2,193 research outputs found
Discovery of the Narrow-Line Seyfert 1 galaxy Mkn 335 in an historical low X-ray flux state
We report the discovery of the Narrow-Line Seyfert 1 galaxy Mkn 335 in an
extremely low X-ray state. A comparison of Swift observations obtained in May
and June/July 2007 with all previous X-ray observations between 1971 to 2006
show the AGN to have diminished in flux by a factor of more than 30, the lowest
X-ray flux Mkn 335 has ever been observed in. The Swift observations show an
extremely hard X-ray spectrum at energies above 2 keV. Possible interpretations
include partial covering absorption or X-ray reflection from the disk. In this
letter we consider the partial covering interpretation. The Swift observations
can be well fit by a strong partial covering absorber with varying absorption
column density N_H= 1-4 x 10^{23} cm-2 and a covering fraction f_c=0.9 - 1.
When corrected for intrinsic absorption, the X-ray flux of Mkn 335 varies by
only factors of 4-6. In the UV Mkn 335 shows variability in the order of 0.2
mag. We discuss the similarity of Mkn 335 with the highly variable NLS1
WPVS007, and speculate about a possible link between NLS1 galaxies and
broad-absorption line quasars.Comment: ApJ Letter accepted; 8 pages, 2 figures; The new version has three
more sentences in the introduction and three references added to the
discussio
The hard X-ray perspective on the soft X-ray excess
The X-ray spectra of many active galactic nuclei (AGN) exhibit a `soft
excess' below 1keV, whose physical origin remains unclear. Diverse models have
been suggested to account for it, including ionised reflection of X-rays from
the inner part of the accretion disc, ionised winds/absorbers, and
Comptonisation. The ionised reflection model suggests a natural link between
the prominence of the soft excess and the Compton reflection hump strength
above 10keV, but it has not been clear what hard X-ray signatures, if any, are
expected from the other soft X-ray candidate models. Additionally, it has not
been possible up until recently to obtain high-quality simultaneous
measurements of both soft and hard X-ray emission necessary to distinguish
these models, but upcoming joint XMM-NuSTAR programmes provide precisely this
opportunity. In this paper, we present an extensive analysis of simulations of
XMM+NuSTAR observations, using two candidate soft excess models as inputs, to
determine whether such campaigns can disambiguate between them by using hard
and soft X-ray observations in tandem. The simulated spectra are fit with the
simplest "observer's model" of a black body and neutral reflection to
characterise the strength of the soft and hard excesses. A plot of the strength
of the hard excess against the soft excess strength provides a diagnostic plot
which allows the soft excess production mechanism to be determined in
individual sources and samples using current state-of-the-art and next
generation hard X-ray enabled observatories. This approach can be
straightforwardly extended to other candidate models for the soft excess.Comment: 12 pages, 11 figures, accepted for publication in ApJ. Added
reference
La microflora simpagica bioindicatrice di condizioni ambientali estreme nell'ecosistema pack-ice.
Use of simple body measurements and allometry to predict the chemical growth and feed intake in pigs
Nel lavoro si propone una procedura per stimare le variazioni di composizione chimica corporea e dell'in gestione alimentare di suini, allevati in condizioni non limitanti, basata su rilievi di peso vivo (BW) e di spessore del grasso dorsale (P2) ripetuti a diverse età. Si è utilizzata una banca dati riguardante 920 suini ibridi maschi (Goland) alimentati ad libitum che ha fornito informazioni individuali di BW, misurato a 71 ± 4 (t1), 126 ± 5 (t2) and 184 ± 5 (t3) giorni di età, di P2, misurato alle età t2 e t3, e di ingestioni ali mentari (FI), registrate nell'intervallo di tempo tra t2 e t3 mediante stazioni di alimentazione automatiz zate (IVOG). La massa corporea di lipidi (kg) è stata stimata con l'equazione L= (9,17 + 0,70*P2)*BW/100 e gli altri costituenti corporei sono stati calcolati dal peso vivo netto meno la frazione lipidica, utilizzando funzioni di allometria. Dai cambiamenti stimati di composizione corporea tra le età t2 e t3 sono stati quindi valutati i fabbisogni di energia per il mantenimento e per la crescita ottenendo i cor rispondenti quantitativi di mangime previsti per il periodo