Modeling the physical properties in the ISM of the low-metallicity galaxy NGC4214

We present a model for the interstellar medium of NGC4214 with the objective to probe the physical conditions in the two main star-forming regions and their connection with the star formation activity of the galaxy. We used the spectral synthesis code Cloudy to model an HII region and the associated photodissociation region (PDR) to reproduce the emission of mid- and far-infrared fine-structure cooling lines from the Spitzer and Herschel space telescopes for these two regions. Input parameters of the model, such as elemental abundances and star formation history, are guided by earlier studies of the galaxy, and we investigated the effect of the mode in which star formation takes place (bursty or continuous) on the line emission. Furthermore, we tested the effect of adding pressure support with magnetic fields and turbulence on the line predictions. We find that this model can satisfactorily predict (within a factor of ~2) all observed lines that originate from the ionized medium ([SIV] 10.5um, [NeIII] 15.6um, [SIII] 18.7um, [SIII] 33.5um, and [OIII] 88um), with the exception of [NeII] 12.8um and [NII] 122um, which may arise from a lower ionization medium. In the PDR, the [OI] 63um, [OI] 145um, and [CII] 157um lines are matched within a factor of ~5 and work better when weak pressure support is added to the thermal pressure or when the PDR clouds are placed farther away from the HII regions and have covering factors lower than unity. Our models of the HII region agree with different evolutionary stages found in previous studies, with a more evolved, diffuse central region, and a younger, more compact southern region. However, the local PDR conditions are averaged out on the 175 pc scales that we probe and do not reflect differences observed in the star formation properties of the two regions.Comment: accepted for publication in A&

The Nature of the Low-Metallicity ISM in the Dwarf Galaxy NGC 1569

We are modeling the spectra of dwarf galaxies from infrared to submillimeter wavelengths to understand the nature of the various dust components in low-metallicity environments, which may be comparable to the ISM of galaxies in their early evolutionary state. The overall nature of the dust in these environments appears to differ from those of higher metallicity starbursting systems. Here, we present a study of one of our sample of dwarf galaxies, NGC 1569, which is a nearby, well-studied starbursting dwarf. Using ISOCAM, IRAS, ISOPHOT and SCUBA data with the Desert et al. (1990) model, we find consistency with little contribution from PAHs and Very Small Grains and a relative abundance of bigger colder grains, which dominate the FIR and submillimeter wavelengths. We are compelled to use 4 dust components, adding a very cold dust component, to reproduce the submillimetre excess of our observations.Comment: 4 pages, 4 postscript figures. Proceedings of "Infrared and Submillimeter Astronomy. An International Colloquium to Honor the Memory of Guy Serra" (2002

Variations of the Mid-IR Aromatic Features Inside and Among Galaxies

We present the results of a systematic study of mid-IR spectra of Galactic regions, Magellanic HII regions, and galaxies of various types (dwarf, spiral, starburst), observed by the satellites ISO and Spitzer. We study the relative variations of the 6.2, 7.7, 8.6 and 11.3 micron features inside spatially resolved objects (such as M82, M51, 30 Doradus, M17 and the Orion Bar), as well as among 90 integrated spectra of 50 objects. Our main results are that the 6.2, 7.7 and 8.6 micron bands are essentially tied together, while the ratios between these bands and the 11.3 micron band varies by one order of magnitude. This implies that the properties of the PAHs are remarkably universal throughout our sample, and that the relative variations of the band ratios are mainly controled by the fraction of ionized PAHs. In particular, we show that we can rule out both the modification of the PAH size distribution, and the mid-infrared extinction, as an explanation of these variations. Using a few well-studied Galactic regions (including the spectral image of the Orion Bar), we give an empirical relation between the I(6.2)/I(11.3) ratio and the ionization/recombination ratio G0/ne.Tgas^0.5, therefore providing a useful quantitative diagnostic tool of the physical conditions in the regions where the PAH emission originates. Finally, we discuss the physical interpretation of the I(6.2)/I(11.3) ratio, on galactic size scales.Comment: Accepted by the ApJ, 67 pages, 70 figure

Individualisation of time-motion analysis : a method comparison and case report series

