Spatial data mining for enhanced soil map modelling

The principle of using induction rules based on spatial environmental data to model a soil map has previously been demonstrated Whilst the general pattern of classes of large spatial extent and those with close association with geology were delineated small classes and the detailed spatial pattern of the map were less well rendered Here we examine several strategies to improve the quality of the soil map models generated by rule induction Terrain attributes that are better suited to landscape description at a resolution of 250 m are introduced as predictors of soil type A map sampling strategy is developed Classification error is reduced by using boosting rather than cross validation to improve the model Further the benefit of incorporating the local spatial context for each environmental variable into the rule induction is examined The best model was achieved by sampling in proportion to the spatial extent of the mapped classes boosting the decision trees and using spatial contextual information extracted from the environmental variables.

The large-scale distribution of neutral hydrogen in the Fornax region

Using data from the H I Parkes All Sky Survey (HIPASS), we have searched for neutral hydrogen in galaxies in a region similar to25x25 deg(2) centred on NGC 1399, the nominal centre of the Fornax cluster. Within a velocity search range of 300-3700 km s(-1) and to a 3sigma lower flux limit of similar to40 mJy, 110 galaxies with H I emission were detected, one of which is previously uncatalogued. None of the detections has early-type morphology. Previously unknown velocities for 14 galaxies have been determined, with a further four velocity measurements being significantly dissimilar to published values. Identification of an optical counterpart is relatively unambiguous for more than similar to90 per cent of our H I galaxies. The galaxies appear to be embedded in a sheet at the cluster velocity which extends for more than 30degrees across the search area. At the nominal cluster distance of similar to20 Mpc, this corresponds to an elongated structure more than 10 Mpc in extent. A velocity gradient across the structure is detected, with radial velocities increasing by similar to500 km s(-1) from south-east to north-west. The clustering of galaxies evident in optical surveys is only weakly suggested in the spatial distribution of our H I detections. Of 62 H I detections within a 10degrees projected radius of the cluster centre, only two are within the core region (projected radius

The evidence for better health from health assessments: A large clustered randomised controlled trial

Aim: To test the efficacy of a comprehensive health assessment using the CHAP tool in adults with an intellectual disability (ID). Method: A cluster randomised control design was used. The intervention group received the CHAP, while the control group received usual care. This tool directed carers to gather a health history, which was reviewed by the person’s general practitioner (GP) who completed a medical examination and a healthcare plan. The tool acted as an advocacy tool, a ticket-of-entry to the GPs surgery and educated the GP and the caregiver about the deficits in the healthcare of adults with ID. The healthcare of the participants was followed for one-year after intervention by the collection of data from GP and service providers’ notes. Also interviews were performed with all those involved. Results: We obtained a representative sample of  adults with ID (RR%). We found the intervention group received a significant increase in many health promotion/disease prevention activities e.g. hearing screening was  times and a Pap smear was  times more likely to have occurred in the intervention groups.We also found a trend towards earlier detection of disease. Conclusions: The CHAP process improves the provision of health screening/promotion activities and should be implemented.

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.

Relating body mass index to figural stimuli: population-based normative data for Caucasians

OBJECTIVE: To establish body mass index (BMI) norms for standard figural stimuli using a large Caucasian population-based sample. In addition, we sought to determine the effectiveness of the figural stimuli to identify individuals as obese or thin. DESIGN: All Caucasian twins born in Virginia between 1915 and 1971 were identified by public birth record. In addition, 3347 individual twins responded to a letter published in the newsletter of the American Association of Retired Persons (AARP). All adult twins (aged 18 and over) from both of these sources and their family members were mailed a 16 page 'Health and Lifestyle' questionnaire. SUBJECTS: BMI and silhouette data were available on 16 728 females and 11 366 males ranging in age from 18- 100. MEASUREMENTS: Self-report information on height-weight, current body size, desired body size and a discrepancy score using standard figural stimuli. RESULTS: Gender- and age-specific norms are presented linking BMI to each of the figural stimuli. Additional norms for desired body size and discrepancy scores are also presented. Receiver operating curves (ROC) indicate that the figural stimuli are effective in classifying individuals as obese or thin. CONCLUSIONS: With the establishment of these norms, the silhouettes used in standard body image assessment can now be linked to BMI. Differences were observed between women and men in terms of desired body size and discrepancy scores, with women preferring smaller sizes. The figural stimuli are a robust technique for classifying individuals as obese or thin.

Changes in progesterone and testosterone during the breeding season of the large-footed myotis Myotis moluccarum (Microchiroptera : Vespertilionidae)

The reproductive biology of the large-footed myotis, Myotis moluccarum, was studied during the annual breeding season in southeast Queensland, Australia. Previous research has shown the species to be polyoestrous and monotoccous, producing two consecutive young with some degree of synchrony in late October to early November and again in late January to early February. Hormonal data was collected and observations of the female reproductive tract made in order to ascertain the reproductive cycle of this species. In July, when females were not pregnant, progesterone concentrations were 1.9 +/- 0.9 ng/ml. During the two gestation periods, progesterone concentrations increased progressively until late pregnancy at the end of October through to early November and again in late January to early February. During the latest stages of pregnancy, progesterone concentrations of 69.9 +/- 18.7 ng/ml were reached. It is suggested that a plasma progesterone concentration in excess of about 8 ng/ml indicates pregnancy in this species. Plasma testosterone concentration in males reached a peak of 43.1 +/- 9.81 ng/ml in July, and was then variable until December when levels declined significantly to 2.0 +/- 1.7 ng/ml.

