Synthesis of PID controllers for a class of time delay systems

In this paper we use the Hermite-Biehler theorem to establish results on the design of proportional plus integral plus derivative (PID) controllers for a class of time delay systems. Using the property of interlacing at high frequencies of the class of systems considered and linear programming we obtain the set of all stabilizing PID controllers. As far as we know, previous results on the synthesis of PID controllers rely on the solution of transcendental equations. This paper also extends previous results on the synthesis of proportional controllers for a class of delay systems Of retarded type to a larger class of delay systems. (C) 2009 Elsevier Ltd. All rights reserved.

Effects of time delay and transportation on isolation of pathogenic fungi from skin biopsies

BACKGROUND - It is not clear how culture media used during transport and the interval between the biopsy procedure and final processing can affect the successful isolation of fungi. OBJECTIVE - The aim of this study was to investigate the effects of late inoculation of skin biopsies, transported in different sterile fluids, on the isolation rate of pathogenic fungi. METHODS -A total of 278 punch biopsy specimens were collected from 47 patients with suspected lesions of invasive mycoses. Each biopsy was transported in vials with Sabouraud medium with chloramphenicol or saline solution and finally inoculated on Sabouraud agar and 2% chloramphenicol after a 48-72-hour (early) or after 72-hour-7-day (late) interval, comprising four groups of study. RESULTS - The medians of isolation rate of the four sporotrichosis groups were 100%. For paracoccidioidomycosis, the medians ranged from 50% to 84%, with no statistically significant difference among the groups (p=0.88). CONCLUSION - It was concluded that skin biopsies can be transported in Sabouraud medium or saline solution within a 7-day interval from specimen collection up to final inoculation, at room temperature, maintaining viability and growth rate of fungus in culture.

Influence of Water Content, Time, and Temperature on the Rheological Behavior of Polyethylene Terephtalate

In this work, the main factors affecting the rheological behavior of polyethylene terephtalate (PET) in the linear viscoelastic regime (water content, time delay before test, duration of experiment, and temperature) were accessed. Small amplitude oscillatory shear tests were performed after different time delays ranging from 300 to 5000 s for samples with water contents ranging from 0.02 to 0.45 wt %. Time sweep tests were carried out for different durations to explain the changes undergone by PET before and during small amplitude oscillatory shear measurements. Immediately after the time sweep tests, the PET samples were removed from the rheometer, analyzed by differential scanning calorimetry and their molar mass was obtained by viscometry analysis. It was shown that for all the samples, the delay before test and residence time within the rheometer (i.e. duration of experiment) result in structural changes of the PET samples, such as increase or decrease of molar mass, broadening of molar mass distribution, and branching phenomena. (C) 2010 Wiley Periodicals, Inc. J Appl Polym Sci 116: 3525-3533, 2010

Existence results for partial neutral functional differential equations with state-dependent delay

In this paper we study the existence of mild solutions for a class of first order abstract partial neutral differential equations with state-dependent delay. (C) 2008 Elsevier Ltd. All rights reserved.

Simultaneous saccharification and ethanol fermentation of oxalic acid pretreated corncob assessed with response surface methodology

Response surface methodology was used to evaluate optimal time, temperature and oxalic acid concentration for simultaneous saccharification and fermentation (SSF) of corncob particles by Pichia stipitis CBS 6054. Fifteen different conditions for pretreatment were examined in a 2(3) full factorial design with six axial points. Temperatures ranged from 132 to 180 degrees C, time from 10 to 90 min and oxalic acid loadings from 0.01 to 0.038 g/g solids. Separate maxima were found for enzymatic saccharification and hemicellulose fermentation, respectively, with the condition for maximum saccharification being significantly more severe. Ethanol production was affected by reaction temperature more than by oxalic acid and reaction time over the ranges examined. The effect of reaction temperature was significant at a 95% confidence level in its effect on ethanol production. Oxalic acid and reaction time were statistically significant at the 90% level. The highest ethanol concentration (20 g/l) was obtained after 48 h with an ethanol volumetric production rate of 0.42 g ethanol l(-1) h(-1). The ethanol yield after SSF with P. stipitis was significantly higher than predicted by sequential saccharification and fermentation of substrate pretreated under the same condition. This was attributed to the secretion of beta-glucosidase by P. stipitis. During SSF, free extracellular beta-glucosidase activity was 1.30 pNPG U/g with P. stipitis, while saccharification without the yeast was 0.66 pNPG U/g. Published by Elsevier Ltd.