di crescita in esame (PFI) per ciascun indivi duo. I valori misurati di consumo alimentare (FI) ottenuti dalle stazioni IVOG sono stati sottoposti ad ana lisi della varianza per gli effetti: mese, partita (entro mese), BWt2, P2t2, accrescimento medio giornaliero e variazioni di P2 nel periodo tra t2 e t3. I valori di FI sono stati anche analizzati sostituendo, come fonti di variazione, le misure corporee dirette con stime derivate di PFI. Risultati. L'approccio seguito ha con sentito di stimare i parametri delle curve di Gompertz che definiscono la crescita proteica potenziale di ciascun individuo, la massa proteica matura (Pm, kg), il coefficiente di accrescimento relativo (B, d-1) e il rapporto lipidi:proteine a maturità (Lm/Pm), risultati in media pari a 43,5 ± 5,8 kg, 0,0116 ± 0,0011 d-1 e 1,81 ± 0,30, rispettivamente. Nel periodo compreso tra t2 e t3 la massa proteica mediamente pre sente è risultata pari a 18,5 + 1,6 kg e le ritenzioni medie di proteine e lipidi sono state in media pari a 177 ± 21 e 239 ± 62 g/d, rispettivamente. I valori medi di FI e di PFI sono stati, rispettivamente, pari a 2,824 ± 0,448 and 2,814 ± 0,393 kg/d. Nel modello di analisi statistica la sostituzione delle misure cor poree dirette con i valori di PFI non ha modificato la proporzione di varianza spiegata (83%) né i valori di deviazione standard residua (0,199 g/d). I valori di "residual feed intake" risultanti dall'applicazione dei due modelli di analisi sono risultati altamente correlati (RSD= 0,043 kg/d; R2= 0.961). L'approccio impiegato ha quindi consentito di ottenere una buona interpretazione biologica della varianza dei valori di FI associata alle diverse misure corporee. La sostanziale coincidenza tra valori misurati e stimati di ingestione alimentare ha fornito una ragionevole garanzia sulla validità dei valori di composizione corpo rea stimati. Così, un protocollo di misure ripetute di peso vivo e di spessore del lardo dorsale nel corso della crescita, accoppiato ad elaborazioni di tipo allometrico, può essere proposto per stimare in vivo lo stato chimico corporeo di suini allevati in condizioni ritenute non limitanti. The paper provides a practical procedure to estimate the chemical composition of pigs, their compositional growth and the expected feed intake from measurements of body weight (BW) and backfat thickness (P2) serially performed in vivo. A farm data set provided information on 920 individuals including BW, measured at 71 ± 4 (t1), 126 ± 5 (t2) and 184 ± 5 (t3) days of age, of P2 at t2 and t3, and of voluntary daily feed intake (FI), recorded over the period from t2 to t3 by automated IVOG feeders. Body lipid mass was estimated as L= (9.17 + 0.70*P2) *BW/100 and the other chemical constituents were predicted from fat free empty body mass using Gompertz growth functions and allometry. Using individual changes of body composition from age t2 to t3, energy requirements for maintenance and growth and the corresponding predicted feed intakes (PFI) were estimated. Measured FI were analysed for the effects of month, batch (within month), BWt2, P2t2, average metabolic weight, average daily gain and variation of P2 from t2 to t3. The same model was run again replacing the direct simple body measurements (BW and P2) with the estimated values of PFI as source of variation. Results. The Gompertz estimates of mature protein mass (Pm), relative growth rate parameter (B) and lipid to protein ratio at maturity were 43.5 ± 5.8 kg, 0.0116 ± 0.0011 d-1 and 1.81 ± 0.30, respectively. The current protein mass averaged 18.5 + 1.6 kg and the daily retentions of protein and lipid were 177 ± 21 and 239 ± 62 g/d, respectively. FI and PFI averaged 2.824 ± 0.448 and 2.814 ± 0.393 kg/d, respectively. In the ANOVA of the FI data, the replacement of direct body measurements by PFI did not change the proportion of variance explained (83%) and the RSD (0.199 g/d). The two sets of residual feed intake values obtained from the two ANOVA were highly correlated (RSD = 0.043 kg/d; R2= 0.961). Agreement between predicted and determined feed intakes provided a reasonable guarantee to the estimated (based on BW and P2) changes of body composition. Thus, a scheduled protocol of measurement of BW and P2 over the course of growth, coupled with the use of allometry, can be proposed to estimate in vivo the change of the chemical status of pigs kept under non limiting conditions
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