Identification of MIMO Hammerstein systems using cardinal spline functions

A new approach to identify multivariable Hammerstein systems is proposed in this paper. By using cardinal cubic spline functions to model the static nonlinearities, the proposed method is effective in modelling processes with hard and/or coupled nonlinearities. With an appropriate transformation, the nonlinear models are parameterized such that the nonlinear identification problem is converted into a linear one. The persistently exciting condition for the transformed input is derived to ensure the estimates are consistent with the true system. A simulation study is performed to demonstrate the effectiveness of the proposed method compared with the existing approaches based on polynomials. (C) 2006 Elsevier Ltd. All rights reserved.

Substrate-bound carbohydrates stimulate signal transduction and neurite outgrowth in an olfactory neuron cell line

SUBPOPULATIONS of olfactory receptor neurons, which are dispersed throughout the olfactory neuroepithelium, express specific cell surface carbohydrates and project to discrete regions of the olfactory bulb. Cell surface carbohydrates such as N-acetyl-lactosamine have been postulated to mediate sorting and selective fasciculation of discrete axon subpopulations during development of the olfactory pathway. Substrate-bound N-acetyl-lactosamine promotes neurite outgrowth by both clonal olfactory receptor neuron cell lines and olfactory receptor neurons in vitro, indicating that cell surface carbohydrates may be ligands for receptor-mediated stimulation of axon growth in vivo. In the present study, the role of transmembrane signaling in N-acetyl-lactosamine-stimulated neurite outgrowth was examined in the clonal olfactory neuron cell line 4.4.2. Substrate-bound N-acetyl-lactosamine stimulated neurite outgrowth which was specifically inhibited by antagonists to N- and L-type calcium channels and to tyrosine kinase phosphorylation. These results indicate that N-acetyl-lactosamine can evoke transmembrane receptor-mediated responses capable of influencing neurite outgrowth.

An extensive repertoire of type III secretion effectors in Escherichia coli O157 and the role of lambdoid phages in their dissemination

Several pathogenic strains of Escherichia coli exploit type III secretion to inject effector proteins into human cells, which then subvert eukaryotic cell biology to the bacterium's advantage. We have exploited bioinformatics and experimental approaches to establish that the effector repertoire in the Sakai strain of enterohemorrhagic E. coli (EHEC) O157:H7 is much larger than previously thought. Homology searches led to the identification of > 60 putative effector genes. Thirteen of these were judged to be likely pseudogenes, whereas 49 were judged to be potentially functional. In total, 39 proteins were confirmed experimentally as effectors: 31 through proteomics and 28 through translocation assays. At the protein level, the EHEC effector sequences fall into > 20 families. The largest family, the NleG family, contains 14 members in the Sakai strain alone. EHEC also harbors functional homologs of effectors from plant pathogens (HopPtoH, HopW, AvrA) and from Shigella (OspD, OspE, OspG), and two additional members of the Map/IpgB family. Genes encoding proven or predicted effectors occur in > 20 exchangeable effector loci scattered throughout the chromosome. Crucially, the majority of functional effector genes are encoded by nine exchangeable effector loci that lie within lambdoid prophages. Thus, type III secretion in E. coli is linked to a vast phage metagenome, acting as a crucible for the evolution of pathogenicity.

Identification of "pathologs" (disease-related genes) from the RIKEN mouse cDNA dataset using human curation plus FACTS, a new biological information extraction system

Background: A major goal in the post-genomic era is to identify and characterise disease susceptibility genes and to apply this knowledge to disease prevention and treatment. Rodents and humans have remarkably similar genomes and share closely related biochemical, physiological and pathological pathways. In this work we utilised the latest information on the mouse transcriptome as revealed by the RIKEN FANTOM2 project to identify novel human disease-related candidate genes. We define a new term patholog to mean a homolog of a human disease-related gene encoding a product ( transcript, anti-sense or protein) potentially relevant to disease. Rather than just focus on Mendelian inheritance, we applied the analysis to all potential pathologs regardless of their inheritance pattern. Results: Bioinformatic analysis and human curation of 60,770 RIKEN full-length mouse cDNA clones produced 2,578 sequences that showed similarity ( 70 - 85% identity) to known human-disease genes. Using a newly developed biological information extraction and annotation tool ( FACTS) in parallel with human expert analysis of 17,051 MEDLINE scientific abstracts we identified 182 novel potential pathologs. Of these, 36 were identified by computational tools only, 49 by human expert analysis only and 97 by both methods. These pathologs were related to neoplastic ( 53%), hereditary ( 24%), immunological ( 5%), cardio-vascular (4%), or other (14%), disorders. Conclusions: Large scale genome projects continue to produce a vast amount of data with potential application to the study of human disease. For this potential to be realised we need intelligent strategies for data categorisation and the ability to link sequence data with relevant literature. This paper demonstrates the power of combining human expert annotation with FACTS, a newly developed bioinformatics tool, to identify novel pathologs from within large-scale mouse transcript datasets.

Time-reversal test for stochastic quantum dynamics

The calculation of quantum dynamics is currently a central issue in theoretical physics, with diverse applications ranging from ultracold atomic Bose-Einstein condensates to condensed matter, biology, and even astrophysics. Here we demonstrate a conceptually simple method of determining the regime of validity of stochastic simulations of unitary quantum dynamics by employing a time-reversal test. We apply this test to a simulation of the evolution of a quantum anharmonic oscillator with up to 6.022×1023 (Avogadro's number) of particles. This system is realizable as a Bose-Einstein condensate in an optical lattice, for which the time-reversal procedure could be implemented experimentally.

