Identification and minimization of IIR tap coefficients for the cancellation of complex multipath in terrestrial television

By using a deterministic approach, an exact form for the synchronous detected video signal under a ghosted condition is presented. Information regarding the phase quadrature-induced ghost component derived from the quadrature forming nature of the vestigial sideband (VSB) filter is obtained by crosscorrelating the detected video with the ghost cancel reference (GCR) signal. As a result, the minimum number of taps required to correctly remove all the ghost components is subsequently presented. The results are applied to both National Television System Committee (NTSC) and phase alternate line (PAL) television.

Spectro-electrochemical and DFT studies of a planar Cu(II)–phenolate complex active in the aerobic oxidation of primary alcohols

A square-planar compound [Cu(pyrimol)Cl] (pyrimol = 4-methyl-2-N-(2-pyridylmethylene)aminophenolate) abbreviated as CuL–Cl) is described as a biomimetic model of the enzyme galactose oxidase (GOase). This copper(II) compound is capable of stoichiometric aerobic oxidation of activated primary alcohols in acetonitrile/water to the corresponding aldehydes. It can be obtained either from Hpyrimol (HL) or its reduced/hydrogenated form Hpyramol (4-methyl-2-N-(2-pyridylmethyl)aminophenol; H2L) readily converting to pyrimol (L-) on coordination to the copper(II) ion. Crystalline CuL–Cl and its bromide derivative exhibit a perfect square-planar geometry with Cu–O(phenolate) bond lengths of 1.944(2) and 1.938(2) Å. The cyclic voltammogram of CuL–Cl exhibits an irreversible anodic wave at +0.50 and +0.57 V versus ferrocene/ferrocenium (Fc/Fc+) in dry dichloromethane and acetonitrile, respectively, corresponding to oxidation of the phenolate ligand to the corresponding phenoxyl radical. In the strongly donating acetonitrile the oxidation path involves reversible solvent coordination at the Cu(II) centre. The presence of the dominant CuII–L. chromophore in the electrochemically and chemically oxidised species is evident from a new fairly intense electronic absorption at 400–480 nm ascribed to a several electronic transitions having a mixed pi-pi(L.) intraligand and Cu–Cl -> L. charge transfer character. The EPR signal of CuL–Cl disappears on oxidation due to strong intramolecular antiferromagnetic exchange coupling between the phenoxyl radical ligand (L.) and the copper(II) centre, giving rise to a singlet ground state (S = 0). The key step in the mechanism of the primary alcohol oxidation by CuL–Cl is probably the alpha-hydrogen abstraction from the equatorially bound alcoholate by the phenoxyl moiety in the oxidised pyrimol ligand, Cu–L., through a five-membered cyclic transition state.

Entrepreneurial opportunities, implicit contracts and market making for complex consumer goods

This article extends the theory of entrepreneurial opportunity exploitation, outlining how under certain conditions, opportunity exploitation is dependent on market making innovations. Where adverse selection and moral hazard characterize markets, consumers are likely to withdraw regardless of product quality. In order to overcome consumer resistance, entrepreneurs must signal credible commitments. But because consumers purchase without fully specifying requirements, entrepreneurs' commitments take the partial form of implicit contracts, creating strong mutual commitments to repeated transactions. These commitments enable novel markets to function, but introduce additional costs. This article illustrates the theory with the historic case of Singer in sewing machines

Epoxide ring opening in a zinc(II) complex in water without any Lewis acid catalyst: formation of only one diastereomer out of 2