Using Reverberation to Improve Range and Elevation Discrimination for Small Array Sound Source Localization

Sound source localization (SSL) is an essential task in many applications involving speech capture and enhancement. As such, speaker localization with microphone arrays has received significant research attention. Nevertheless, existing SSL algorithms for small arrays still have two significant limitations: lack of range resolution, and accuracy degradation with increasing reverberation. The latter is natural and expected, given that strong reflections can have amplitudes similar to that of the direct signal, but different directions of arrival. Therefore, correctly modeling the room and compensating for the reflections should reduce the degradation due to reverberation. In this paper, we show a stronger result. If modeled correctly, early reflections can be used to provide more information about the source location than would have been available in an anechoic scenario. The modeling not only compensates for the reverberation, but also significantly increases resolution for range and elevation. Thus, we show that under certain conditions and limitations, reverberation can be used to improve SSL performance. Prior attempts to compensate for reverberation tried to model the room impulse response (RIR). However, RIRs change quickly with speaker position, and are nearly impossible to track accurately. Instead, we build a 3-D model of the room, which we use to predict early reflections, which are then incorporated into the SSL estimation. Simulation results with real and synthetic data show that even a simplistic room model is sufficient to produce significant improvements in range and elevation estimation, tasks which would be very difficult when relying only on direct path signal components.

Detection of Auditory Cortex Activity by fMRI Using a Dependent Component Analysis

Functional MRI (fMRI) data often have low signal-to-noise-ratio (SNR) and are contaminated by strong interference from other physiological sources. A promising tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). BSS is based on the assumption that the detected signals are a mixture of a number of independent source signals that are linearly combined via an unknown mixing matrix. BSS seeks to determine the mixing matrix to recover the source signals based on principles of statistical independence. In most cases, extraction of all sources is unnecessary; instead, a priori information can be applied to extract only the signal of interest. Herein we propose an algorithm based on a variation of ICA, called Dependent Component Analysis (DCA), where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We applied such method to inspect functional Magnetic Resonance Imaging (fMRI) data, aiming to find the hemodynamic response that follows neuronal activation from an auditory stimulation, in human subjects. The method localized a significant signal modulation in cortical regions corresponding to the primary auditory cortex. The results obtained by DCA were also compared to those of the General Linear Model (GLM), which is the most widely used method to analyze fMRI datasets.

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.

Tidal-amplitude rhythms of larval release: variable departure from presumed optimal timing among populations of the mottled shore crab

It is widely assumed that optimal timing of larval release is of major importance to offspring survival, but the extent to which environmental factors entrain synchronous reproductive rhythms in natural populations is not well known. We sampled the broods of ovigerous females of the common shore crab Pachygrapsus transversus at both sheltered and exposed rocky shores interspersed along a so-km coastline, during four different periods, to better assess inter-population differences of larval release timing and to test for the effect of wave action. Shore-specific patterns were consistent through time. Maximum release fell within 1 day around syzygies on all shores, which matched dates of maximum tidal amplitude. Within this very narrow range, populations at exposed shores anticipated hatching compared to those at sheltered areas, possibly due to mechanical stimulation by wave action. Average departures from syzygial release ranged consistently among shores from 2.4 to 3.3 days, but in this case we found no evidence for the effect of wave exposure. Therefore, processes varying at the scale of a few kilometres affect the precision of semilunar timing and may produce differences in the survival of recently hatched larvae. Understanding the underlying mechanisms causing departures from presumed optimal release timing is thus important for a more comprehensive evaluation of reproductive success of invertebrate populations.

Simultaneous optimization by neuro-genetic approach for analysis of plant materials by laser induced breakdown spectroscopy

