On the Filtering Problem for Continuous-Time Markov Jump Linear Systems with no Observation of the Markov Chain

We consider in this paper the optimal stationary dynamic linear filtering problem for continuous-time linear systems subject to Markovian jumps in the parameters (LSMJP) and additive noise (Wiener process). It is assumed that only an output of the system is available and therefore the values of the jump parameter are not accessible. It is a well known fact that in this setting the optimal nonlinear filter is infinite dimensional, which makes the linear filtering a natural numerically, treatable choice. The goal is to design a dynamic linear filter such that the closed loop system is mean square stable and minimizes the stationary expected value of the mean square estimation error. It is shown that an explicit analytical solution to this optimal filtering problem is obtained from the stationary solution associated to a certain Riccati equation. It is also shown that the problem can be formulated using a linear matrix inequalities (LMI) approach, which can be extended to consider convex polytopic uncertainties on the parameters of the possible modes of operation of the system and on the transition rate matrix of the Markov process. As far as the authors are aware of this is the first time that this stationary filtering problem (exact and robust versions) for LSMJP with no knowledge of the Markov jump parameters is considered in the literature. Finally, we illustrate the results with an example.

Discrete-time mean variance optimal control of linear systems with Markovian jumps and multiplicative noise

In this article, we consider the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noise under three kinds of performance criterions related to the final value of the expectation and variance of the output. In the first problem it is desired to minimise the final variance of the output subject to a restriction on its final expectation, in the second one it is desired to maximise the final expectation of the output subject to a restriction on its final variance, and in the third one it is considered a performance criterion composed by a linear combination of the final variance and expectation of the output of the system. We present explicit sufficient conditions for the existence of an optimal control strategy for these problems, generalising previous results in the literature. We conclude this article presenting a numerical example of an asset liabilities management model for pension funds with regime switching.

Non-linear modal analysis for beams subjected to axial loads: Analytical and finite-element solutions

A rigorous derivation of non-linear equations governing the dynamics of an axially loaded beam is given with a clear focus to develop robust low-dimensional models. Two important loading scenarios were considered, where a structure is subjected to a uniformly distributed axial and a thrust force. These loads are to mimic the main forces acting on an offshore riser, for which an analytical methodology has been developed and applied. In particular, non-linear normal modes (NNMs) and non-linear multi-modes (NMMs) have been constructed by using the method of multiple scales. This is to effectively analyse the transversal vibration responses by monitoring the modal responses and mode interactions. The developed analytical models have been crosschecked against the results from FEM simulation. The FEM model having 26 elements and 77 degrees-of-freedom gave similar results as the low-dimensional (one degree-of-freedom) non-linear oscillator, which was developed by constructing a so-called invariant manifold. The comparisons of the dynamical responses were made in terms of time histories, phase portraits and mode shapes. (C) 2008 Elsevier Ltd. All rights reserved.

Linear minimum mean square filter for discrete-time linear systems with Markov jumps and multiplicative noises

In this paper we obtain the linear minimum mean square estimator (LMMSE) for discrete-time linear systems subject to state and measurement multiplicative noises and Markov jumps on the parameters. It is assumed that the Markov chain is not available. By using geometric arguments we obtain a Kalman type filter conveniently implementable in a recurrence form. The stationary case is also studied and a proof for the convergence of the error covariance matrix of the LMMSE to a stationary value under the assumption of mean square stability of the system and ergodicity of the associated Markov chain is obtained. It is shown that there exists a unique positive semi-definite solution for the stationary Riccati-like filter equation and, moreover, this solution is the limit of the error covariance matrix of the LMMSE. The advantage of this scheme is that it is very easy to implement and all calculations can be performed offline. (c) 2011 Elsevier Ltd. All rights reserved.