The epoxide ring in 5,6-dihydro-5,6-epoxy-1,10-phenanthroline (L) opens up in its reaction with 4-methylaniline and 4-methoxyaniline in water in equimolar proportion at room temperature without any Lewis acid catalyst to give a monohydrate of 6-(4-methyl-phenylamino)-5,6-dihydro-1,10-phenanthrolin-5-ol (L′·H2O) and 6-(4-methoxyphenyl-amino)-5,6-dihydro-1,10-phenanthrolin-5-ol (L″) respectively. Reaction time decreases from 72 to 14 h in boiling water. But the yields become less. Reaction of L with Zn(ClO4)2·6H2O in methanol in 3:1 molar ratio at room temperature affords white [ZnL3](ClO4)2·H2O. The X-ray crystal structure of the acetonitrile solvate [ZnL3](ClO4)2·MeCN has been determined which shows that the metal has a distorted octahedral N6 coordination sphere. [ZnL3](ClO4)2·2H2O reacts with 4-methylaniline and 4-methoxyaniline in boiling water in 1:3 molar proportion in the absence of any Lewis acid catalyst to produce [ZnL′3](ClO4)2·4H2O and [ZnL″3](ClO4)2·H2O, respectively in 1–4 h time in somewhat low yield. In the 1H NMR spectra of [ZnL′3](ClO4)2·4H2O and [ZnL″3](ClO4)2·H2O, only one sharp methyl signal is observed implicating that only one diastereomer out of the 23 possibilities is formed. The same diastereomers are obtained when L′·H2O and L″ are reacted directly with Zn(ClO4)2·6H2O in tetrahydrofuran at room temperature in very good yields. Reactions of L′·H2O and L″ with Ru(phen)2Cl2·2H2O (phen = 1,10-phenanthroline) in equimolar proportion in methanol–water mixture under refluxing condition lead to the isolation of two diastereomers of [Ru(phen)2L′](ClO4)2·2H2O and [Ru(phen)2L″](ClO4)2·2H2O.

Complex-valued b-spline neural networks for modelling and inverse of wiener systems

Communication signal processing applications often involve complex-valued (CV) functional representations for signals and systems. CV artificial neural networks have been studied theoretically and applied widely in nonlinear signal and data processing [1–11]. Note that most artificial neural networks cannot be automatically extended from the real-valued (RV) domain to the CV domain because the resulting model would in general violate Cauchy-Riemann conditions, and this means that the training algorithms become unusable. A number of analytic functions were introduced for the fully CV multilayer perceptrons (MLP) [4]. A fully CV radial basis function (RBF) nework was introduced in [8] for regression and classification applications. Alternatively, the problem can be avoided by using two RV artificial neural networks, one processing the real part and the other processing the imaginary part of the CV signal/system. A even more challenging problem is the inverse of a CV

Complex-valued B-spline neural networks for modeling and inverting Hammerstein systems

Many communication signal processing applications involve modelling and inverting complex-valued (CV) Hammerstein systems. We develops a new CV B-spline neural network approach for efficient identification of the CV Hammerstein system and effective inversion of the estimated CV Hammerstein model. Specifically, the CV nonlinear static function in the Hammerstein system is represented using the tensor product from two univariate B-spline neural networks. An efficient alternating least squares estimation method is adopted for identifying the CV linear dynamic model’s coefficients and the CV B-spline neural network’s weights, which yields the closed-form solutions for both the linear dynamic model’s coefficients and the B-spline neural network’s weights, and this estimation process is guaranteed to converge very fast to a unique minimum solution. Furthermore, an accurate inversion of the CV Hammerstein system can readily be obtained using the estimated model. In particular, the inversion of the CV nonlinear static function in the Hammerstein system can be calculated effectively using a Gaussian-Newton algorithm, which naturally incorporates the efficient De Boor algorithm with both the B-spline curve and first order derivative recursions. The effectiveness of our approach is demonstrated using the application to equalisation of Hammerstein channels.

