Quasars from a complete spectroscopic survey

With the advent of multi-fibre spectrographs such as the 'Two-Degree Field' (2dF) instrument at the Angle-Australian Telescope, quasar surveys that are free of any preselection of candidates and any biases this implies have become possible for the first time. The first of these is that which is being undertaken as part of the Fornax Spectroscopic Survey, a survey of the area around the Fornax Cluster of galaxies, and aims to obtain the spectra of all objects in the magnitude range 16.5 < b(j) < 19.7. To date, 3679 objects in the central pi -deg(2) area have been successfully identified from their spectral characteristics. Of these, 71 are found to be quasars, 61 with redshifts 0.3 < z < 2.2 and 10 with redshifts z > 2.2. Using this complete quasar sample, a new determination of quasar number counts is made, enabling an independent check of existing quasars surveys. Cumulative counts per square degree at a magnitude limit of b(j) < 19.5 are found to be 11.5 +/- 2.2 for 0.3 < z < 2.2, 2.22 +/- 0.93 for z > 2.2 and 13.7 +/- 3.1 for z > 0.3. Given the likely detection of extra quasars in the Fornax survey, we make a more detailed examination of existing quasar selection techniques. First, looking at the use of a stellar criterion, four of the 71 quasars are 'non-stellar' on the basis of the automated plate measuring facility (APM) b(j) classification, however inspection shows all are consistent with stellar, but misclassified due to image confusion. Examining the ultraviolet excess and multicolour selection techniques, for the selection criteria investigated, ultraviolet excess would find 69 +/- 6 per cent of our 0.3 < z < 2.2 quasars and only 50(-18)(+14), per cent of our z > 2.2 quasars, while the completeness level for multicolour selection is found to be 90(-4)(+3) per cent for 0.3 < z < 2.2 quasars and 80(-12)(+14) per cent for z > 2.2 quasars. The extra quasars detected by our all-object survey thus have unusually red star-like colours, and this appears to be a result of the continuum shape rather than any emission features. An intrinsic dust extinction model may, at least partly, account for the red colours.

The Fornax Cluster Spectroscopic Survey: a sample of confirmed cluster dwarfs

The Fornax Cluster Spectroscopic Survey (FCSS) project utilizes the Two-degree Field (2dF) multi-object spectrograph on the Anglo-Australian Telescope (AAT). Its aim is to obtain spectra for a complete sample of all 14 000 objects with 16 5 less than or equal to b(j) less than or equal to 19 7 irrespective of their morphology in a 12 deg(2) area centred on the Fornax cluster. A sample of 24 Fornax cluster members has been identified from the first 2dF field (3.1 deg(2) in area) to be completed. This is the first complete sample of cluster objects of known distance with well-defined selection limits. Nineteen of the galaxies (with -15.8 < M-B < 12.7) appear to be conventional dwarf elliptical (dE) or dwarf S0 (dS0) galaxies. The other five objects (with -13.6 < M-B < 11.3) are those galaxies which were described recently by Drinkwater et al. and labelled 'ultracompact dwarfs' (UCDs). A major result is that the conventional dwarfs all have scale sizes alpha greater than or similar to 3 arcsec (similar or equal to300 pc). This apparent minimum scale size implies an equivalent minimum luminosity for a dwarf of a given surface brightness. This produces a limit on their distribution in the magnitude-surface brightness plane, such that we do not observe dEs with high surface brightnesses but faint absolute magnitudes. Above this observed minimum scale size of 3 arcsec, the dEs and dS0s fill the whole area of the magnitude-surface brightness plane sampled by our selection limits. The observed correlation between magnitude and surface brightness noted by several recent studies of brighter galaxies is not seen with our fainter cluster sample. A comparison of our results with the Fornax Cluster Catalog (FCC) of Ferguson illustrates that attempts to determine cluster membership solely on the basis of observed morphology can produce significant errors. The FCC identified 17 of the 24 FCSS sample (i.e. 71 per cent) as being 'cluster' members, in particular missing all five of the UCDs. The FCC also suffers from significant contamination: within the FCSS's field and selection limits, 23 per cent of those objects described as cluster members by the FCC are shown by the FCSS to be background objects.