Double generalized linear model for tissue culture proportion data: a Bayesian perspective

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

ECONOMICAL OCCUPATION OF AGRICULTURAL AREA OF PIRACICABA (SAO PAULO STATE, BRAZIL), INCLUDING RISK THROUGH LINEAR PROGRAMMING

The economic occupation of an area of 500 ha for Piracicaba was studied with the irrigated cultures of maize, tomato, sugarcane and beans, having used models of deterministic linear programming and linear programming including risk for the Target-Motad model, where two situations had been analyzed. In the deterministic model the area was the restrictive factor and the water was not restrictive for none of the tested situations. For the first situation the gotten maximum income was of R$ 1,883,372.87 and for the second situation it was of R$ 1,821,772.40. In the model including risk a producer that accepts risk can in the first situation get the maximum income of R$ 1,883,372. 87 with a minimum risk of R$ 350 year(-1), and in the second situation R$ 1,821,772.40 with a minimum risk of R$ 40 year(-1). Already a producer averse to the risk can get in the first situation a maximum income of R$ 1,775,974.81 with null risk and for the second situation R$ 1.707.706, 26 with null risk, both without water restriction. These results stand out the importance of the inclusion of the risk in supplying alternative occupations to the producer, allowing to a producer taking of decision considered the risk aversion and the pretension of income.

Genetic transformation of Citrus sinensis cv. Hamlin with hrpN gene from Erwinia amylovora and evaluation of the transgenic lines for resistance to citrus canker

Transgenic Citrus sinensis (L.) Osb. cv. Hamlin plants expressing the hrpN gene were obtained by Agrobacterium tumefaciens (Smith and Towns) Conn-mediated transformation. hrpN encodes a harpin protein, which elicits the hypersensitive response and systemic acquired resistance in plants. The gene construct consisted of gst1, a pathogen-inducible promoter, a signal peptide for protein secretion to the apoplast, the selection genes nptI1 or aacC1 and the Nos terminator. The function of gst1 in citrus was evaluated in transgenic C. sinensis cv. Valencia harboring the reporter gene uidA (gus) driven by this promoter. Histochemical analysis for gus revealed that gst1 is activated in citrus leaves by both wounding and inoculation with Xanthomonas axonopodis Starr and Garces pv. citri (Hasse) Vauterin et al. Genetic transformation was confirmed by Southern blot hybridization in eight cv. Hamlin acclimatized plants. RT-PCR confirmed hrpN gene expression in seven cv. Hamlin transgenic lines before pathogen inoculation. Some hrpN transgenic lines showed severe leaf curling and abnormal growth. Six hrpN transgenic lines were propagated and evaluated for susceptibility to X axonopodis pv. citri. RT-PCR confirmed gene expression in all six hrpN transgenic lines after pathogen inoculation. Several of the hrpN transgenic lines showed reduction in susceptibility to citrus canker as compared with non-transgenic plants. One hrpN transgenic line exhibited normal vegetative development and displayed very high resistance to the pathogen, estimated as up to 79% reduction in disease severity. This is the first report of genetic transformation of citrus using a pathogen-inducible promoter and the hrpN gene. Further evaluations of the transgenic plants under field conditions are planned. Nevertheless, the evidence to date suggests that the hrpN gene reduces the susceptibility of citrus plants to the canker disease. (C) 2009 Elsevier B.V. All rights reserved.

A Log-Linear Regression Model for the Beta-Weibull Distribution

We introduce the log-beta Weibull regression model based on the beta Weibull distribution (Famoye et al., 2005; Lee et al., 2007). We derive expansions for the moment generating function which do not depend on complicated functions. The new regression model represents a parametric family of models that includes as sub-models several widely known regression models that can be applied to censored survival data. We employ a frequentist analysis, a jackknife estimator, and a parametric bootstrap for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes, and censoring percentages, several simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We define martingale and deviance residuals to evaluate the model assumptions. The extended regression model is very useful for the analysis of real data and could give more realistic fits than other special regression models.