Single-carrier frequency domain equalisation for hammerstein communication systems using complex-valued neural networks

Single-carrier (SC) block transmission with frequency-domain equalisation (FDE) offers a viable transmission technology for combating the adverse effects of long dispersive channels encountered in high-rate broadband wireless communication systems. However, for high bandwidthefficiency and high power-efficiency systems, the channel can generally be modelled by the Hammerstein system that includes the nonlinear distortion effects of the high power amplifier (HPA) at transmitter. For such nonlinear Hammerstein channels, the standard SC-FDE scheme no longer works. This paper advocates a complex-valued (CV) B-spline neural network based nonlinear SC-FDE scheme for Hammerstein channels. Specifically, We model the nonlinear HPA, which represents the CV static nonlinearity of the Hammerstein channel, by a CV B-spline neural network, and we develop two efficient alternating least squares schemes for estimating the parameters of the Hammerstein channel, including both the channel impulse response coefficients and the parameters of the CV B-spline model. We also use another CV B-spline neural network to model the inversion of the nonlinear HPA, and the parameters of this inverting B-spline model can easily be estimated using the standard least squares algorithm based on the pseudo training data obtained as a natural byproduct of the Hammerstein channel identification. Equalisation of the SC Hammerstein channel can then be accomplished by the usual one-tap linear equalisation in frequency domain as well as the inverse B-spline neural network model obtained in time domain. Extensive simulation results are included to demonstrate the effectiveness of our nonlinear SC-FDE scheme for Hammerstein channels.

Application of complex extreme learning machine to multiclass classification problems with high dimensionality: a THz spectra classification problem

We extend extreme learning machine (ELM) classifiers to complex Reproducing Kernel Hilbert Spaces (RKHS) where the input/output variables as well as the optimization variables are complex-valued. A new family of classifiers, called complex-valued ELM (CELM) suitable for complex-valued multiple-input–multiple-output processing is introduced. In the proposed method, the associated Lagrangian is computed using induced RKHS kernels, adopting a Wirtinger calculus approach formulated as a constrained optimization problem similarly to the conventional ELM classifier formulation. When training the CELM, the Karush–Khun–Tuker (KKT) theorem is used to solve the dual optimization problem that consists of satisfying simultaneously smallest training error as well as smallest norm of output weights criteria. The proposed formulation also addresses aspects of quaternary classification within a Clifford algebra context. For 2D complex-valued inputs, user-defined complex-coupled hyper-planes divide the classifier input space into four partitions. For 3D complex-valued inputs, the formulation generates three pairs of complex-coupled hyper-planes through orthogonal projections. The six hyper-planes then divide the 3D space into eight partitions. It is shown that the CELM problem formulation is equivalent to solving six real-valued ELM tasks, which are induced by projecting the chosen complex kernel across the different user-defined coordinate planes. A classification example of powdered samples on the basis of their terahertz spectral signatures is used to demonstrate the advantages of the CELM classifiers compared to their SVM counterparts. The proposed classifiers retain the advantages of their ELM counterparts, in that they can perform multiclass classification with lower computational complexity than SVM classifiers. Furthermore, because of their ability to perform classification tasks fast, the proposed formulations are of interest to real-time applications.

Decomposition of surface electromyographic signal using Hidden Markov Model

The detection of physiological signals from the motor system (electromyographic signals) is being utilized in the practice clinic to guide the therapist in a more precise and accurate diagnosis of motor disorders. In this context, the process of decomposition of EMG (electromyographic) signals that includes the identification and classification of MUAP (Motor Unit Action Potential) of a EMG signal, is very important to help the therapist in the evaluation of motor disorders. The EMG decomposition is a complex task due to EMG features depend on the electrode type (needle or surface), its placement related to the muscle, the contraction level and the health of the Neuromuscular System. To date, the majority of researches on EMG decomposition utilize EMG signals acquired by needle electrodes, due to their advantages in processing this type of signal. However, relatively few researches have been conducted using surface EMG signals. Thus, this article aims to contribute to the clinical practice by presenting a technique that permit the decomposition of surface EMG signal via the use of Hidden Markov Models. This process is supported by the use of differential evolution and spectral clustering techniques. The developed system presented coherent results in: (1) identification of the number of Motor Units actives in the EMG signal; (2) presentation of the morphological patterns of MUAPs in the EMG signal; (3) identification of the firing sequence of the Motor Units. The model proposed in this work is an advance in the research area of decomposition of surface EMG signals.

