An allelic series reveals essential roles for FY in plant development in addition to flowering-time control

The autonomous pathway functions to promote flowering in Arabidopsis by limiting the accumulation of the floral repressor FLOWERING LOCUS C (FLC). Within this pathway FCA is a plant-specific, nuclear RNA-binding protein, which interacts with FY, a highly conserved eukaryotic polyadenylation factor. FCA and FY function to control polyadenylation site choice during processing of the FCA transcript. Null mutations in the yeast FY homologue Pfs2p are lethal. This raises the question as to whether these essential RNA processing functions are conserved in plants. Characterisation of an allelic series of fy mutations reveals that null alleles are embryo lethal. Furthermore, silencing of FY, but not FCA, is deleterious to growth in Nicotiana. The late-flowering fy alleles are hypomorphic and indicate a requirement for both intact FY WD repeats and the C-terminal domain in repression of FLC. The FY C-terminal domain binds FCA and in vitro assays demonstrate a requirement for both C-terminal FY-PPLPP repeats during this interaction. The expression domain of FY supports its roles in essential and flowering-time functions. Hence, FY may mediate both regulated and constitutive RNA 3'-end processing.

Representations and algorithms for finite-state bisimulations of linear discrete-time control systems

While a large amount of research over the past two decades has focused on discrete abstractions of infinite-state dynamical systems, many structural and algorithmic details of these abstractions remain unknown. To clarify the computational resources needed to perform discrete abstractions, this paper examines the algorithmic properties of an existing method for deriving finite-state systems that are bisimilar to linear discrete-time control systems. We explicitly find the structure of the finite-state system, show that it can be enormous compared to the original linear system, and give conditions to guarantee that the finite-state system is reasonably sized and efficiently computable. Though constructing the finite-state system is generally impractical, we see that special cases could be amenable to satisfiability based verification techniques. ©2009 IEEE.

Monte Carlo filtering and smoothing with application to time-varying spectral estimation

We develop methods for performing filtering and smoothing in non-linear non-Gaussian dynamical models. The methods rely on a particle cloud representation of the filtering distribution which evolves through time using importance sampling and resampling ideas. In particular, novel techniques are presented for generation of random realisations from the joint smoothing distribution and for MAP estimation of the state sequence. Realisations of the smoothing distribution are generated in a forward-backward procedure, while the MAP estimation procedure can be performed in a single forward pass of the Viterbi algorithm applied to a discretised version of the state space. An application to spectral estimation for time-varying autoregressions is described.

Bayesian model selection for time series using Markov chain Monte Carlo

We present a stochastic simulation technique for subset selection in time series models, based on the use of indicator variables with the Gibbs sampler within a hierarchical Bayesian framework. As an example, the method is applied to the selection of subset linear AR models, in which only significant lags are included. Joint sampling of the indicators and parameters is found to speed convergence. We discuss the possibility of model mixing where the model is not well determined by the data, and the extension of the approach to include non-linear model terms.

Nucleated polymerization with secondary pathways. I. Time evolution of the principal moments.

Self-assembly processes resulting in linear structures are often observed in molecular biology, and include the formation of functional filaments such as actin and tubulin, as well as generally dysfunctional ones such as amyloid aggregates. Although the basic kinetic equations describing these phenomena are well-established, it has proved to be challenging, due to their non-linear nature, to derive solutions to these equations except for special cases. The availability of general analytical solutions provides a route for determining the rates of molecular level processes from the analysis of macroscopic experimental measurements of the growth kinetics, in addition to the phenomenological parameters, such as lag times and maximal growth rates that are already obtainable from standard fitting procedures. We describe here an analytical approach based on fixed-point analysis, which provides self-consistent solutions for the growth of filamentous structures that can, in addition to elongation, undergo internal fracturing and monomer-dependent nucleation as mechanisms for generating new free ends acting as growth sites. Our results generalise the analytical expression for sigmoidal growth kinetics from the Oosawa theory for nucleated polymerisation to the case of fragmenting filaments. We determine the corresponding growth laws in closed form and derive from first principles a number of relationships which have been empirically established for the kinetics of the self-assembly of amyloid fibrils.

Modified Kanerva model. Results for real time word recognition

This paper describes results obtained using the modified Kanerva model to perform word recognition in continuous speech after being trained on the multi-speaker Alvey 'Hotel' speech corpus. Theoretical discoveries have recently enabled us to increase the speed of execution of part of the model by two orders of magnitude over that previously reported by Prager & Fallside. The memory required for the operation of the model has been similarly reduced. The recognition accuracy reaches 95% without syntactic constraints when tested on different data from seven trained speakers. Real time simulation of a model with 9,734 active units is now possible in both training and recognition modes using the Alvey PARSIFAL transputer array. The modified Kanerva model is a static network consisting of a fixed nonlinear mapping (location matching) followed by a single layer of conventional adaptive links. A section of preprocessed speech is transformed by the non-linear mapping to a high dimensional representation. From this intermediate representation a simple linear mapping is able to perform complex pattern discrimination to form the output, indicating the nature of the speech features present in the input window.

