Modelling the luminosities and sizes of radio sources: radio luminosity function at z = 6

We present a model to predict the luminosity function for radio galaxies and their linear size distribution at any redshift. The model takes a black hole mass function and Eddington ratio distribution as input and tracks the evolution of radio sources, taking into account synchrotron, adiabatic and inverse Compton energy losses. We first test the model at z = 2 where plenty of radio data are available and show that the radio luminosity function (RLF) is consistent with observations. We are able to reproduce the break in luminosity function that separates locally the Fanaroff-Riley class I and Fanaroff-Riley class I radio sources. Our prediction for linear size distribution at z = 2 matches the observed distribution too. We then use our model to predict an RLF and linear size distribution at z = 6, as this is the epoch when radio galaxies can be used as probes of reionization. We demonstrate that higher inverse Compton losses lead to shorter source lifetimes and smaller sizes at high redshifts. The predicted sizes are consistent with the generally observed trend with redshift. We evolve the z = 2 RLF based on observed quasar space densities at high redshifts, and show that our RLF prediction at z = 6 is consistent. Finally, we predict the detection of 0.63, 0.092 and 0.0025 z ≥ 6 sources deg2 at flux density limits of 0.1, 0.5 and 3.5 mJy. We assess the trade-off between coverage area and depth and show that LOFAR surveys with flux density limits of 0.1 and 0.5 mJy are the most efficient at detecting a large number of z ≥ 6 radio sources

Herschel-ATLAS/GAMA: A difference between star formation rates in strong-line and weak-line radio galaxies

We have constructed a sample of radio-loud objects with optical spectroscopy from the Galaxy and Mass Assembly (GAMA) project over the Herschel Astrophysical Terahertz Large Area Survey (Herschel-ATLAS) Phase 1 fields. Classifying the radio sources in terms of their optical spectra, we find that strong-emission-line sources ('high-excitation radio galaxies') have, on average, a factor of ~4 higher 250-μm Herschel luminosity than weak-line ('lowexcitation') radio galaxies and are also more luminous than magnitude-matched radio-quiet galaxies at the same redshift. Using all five H-ATLAS bands, we show that this difference in luminosity between the emission-line classes arises mostly from a difference in the average dust temperature; strong-emission-line sources tend to have comparable dust masses to, but higher dust temperatures than, radio galaxies with weak emission lines. We interpret this as showing that radio galaxies with strong nuclear emission lines are much more likely to be associated with star formation in their host galaxy, although there is certainly not a one-to-one relationship between star formation and strong-line active galactic nuclei (AGN) activity. The strong-line sources are estimated to have star formation rates at least a factor of 3-4 higher than those in the weak-line objects. Our conclusion is consistent with earlier work, generally carried out using much smaller samples, and reinforces the general picture of high-excitation radio galaxies as being located in lower-mass, less evolved host galaxies than their low-excitation counterparts.Peer reviewe

Bullying behaviors and victimization experiences among adolescent students: the role of resilience

The role of resilience in the relationship between bullying behaviours, victimisation experiences, and self-efficacy was examined. Three hundred and 93 (191 male, 202 female) adolescents (mean age = 15.88, SD = .64) from schools in Coimbatore, India completed scales to assess bullying behaviours and victimisation experiences, resilience, and self-efficacy. Multigroup SEM, with separate groups created according to participant sex, revealed that resilience mediated the relationship between bullying behaviours and self-efficacy in males. Males engaged in bullying behaviours and experienced victimisation more frequently than females. The findings of the study have implication for designing intervention programs to enhance resilience among adolescents and young adults to enable them to manage bullying behaviours

Herschel*-ATLAS: correlations between dust and gas in local submm-selected galaxies

We present an analysis of CO molecular gas tracers in a sample of 500 μ m-selected Herschel -ATLAS galaxies at z < 0 . 05 ( cz < 14990 km s − 1 ). Using 22 − 500 μ m photom- etry from WISE , IRAS and Herschel , with H i data from the literature, we investigate correlations between warm and cold dust, and tracers of the gas in different phases. The correlation between global CO(3–2) line fluxes and FIR–submm fl uxes weakens with increasing IR wavelength ( λ & 60 μ m), as a result of colder dust being less strongly associated with dense gas. Conversely, CO(2–1) and H i line fluxes both ap- pear to be better correlated with longer wavelengths, suggesting that cold dust is more strongly associated with diffuse atomic and molecular gas phases, co nsistent with it being at least partially heated by radiation from old stellar populations . The increased scatter at long wavelengths implies that sub-millimetre fluxes are a po orer tracer of SFR. Fluxes at 22 and 60 μ m are also better correlated with diffuse gas tracers than dense CO(3–2), probably due to very-small-grain emission in the diffu se interstellar medium, which is not correlated with SFR. The FIR/CO luminosity ratio a nd the dust mass/CO luminosity ratio both decrease with increasing luminosit y, as a result of either correlations between mass and metallicity (changing CO/H 2 ) or between CO luminosity and excitation [changing CO(3–2)/CO(1–0)].Web of Scienc