Genetic Transformation of Passionflower and Evaluation of R(1) and R(2) Generations for Resistance to Cowpea aphid borne mosaic virus

We report on the production and evaluation of passionflower transgenic lines for resistance to Cowpea aphid borne mosaic virus (CABMV). Genetic transformation was done using Agrobacterium tumefaciens and transgene integration was confirmed by Southern blot analyses, resulting in nine transgenic lines for `IAC 275` and three for `IAC 277`. Transgenic lines were clonally propagated and evaluated for resistance to CABMV After the third inoculation, under higher inoculum pressure, only propagated plants of the transgenic line T16 remained asymptomatic, indicating a high resistance to infection with CABMV. This transgenic line was self-pollinated and the RI generation was evaluated together with the RI generation of another resistant transgenic line (T2) identified previously. Plants were inoculated with CABMV by means of viruliferous Myzus nicotianae. All 524 T2R(1) plants became infected, whereas 13 of 279 T16R(1) remained asymptomatic after four successive inoculations. A TI6R(2) generation was obtained and plants were inoculated with CABMV mechanically or by aphids. After successive inoculations, 118 of 258 plants were symptomless, suggesting that the resistance to CABMV was maintained in the plant genome as the homozygous condition was achieved. Five selected resistant TI6R(2) plants which contained the capsid protein gene are being crossed for further analyses.

Elevated blood lead levels in a riverside population in the Brazilian Amazon

Lead (Pb) is recognized as one of the most toxic metals. Sources of Pb exposure have been widely documented in North America, and the removal of Pb additives from gasoline was reflected in a dramatic lowering of blood Pb concentration. In Latin America, the removal of Pb from gasoline resulted in decreased exposure, but Pb levels in many areas remain high due to occupational and environmental sources of exposure. While many of the Pb sources have been identified (mining, industries, battery recycling, lead-based paint, ceramics), new ones occasionally crop up. Here we report on blood Pb (B-Pb) levels in remote riverside communities of the Brazilian Amazon. Blood Pb (B-Pb) levels were determined in 448 persons from 12 villages of the Lower Tapajos River Basin, Par, Brazil. Socio-demographic and dietary information, as well as occupational, residential and medical history was collected using an interview-administered questionnaire. B-Pb, measured by ICP-MS, showed elevated concentrations. Mean B-Pb was 13.1 mu g/dL +/- 8.5, median B-Pb was 11.2 mu g/dL and ranged from 0.59 to 48.3 mu g/dL. Men had higher B-Pb compared to women (median: 15.3 mu g/dL vs 7.9 mu g/dL respectively). B-Pb increased with age for women, while it decreased for men. For both genders, B-Pb decreased with education. There were significant differences between villages. Exploratory analyses, using linear partition models, showed that for men B-Pb was lower among those who were involved in cattle-raising, and higher among those who hunted, farmed and fished. The distribution profile of B-Pb directed us towards artisanal transformation of manioc to flour (farinha), which requires heating in a large metal pan, with stirring primarily done by young men. In the village with the highest B-Pb, analysis of Pb concentrations (dry weight) of manioc (prior to transformation) and farinha (following transformation) from 6 houses showed a tenfold increase in Pb concentration (mean: 0.017 +/- 0.016 to 0.19 +/- 0.10 mu g/g). This was confirmed in one of these villages where we sampled manioc paste Oust before roasting) and the roasted farinha (0.05 mu g/g vs 0.20 mu g/g). While there may be other sources (ammunition, sinkers for fishing nets), the high concentrations in farinha, a dietary staple, assuredly makes an important contribution. Further action needs to reduce Pb sources in this region. (C) 2009 Elsevier Inc. All rights reserved.

A scheme for efficient quantum computation wtih linear optics

Quantum computers promise to increase greatly the efficiency of solving problems such as factoring large integers, combinatorial optimization and quantum physics simulation. One of the greatest challenges now is to implement the basic quantum-computational elements in a physical system and to demonstrate that they can be reliably and scalably controlled. One of the earliest proposals for quantum computation is based on implementing a quantum bit with two optical modes containing one photon. The proposal is appealing because of the ease with which photon interference can be observed. Until now, it suffered from the requirement for non-linear couplings between optical modes containing few photons. Here we show that efficient quantum computation is possible using only beam splitters, phase shifters, single photon sources and photo-detectors. Our methods exploit feedback from photo-detectors and are robust against errors from photon loss and detector inefficiency. The basic elements are accessible to experimental investigation with current technology.