7 research outputs found

    Gas-to-Dust mass ratios in local galaxies over a 2 dex metallicity range

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    This paper analyses the behaviour of the gas-to-dust mass ratio (G/D) of local Universe galaxies over a large metallicity range. We combine three samples: the Dwarf Galaxy Survey, the KINGFISH survey and a subsample from Galametz et al. (2011) totalling 126 galaxies, covering a 2 dex metallicity range, with 30% of the sample with 12+log(O/H) < 8.0. The dust masses are homogeneously determined with a semi-empirical dust model, including submm constraints. The atomic and molecular gas masses are compiled from the literature. Two XCO are used to estimate molecular gas masses: the Galactic XCO, and a XCO depending on the metallicity (as Z^{-2}). Correlations with morphological types, stellar masses, star formation rates and specific star formation rates are discussed. The trend between G/D and metallicity is empirically modelled using power-laws (slope of -1 and free) and a broken power-law. We compare the evolution of the G/D with predictions from chemical evolution models. We find that out of the five tested galactic parameters, metallicity is the galactic property driving the observed G/D. The G/D versus metallicity relation cannot be represented by a power-law with a slope of -1 over the whole metallicity range. The observed trend is steeper for metallicities lower than ~ 8.0. A large scatter is observed in the G/D for a given metallicity, with a dispersion of 0.37 dex in metallicity bins of ~0.1 dex. The broken power-law reproduces best the observed G/D and provides estimates of the G/D that are accurate to a factor of 1.6. The good agreement of the G/D and its scatter with the three tested chemical evolution models shows that the scatter is intrinsic to galactic properties, reflecting the different star formation histories, dust destruction efficiencies, dust grain size distributions and chemical compositions across the sample. (abriged)Comment: 23 pages, 12 figures, accepted in Astronomy & Astrophysic

    Change in Blood Pressure Variability Among Treated Elderly Hypertensive Patients and Its Association With Mortality

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    Background: Information is scarce regarding effects of antihypertensive medication on blood pressure variability (BPV) and associated clinical outcomes. We examined whether antihypertensive treatment changes BPV over time and whether such change (decline or increase) has any association with long-term mortality in an elderly hypertensive population. Methods and Results: We used data from a subset of participants in the Second Australian National Blood Pressure study (n=496) aged ≥65 years who had 24-hour ambulatory blood pressure recordings at study entry (baseline) and then after a median of 2 years while on treatment (follow-up). Weighted day-night systolic BPV was calculated for both baseline and follow-up as a weighted mean of daytime and nighttime blood pressure standard deviations. The annual rate of change in BPV over time was calculated from these BPV estimates. Furthermore, we classified both BPV estimates as high and low based on the baseline median BPV value and then classified BPV changes into stable: low BPV, stable: high BPV, decline: high to low, and increase: low to high. We observed an annual decline (mean±SD: −0.37±1.95; 95% CI, −0.54 to −0.19; P<0.001) in weighted day-night systolic BPV between baseline and follow-up. Having constant stable: high BPV was associated with an increase in all-cause mortality (hazard ratio: 3.03; 95% CI, 1.67–5.52) and cardiovascular mortality (hazard ratio: 3.70; 95% CI, 1.62–8.47) in relation to the stable: low BPV group over a median 8.6 years after the follow-up ambulatory blood pressure monitoring. Similarly, higher risk was observed in the decline: high to low group. Conclusions: Our results demonstrate that in elderly hypertensive patients, average BPV declined over 2 years of follow-up after initiation of antihypertensive therapy, and having higher BPV (regardless of any change) was associated with increased long-term mortality

    General practitioner participation in the second Australian National Blood Pressure Study (ANBP2)

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    SUMMARY 1. The second Australian National Blood Pressure Study (ANBP2) is an outcome trial of the treatment of hypertension in the elderly conducted entirely in general practices across Australia. Prior to ANBP2, no study of this size and nature had been undertaken in Australian general practice and the response of General Practitioners (GPs) to becoming involved in long-term cardiovascular research was unknown. 2. Academic departments and Divisions of General Practice were approached to support the project. General Practitioners were approached by letter of invitation and contacted by a regional medical coordinator (RMC) either at a face-to-face meeting or by telephone. 3. At the close of recruitment to ANBP2, 1938 GPs from 950 practices had registered as investigators. Sixty-two Divisions of General Practice were approached to support the study in five mainland Australian states with 39 (63%) participating, although participation by state was highly variable (range: 18–100%). Thirty divisional or promotional dinner meetings were held, with 56% (368/658) of those attending registering as investigators. Of the 8098 GPs sent a letter of invitation to participate in the study, 1357 (17%) expressed interest and eventually enrolled as investigators, ranging from 8% in Queensland to 28% in New South Wales. Ninety-six per cent of GPs who had a personal face-to-face contact (696/724) with the RMC registered in the study. 4. The GP recruitment phase of ANBP2 has been successfully completed. Peer-to-peer recruitment was the most successful strategy; however, success varied between states. General Practitioner recruitment to long-term clinical trials appears to be successful with a multifactorial approach focusing on peer-to-peer recruitment.Christopher M Reid, Phillip Ryan, Mark Nelson, Paul Beckinsale, Marilyn McMurchie, David Gleave, Fred DeLoozeƒ and Lindon M Win

    The DCA: Some Comparison a Comparative Study between Two Biologically-Inspired Algorithms

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