Social rules and attributions in the personnel selection interview

The study investigated the social rules applicable to selection interviews, and the attributions ions made by interviewers in response to rule-breaking behaviours by candidates. Sixty personnel specialists (31 males and 29 females) participated in the main study which examined their perceptions of social rules and attributions about rule breaking in their work experience. They listened to audiotapes of actual selection interviews, and made judgments about hireability communication competence, and specific social rules. Results indicated that interview rules could be categorized into two groups: specific interview presentation skills and general interpersonal competence. While situational attributions were more salient in explaining the breaking of general interpersonal competence rules, internal attributions (ability, effort) were more salient explanations for the breaking of more specific interview rules (with the exception of the preparation rule where lack of effort was the most likely explanation for rule breaking). Candidates previously judged as competent communicators were rated more favourably on both global and specific measures of rule-following competence, as well as on hireability. The theoretical and practical implications of combining social rules and attribution theory in the study of selection interviews are discussed.

Detecting environmental impacts on metapopulations of mound spring invertebrates - Assessing an incidence function model

We use a stochastic patch occupancy model of invertebrates in the Mound Springs ecosystem of South Australia to assess the ability of incidence function models to detect environmental impacts on metapopulations. We assume that the probability of colonisation decreases with increasing isolation and the probability of extinction is constant across spring vents. We run the models to quasi-equilibrium, and then impose an impact by increasing the local extinction probability. We sample the output at various times pre- and postimpact, and examine the probability of detecting a significant change in population parameters. The incidence function model approach turns out to have little power to detect environmental impacts on metapopulations with small numbers of patches. (C) 2001 Elsevier Science Ltd. All rights reserved.

Host selection in phytophagous insects: a new explanation for learning in adults

Insect learning can change the preferences an egg laying female displays towards different host plant species. Current hypotheses propose that learning may be advantageous in adult host selection behaviour through improved recognition, accuracy or selectivity in foraging. In this paper, we present a hypothesis for when learning can be advantageous without such improvements in adult host foraging. Specifically, that learning can be an advantageous strategy for egg laying females when larvae must feed on more than one plant in order to complete development, if the fitness of larvae is reduced when they switch to a different host species. Here, larvae benefit from developing on the most abundant host species, which is the most likely choice of host for an adult insect which increases its preference for a host species through learning. The hypothesis is formalised with a mathematical model and we provide evidence from studies on the behavioural ecology, of a number of insect species which demonstrate that the assumptions of this hypothesis may frequently be fulfilled in nature. We discuss how multiple mechanisms may convey advantages in insect learning and that benefits to larval development, which have so far been overlooked, should be considered in explanations for the widespread occurrence of learning.

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.

The validity and heritability of self-report osteoarthritis in an Australian older twin sample

In order to investigate the genetic and environmental antecedents of osteoarthritis (CA), self-report measures of joint pain, stiffness and swelling were obtained from a population-based sample of 1242 twin pairs over 50 years of age. In order to provide validation for these self-report measures, a subsample of 118 twin pairs were examined according to the American College of Rheumatology clinical and radiographic criteria for the classification of osteoarthritis. A variety of statistical methods were employed to identify the model derived from self-report variables which would provide optimal prediction of these standardised assessments, and structural equation modelling was used to determine the relative influences of genetic and environmental influences on the development of osteoarthritis. Significant genetic effects were found to contribute to osteoarthritis of the hands, hips and knees in women, with heritability estimates ranging from 30-46% depending on the site. In addition, the additive genetic effects contributing to osteoarthritis in various parts of the body were confirmed to be the same. Statistically significant familial aggregation of osteoarthritis in men was also observed, but it was not possible to determine whether this was due to genetic or shared environmental effects.

