Subgrid-scale stresses and scalar fluxes constructed by the multi-scale turnover Lagrangian map

The multi-scale turnover Lagrangianmap(MTLM)[C. Rosales and C. Meneveau, "Anomalous scaling and intermittency in three-dimensional synthetic turbulence," Phys. Rev. E 78, 016313 (2008)] uses nested multi-scale Lagrangian advection of fluid particles to distort a Gaussian velocity field and, as a result, generate non-Gaussian synthetic velocity fields. Passive scalar fields can be generated with the procedure when the fluid particles carry a scalar property [C. Rosales, "Synthetic three-dimensional turbulent passive scalar fields via the minimal Lagrangian map," Phys. Fluids 23, 075106 (2011)]. The synthetic fields have been shown to possess highly realistic statistics characterizing small scale intermittency, geometrical structures, and vortex dynamics. In this paper, we present a study of the synthetic fields using the filtering approach. This approach, which has not been pursued so far, provides insights on the potential applications of the synthetic fields in large eddy simulations and subgridscale (SGS) modelling. The MTLM method is first generalized to model scalar fields produced by an imposed linear mean profile. We then calculate the subgrid-scale stress, SGS scalar flux, SGS scalar variance, as well as related quantities from the synthetic fields. Comparison with direct numerical simulations (DNSs) shows that the synthetic fields reproduce the probability distributions of the SGS energy and scalar dissipation rather well. Related geometrical statistics also display close agreement with DNS results. The synthetic fields slightly under-estimate the mean SGS energy dissipation and slightly over-predict the mean SGS scalar variance dissipation. In general, the synthetic fields tend to slightly under-estimate the probability of large fluctuations for most quantities we have examined. Small scale anisotropy in the scalar field originated from the imposed mean gradient is captured. The sensitivity of the synthetic fields on the input spectra is assessed by using truncated spectra or model spectra as the input. Analyses show that most of the SGS statistics agree well with those from MTLM fields with DNS spectra as the input. For the mean SGS energy dissipation, some significant deviation is observed. However, it is shown that the deviation can be parametrized by the input energy spectrum, which demonstrates the robustness of the MTLM procedure. Published by AIP Publishing

Stroke in critically ill patients with respiratory failure due to COVID-19: Disparities between low-middle and high-income countries

Purpose: We aimed to compare the incidence of stroke in low-and middle-income countries (LMICs) versus high-income countries (HICs) in critically ill patients with COVID-19 and its impact on in-hospital mortality. Methods: International observational study conducted in 43 countries. Stroke and mortality incidence rates and rate ratios (IRR) were calculated per admitted days using Poisson regression. Inverse probability weighting (IPW) was used to address the HICs vs. LMICs imbalance for confounders. Results: 23,738 patients [20,511(86.4 %) HICs vs. 3,227(13.6 %) LMICs] were included. The incidence stroke/1000 admitted-days was 35.7 (95 %CI = 28.4–44.9) LMICs and 17.6 (95 %CI = 15.8–19.7) HICs; ischemic 9.47 (95 %CI = 6.57–13.7) LMICs, 1.97 (95 %CI = 1.53, 2.55) HICs; hemorrhagic, 7.18 (95 %CI = 4.73–10.9) LMICs, and 2.52 (95 %CI = 2.00–3.16) HICs; unspecified stroke type 11.6 (95 %CI = 7.75–17.3) LMICs, 8.99 (95 %CI = 7.70–10.5) HICs. In regression with IPW, LMICs vs. HICs had IRR = 1.78 (95 %CI = 1.31–2.42, p < 0.001). Patients from LMICs were more likely to die than those from HICs [43.6% vs 29.2 %; Relative Risk (RR) = 2.59 (95 %CI = 2.29–2.93), p < 0.001)]. Patients with stroke were more likely to die than those without stroke [RR = 1.43 (95 %CI = 1.19–1.72), p < 0.001)]. Conclusions: Stroke incidence was low in HICs and LMICs although the stroke risk was higher in LMICs. Both LMIC status and stroke increased the risk of death. Improving early diagnosis of stroke and redistribution of healthcare resources should be a priority. Trial registration: ACTRN12620000421932 registered on 30/03/2020