Familial Paget's disease of bone: Nonlinkage to the PDB1 and PDB2 loci on chromosomes 6p and 18q in a large pedigree

Paget's disease of bone is a common condition characterized by bone pain, deformity, pathological fracture, and an increased incidence of osteosarcoma. Genetic factors play a role in the pathogenesis of Paget's disease but the molecular basis remains largely unknown. Susceptibility loci for Paget's disease of bone have been mapped to chromosome 6p21.3 (PDB1) and 18q121.1-q22 (PDB2) in different pedigrees, We have identified a large pedigree of over 250 individuals with 49 informative individuals affected with Paget's disease of bone; 31 of whom are available for genotypic analysis. The disease is inherited as an autosomal dominant trait in the pedigree with high penetrance by the sixth decade. Linkage analysis has been performed with markers at PDB1; these data show significant exclusion of linkage with log,, of the odds ratio (LOD) scores < -2 in this region. Linkage analysis of microsatellite markers from the PDB2 region has excluded linkage with this region, with a 30 cM exclusion region (LOD score < -2.0) centered on D18S42, These data confirm the genetic heterogeneity of Paget's disease of bone. Our hypothesis is that a novel susceptibility gene relevant to the pathogenesis of Paget's disease of bone lies elsewhere in the genome in the affected members of this pedigree and will be identified using a microsatellite genomewide scan followed by positional cloning.

Integrating technology to improve the efficiency of qualitative data analysis - A note on methods

Qualitative data analysis (QDA) is often a time-consuming and laborious process usually involving the management of large quantities of textual data. Recently developed computer programs offer great advances in the efficiency of the processes of QDA. In this paper we report on an innovative use of a combination of extant computer software technologies to further enhance and simplify QDA. Used in appropriate circumstances, we believe that this innovation greatly enhances the speed with which theoretical and descriptive ideas can be abstracted from rich, complex, and chaotic qualitative data. © 2001 Human Sciences Press, Inc.

Inferring population history from microsatellite and enzyme data in serially introduced cane toads, Bufo marinus

Much progress has been made on inferring population history from molecular data. However, complex demographic scenarios have been considered rarely or have proved intractable. The serial introduction of the South-Central American cane Load Bufo marinas in various Caribbean and Pacific islands involves four major phases: a possible genetic admixture during the first introduction, a bottleneck associated with founding, a transitory, population boom, and finally, a demographic stabilization. A large amount of historical and demographic information is available for those introductions and can be combined profitably with molecular data. We used a Bayesian approach to combine this information With microsatellite (10 loci) and enzyme (22 loci) data and used a rejection algorithm to simultaneously estimate the demographic parameters describing the four major phases of the introduction history,. The general historical trends supported by microsatellites and enzymes were similar. However, there was a stronger support for a larger bottleneck at introductions for microsatellites than enzymes and for a more balanced genetic admixture for enzymes than for microsatellites. Verb, little information was obtained from either marker about the transitory population boom observed after each introduction. Possible explanations for differences in resolution of demographic events and discrepancies between results obtained with microsatellites and enzymes were explored. Limits Of Our model and method for the analysis of nonequilibrium populations were discussed.

A zero-augmented gamma mixed model for longitudinal data with many zeros

In many occupational safety interventions, the objective is to reduce the injury incidence as well as the mean claims cost once injury has occurred. The claims cost data within a period typically contain a large proportion of zero observations (no claim). The distribution thus comprises a point mass at 0 mixed with a non-degenerate parametric component. Essentially, the likelihood function can be factorized into two orthogonal components. These two components relate respectively to the effect of covariates on the incidence of claims and the magnitude of claims, given that claims are made. Furthermore, the longitudinal nature of the intervention inherently imposes some correlation among the observations. This paper introduces a zero-augmented gamma random effects model for analysing longitudinal data with many zeros. Adopting the generalized linear mixed model (GLMM) approach reduces the original problem to the fitting of two independent GLMMs. The method is applied to evaluate the effectiveness of a workplace risk assessment teams program, trialled within the cleaning services of a Western Australian public hospital.

A mixture model-based approach to the clustering of microarray expression data

Motivation: This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. Results: The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets.

Modelling High-Dimensional Data by Mixtures of Factor Analyzers

We focus on mixtures of factor analyzers from the perspective of a method for model-based density estimation from high-dimensional data, and hence for the clustering of such data. This approach enables a normal mixture model to be fitted to a sample of n data points of dimension p, where p is large relative to n. The number of free parameters is controlled through the dimension of the latent factor space. By working in this reduced space, it allows a model for each component-covariance matrix with complexity lying between that of the isotropic and full covariance structure models. We shall illustrate the use of mixtures of factor analyzers in a practical example that considers the clustering of cell lines on the basis of gene expressions from microarray experiments. (C) 2002 Elsevier Science B.V. All rights reserved.