Genetic and environmental contributions to cannabis dependence in a national young adult twin sample

Background. This paper examines genetic and environmental contributions to risk of cannabis dependence. Method. Symptoms of cannabis dependence and measures of social, family and individual risk factors were assessed in a sample of 6265 young adult male and female Australian twins born 1964-1971. Results. Symptoms of cannabis dependence were common: 11(.)0% of sample (15(.)1% of men and 7(.)8% of women) reported two or more symptoms of dependence. Correlates of cannabis dependence included educational attainment, exposure to parental conflict, sexual abuse, major depression, social anxiety and childhood conduct disorder. However, even after control for the effects of these factors, there was evidence of significant genetic effects on risk of cannabis dependence. Standard genetic modelling indicated that 44(.)7% (95% CI = 15-72(.)2) of the variance in liability to cannabis dependence could be accounted for by genetic factors, 20(.)1% (95 CI = 0-43(.)6) could be attributed to shared environment factors and 35(.)3% (95% CI = 26(.)4-45(.)7) could be attributed to non-shared environmental factors. However, while there was no evidence of significant gender differences in the magnitude of genetic and environmental influences, a model which assumed both genetic and shared environmental influences on risks of cannabis dependence among men and shared environmental but no genetic influences among women provided an equally good fit to the data. Conclusions. There was consistent evidence that genetic risk factors are important determinants of risk of cannabis dependence among men. However, it remains uncertain whether there are genetic influences on liability to cannabis dependence among women.

Microevolution in island forms: the roles of drift and directional selection in morphological divergence of a passerine bird

Theory predicts that in small isolated populations random genetic drift can lead to phenotypic divergence; however this prediction has rarely been tested quantitatively in natural populations. Here we utilize natural repeated island colonization events by members of the avian species complex, Zosterops lateralis, to assess whether or not genetic drift alone is an adequate explanation for the observed patterns of microevolutionary divergence in morphology. Morphological and molecular genetic characteristics of island and mainland populations are compared to test three predictions of drift theory: (1) that the pattern of morphological change is idiosyncratic to each island; (2) that there is concordance between morphological and neutral genetic shifts across island populations; and (3) for populations whose time of colonization is known, that the rate of morphological change is sufficiently slow to be accounted for solely by genetic drift. Our results are not consistent with these predictions. First, the direction of size shifts was consistently towards larger size, suggesting the action of a nonrandom process. Second, patterns of morphological divergence among recently colonized populations showed little concordance with divergence in neutral genetic characters. Third, rate tests of morphological change showed that effective population sizes were not small enough for random processes alone to account for the magnitude of microevolutionary change. Altogether, these three lines of evidence suggest that drift alone is not an adequate explanation of morphological differentiation in recently colonized island Zosterops and therefore we suggest that the observed microevolutionary changes are largely a result of directional natural selection.

Model specification tests in nonparametric stochastic regression models

In this paper, we consider testing for additivity in a class of nonparametric stochastic regression models. Two test statistics are constructed and their asymptotic distributions are established. We also conduct a small sample study for one of the test statistics through a simulated example. (C) 2002 Elsevier Science (USA).

Monitoring the composition and form of urban environments based on the vegetation-impervious surface-soil (VIS) model by sub-pixel analysis techniques

The majority of the world's population now resides in urban environments and information on the internal composition and dynamics of these environments is essential to enable preservation of certain standards of living. Remotely sensed data, especially the global coverage of moderate spatial resolution satellites such as Landsat, Indian Resource Satellite and Systeme Pour I'Observation de la Terre (SPOT), offer a highly useful data source for mapping the composition of these cities and examining their changes over time. The utility and range of applications for remotely sensed data in urban environments could be improved with a more appropriate conceptual model relating urban environments to the sampling resolutions of imaging sensors and processing routines. Hence, the aim of this work was to take the Vegetation-Impervious surface-Soil (VIS) model of urban composition and match it with the most appropriate image processing methodology to deliver information on VIS composition for urban environments. Several approaches were evaluated for mapping the urban composition of Brisbane city (south-cast Queensland, Australia) using Landsat 5 Thematic Mapper data and 1:5000 aerial photographs. The methods evaluated were: image classification; interpretation of aerial photographs; and constrained linear mixture analysis. Over 900 reference sample points on four transects were extracted from the aerial photographs and used as a basis to check output of the classification and mixture analysis. Distinctive zonations of VIS related to urban composition were found in the per-pixel classification and aggregated air-photo interpretation; however, significant spectral confusion also resulted between classes. In contrast, the VIS fraction images produced from the mixture analysis enabled distinctive densities of commercial, industrial and residential zones within the city to be clearly defined, based on their relative amount of vegetation cover. The soil fraction image served as an index for areas being (re)developed. The logical match of a low (L)-resolution, spectral mixture analysis approach with the moderate spatial resolution image data, ensured the processing model matched the spectrally heterogeneous nature of the urban environments at the scale of Landsat Thematic Mapper data.