© Georg Thieme Verlag KG. This study compared the intensity distribution of time-motion analysis data, when speed zones were categorized by different methods. 12 U18 players undertook a routine battery of laboratory- and field-based assessments to determine their running speed corresponding to the respiratory compensation threshold (RCT), maximal aerobic speed (MAS), maximal oxygen consumption (vVO 2max ) and maximal sprint speed (MSS). Players match-demands were tracked using 5 Hz GPS units in 22 fixtures (50 eligible match observations). The percentage of total distance covered running at high-speed (%HSR), very-high speed (%VHSR) and sprinting were determined using the following speed thresholds: 1) arbitrary; 2) individualised (IND) using RCT, vVO 2max and MSS; 3) individualised via MAS per se; 4) individualised via MSS per se; and 5) individualised using MAS and MSS as measures of locomotor capacities (LOCO). Using MSS in isolation resulted in 61 % and 39 % of player's % HSR and % VHSR, respectively, being incorrectly interpreted, when compared to the IND technique. Estimating the RCT from fractional values of MAS resulted in erroneous interpretations of % HSR in 50 % of cases. The present results suggest that practitioners and researchers should avoid using singular fitness characteristics to individualise the intensity distribution of time-motion analysis data. A combination of players' anaerobic threshold, MAS, and MSS characteristics are recommended to individualise player-tracking data

Familial aggregation of migraine and depression: Insights from a large Australian twin sample

Free to read\ud \ud Objectives: This research examined the familial aggregation of migraine, depression, and their co-occurrence.\ud \ud Methods: Diagnoses of migraine and depression were determined in a sample of 5,319 Australian twins. Migraine was diagnosed by either self-report, the ID migraine™ Screener, or International Headache Society (IHS) criteria. Depression was defined by fulfilling either major depressive disorder (MDD) or minor depressive disorder (MiDD) based on the Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria. The relative risks (RR) for migraine and depression were estimated in co-twins of twin probands reporting migraine or depression to evaluate their familial aggregation and co-occurrence.\ud \ud Results: An increased RR of both migraine and depression in co-twins of probands with the same trait was observed, with significantly higher estimates within monozygotic (MZ) twin pairs compared to dizygotic (DZ) twin pairs. For cross-trait analysis, the RR for migraine in co-twins of probands reporting depression was 1.36 (95% CI: 1.24–1.48) in MZ pairs and 1.04 (95% CI: 0.95–1.14) in DZ pairs; and the RR for depression in co-twins of probands reporting migraine was 1.26 (95% CI: 1.14–1.38) in MZ pairs and 1.02 (95% CI: 0.94–1.11) in DZ pairs. The RR for strict IHS migraine in co-twins of probands reporting MDD was 2.23 (95% CI: 1.81–2.75) in MZ pairs and 1.55 (95% CI: 1.34–1.79) in DZ pairs; and the RR for MDD in co-twins of probands reporting IHS migraine was 1.35 (95% CI: 1.13–1.62) in MZ pairs and 1.06 (95% CI: 0.93–1.22) in DZ pairs.\ud \ud Conclusions: We observed significant evidence for a genetic contribution to familial aggregation of migraine and depression. Our findings suggest a bi-directional association between migraine and depression, with an increased risk for depression in relatives of probands reporting migraine, and vice versa. However, the observed risk for migraine in relatives of probands reporting depression was considerably higher than the reverse. These results add further support to previous studies suggesting that patients with comorbid migraine and depression are genetically more similar to patients with only depression than patients with only migraine

Shared genetic factors underlie migraine and depression

Free to read\ud \ud Migraine frequently co-occurs with depression. Using a large sample of Australian twin pairs, we aimed to characterize the extent to which shared genetic factors underlie these two disorders. Migraine was classified using three diagnostic measures, including self-reported migraine, the ID migraine screening tool, or migraine without aura (MO) and migraine with aura (MA) based on International Headache Society (IHS) diagnostic criteria. Major depressive disorder (MDD) and minor depressive disorder (MiDD) were classified using the Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria. Univariate and bivariate twin models, with and without sex-limitation, were constructed to estimate the univariate and bivariate variance components and genetic correlation for migraine and depression. The univariate heritability of broad migraine (self-reported, ID migraine, or IHS MO/MA) and broad depression (MiDD or MDD) was estimated at 56% (95% confidence interval [CI]: 53-60%) and 42% (95% CI: 37-46%), respectively. A significant additive genetic correlation (r G = 0.36, 95% CI: 0.29-0.43) and bivariate heritability (h 2 = 5.5%, 95% CI: 3.6-7.8%) was observed between broad migraine and depression using the bivariate Cholesky model. Notably, both the bivariate h 2 (13.3%, 95% CI: 7.0-24.5%) and r G (0.51, 95% CI: 0.37-0.69) estimates significantly increased when analyzing the more narrow clinically accepted diagnoses of IHS MO/MA and MDD. Our results indicate that for both broad and narrow definitions, the observed comorbidity between migraine and depression can be explained almost entirely by shared underlying genetically determined disease mechanisms