Fitting genetic models to twin data with binary and ordered categorical responses: A comparison of structural equation modelling and Bayesian hierarchical models

We compare Bayesian methodology utilizing free-ware BUGS (Bayesian Inference Using Gibbs Sampling) with the traditional structural equation modelling approach based on another free-ware package, Mx. Dichotomous and ordinal (three category) twin data were simulated according to different additive genetic and common environment models for phenotypic variation. Practical issues are discussed in using Gibbs sampling as implemented by BUGS to fit subject-specific Bayesian generalized linear models, where the components of variation may be estimated directly. The simulation study (based on 2000 twin pairs) indicated that there is a consistent advantage in using the Bayesian method to detect a correct model under certain specifications of additive genetics and common environmental effects. For binary data, both methods had difficulty in detecting the correct model when the additive genetic effect was low (between 10 and 20%) or of moderate range (between 20 and 40%). Furthermore, neither method could adequately detect a correct model that included a modest common environmental effect (20%) even when the additive genetic effect was large (50%). Power was significantly improved with ordinal data for most scenarios, except for the case of low heritability under a true ACE model. We illustrate and compare both methods using data from 1239 twin pairs over the age of 50 years, who were registered with the Australian National Health and Medical Research Council Twin Registry (ATR) and presented symptoms associated with osteoarthritis occurring in joints of the hand.

Effect of changing data collection parameters on statistical motor unit number estimates

The effect of number of samples and selection of data for analysis on the calculation of surface motor unit potential (SMUP) size in the statistical method of motor unit number estimates (MUNE) was determined in 10 normal subjects and 10 with amyotrophic lateral sclerosis (ALS). We recorded 500 sequential compound muscle action potentials (CMAPs) at three different stable stimulus intensities (10–50% of maximal CMAP). Estimated mean SMUP sizes were calculated using Poisson statistical assumptions from the variance of 500 sequential CMAP obtained at each stimulus intensity. The results with the 500 data points were compared with smaller subsets from the same data set. The results using a range of 50–80% of the 500 data points were compared with the full 500. The effect of restricting analysis to data between 5–20% of the CMAP and to standard deviation limits was also assessed. No differences in mean SMUP size were found with stimulus intensity or use of different ranges of data. Consistency was improved with a greater sample number. Data within 5% of CMAP size gave both increased consistency and reduced mean SMUP size in many subjects, but excluded valid responses present at that stimulus intensity. These changes were more prominent in ALS patients in whom the presence of isolated SMUP responses was a striking difference from normal subjects. Noise, spurious data, and large SMUP limited the Poisson assumptions. When these factors are considered, consistent statistical MUNE can be calculated from a continuous sequence of data points. A 2 to 2.5 SD or 10% window are reasonable methods of limiting data for analysis. Muscle Nerve 27: 320–331, 2003

Evaluation of cyclooxygenase 2 inhibitor use in patients admitted to a large teaching hospital

Background: The heavy usage of coxibs in Australia far outstrips the predicted usage that was based on the treatment of patients with risk factors for upper gastro-intestinal adverse events from conventional anti--inflammatory agents. This raises questions regarding the appropriateness of prescribing. Aims: To determine: (i) the relationship between prescriptions for cyclooxygenase 2 (COX-2) inhibitors and objective evidence of inflammatory arthritis, (ii) prior experience with paracetamol and/or conventional non-steroidal anti-inflammatory drugs (NSAIDs), and (iii) contraindications to the use of NSAIDs. Methods: Drug utilization evaluation and rheumato-logical assessment was conducted on 70 consecutive patients admitted on COX-2 inhibitors to a 480-bed metropolitan hospital. The main outcome measures were: the indication for COX-2 inhibitor; objective -evidence of inflammatory arthritis; previous trial of -paracetamol or conventional NSAIDs; and patient -satisfaction. Results: Only 11 patients (16%) had symptoms or signs of an inflammatory arthropathy, and met Pharmaceut-ical Benefits Schedule criteria for prescribing a COX-2 inhibitor. Fifty-nine patients (84%) had chronic osteo-arthritis, degenerative spinal disease, injury or malignancy, without overt active inflammation. Fourteen patients (20%) had trialled regular paracetamol prior to using any NSAID treatment. Conventional NSAIDs had been previously used by 51 patients (73%). Eleven patients (16%) reported previous adverse gastrointestinal effects from conventional NSAIDs. On the basis of significant renal impairment (creatinine clearance 5/10). Conclusions: Drug utilization data indicate that COX-2 inhibitors are frequently used first line for degenerative osteoarthritis in the absence of overt inflammation, without prior adequate trial of paracetamol and with disregard for the cautions and contraindications of these agents. These findings may explain the unprecedented Pharmaceutical Benefits Schedule expenditure on COX-2 inhibitors in Australia.