Application of spatial analysis techniques to adjust for fertility trends and identify interplot competition in early stage sugarcane selection trials

Most sugarcane breeding programs in Australia use large unreplicated trials to evaluate clones in the early stages of selection. Commercial varieties that are replicated provide a method of local control of soil fertility. Although such methods may be useful in detecting broad trends in the field, variation often occurs on a much smaller scale. Methods such as spatial analysis adjust a plot for variability by using information from immediate neighbours. These techniques are routinely used to analyse cereal data in Australia and have resulted in increased accuracy and precision in the estimates of variety effects. In this paper, spatial analyses in which the variability is decomposed into local, natural, and extraneous components are applied to early selection trials in sugarcane. Interplot competition in cane yield and trend in sugar content were substantial in many of the trials and there were often large differences in the selections between the spatial and current method used by the Bureau of Sugar Experiment Stations. A joint modelling approach for tonnes sugar per hectare in response to fertility trends and interplot competition is recommended.

The impact of participation in activities while on vacation on senior's psychological well-being: A path model application

This article extends earlier research regarding the relationships between senior travelers’ participation in activities while on vacation, their overall satisfaction with their travel experiences, and their psychological well-being. A path model was developed to depict the direct and indirect relationships between these variables by using a sample of senior tourists traveling on North American escorted tour itineraries. Whereas the direct effect accounted for 98% of the relationships between the senior tourists’ levels of participation in activities and their psychological well-being, the indirect effect was negligible. The study concluded that senior tourists’activity levels were significantly related to their psychological well-being, but their satisfaction with the tours was not.

Using crop simulation to generate genotype by environment interaction effects for sorghum in water-limited environments

Multi-environment trials (METs) used to evaluate breeding lines vary in the number of years that they sample. We used a cropping systems model to simulate the target population of environments (TPE) for 6 locations over 108 years for 54 'near-isolines' of sorghum in north-eastern Australia. For a single reference genotype, each of 547 trials was clustered into 1 of 3 'drought environment types' (DETs) based on a seasonal water stress index. Within sequential METs of 2 years duration, the frequencies of these drought patterns often differed substantially from those derived for the entire TPE. This was reflected in variation in the mean yield of the reference genotype. For the TPE and for 2-year METs, restricted maximum likelihood methods were used to estimate components of genotypic and genotype by environment variance. These also varied substantially, although not in direct correlation with frequency of occurrence of different DETs over a 2-year period. Combined analysis over different numbers of seasons demonstrated the expected improvement in the correlation between MET estimates of genotype performance and the overall genotype averages as the number of seasons in the MET was increased.

The E(NK) model: extending the NK model to incorporate gene-by-environment interactions and epistasis for diploid genomes

The haploid NK model developed by Kauffman can be extended to diploid genomes and to incorporate gene-by-environment interaction effects in combination with epistasis. To provide the flexibility to include a wide range of forms of gene-by-environment interactions, a target population of environment types (TPE) is defined. The TPE consists of a set of E different environment types, each with their own frequency of occurrence. Each environment type conditions a different NK gene network structure or series of gene effects for a given network structure, providing the framework for defining gene-by-environment interactions. Thus, different NK models can be partially or completely nested within the E environment types of a TPE, giving rise to the E(NK) model for a biological system. With this model it is possible to examine how populations of genotypes evolve in context with properties of the environment that influence the contributions of genes to the fitness values of genotypes. We are using the E(NK) model to investigate how both epistasis and gene-by-environment interactions influence the genetic improvement of quantitative traits by plant breeding strategies applied to agricultural systems. © 2002 Wiley Periodicals, Inc.