Some contagious diseases, such as COVID-19, spread through the transmission of aerosols and droplets. Aerosol and droplet formation occurs inside and outside of the respiratory tract, the latter being observed during speaking and sneezing. Upon sneezing, saliva is expelled as a flat sheet, which destabilizes into filaments that subsequently break up into droplets. The presence of macromolecules (such as mucins) in saliva influences the dynamics of aerosol generation, since elasticity is expected to stabilize both fluid sheets and filaments, hence deterring droplet formation. In this study, the process of aerosol formation outside the respiratory tract is systematically replicated using an impinging jet setup, where two liquid jets collide and form a thin fluid sheet that can fragment into ligaments and droplets. The experimental setup enables us to investigate a range of dynamic conditions, quantified by the relevant non-dimensional numbers, which encompass those experienced during sneezing. Experiments are conducted with human saliva provided by different donors, revealing significant variations in their stability and breakup. We quantify the effect of viscoelasticity via shear and extensional rheology experiments, concluding that the extensional relaxation time is the most adequate measure of a saliva's elasticity. We summarize our results in terms of the dimensionless Weber, Reynolds, and Deborah numbers and construct universal state diagrams that directly compare our data to human sneezing, concluding that the aerosolization propensity is correlated with diminished saliva elasticities, higher emission velocities, and larger ejecta volumes. This could entail variations in disease transmission between individuals which hitherto have not been recognized.
Epigenome is susceptible to modulation by environmental pressures—namely, through alterations in global DNA methylation, impacting the organism condition and, ultimately, reverberating on the phenotype of the subsequent generations. Hence, an intergenerational study was conducted, aiming to clarify the influence of genotoxicants on global DNA methylation of the crayfish Procambarus clarkii. Two subsequent generations were exposed to the herbicide penoxsulam (Px; 23 µg·L−1) and to the genotoxicant model ethyl methanesulfonate (EMS; 5 mg·L−1). Px did not induce changes in DNA methylation of adult crayfish (F0). However, the hypomethylation occurring in unexposed F1 juveniles demonstrated that the history of exposure per se can modulate epigenome. In F1 descendants of the Px-exposed group, methylome (hypermethylated) was more affected in males than in females. EMS-induced hypomethylation in adult females (F0), also showed gender specificity. In addition, hypomethylation was also observed in the unexposed F1 crayfish, indicating an intergenerational epigenetic effect. The modulatory role of past exposure to penoxsulam or to EMS also showed a dependency on the crayfish developmental stage. Overall, this research revealed that indirect experiences (events occurring in a predecessor generation) can have an impact even greater than direct experiences (present events) on the epigenetic dynamics.
In this paper, we obtain a saddlepoint approximation for the small sample distribution of several variogram estimators such as the classical Matheron’s estimator, some M-estimators like the robust Huber’s variogram estimator, and also the α-trimmed variogram estimator. The tail probability approximation obtained is very accurate even for small sample sizes. In the approximations we consider that the observations follow a distribution close to the normal, specifically, a scale contaminated normal model. To obtain the approximations we transform the original observations into a new ones, which can be considered independent if a linearized variogram can be accepted as model for them. To check this, a goodness of fit test for a variogram model is defined in the last part of the paper.
The 𝐸2/𝑀1 ratio (EMR) of the Δ(1232) is extracted from the world data in pion photoproduction by means of an effective Lagrangian approach (ELA). This quantity has been derived within a crossing symmetric, gauge invariant, and chiral symmetric Lagrangian model which also contains a consistent modern treatment of the Δ(1232) resonance. The bare 𝑠-channel Δ(1232) contribution is well isolated and final state interactions (FSI) are effectively taken into account fulfilling Watson's theorem. The obtained EMR value, EMR =(−1.30±0.52)%, is in good agreement with the latest lattice QCD calculations [Phys. Rev. Lett. 94, 021601 (2005)] and disagrees with results of current quark model calculations.