observational studies, and expert opinion. For resource inputs, quantifies came from WHO guidelines, literature, and expert opinion, and prices from the WHO choosing interventions that are cost effective database. Main outcome measures Cost per disability adjusted life year (DALY) averted in year 2000 international dollars. Results The most cost effective mix of interventions was similar in Afr-E and Sear-D. These were the community based newborn care package, followed by antenatal care (tetanus toxoid, screening for pre-eclampsia, screening and treatment of asymptomatic bacteriuria and syphilis); skilled attendance at birth, offering first level maternal and neonatal care around childbirth; and emergency obstetric and neonatal care around and after birth. Screening and treatment of maternal syphilis, community based management of neonatal pneumonia, and steroids given during the antenatal period were relatively less cost effective in Sear-D. Scaling up all of the included interventions to 95% coverage would halve neonatal and maternal deaths. Conclusion Preventive interventions at the community level for newborn babies and at the primary care level for mothers and newborn babies are extremely cost effective, but the millennium development goals for maternal and child health will not be achieved without universal access to clinical services as well.

High-breakdown linear discriminant analysis

The classification rules of linear discriminant analysis are defined by the true mean vectors and the common covariance matrix of the populations from which the data come. Because these true parameters are generally unknown, they are commonly estimated by the sample mean vector and covariance matrix of the data in a training sample randomly drawn from each population. However, these sample statistics are notoriously susceptible to contamination by outliers, a problem compounded by the fact that the outliers may be invisible to conventional diagnostics. High-breakdown estimation is a procedure designed to remove this cause for concern by producing estimates that are immune to serious distortion by a minority of outliers, regardless of their severity. In this article we motivate and develop a high-breakdown criterion for linear discriminant analysis and give an algorithm for its implementation. The procedure is intended to supplement rather than replace the usual sample-moment methodology of discriminant analysis either by providing indications that the dataset is not seriously affected by outliers (supporting the usual analysis) or by identifying apparently aberrant points and giving resistant estimators that are not affected by them.

Numerical and experimental study of a homogenizer impinging jet

High-pressure homogenization is a key unit operation used to disrupt cells containing intracellular bioproducts. Modeling and optimization of this unit are restrained by a lack of information on the flow conditions within a homogenizer value. A numerical investigation of the impinging radial jet within a homogenizer value is presented. Results for a laminar and turbulent (k-epsilon turbulent model) jet are obtained using the PHOENICS finite-volume code. Experimental measurement of the stagnation region width and correlation of the cell disruption efficiency with jet stagnation pressure both indicate that the impinging jet in the homogenizer system examined is likely to be laminar under normal operating conditions. Correlation of disruption data with laminar stagnation pressure provides a better description of experimental variability than existing correlations using total pressure drop or the grouping 1/Y(2)h(2).

Effect of body composition at selection on reproductive development in large white gilts

Fifty-four Large White gilts were used to determine the effect of body composition at selection (145 d of age) on the onset of puberty and subsequent reproductive development until 202 d of age. Gilts were assigned to one of three groups based on their backfat depth at selection: 10 to 12 mm (L), 13 to 15 mm (M), and 16 to 18 mm (F). All of the F gilts, 92% of the M gilts, and 67% of the L gilts reached puberty by slaughter at 202 d of age. Data from a subgroup (first 67% to reach puberty in each group; L = Lp, M = Mp, and F = Fp) was also used. The M (Mp) and F (Fp) gilts reached puberty at 172 d (166 d) and 170 d (166 d) of age, respectively, but the L (Lp) gilts at 184.5 d were 12 d (18 d) older than M(P < .05), Mp(P < .001), and F(P < .01), Fp (P < .001) gilts. The Lp (97.68 kg) and Mp (98.33 kg) gilts were lighter (P < .01) than Fp (108.72 kg) gilts at puberty. There were no differences (P < .05) among the L, M, and F gilts in terms of backfat depth or weight at puberty. The L (Lp) gilts had a mean of 1.16 (1.75) estrous cycles, which was lower (P < .01) than for M (Mp) and (P < .01) F (Fp) gilts, with 1.96 (2.29) and 2.25 (2.33) cycles, respectively. L (Lp) gilts had fewer (P < .05) follicles, 13.14 (12.63), than either M (Mp), 19.08 (18.71), or F (Fp), 18.25 (17.42) gilts. The number of corpora lutea was not influenced (P > .05) by grouping at selection, but Fp gilts had fewer (P < .05) corpora lutea than Mp or Fp gilts. Live weight at slaughter was not influenced (P > .10) by grouping at selection or subgrouping at puberty. The L gilts with a mean of 18.05 mm of backfat at slaughter were leaner (P < .05) than the F (21.66 mm) but not (P > .10) the M gilts (19.41 mm). Subgrouping had no effect. Fat deposition and protein deposition were higher (P < .05) in those animals that attained puberty. We conclude that the rate of fat and protein deposition seems to be one of the determinants of puberty attainment.