Bias-dependent recovery time of all-optical resonant nonlinearity in InGaAsP/InGaAsP MQW waveguide

We have investigated a resonant refractive nonlinearity in a semiconductor waveguide by measuring intensity dependent phase shifts and bias-dependent recovery times. The measurements were performed on an optimized 750-μm-long AR coated buried heterostructure MQW p-i-n waveguide with a bandedge at 1.48 μm. Figure 1 shows the experimental arrangement. The mode-locked color center laser was tuned to 50 meV beyond the bandedge and 8 ps pulses with peak incident power up to 57 W were coupled into the waveguide. Some residual bandtail absorption remains at this wavelength and this is sufficient to cause carriers to be photogenerated and these give rise to a refractive nonlinearity, predominantly by plasma and bandfilling effects. A Fabry-Perot interferometer is used to measure the spectrum of the light which exits the waveguide. The nonlinearity within the guide causes self phase modulation (SPM) of the light and a study of the spectrum allows information to be recovered on the magnitude and recovery time of the nonlinear phase shift with a reasonable degree of accuracy. SPM spectra were recorded for a variety of pulse energies coupled into he unbiased waveguide. Figure 2 shows the resultant phase shift measured from the SPM spectra as a function of pulse energy. The relationship is a linear one, indicating that no saturation of the nonlinearity occurs for coupled pulse energies up to 230 pJ. A π phase shift, the minimum necessary for an all-optical switch, is obtained for a coupled pulse energy of 57 pJ while the maximum phase shift, 4 π, was measured for 230 pJ. The SPM spectra were highly asymmetric with pulse energy shifted to higher frequencies. Such spectra are characteristic of a slow, negative nonlinearity. This relatively slow speed is expected for the unbiased guide as the recovery time will be of the order of the recombination time of the photogenerated electrons, about 1 ns for InGaAsP material. In order to reduce the recovery time of the nonlinearity, it is necessary to remove the photogenerated carriers from the waveguide by a process other than recombination. One such technique is to apply a reverse bias to the waveguide in order to sweep the carriers out. Figure 3 shows the effect on the recovery time of the nonlinearity of applying reverse bias to the waveguide for 230 pJ coupled power. The recovery time was reduced from one much longer than the length of the pulse, estimated to be about 1 ns, at zero bias to 18 ± 3 ps for a bias voltage greater than -4 V. This compares with a value of 24 ps obtained in a bulk waveguide.

Energy scattering in weakly non-linear systems.

The Chinese Tam-Tam exhibits non-linear behavior in its vibro-acoustic response. The frequency content of the response during free, unforced vibration smoothly changes, with energy being progressively smeared out over a greater bandwidth with time. This is used as a motivating case for the general study of the phenomenon of energy cascading through weak nonlinearity. Numerical models based upon the Fermi-Pasta-Ulam system of non-linearly coupled oscillators, modified with the addition of damping, have been developed. These were used to study the response of ensembles of systems with randomized natural frequencies. Results from simulations will be presented here. For un-damped systems, individual ensemble members exhibit cyclical energy exchange between linear modes, but the ensemble average displays a steady state. For the ensemble response of damped systems, lightly damped modes can exhibit an effective damping which is higher than predicated by linear theory. The presence of a non-linearity provides a path for energy flow to other modes, increasing the apparent damping spectrum at some frequencies and reducing it at others. The target of this work is a model revealing the governing parameters of a generic system of this type and leading to predictions of the ensemble response.

Application of the fixed point method for solution in time stepping finite element analysis using the inverse vector Jiles-Atherton model

An implementation of the inverse vector Jiles-Atherton model for the solution of non-linear hysteretic finite element problems is presented. The implementation applies the fixed point method with differential reluctivity values obtained from the Jiles-Atherton model. Differential reluctivities are usually computed using numerical differentiation, which is ill-posed and amplifies small perturbations causing large sudden increases or decreases of differential reluctivity values, which may cause numerical problems. A rule based algorithm for conditioning differential reluctivity values is presented. Unwanted perturbations on the computed differential reluctivity values are eliminated or reduced with the aim to guarantee convergence. Details of the algorithm are presented together with an evaluation of the algorithm by a numerical example. The algorithm is shown to guarantee convergence, although the rate of convergence depends on the choice of algorithm parameters. © 2011 IEEE.

Optimisation of fuel usage and steam availability in the power and steam plant of a paper mill

This paper presents the results of a project aimed at minimising fuel usage while maximising steam availability in the power and steam plant of a large newsprint mill. The approach taken was to utilise the better regulation and plant wide optimisation capabilities of Advanced Process Control, especially Model Predictive Control (MPC) techniques. These have recently made their appearance in the pulp and paper industry but are better known in the oil and petrochemical industry where they have been used for nearly 30 years. The issue in the power and steam plant is to ensure that sufficient steam is available when the paper machines require it and yet not to have to waste too much steam when one or more of the machines suffers an outage. This is a problem for which MPC is well suited. It allows variables to be kept within declared constraint ranges, a feature which has been used, effectively, to increase the steam storage capacity of the existing plant. This has resulted in less steam being condensed when it is not required and in significant reductions in the need for supplementary firing. The incidence of steam being dump-condensed while also supplementary firing the Combined Heat & Power (CHP) plant has been reduced by 95% and the overall use of supplementary firing is less than 30% of what it was. In addition the plant runs more smoothly and requires less operator time. The yearly benefit provided by the control system is greater than £200,000, measured in terms of 2005 gas prices.