Synchronization in networks of identical linear systems

The paper investigates the synchronization of a network of identical linear state-space models under a possibly time-varying and directed interconnection structure. The main result is the construction of a dynamic output feedback coupling that achieves synchronization if the decoupled systems have no exponentially unstable mode and if the communication graph is uniformly connected. The result can be interpreted as a generalization of classical consensus algorithms. Stronger conditions are shown to be sufficient-but to some extent, also necessary-to ensure synchronization with the diffusive static output coupling often considered in the literature. © 2009 Elsevier Ltd. All rights reserved.

Correct biological timing in Arabidopsis requires multiple light-signaling pathways.

Circadian oscillators provide rhythmic temporal cues for a range of biological processes in plants and animals, enabling anticipation of the day/night cycle and enhancing fitness-associated traits. We have used engineering models to understand the control principles of a plant's response to seasonal variation. We show that the seasonal changes in the timing of circadian outputs require light regulation via feed-forward loops, combining rapid light-signaling pathways with entrained circadian oscillators. Linear time-invariant models of circadian rhythms were computed for 3,503 circadian-regulated genes and for the concentration of cytosolic-free calcium to quantify the magnitude and timing of regulation by circadian oscillators and light-signaling pathways. Bioinformatic and experimental analysis show that rapid light-induced regulation of circadian outputs is associated with seasonal rephasing of the output rhythm. We identify that external coincidence is required for rephasing of multiple output rhythms, and is therefore important in general phase control in addition to specific photoperiod-dependent processes such as flowering and hypocotyl elongation. Our findings uncover a fundamental design principle of circadian regulation, and identify the importance of rapid light-signaling pathways in temporal control.

Predictive techniques for turbulent oscillatory flows

The prediction of turbulent oscillatory flow at around transitional Reynolds numbers is considered for an idealized electronics system. To assess the accuracy of turbulence models, comparison is made with measurements. A stochastic procedure is used to recover instantaneous velocity time traces from predictions. This procedure enables more direct comparison with turbulence intensity measurements which have not been filtered to remove the oscillatory flow component. Normal wall distances, required in some turbulence models, are evaluated using a modified Poisson equation based technique. A range of zero, one and two equation turbulence models are tested, including zonal and a non-linear eddy viscosity models. The non-linear and zonal models showed potential for accuracy improvements.

Transient reflectivity on vertically aligned single-wall carbon nanotubes

One-color transient reflectivity measurements are carried out on two different samples of vertically aligned single-wall carbon nanotube bundles and compared with the response recently published on unaligned bundles. The negative sign of the optical response for both samples indicates that the free electron character revealed on unaligned bundles is only due to the intertube interactions favored by the tube bending. Neither the presence of bundles nor the existence of structural defects in aligned bundles is able to induce a free-electron like behavior of the photoexcited carriers. This result is also confirmed by the presence of non-linear excitonic effects in the transient response of the aligned bundles. © 2013 Elsevier B.V.

Rao-Blackwellized particle smoothers for mixed linear/nonlinear state-space models

We consider the smoothing problem for a class of conditionally linear Gaussian state-space (CLGSS) models, referred to as mixed linear/nonlinear models. In contrast to the better studied hierarchical CLGSS models, these allow for an intricate cross dependence between the linear and the nonlinear parts of the state vector. We derive a Rao-Blackwellized particle smoother (RBPS) for this model class by exploiting its tractable substructure. The smoother is of the forward filtering/backward simulation type. A key feature of the proposed method is that, unlike existing RBPS for this model class, the linear part of the state vector is marginalized out in both the forward direction and in the backward direction. © 2013 IEEE.