48 resultados para Spacial variability
Resumo:
Intense phytoplankton blooms were observed along the Patagonian shelf-break with satellite ocean color data, but few in situ optical observations were made in that region. We examine the variability of phytoplankton absorption and particulate scattering coefficients during such blooms on the basis of field data. The chlorophyll-a concentration, [Chla], ranged from 0.1 to 22.3 mg m−3 in surface waters. The size fractionation of [Chla] showed that 80% of samples were dominated by nanophytoplankton (N-group) and 20% by microphytoplankton (M-group). Chlorophyll-specific phytoplankton absorption coefficients at 440 and 676 nm, a*ph(440) and a*ph(676), and particulate scattering coefficient at 660 nm, b*p(660), ranged from 0.018 to 0.173, 0.009 to 0.046, and 0.031 to 2.37 m2 (mg Chla)−1, respectively. Both a*ph(440) and a*ph(676) were statistically higher for the N-group than M-group and also considerably higher than expected from global trends as a function of [Chla]. This result suggests that size of phytoplankton cells in Patagonian waters tends to be smaller than in other regions at similar [Chla]. The phytoplankton cell size parameter, Sf, derived from phytoplankton absorption spectra, proved to be useful for interpreting the variability in the data around the general inverse dependence of a*ph(440), a*ph(676), and b*p(660) on [Chla]. Sf also showed a pattern along the increasing trend of a*ph(440) and a*ph(676) as a function of the ratios of some accessory pigments to [Chla]. Our results suggest that the variability in phytoplankton absorption and scattering coefficients in Patagonian waters is caused primarily by changes in the dominant phytoplankton cell size accompanied by covariation in the concentrations of accessory pigments.
Resumo:
Rationale: NAVA is an assisted ventilatory mode that uses the electrical activity of the diaphragm (Edi) to trigger and cycle the ventilator, and to offer inspiratory assistance in proportion to patient effort. Since Edi varies from breath to breath, airway pressure and tidal volume also vary according to the patient's breathing pattern. Our objective was to compare the variability of NAVA with PSV in mechanically ventilated patients during the weaning phase. Methods: We analyzed the data collected for a clinical trial that compares PSV and NAVA during spontaneous breathing trials using PSV, with PS of 5 cmH2O, and NAVA, with Nava level titrated to generate a peak airway pressure equivalent to PSV of 5 cmH2O (NCT01137271). We captured flow, airway pressure and Edi at 100Hz from the ventilator using a dedicated software (Servo Tracker v2, Maquet, Sweden), and processed the cycles using a MatLab (Mathworks, USA) code. The code automatically detects the tidal volume (Vt), respiratory rate (RR), Edi and Airway pressure (Paw) on a breath-by-breath basis for each ventilatory mode. We also calculated the coefficient of variation (standard deviation, SD, divided by the mean). Results: We analyzed data from eleven patients. The mean Vt was similar on both modes (370 ±70 for Nava and 347± 77 for PSV), the RR was 26±6 for Nava and 26±7 or PSV. Paw was higher for Nava than for PSV (14±1 vs 11±0.4, p=0.0033), and Edi was similar for both modes (12±8 for Nava and 11±6 for PSV). The variability of the respiratory pattern, assessed with the coefficient of variation, was larger for Nava than for PSV for the Vt ( 23%±1% vs 15%±1%, p=0.03) and Paw (17%±1% vs 1% ±0.1%, p=0.0033), but not for RR (21% ±1% vs 16% ±8%, p=0.050) or Edi (33%±14% vs 39% ±16%,p=0.07). Conclusion: The variability of the breathing pattern is high during spontaneous breathing trials independent of the ventilatory mode. This variability results in variability of airway pressure and tidal volume, which are higher on Nava than on PSV. Our results suggest that Nava better reflects the normal variability of the breathing pattern during assisted mechanical ventilation.
Resumo:
We report on four years of observations of 3C 273 at 7mm obtained with the Itapetinga radio telescope, in Brazil, between 2009 and 2013. We detected a flare in 2010 March, when the flux density increased by 50 per cent and reached 35 Jy. After the flare, the flux density started to decrease and reached values lower than 10 Jy. We suggest that the 7-mm flare is the radio counterpart of the γ -ray flare observed by the Fermi Large Area Telescope in 2009 September, in which the flux density at high energies reached a factor of 50 of its average value. A delay of 170 d between the radio and γ -ray flares was revealed using the discrete correlation function (DCF) that can be interpreted in the context of a shock model, in which each flare corresponds to the formation of a compact superluminal component that expands and becomes optically thin at radio frequencies at latter epochs. The differences in flare intensity between frequencies and at different times are explained as a consequence of an increase in the Doppler factor δ, as predicted by the 16-yr precession model proposed by Abraham & Romero. This increase has a large effect on boosting at high frequencies while it does not affect the observed optically thick radio emission too much. We discuss other observable effects of the variation in δ, such as the increase in the formation rate of superluminal components, the variations in the time delay between flares and the periodic behaviour of the radio light curve that we have found to be compatible with changes in the Doppler factor.