Capillary instability of a two-layer annular film: an airway closure model

Capillary instability of a two-layer liquid film lining a rigid tube is studied computationally as a model for liquid plug formation and closure of human airways. The two-layer liquid consists of a serous layer, also called the periciliary liquid layer, at the inner side and a mucus layer at the outer side. Together, they form the airway surface liquid lining the airway wall and surrounding an air core. Liquid plug formation occurs due to Plateau–Rayleigh instability when the liquid film thickness exceeds a critical value. Numerical simulations are performed for the entire closure process, including the pre- and post-coalescence phases. The mechanical stresses and their gradients on the airway wall are investigated for physiologically relevant ranges of the mucus-to-serous thickness ratio, the viscosity ratio, and the air–mucus and serous–mucus surface tensions encompassing healthy and pathological conditions of a typical adult human lung. The growth rate of the two-layer model is found to be higher in comparison with a one-layer equivalent configuration. This leads to a much sooner closure in the two-layer model than that in the corresponding one-layer model. Moreover, it is found that the serous layer generally provides an effective protection to the pulmonary epithelium against high shear stress excursions and their gradients. A linear stability analysis is also performed, and the results are found to be in good qualitative agreement with the simulations. Finally, a secondary coalescence that may occur during the post-closure phase is investigated.

An idealized 1½-layer isentropic model with convection and precipitation for satellite data assimilation research. Part II: model derivation

In this part II paper we present a fully consistent analytical derivation of the ‘dry’ isentropic 1½-layer shallow water model described and used in part I of this study, with no convection and precipitation. The mathematical derivation presented here is based on a combined asymptotic and slaved Hamiltonian analysis which is used to resolve an apparent inconsistency arising from the application of a rigid-lid approximation to an isentropic two-layer shallow water model. Real observations based on radiosonde data are used to justify the scaling assumptions used throughout the paper, as well as in part I. Eventually, a fully consistent isentropic 1½-layer model emerges from imposing fluid at rest (v1 = 0) and zero Montgomery potential (M1 = 0) in the upper layer of an isentropic two-layer model.

Female craniometrics support the ‘two-layer model’ of human dispersal in Eastern Eurasia

This study reports a cranio-morphometric analysis of female human remains from seven archaeological sites in China, Vietnam and Taiwan that date between 16,000 and 5300 BP. The aim of the analysis is to test the “two-layer” model of human dispersal in eastern Eurasia, using previously unanalysed female remains to balance the large sample of previously-analysed males. The resulting craniometric data indicate that the examined specimens all belong to the “first layer” of dispersal, and share a common ancestor with recent Australian and Papuan populations, and the ancient Jomon people of Japan. The analysed specimens pre-date the expansion of agricultural populations of East/Northeast Asian origin—that is, the “second layer” of human dispersal proposed by the model. As a result of this study, the two-layer model, which has hitherto rested on evidence only from male skeletons, is now strongly supported by female-derived data. Further comparisons reveal that the people of the first layer were closer in terms of their facial morphology to modern Africans and Sri Lankan Veddah than to modern Asians and Europeans, suggesting that the Late Pleistocene through Middle Holocene hunter-gatherers examined in this study were direct descendants of the anatomically modern humans who first migrated out of Africa through southern Eurasia.

Heterogeneous node copying from hidden network structure

Node copying is an important mechanism for network formation, yet most models assume uniform copying rules. Motivated by observations of heterogeneous triadic closure in real networks, we introduce the concept of a hidden network model—a generative two-layer model in which an observed network evolves according to the structure of an underlying hidden layer—and apply the framework to a model of heterogeneous copying. Framed in a social context, these two layers represent a node’s inner social circle, and wider social circle, such that the model can bias copying probabilities towards, or against, a node’s inner circle of friends. Comparing the case of extreme inner circle bias to an equivalent model with uniform copying, we find that heterogeneous copying suppresses the power-law degree distributions commonly seen in copying models, and results in networks with much higher clustering than even the most optimum scenario for uniform copying. Similarly large clustering values are found in real collaboration networks, lending empirical support to the mechanism.