Large-scale clustering measurements with photometric redshifts: comparing the dark matter haloes of X-ray AGN, star-forming and passive galaxies at z ≈ 1

We combine multi-wavelength data in the AEGIS-XD and C-COSMOS surveys to measure the typical dark matter halo mass of X-ray selected active galactic nuclei (AGN) [L_X(2–10 keV) > 10^42 erg s^− 1] in comparison with far-infrared selected star-forming galaxies detected in the Herschel/PEP survey (PACS Evolutionary Probe; L_IR > 10^11 L_⊙) and quiescent systems at z ≈ 1. We develop a novel method to measure the clustering of extragalactic populations that uses photometric redshift probability distribution functions in addition to any spectroscopy. This is advantageous in that all sources in the sample are used in the clustering analysis, not just the subset with secure spectroscopy. The method works best for large samples. The loss of accuracy because of the lack of spectroscopy is balanced by increasing the number of sources used to measure the clustering. We find that X-ray AGN, far-infrared selected star-forming galaxies and passive systems in the redshift interval 0.6 < z < 1.4 are found in haloes of similar mass, log M_DMH/(M_⊙ h^−1) ≈ 13.0. We argue that this is because the galaxies in all three samples (AGN, star-forming, passive) have similar stellar mass distributions, approximated by the J-band luminosity. Therefore, all galaxies that can potentially host X-ray AGN, because they have stellar masses in the appropriate range, live in dark matter haloes of log M_DMH/(M_⊙ h^−1) ≈ 13.0 independent of their star formation rates. This suggests that the stellar mass of X-ray AGN hosts is driving the observed clustering properties of this population. We also speculate that trends between AGN properties (e.g. luminosity, level of obscuration) and large-scale environment may be related to differences in the stellar mass of the host galaxies.

An adaptive algorithm for clustering cumulative probability distribution functions using the Kolmogorov–Smirnov two-sample test

This paper proposes an adaptive algorithm for clustering cumulative probability distribution functions (c.p.d.f.) of a continuous random variable, observed in different populations, into the minimum homogeneous clusters, making no parametric assumptions about the c.p.d.f.’s. The distance function for clustering c.p.d.f.’s that is proposed is based on the Kolmogorov–Smirnov two sample statistic. This test is able to detect differences in position, dispersion or shape of the c.p.d.f.’s. In our context, this statistic allows us to cluster the recorded data with a homogeneity criterion based on the whole distribution of each data set, and to decide whether it is necessary to add more clusters or not. In this sense, the proposed algorithm is adaptive as it automatically increases the number of clusters only as necessary; therefore, there is no need to fix in advance the number of clusters. The output of the algorithm are the common c.p.d.f. of all observed data in the cluster (the centroid) and, for each cluster, the Kolmogorov–Smirnov statistic between the centroid and the most distant c.p.d.f. The proposed algorithm has been used for a large data set of solar global irradiation spectra distributions. The results obtained enable to reduce all the information of more than 270,000 c.p.d.f.’s in only 6 different clusters that correspond to 6 different c.p.d.f.’s.

Tables describing small-sample properties of the mean, median, standard deviation, and other statistics in sampling from various distributions /

Mode of access: Internet.

Perceived social support in a large community sample - Age and sex differences

Background. The positive health and wellbeing effects of social support have been consistently demonstrated in the literature since the late 1970s. However, a better understanding of the effects of age and sex is required. Method. We examined the factor structure and reliability of Kessler's Perceived Social Support (KPSS) measure in a community-based sample that comprised younger and older adult cohorts from the Australian Twin Registry (ATR), totalling 11,389 males and females aged 18-95, of whom 887 were retested 25 months later. Results. Factor analysis consistently identified seven factors: support from spouse, twin, children, parents, relatives, friends and helping support. Internal reliability for the seven dimensions ranged from 0.87 to 0.71 and test-retest reliability ranged from 0.75 to 0.48. Perceived support was only marginally higher in females. Age dependencies were explored. Across the age range, there was a slight decline (more marked in females) in the perceived support from spouse, parent and friend, a slight increase in perceived relative and helping support for males but none for females, a substantial increase in the perceived support from children for males and females and a negligible decline in total KPSS for females against a negligible increase for males. The perceived support from twin remained constant. Females were more likely to have a confidant, although this declined with age whilst increasing with age for males. Conclusions. Total scores for perceived social support conflate heterogeneous patterns on sub-scales that differ markedly by age and sex. Our paper describes these relationships in detail in a very large Australian sample.

