Asymmetric redirection of flow through the heart

Through cardiac looping during embryonic development, paths of flow through the mature heart have direction changes and asymmetries whose topology and functional significance remain relatively unexplored. Here we show, using magnetic resonance velocity mapping, the asymmetric redirection of streaming blood in atrial and ventricular cavities of the adult human heart, with sinuous, chirally asymmetric paths of flow through the whole. On the basis of mapped flow fields and drawings that illustrate spatial relations between flow paths, we propose that asymmetries and curvatures of the looped heart have potential fluidic and dynamic advantages. Patterns of atrial filling seem to be asymmetric in a manner that allows the momentum of inflowing streams to be redirected towards atrio-ventricular valves, and the change in direction at ventricular level is such that recoil away from ejected blood is in a direction that can enhance rather than inhibit ventriculo-atrial coupling. Chiral asymmetry might help to minimize dissipative interaction between entering, recirculating and outflowing streams. These factors might combine to allow a reciprocating, sling-like, 'morphodynamic' mode of action to come into effect when heart rate and output increase during exercise.     

Integrating Quarterly Data into a Dynamic Factor Model of US Monthly GDP

This paper develops and estimates a dynamic factor model in which estimates for unobserved monthly US Gross Domestic Product (GDP) are consistent with observed quarterly data. In contrast to existing approaches, the quarterly averages of our monthly estimates are exactly equal to the Bureau of Economic Analysis (BEA) quarterly estimates. The relationship between our monthly estimates and the quarterly data is therefore the same as the relationship between quarterly and annual data. The study makes use of Bayesian Markov chain Monte Carlo and data augmentation techniques to simulate values for the logarithms on monthly US GDP. The imposition of the exact linear quarterly constraint produces a non‐standard distribution, necessitating the implementation of a Metropolis simulation step in the estimation. Our methodology can be easily generalized to cases where the variable of interest is monthly GDP and in such a way that the final results incorporate the statistical uncertainty associated with the monthly GDP estimates. We provide an example by incorporating our monthly estimates into a Markov switching model of the US business cycle. Copyright © 2016 John Wiley & Sons, Ltd.