Identification of residues involved in binding of IL5 to beta(com) using beta(IL3) and beta(com) chimeras

In mice there are two forms of the beta chain used in the IL3 receptor system, beta(com) and beta(IL3). beta(com) is used by the IL3, ILS and GM-CSF receptors whereas Pns is only used in the IL3 receptor. In this work an assay was developed to identify residues of beta(IL3) that restrict IL5 activity. It was found that such residues reside within the 2nd CRM of the molecule. Furthermore, when residues in the beta(IL3) B'-C' loop were replaced with beta(com) sequence a form of beta(IL3) was produced that was able to respond to IL5. This region is also responsible for IL3 binding to beta(IL3) in the absence of alpha chain. It is therefore an important structural motif of beta(com) and beta(IL3) responsible for both ligand interaction and specificity. (C) 1999 Federation of European Biochemical Societies.

Optimal release strategies for biological control agents: an application of stochastic dynamic programming to population management

1. Establishing biological control agents in the field is a major step in any classical biocontrol programme, yet there are few general guidelines to help the practitioner decide what factors might enhance the establishment of such agents. 2. A stochastic dynamic programming (SDP) approach, linked to a metapopulation model, was used to find optimal release strategies (number and size of releases), given constraints on time and the number of biocontrol agents available. By modelling within a decision-making framework we derived rules of thumb that will enable biocontrol workers to choose between management options, depending on the current state of the system. 3. When there are few well-established sites, making a few large releases is the optimal strategy. For other states of the system, the optimal strategy ranges from a few large releases, through a mixed strategy (a variety of release sizes), to many small releases, as the probability of establishment of smaller inocula increases. 4. Given that the probability of establishment is rarely a known entity, we also strongly recommend a mixed strategy in the early stages of a release programme, to accelerate learning and improve the chances of finding the optimal approach.

Disagreement between correlations of quantum mechanics and stochastic electrodynamics in the damped parametric oscillator

Intracavity and external third order correlations in the damped nondegenerate parametric oscillator are calculated for quantum mechanics and stochastic electrodynamics (SED), a semiclassical theory. The two theories yield greatly different results, with the correlations of quantum mechanics being cubic in the system's nonlinear coupling constant and those of SED being linear in the same constant. In particular, differences between the two theories are present in at least a mesoscopic regime. They also exist when realistic damping is included. Such differences illustrate distinctions between quantum mechanics and a hidden variable theory for continuous variables.

Identification of the coupling between skeletal muscle store-operated Ca2+ entry and the inositol trisphosphate receptor

Examination of store-operated Ca2+ entry (SOC) in single, mechanically skinned skeletal muscle cells by confocal microscopy shows that the inositol 1,4,5-trisphosphate (IP3) receptor acts as a sarcoplasmic reticulum [Ca2+] sensor and mediates SOC by physical coupling without playing a key role in Ca2+ release from internal stores, as is the case with various cell types in which SOC was investigated previously. The results have broad implications for understanding the mechanism of SOC that is essential for cell function in general and muscle function in particular. Moreover, the study ascribes an important role to the IN receptors in skeletal muscle, the role of which with respect to Ca2+ homeostasis was ill defined until now.

Analysis of dynamic process models for structural insight and model reduction .1. Structural identification measures

An important consideration in the development of mathematical models for dynamic simulation, is the identification of the appropriate mathematical structure. By building models with an efficient structure which is devoid of redundancy, it is possible to create simple, accurate and functional models. This leads not only to efficient simulation, but to a deeper understanding of the important dynamic relationships within the process. In this paper, a method is proposed for systematic model development for startup and shutdown simulation which is based on the identification of the essential process structure. The key tool in this analysis is the method of nonlinear perturbations for structural identification and model reduction. Starting from a detailed mathematical process description both singular and regular structural perturbations are detected. These techniques are then used to give insight into the system structure and where appropriate to eliminate superfluous model equations or reduce them to other forms. This process retains the ability to interpret the reduced order model in terms of the physico-chemical phenomena. Using this model reduction technique it is possible to attribute observable dynamics to particular unit operations within the process. This relationship then highlights the unit operations which must be accurately modelled in order to develop a robust plant model. The technique generates detailed insight into the dynamic structure of the models providing a basis for system re-design and dynamic analysis. The technique is illustrated on the modelling for an evaporator startup. Copyright (C) 1996 Elsevier Science Ltd

Lanczos subspace filter diagonalization: Homogeneous recursive filtering and a low-storage method for the calculation of matrix elements

We develop a new iterative filter diagonalization (FD) scheme based on Lanczos subspaces and demonstrate its application to the calculation of bound-state and resonance eigenvalues. The new scheme combines the Lanczos three-term vector recursion for the generation of a tridiagonal representation of the Hamiltonian with a three-term scalar recursion to generate filtered states within the Lanczos representation. Eigenstates in the energy windows of interest can then be obtained by solving a small generalized eigenvalue problem in the subspace spanned by the filtered states. The scalar filtering recursion is based on the homogeneous eigenvalue equation of the tridiagonal representation of the Hamiltonian, and is simpler and more efficient than our previous quasi-minimum-residual filter diagonalization (QMRFD) scheme (H. G. Yu and S. C. Smith, Chem. Phys. Lett., 1998, 283, 69), which was based on solving for the action of the Green operator via an inhomogeneous equation. A low-storage method for the construction of Hamiltonian and overlap matrix elements in the filtered-basis representation is devised, in which contributions to the matrix elements are computed simultaneously as the recursion proceeds, allowing coefficients of the filtered states to be discarded once their contribution has been evaluated. Application to the HO2 system shows that the new scheme is highly efficient and can generate eigenvalues with the same numerical accuracy as the basic Lanczos algorithm.