Regulation of early steps of GPVI signal transduction by phosphatases: a systems biology approach

We present a data-driven mathematical model of a key initiating step in platelet activation, a central process in the prevention of bleeding following Injury. In vascular disease, this process is activated inappropriately and causes thrombosis, heart attacks and stroke. The collagen receptor GPVI is the primary trigger for platelet activation at sites of injury. Understanding the complex molecular mechanisms initiated by this receptor is important for development of more effective antithrombotic medicines. In this work we developed a series of nonlinear ordinary differential equation models that are direct representations of biological hypotheses surrounding the initial steps in GPVI-stimulated signal transduction. At each stage model simulations were compared to our own quantitative, high-temporal experimental data that guides further experimental design, data collection and model refinement. Much is known about the linear forward reactions within platelet signalling pathways but knowledge of the roles of putative reverse reactions are poorly understood. An initial model, that includes a simple constitutively active phosphatase, was unable to explain experimental data. Model revisions, incorporating a complex pathway of interactions (and specifically the phosphatase TULA-2), provided a good description of the experimental data both based on observations of phosphorylation in samples from one donor and in those of a wider population. Our model was used to investigate the levels of proteins involved in regulating the pathway and the effect of low GPVI levels that have been associated with disease. Results indicate a clear separation in healthy and GPVI deficient states in respect of the signalling cascade dynamics associated with Syk tyrosine phosphorylation and activation. Our approach reveals the central importance of this negative feedback pathway that results in the temporal regulation of a specific class of protein tyrosine phosphatases in controlling the rate, and therefore extent, of GPVI-stimulated platelet activation.

Light modulates the melanophore response to alpha-MSH in Xenopus laevis: An analysis of the signal transduction crosstalk mechanisms involved

Melanin granule (melanosome) dispersion within Xenopus laevis melanophores is evoked either by light or alpha-MSH. We have previously demonstrated that the initial biochemical steps of light and alpha-MSH signaling are distinct, since the increase in cAMP observed in response to alpha-MSH was not seen after light exposure. cAMP concentrations in response to alpha-MSH were significantly lower in cells pre-exposed to light as compared to the levels in dark-adapted melanophores. Here we demonstrate the presence of an adenylyl cyclase (AC) in the Xenopus melanophore, similar to the mammalian type IX which is inhibited by Ca(2+)-calmodulin-activated phosphatase. This finding supports the hypothesis that the cyclase could be negatively modulated by a light-promoted Ca(2+) increase. In fact, the activity of calcineurin PP2B phosphatase was increased by light, which could result in AC IX inhibition, thus decreasing the response to alpha-MSH. St-Ht31, a disrupting agent of protein kinase A (PKA)-anchoring kinase A protein (AKAP) complex totally blocked the melanosome dispersing response to alpha-MSH, but did not impair the photo-response in Xenopus melanophores. Sequence comparison of a melanophore AKAP partial clone with GenBank sequences showed that the anchoring protein was a gravin-like adaptor previously sequenced from Xenopus non-pigmentary tissues. Co-immunoprecipitation of Xenopus AKAP and the catalytic subunit of PKA demonstrated that PKA is associated with AKAP and it is released in the presence of alpha-MSH. We conclude that in X laevis melanophores, AKAP12 (gravin-like) contains a site for binding the inactive PKA thus compartmentalizing PKA signaling and also possesses binding sites for PKC. Light diminishes alpha-MSH-induced increase of cAMP by increasing calcineurin (PP2B) activity, which in turn inhibits adenylyl cyclase type IX, and/or by activating PKC, which phosphorylates the gravin-like molecule, thus destabilizing its binding to the cell membrane. (C) 2009 Elsevier Inc. All rights reserved.