Sexual abuse and suicidality: gender differences in a large community sample of adolescents

Objective: A cross-sectional study of gender specific relationships between self-reported child sexual abuse and suicidality in a community sample of adolescents. Method: Students aged 14 years on average (N = 2,485) from 27 schools in South Australia completed a questionnaire including items on sexual abuse and suicidality, and measures of depression (Centre for Epidemiological Studies Depression Scale), hopelessness (Beck Hopelessness Scale), and family functioning (McMaster Family Assessment Device General Functioning Subscale). Data analysis included logistic regression. Results: In boys, self-report sexual abuse is strongly and independently associated with suicidal thoughts, plans, threats, deliberate self-injury, and suicide attempts, after controlling for current levels of depression, hopelessness, and family dysfunction. In girls, the relationship between sexual abuse and suicidality is mediated fully by depression, hopelessness, and family dysfunction. Girls who report current high distress about sexual abuse, however, have a threefold increased risk of suicidal thoughts and plans, compared to non-abused girls. Boys who report current high distress about sexual abuse have 10-fold increased risk for suicidal plans and threats, and 15-fold increased risk for suicide attempts, compared to non-abused boys. Fifty-five percent (n = 15) of sexually abused boys attempted suicide versus 29% (n = 17) girls. Conclusions: A history of sexual abuse should alert clinicians, professionals and caters in contact with adolescents, to greatly increased risks of suicidal behavior and attempts in boys, even in the absence of depression and hopelessness. Distress following sexual abuse, along with depression and hopelessness indicate increased risk of suicidal behavior in girls, as well as boys. (C) 2004 Published by Elsevier Ltd.

A study of the scattering of fast neutrons in large samples

In the present work, the elastic scattering of fast neutrons from iron and concrete samples were studied at incident neutron energies of 14.0 and 14.4 Mev, using a neutron spectrometer based on the associated particle time-of-flight technique. These samples were chosen because of their importance in the design of fusion reactor shielding and construction. Using the S.A.M.E.S. accelerator and the 3 M v Dynamitron accelerator at the Radiation Centre, 14.0 and 14.4 Mev neutrons were produced by the T(d, n)4He reaction at incident deuteron energies of 140 keV and 900 keV mass III ions respectively. The time of origin of the neutron was determined by detecting the associated alpha particles. The samples used were extended flat plates of thicknesses up to 1.73 mean free paths for iron and 2.3 mean free paths for concrete. The associated alpha particles and fast neutrons were detected by means of a plastic scintillator mounted on a fast focused photomultiplier tube. The differential neutron elastic scattering cross-sections were measured for 14 Mev neutrons in various thicknesses of iron and concrete in the angular range from zero to 90°. In addition, the angular distributions of 14.4 Mev neutrons after passing through extended samples of iron were measured at several scattering angles in the same angular range. The measurements obtained for the thin sample of iron were compared with the results of Coon et al. The differential cross-sections for the thin iron sample were also analyzed on the optical model using the computer code RAROMP. For the concrete sample, the angular distribution of the thin sample was compared with the cross-sections calculated from the major constituent elements of concrete, and with the predicted values of the optical model for those elements. No published data could be found to compare with the results of the concrete differential cross-sections. In the case of thick samples of iron and concrete, the number of scattered neutrons were compared with a phenomological calculation based on the continuous slowing down model. The variation of measured cross-sections with sample thickness were found to follow the empirical relation σ = σ0 eαx. By using the universal constant "K", good fits were obtained to the experimental data. In parallel with the work at 14.0 and 14.4 Mev, an associated particle time-of-flight spectrometer was investigated which used the 2H(d,n)3He reaction for 3.02 Mev neutron energy at the incident deuteron energy of 1 Mev.

Global distributions of diazotrophs abundance and biomass - Depth integrated values computed from a collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present data set presents depth integrated values of diazotrophs abundance and biomass, computed from a collection of source data sets.

Global distributions of diazotrophs nitrogen fixation rates - Depth integrated values computed from a collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present data set presents depth integrated values of diazotrophs nitrogen fixation rates, computed from a collection of source data sets.

A fully Bayesian approach to inference for Coxian phase-type distributions with covariate dependent mean

Phase-type distributions represent the time to absorption for a finite state Markov chain in continuous time, generalising the exponential distribution and providing a flexible and useful modelling tool. We present a new reversible jump Markov chain Monte Carlo scheme for performing a fully Bayesian analysis of the popular Coxian subclass of phase-type models; the convenient Coxian representation involves fewer parameters than a more general phase-type model. The key novelty of our approach is that we model covariate dependence in the mean whilst using the Coxian phase-type model as a very general residual distribution. Such incorporation of covariates into the model has not previously been attempted in the Bayesian literature. A further novelty is that we also propose a reversible jump scheme for investigating structural changes to the model brought about by the introduction of Erlang phases. Our approach addresses more questions of inference than previous Bayesian treatments of this model and is automatic in nature. We analyse an example dataset comprising lengths of hospital stays of a sample of patients collected from two Australian hospitals to produce a model for a patient's expected length of stay which incorporates the effects of several covariates. This leads to interesting conclusions about what contributes to length of hospital stay with implications for hospital planning. We compare our results with an alternative classical analysis of these data.