Initial Condition Sensitivity of Global Quantities in Magnetohydrodynamic Turbulence

In this paper we study the effect of subtle changes in initial conditions on the evolution of global quantities in two-dimensional Magnetohydrodynamic (MHD) turbulence. We find that a change in the initial phases of complex Fourier modes of the Els\"{a}sser variables, while keeping the initial values of total energy, cross helicity and Alfv\'{e}n ratio unchanged, has a significant effect on the evolution of cross helicity. On the contrary, the total energy and Alfv\'{e}n ratio are insensitive to the initial phases. Our simulations are based on direct numerical simulation using the pseudo-spectral method.Comment: 12 pages LateX, 11 ps figures. Accepted for publication by Physics of Plasma

Energy transfer in two-dimensional magnetohydrodynamic turbulence: formalism and numerical results

The basic entity of nonlinear interaction in Navier-Stokes and the Magnetohydrodynamic (MHD) equations is a wavenumber triad ({\bf k,p,q}) satisfying ${\bf k+p+q=0}$. The expression for the combined energy transfer from two of these wavenumbers to the third wavenumber is known. In this paper we introduce the idea of an effective energy transfer between a pair of modes by the mediation of the third mode, and find an expression for it. Then we apply this formalism to compute the energy transfer in the quasi-steady-state of two-dimensional MHD turbulence with large-scale kinetic forcing. The computation of energy fluxes and the energy transfer between different wavenumber shells is done using the data generated by the pseudo-spectral direct numerical simulation. The picture of energy flux that emerges is quite complex---there is a forward cascade of magnetic energy, an inverse cascade of kinetic energy, a flux of energy from the kinetic to the magnetic field, and a reverse flux which transfers the energy back to the kinetic from the magnetic. The energy transfer between different wavenumber shells is also complex---local and nonlocal transfers often possess opposing features, i.e., energy transfer between some wavenumber shells occurs from kinetic to magnetic, and between other wavenumber shells this transfer is reversed. The net transfer of energy is from kinetic to magnetic. The results obtained from the studies of flux and shell-to-shell energy transfer are consistent with each other.Comment: 27 pages REVTEX; 14 ps figure

Recent smell loss is the best predictor of COVID-19 among individuals with recent respiratory symptoms

In a preregistered, cross-sectional study we investigated whether olfactory loss is a reliable predictor of COVID-19 using a crowdsourced questionnaire in 23 languages to assess symptoms in individuals self-reporting recent respiratory illness. We quantified changes in chemosensory abilities during the course of the respiratory illness using 0-100 visual analog scales (VAS) for participants reporting a positive (C19+; n=4148) or negative (C19-; n=546) COVID-19 laboratory test outcome. Logistic regression models identified univariate and multivariate predictors of COVID-19 status and post-COVID-19 olfactory recovery. Both C19+ and C19- groups exhibited smell loss, but it was significantly larger in C19+ participants (mean±SD, C19+: -82.5±27.2 points; C19-: -59.8±37.7). Smell loss during illness was the best predictor of COVID-19 in both univariate and multivariate models (ROC AUC=0.72). Additional variables provide negligible model improvement. VAS ratings of smell loss were more predictive than binary chemosensory yes/no-questions or other cardinal symptoms (e.g., fever). Olfactory recovery within 40 days of respiratory symptom onset was reported for ~50% of participants and was best predicted by time since respiratory symptom onset. We find that quantified smell loss is the best predictor of COVID-19 amongst those with symptoms of respiratory illness. To aid clinicians and contact tracers in identifying individuals with a high likelihood of having COVID-19, we propose a novel 0-10 scale to screen for recent olfactory loss, the ODoR-19. We find that numeric ratings ≤2 indicate high odds of symptomatic COVID-19 (4<10). Once independently validated, this tool could be deployed when viral lab tests are impractical or unavailable

Solutes unmask differences in clustering versus phase separation of FET proteins

Acknowledgements: We are grateful to Andrei Pozniakovsky for the DNA constructs of all proteins, to Régis Lemaitre and Barbara Borgonovo for technical support with protein expression, purification, and characterization at MPI-CBG, and to Ralf Kühnemuth and Oleg Opanasyuk for technical assistance. We thank Eric Geertsma, Timothy Lohman, and Min Kyung Shinn for helpful discussions. This work was funded by a direct grant from the Max Planck Society (to A.A.H.), a grant from the NOMIS foundation (to A.A.H.), the Wellcome trust (209194/Z/17/Z to A.A.H.), the Deutsche Forschungsgemeinschaft (DFG) under Germany’s Excellence Strategy—EXC-2068—390729961- Cluster of Excellence Physics of Life of TU Dresden (to A.A.H.), the European Research Council through the ERC grant PhysProt (to T.P.J.K., agreement no. 337969), the Wellcome Trust and the Frances and Augustus Newman foundation (to T.P.J.K.), SPP2191 from the Deutsche Forschungsgemeinschaft (to C.A.M.S. and R.V.P.), the US National Institutes of Health (R01NS121114 to R.V.P.), the US National Science Foundation (MCB-2227268 to R.V.P.), and the St. Jude Children’s Research Hospital collaborative research consortium on the Biology and Biophysics of RNP Granules (to R.V.P.).AbstractPhase separation and percolation contribute to phase transitions of multivalent macromolecules. Contributions of percolation are evident through the viscoelasticity of condensates and through the formation of heterogeneous distributions of nano- and mesoscale pre-percolation clusters in sub-saturated solutions. Here, we show that clusters formed in sub-saturated solutions of FET (FUS-EWSR1-TAF15) proteins are affected differently by glutamate versus chloride. These differences on the nanoscale, gleaned using a suite of methods deployed across a wide range of protein concentrations, are prevalent and can be unmasked even though the driving forces for phase separation remain unchanged in glutamate versus chloride. Strikingly, differences in anion-mediated interactions that drive clustering saturate on the micron-scale. Beyond this length scale the system separates into coexisting phases. Overall, we find that sequence-encoded interactions, mediated by solution components, make synergistic and distinct contributions to the formation of pre-percolation clusters in sub-saturated solutions, and to the driving forces for phase separation.</jats:p