H-ATLAS/GAMA: magnification bias tomography. Astrophysical constraints above ~1 arcmin

An unambiguous manifestation of the magnification bias is the cross-correlation between two source samples with non-overlapping redshift distributions. In this work we measure and study the cross-correlation signal between a foreground sample of GAMA galaxies with spectroscopic redshifts in the range 0.2<z<0.8, and a background sample of H-ATLAS galaxies with photometric redshifts gsim1.2. It constitutes a substantial improvement over the cross-correlation measurements made by Gonzalez-Nuevo et al. (2014) with updated catalogues and wider area (with S/Ngsim 5 below 10 arcmin and reaching S/N~ 20 below 30 arcsec). The better statistics allow us to split the sample in different redshift bins and to perform a tomographic analysis (with S/Ngsim 3 below 10 arcmin and reaching S/N~ 15 below 30 arcsec). Moreover, we implement a halo model to extract astrophysical information about the background galaxies and the deflectors that are producing the lensing link between the foreground (lenses) and background (sources) samples. In the case of the sources, we find typical mass values in agreement with previous studies: a minimum halo mass to host a central galaxy, Mmin~ 1012.26 M⊙, and a pivot halo mass to have at least one sub-halo satellite, M1~ 1012.84 M⊙. However, the lenses are massive galaxies or even galaxy groups/clusters, with minimum mass of Mminlens~ 1013.06 M⊙. Above a mass of M1lens~ 1014.57 M⊙ they contain at least one additional satellite galaxy which contributes to the lensing effect. The tomographic analysis shows that, while M1lens is almost redshift independent, there is a clear evolution of increase Mminlens with redshift in agreement with theoretical estimations. Finally, the halo modeling allows us to identify a strong lensing contribution to the cross-correlation for angular scales below 30 arcsec. This interpretation is supported by the results of basic but effective simulations

Herschel -ATLAS: rapid evolution of dust in galaxies over the last 5 billion years

We present the first direct and unbiased measurement of the evolution of the dust mass function of galaxies over the past 5 billion years of cosmic history using data from the Science Demonstration Phase of the Herschel-Astrophysical Terahertz Large Area Survey (Herschel-ATLAS). The sample consists of galaxies selected at 250 ?m which have reliable counterparts from the Sloan Digital Sky Survey (SDSS) at z < 0.5, and contains 1867 sources. Dust masses are calculated using both a single-temperature grey-body model for the spectral energy distribution and also a model with multiple temperature components. The dust temperature for either model shows no trend with redshift. Splitting the sample into bins of redshift reveals a strong evolution in the dust properties of the most massive galaxies. At z= 0.4-0.5, massive galaxies had dust masses about five times larger than in the local Universe. At the same time, the dust-to-stellar mass ratio was about three to four times larger, and the optical depth derived from fitting the UV-sub-mm data with an energy balance model was also higher. This increase in the dust content of massive galaxies at high redshift is difficult to explain using standard dust evolution models and requires a rapid gas consumption time-scale together with either a more top-heavy initial mass function (IMF), efficient mantle growth, less dust destruction or combinations of all three. This evolution in dust mass is likely to be associated with a change in overall interstellar medium mass, and points to an enhanced supply of fuel for star formation at earlier cosmic epochs

Multilevel structured additive regression

Models with structured additive predictor provide a very broad and rich framework for complex regression modeling. They can deal simultaneously with nonlinear covariate effects and time trends, unit- or cluster-specific heterogeneity, spatial heterogeneity and complex interactions between covariates of different type. In this paper, we propose a hierarchical or multilevel version of regression models with structured additive predictor where the regression coefficients of a particular nonlinear term may obey another regression model with structured additive predictor. In that sense, the model is composed of a hierarchy of complex structured additive regression models. The proposed model may be regarded as an extended version of a multilevel model with nonlinear covariate terms in every level of the hierarchy. The model framework is also the basis for generalized random slope modeling based on multiplicative random effects. Inference is fully Bayesian and based on Markov chain Monte Carlo simulation techniques. We provide an in depth description of several highly efficient sampling schemes that allow to estimate complex models with several hierarchy levels and a large number of observations within a couple of minutes (often even seconds). We demonstrate the practicability of the approach in a complex application on childhood undernutrition with large sample size and three hierarchy levels