Feedback noncausal model predictive control of wave energy converters

In this paper, a novel feedback noncausal model predictive control (MPC) strategy for sea wave energy converters (WECs) is proposed, where the wave prediction information can be explicitly incorporated into the MPC strategy to improve the WEC control performance. The main novelties of the MPC strategy proposed in this paper include: (i) the recursive feasibility and robust constraints satisfaction are guaranteed without a significant increase in the computational burden; (ii) the information of short-term wave prediction is incorporated into the feedback noncausal MPC method to maximise the potential energy output; (iii) the sea condition for the WEC to safely operate in can be explicitly calculated. The proposed feedback noncausal MPC algorithm can also be extended to a wide class of control design problems, especially to the energy maximisation problems with constraints to be satisfied and subject to persistent but predictable disturbances. Numerical simulations are provided to show the efficacy of the proposed feedback noncausal MPC

Thalidomide-induced Teratogenesis : History and Mechanisms

Peer reviewedPublisher PD

Ferroelectricity induced by interatomic magnetic exchange interaction

Multiferroics, where two or more ferroic order parameters coexist, is one of the hottest fields in condensed matter physics and materials science[1-9]. However, the coexistence of magnetism and conventional ferroelectricity is physically unfavoured[10]. Recently several remedies have been proposed, e.g., improper ferroelectricity induced by specific magnetic[6] or charge orders[2]. Guiding by these theories, currently most research is focused on frustrated magnets, which usually have complicated magnetic structure and low magnetic ordering temperature, consequently far from the practical application. Simple collinear magnets, which can have high magnetic transition temperature, have never been considered seriously as the candidates for multiferroics. Here, we argue that actually simple interatomic magnetic exchange interaction already contains a driving force for ferroelectricity, thus providing a new microscopic mechanism for the coexistence and strong coupling between ferroelectricity and magnetism. We demonstrate this mechanism by showing that even the simplest antiferromagnetic (AFM) insulator MnO, can display a magnetically induced ferroelectricity under a biaxial strain

Microscopic Current Dynamics in Nanoscale Junctions

So far transport properties of nanoscale contacts have been mostly studied within the static scattering approach. The electron dynamics and the transient behavior of current flow, however, remain poorly understood. We present a numerical study of microscopic current flow dynamics in nanoscale quantum point contacts. We employ an approach that combines a microcanonical picture of transport with time-dependent density-functional theory. We carry out atomic and jellium model calculations to show that the time evolution of the current flow exhibits several noteworthy features, such as nonlaminarity and edge flow. We attribute these features to the interaction of the electron fluid with the ionic lattice, to the existence of pressure gradients in the fluid, and to the transient dynamical formation of surface charges at the nanocontact-electrode interfaces. Our results suggest that quantum transport systems exhibit hydrodynamical characteristics which resemble those of a classical liquid.Comment: 8 pages, 5 figures; Accepted for publication in Phys. Rev.

Testing for Network and Spatial Autocorrelation

Testing for dependence has been a well-established component of spatial statistical analyses for decades. In particular, several popular test statistics have desirable properties for testing for the presence of spatial autocorrelation in continuous variables. In this paper we propose two contributions to the literature on tests for autocorrelation. First, we propose a new test for autocorrelation in categorical variables. While some methods currently exist for assessing spatial autocorrelation in categorical variables, the most popular method is unwieldy, somewhat ad hoc, and fails to provide grounds for a single omnibus test. Second, we discuss the importance of testing for autocorrelation in data sampled from the nodes of a network, motivated by social network applications. We demonstrate that our proposed statistic for categorical variables can both be used in the spatial and network setting

Accelerating Bayesian hierarchical clustering of time series data with a randomised algorithm

We live in an era of abundant data. This has necessitated the development of new and innovative statistical algorithms to get the most from experimental data. For example, faster algorithms make practical the analysis of larger genomic data sets, allowing us to extend the utility of cutting-edge statistical methods. We present a randomised algorithm that accelerates the clustering of time series data using the Bayesian Hierarchical Clustering (BHC) statistical method. BHC is a general method for clustering any discretely sampled time series data. In this paper we focus on a particular application to microarray gene expression data. We define and analyse the randomised algorithm, before presenting results on both synthetic and real biological data sets. We show that the randomised algorithm leads to substantial gains in speed with minimal loss in clustering quality. The randomised time series BHC algorithm is available as part of the R package BHC, which is available for download from Bioconductor (version 2.10 and above) via http://bioconductor.org/packages/2.10/bioc/html/BHC.html. We have also made available a set of R scripts which can be used to reproduce the analyses carried out in this paper. These are available from the following URL. https://sites.google.com/site/randomisedbhc/

Non-universal gauge boson Z′Z' and the spin correlation of top quark pair production at e−e+e^{-}e^{+} colliders

In the off-diagonal basis, we discuss the contributions of the non-universal gauge boson $Z'$ predicted by the topcolor-assisted technicolor ($TC2$) model to the spin configurations and the spin correlation observable of the top quark pair production via the process $e^{-}e^{+}\to t\bar{t}$. Our numerical results show that the production cross sections for the like-spin states, which vanish in the standard model, can be significantly large as $M_{Z'}\approx \sqrt{S}$. With reasonable values of the $Z'$ mass $M_{Z'}$ and the coupling parameter $k_{1}$, $Z'$ exchange can generate large corrections to the spin correlation observable.Comment: 16 pages, 5 figure

Pathotypic diversity of Hyaloperonospora brassicae collected from Brassica oleracea

Downy mildew caused by Hyaloperonospora brassicae is an economically destructive disease of brassica crops in many growing regions throughout the world. Specialised pathogenicity of downy mildews from different Brassica species and closely related ornamental or wild relatives has been described from host range studies. Pathotypic variation amongst Hyaloperonospora brassicae isolates from Brassica oleracea has also been described; however, a standard set of B. oleracea lines that could enable reproducible classification of H. brassicae pathotypes was poorly developed. For this purpose, we examined the use of eight genetically refined host lines derived from our previous collaborative work on downy mildew resistance as a differential set to characterise pathotypes in the European population of H. brassicae. Interaction phenotypes for each combination of isolate and host line were assessed following drop inoculation of cotyledons and a spectrum of seven phenotypes was observed based on the level of sporulation on cotyledons and visible host responses. Two host lines were resistant or moderately resistant to the entire collection of isolates, and another was universally susceptible. Five lines showed differential responses to the H. brassicae isolates. A minimum of six pathotypes and five major effect resistance genes are proposed to explain all of the observed interaction phenotypes. The B. oleracea lines from this study can be useful for monitoring pathotype frequencies in H. brassicae populations in the same or other vegetable growing regions, and to assess the potential durability of disease control from different combinations of the predicted downy mildew resistance genes