Studies of aberrant phyllotaxy1 Mutants of Maize Indicate Complex Interactions between Auxin and Cytokinin Signaling in the Shoot Apical Meristem

One of the most fascinating aspects of plant morphology is the regular geometric arrangement of leaves and flowers, called phyllotaxy. The shoot apical meristem (SAM) determines these patterns, which vary depending on species and developmental stage. Auxin acts as an instructive signal in leaf initiation, and its transport has been implicated in phyllotaxy regulation in Arabidopsis (Arabidopsis thaliana). Altered phyllotactic patterns are observed in a maize (Zea mays) mutant, aberrant phyllotaxy1 (abph1, also known as abphyl1), and ABPH1 encodes a cytokinin-inducible type A response regulator, suggesting that cytokinin signals are also involved in the mechanism by which phyllotactic patterns are established. Therefore, we investigated the interaction between auxin and cytokinin signaling in phyllotaxy. Treatment of maize shoots with a polar auxin transport inhibitor, 1-naphthylphthalamic acid, strongly reduced ABPH1 expression, suggesting that auxin or its polar transport is required for ABPH1 expression. Immunolocalization of the PINFORMED1 (PIN1) polar auxin transporter revealed that PIN1 expression marks leaf primordia in maize, similarly to Arabidopsis. Interestingly, maize PIN1 expression at the incipient leaf primordium was greatly reduced in abph1 mutants. Consistently, auxin levels were reduced in abph1, and the maize PIN1 homolog was induced not only by auxin but also by cytokinin treatments. Our results indicate distinct roles for ABPH1 as a negative regulator of SAM size and a positive regulator of PIN1 expression. These studies highlight a complex interaction between auxin and cytokinin signaling in the specification of phyllotactic patterns and suggest an alternative model for the generation of altered phyllotactic patterns in abph1 mutants. We propose that reduced auxin levels and PIN1 expression in abph1 mutant SAMs delay leaf initiation, contributing to the enlarged SAM and altered phyllotaxy of these mutants.

Cell-cell signal-dependent dynamic interactions between HD-GYP and GGDEF domain proteins mediate virulence in Xanthomonas campestris

RpfG is a paradigm for a class of widespread bacterial two-component regulators with a CheY-like receiver domain attached to a histidine-aspartic acid-glycine-tyrosine-proline (HD-GYP) cyclic di-GMP phosphodiesterase domain. In the plant pathogen Xanthomonas campestris pv. campestris (Xcc), a two-component system comprising RpfG and the complex sensor kinase RpfC is implicated in sensing and responding to the diffusible signaling factor (DSF), which is essential for cell-cell signaling. RpfF is involved in synthesizing DSF, and mutations of rpfF, rpfG, or rpfC lead to a coordinate reduction in the synthesis of virulence factors such as extracellular enzymes, biofilm structure, and motility. Using yeast two-hybrid analysis and fluorescence resonance energy transfer experiments in Xcc, we show that the physical interaction of RpfG with two proteins with diguanylate cyclase (GGDEF) domains controls a subset of RpfG-regulated virulence functions. RpfG interactions were abolished by alanine substitutions of the three residues of the conserved GYP motif in the HD-GYP domain. Changing the GYP motif or deletion of the two GGDEF-domain proteins reduced Xcc motility but not the synthesis of extracellular enzymes or biofilm formation. RpfG-GGDEF interactions are dynamic and depend on DSF signaling, being reduced in the rpfF mutant but restored by DSF addition. The results are consistent with a model in which DSF signal transduction controlling motility depends on a highly regulated, dynamic interaction of proteins that influence the localized expression of cyclic di-GMP.

Crystal structure of Bn IV in complex with myristic acid: A Lys49 myotoxic phospholipase A(2) from Bothrops neuwiedi venom

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Signal-flow graphs: Direct method of reduction and MATLAB implementation

Block diagrams and signal-flow graphs are used to represent and to obtain the transfer function of interconnected systems. The reduction of signal-flow graphs is considered simpler than the reduction of block diagrams for systems with complex interrelationships. Signal-flow graphs reduction can be made without graphic manipulations of diagrams, and it is attractive for a computational implementation. In this paper the authors propose a computational method for direct reduction of signal-flow graphs. This method uses results presented in this paper about the calculation of literal determinants without symbolic mathematics tools. The Cramer's rule is applied for the solution of a set of linear equations, A program in MATLAB language for reduction of signal-flow graphs with the proposed method is presented.