Optimal learning under robustness and time-consistency

We model learning in a continuous-time Brownian setting where there is prior ambiguity. The associated model of preference values robustness and is time-consistent. It is applied to study optimal learning when the choice between actions can be postponed, at a per-unit-time cost, in order to observe a signal that provides information about an unknown parameter. The corresponding optimal stopping problem is solved in closed form, with a focus on two specific settings: Ellsberg’s two-urn thought experiment expanded to allow learning before the choice of bets, and a robust version of the classical problem of sequential testing of two simple hypotheses about the unknown drift of a Wiener process. In both cases, the link between robustness and the demand for learning is studied.Accepted manuscrip

Ambiguous volatility and asset pricing in continuous time

This paper formulates a model of utility for a continuous time framework that captures the decision-maker's concern with ambiguity about both volatility and drift. Corresponding extensions of some basic results in asset pricing theory are presented. First, we derive arbitrage-free pricing rules based on hedging arguments. Ambiguous volatility implies market incompleteness that rules out perfect hedging. Consequently, hedging arguments determine prices only up to intervals. However, sharper predictions can be obtained by assuming preference maximization and equilibrium. Thus we apply the model of utility to a representative agent endowment economy to study equilibrium asset returns. A version of the C-CAPM is derived and the effects of ambiguous volatility are described

CFD modelling of buoyancy-driven natural ventilation opposed by wind

This paper presents CFD simulations of natural displacement ventilation airflows in which the buoyancy force produced by a heat source is opposed by a wind force. Cases investigated focus on windbuoyancy force relationships for which a two-layer stratification is maintained. CFD predictions of the position of the interface separating the two layers and the change in reduced gravity (temperature difference) between them are compared with the analytical work and salt-bath measurements of Hunt and Linden (2000, 2005). Comparisons are good with only minor discrepancies in the interface position and a small under-prediction of the upper layer reduced gravity

A systems-biology approach to understanding the ciliopathy disorders.

'Ciliopathies' are an emerging class of genetic multisystemic human disorders that are caused by a multitude of largely unrelated genes that affect ciliary structure/function. They are unified by shared clinical features, such as mental retardation, cystic kidney, retinal defects and polydactyly, and by the common localization of the protein products of these genes at or near the primary cilium of cells. With the realization that many previously disparate conditions are a part of this spectrum of disorders, there has been tremendous interest in the function of cilia in developmental signaling and homeostasis. Ciliopathies are mostly inherited as simple recessive traits, but phenotypic expressivity is under the control of numerous genetic modifiers, putting these conditions at the interface of simple and complex genetics. In this review, we discuss the ever-expanding ciliopathy field, which has three interrelated goals: developing a comprehensive understanding of genes mutated in the ciliopathies and required for ciliogenesis; understanding how the encoded proteins work together in complexes and networks to modulate activity and structure-function relationships; and uncovering signaling pathways and modifier relationships