A simultaneous optimization strategy based on a neuro-genetic approach is proposed for selection of laser induced breakdown spectroscopy operational conditions for the simultaneous determination of macronutrients (Ca, Mg and P), micro-nutrients (B, Cu, Fe, Mn and Zn), Al and Si in plant samples. A laser induced breakdown spectroscopy system equipped with a 10 Hz Q-switched Nd:YAG laser (12 ns, 532 nm, 140 mJ) and an Echelle spectrometer with intensified coupled-charge device was used. Integration time gate, delay time, amplification gain and number of pulses were optimized. Pellets of spinach leaves (NIST 1570a) were employed as laboratory samples. In order to find a model that could correlate laser induced breakdown spectroscopy operational conditions with compromised high peak areas of all elements simultaneously, a Bayesian Regularized Artificial Neural Network approach was employed. Subsequently, a genetic algorithm was applied to find optimal conditions for the neural network model, in an approach called neuro-genetic, A single laser induced breakdown spectroscopy working condition that maximizes peak areas of all elements simultaneously, was obtained with the following optimized parameters: 9.0 mu s integration time gate, 1.1 mu s delay time, 225 (a.u.) amplification gain and 30 accumulated laser pulses. The proposed approach is a useful and a suitable tool for the optimization process of such a complex analytical problem. (C) 2009 Elsevier B.V. All rights reserved.

Optimal recovery process conditions for manganese-peroxidase obtained by solid-state fermentation of eucalyptus residue using Lentinula edodes

Enzyme production is a growing field in biotechnology and increasing attention has been devoted to the solid-state fermentation (SSF) of lignocellulosic biomass for production of industrially relevant lignocellulose deconstruction enzymes, especially manganese-peroxidase (MnP), which plays a crucial role in lignin degradation. However, there is a scarcity of studies regarding extraction of the secreted metabolities that are commonly bound to the fermented solids, preventing their accurate detection and limiting recovery efficiency. In the present work, we assessed the effectiveness of extraction process variables (pH, stirring rate, temperature, and extraction time) on recovery efficiency of manganese-peroxidase (MnP) obtained by SSF of eucalyptus residues using Lentinula edodes using statistical design of experiments. The results from this study indicated that of the variables studied, pH was the most significant (p < 0.05%) parameter affecting MnP recovery yield, while temperature, extraction time, and stirring rate presented no statistically significant effects in the studied range. The optimum pH for extraction of MnP was at 4.0-5.0, which yielded 1500-1700 IU kg (1) of enzyme activity at extraction time 4-5 h, under static condition at room temperature. (C) 2011 Elsevier Ltd. All rights reserved.

Recursive linear estimation for general discrete-time descriptor systems

This paper considers the optimal linear estimates recursion problem for discrete-time linear systems in its more general formulation. The system is allowed to be in descriptor form, rectangular, time-variant, and with the dynamical and measurement noises correlated. We propose a new expression for the filter recursive equations which presents an interesting simple and symmetric structure. Convergence of the associated Riccati recursion and stability properties of the steady-state filter are provided. (C) 2010 Elsevier Ltd. All rights reserved.

Real time optimization (RTO) with model predictive control (MPC)

This paper studies a simplified methodology to integrate the real time optimization (RTO) of a continuous system into the model predictive controller in the one layer strategy. The gradient of the economic objective function is included in the cost function of the controller. Optimal conditions of the process at steady state are searched through the use of a rigorous non-linear process model, while the trajectory to be followed is predicted with the use of a linear dynamic model, obtained through a plant step test. The main advantage of the proposed strategy is that the resulting control/optimization problem can still be solved with a quadratic programming routine at each sampling step. Simulation results show that the approach proposed may be comparable to the strategy that solves the full economic optimization problem inside the MPC controller where the resulting control problem becomes a non-linear programming problem with a much higher computer load. (C) 2010 Elsevier Ltd. All rights reserved.

A Separation Principle for the Continuous-Time LQ-Problem With Markovian Jump Parameters

In this paper, we devise a separation principle for the finite horizon quadratic optimal control problem of continuous-time Markovian jump linear systems driven by a Wiener process and with partial observations. We assume that the output variable and the jump parameters are available to the controller. It is desired to design a dynamic Markovian jump controller such that the closed loop system minimizes the quadratic functional cost of the system over a finite horizon period of time. As in the case with no jumps, we show that an optimal controller can be obtained from two coupled Riccati differential equations, one associated to the optimal control problem when the state variable is available, and the other one associated to the optimal filtering problem. This is a separation principle for the finite horizon quadratic optimal control problem for continuous-time Markovian jump linear systems. For the case in which the matrices are all time-invariant we analyze the asymptotic behavior of the solution of the derived interconnected Riccati differential equations to the solution of the associated set of coupled algebraic Riccati equations as well as the mean square stabilizing property of this limiting solution. When there is only one mode of operation our results coincide with the traditional ones for the LQG control of continuous-time linear systems.

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.