Biohydrogen production in anaerobic fluidized bed reactors: Effect of support material and hydraulic retention time

This study evaluated two different support materials (polystyrene and expanded clay) for biohydrogen production in an anaerobic fluidized bed reactor (AFBR) treating synthetic wastewater containing glucose (4000 mg L(-1)). The AFBRs contained either polystyrene (R1) or expanded clay (R2) as support materials were inoculated with thermally pre-treated anaerobic sludge and operated at a temperature of 30 degrees C and a pH of approximately 5.5. The AFBRs were operated with a range of hydraulic retention times (HRTs) between 1 and 8 h. For R1 with an HRT of 2 h, the maximum hydrogen yield (HY) was 1.90 mol H(2) mol(-1) glucose, with 0.805 mg of biomass (as total volatile solids, or TVS) attached to each g of polystyrene. For R2 operated at an HRT of 2 h, the maximum HY was 2.59 mol H(2) moll glucose, with 1.100 mg of attached biomass (as TVS) g(-1) expanded clay. The highest hydrogen production rates (HPR) were 0.95 and 1.21 L h(-1) L(-1) for R1 and R2, respectively, using an HRT of 1 h. The H(2) content increased from 16-47% for R1 and from 22-51% for R2. No methane was detected in the biogas produced throughout the period of AFBR operation. These results show that the values of HY, HPR, H(2) content, and g of attached biomass g(-1) support material were all higher for AFBRs containing expanded clay than for reactors containing polystyrene. (C) 2010 Professor T. Nejat Veziroglu. Published by Elsevier Ltd. All rights reserved.

Whirlwind: a new cryptographic hash function

A new cryptographic hash function Whirlwind is presented. We give the full specification and explain the design rationale. We show how the hash function can be implemented efficiently in software and give first performance numbers. A detailed analysis of the security against state-of-the-art cryptanalysis methods is also provided. In comparison to the algorithms submitted to the SHA-3 competition, Whirlwind takes recent developments in cryptanalysis into account by design. Even though software performance is not outstanding, it compares favourably with the 512-bit versions of SHA-3 candidates such as LANE or the original CubeHash proposal and is about on par with ECHO and MD6.

Multicriteria analysis in decision making under information uncertainty

This paper presents results of research related to multicriteria decision making under information uncertainty. The Bell-man-Zadeh approach to decision making in a fuzzy environment is utilized for analyzing multicriteria optimization models (< X, M > models) under deterministic information. Its application conforms to the principle of guaranteed result and provides constructive lines in obtaining harmonious solutions on the basis of analyzing associated maxmin problems. This circumstance permits one to generalize the classic approach to considering the uncertainty of quantitative information (based on constructing and analyzing payoff matrices reflecting effects which can be obtained for different combinations of solution alternatives and the so-called states of nature) in monocriteria decision making to multicriteria problems. Considering that the uncertainty of information can produce considerable decision uncertainty regions, the resolving capacity of this generalization does not always permit one to obtain unique solutions. Taking this into account, a proposed general scheme of multicriteria decision making under information uncertainty also includes the construction and analysis of the so-called < X, R > models (which contain fuzzy preference relations as criteria of optimality) as a means for the subsequent contraction of the decision uncertainty regions. The paper results are of a universal character and are illustrated by a simple example. (c) 2007 Elsevier Inc. All rights reserved.

A geometrical approach of 3-D FEA for educational purposes applied to electrostatic fields

A geometrical approach of the finite-element analysis applied to electrostatic fields is presented. This approach is particularly well adapted to teaching Finite Elements in Electrical Engineering courses at undergraduate level. The procedure leads to the same system of algebraic equations as that derived by classical approaches, such as variational principle or weighted residuals for nodal elements with plane symmetry. It is shown that the extension of the original procedure to three dimensions is straightforward, provided the domain be meshed in first-order tetrahedral elements. The element matrices are derived by applying Maxwell`s equations in integral form to suitably chosen surfaces in the finite-element mesh.

Abrasive wear study of white cast iron with different solidification rates

The abrasive wear resistance of white cast iron was studied. The iron was solidified using two solidification rates of 1.5 and 15 degrees C/s. Mass loss was evaluated with tests of the type pin on abrasive disc using alumina of different sizes. Two matrices were tested: one predominantly austenitic and the other predominantly martensitic, containing M(3)C carbides. Samples with cooling rate of 15 degrees C/s showed higher hardness and more refined microstructure compared with those solidified at 1.5 degrees C/s. During the test, the movement of successive abrasives gave rise to the strain hardening of the austenite phase, leading to the attainment of similar levels of surface hardness, which explains why the wear rate showed no difference compared to the austenite samples with different solidification rates. For the austenitic matrix the wear rate seems to depend on the hardness of the worn surface and not on the hardness of the material without deformation. The austenitic samples showed cracking and fracture of M(3)C carbides. For the predominantly martensitic matrix, the wear rate was higher at the solidification rate of 1.5 degrees C/s, for grain size of 66 and 93 mu m. Higher abrasive sizes were found to produce greater penetration and strain hardening of austenitic matrices. However, martensitic iron produces more microcutting, increasing the wear rate of the material. The analysis of the worn surface by scanning electron microscopy indicated abrasive wear mechanisms such as: microcutting, microfatigue and microploughing. Yet, for the iron of austenitic matrix, the microploughing mechanism was more severe. (C) 2009 Elsevier B.V. All rights reserved.

Controlling the luminescence properties of poly(p-phenylene vinylene) entrapped in Langmuir and Langmuir-Blodgett films of stearic acid

Properties of hybrid films can be enhanced if their molecular architecture is controlled. In this paper, poly (p-phenylene vinylene) was mixed with stearic acid in order to form stable hybrid Langmuir monolayers. Surface properties of these films were investigated with measurements of surface pressure, and also with polarization modulation infrared reflection-absorption spectroscopy (PM-IRRAS). The films were transferred from the air-water interface to solid supports through the Langmuir-Blodgett technique, and the viability of the film as optical device was investigated with fluorescence spectroscopy. Comparing the fluorescent spectra for the polymer in solution, as a casting film, and as an LB film, the emission bands for LB films were narrower and appeared at lower wavelengths. The interactions between the film components and the design for the LB film may take advantage of the method to immobilize luminescent polymers in mixed ultrathin films adsorbed in solid matrices. (C) 2011 Elsevier B.V. All rights reserved.

An Array Recursive Least-Squares Algorithm With Generic Nonfading Regularization Matrix

We present a novel array RLS algorithm with forgetting factor that circumvents the problem of fading regularization, inherent to the standard exponentially-weighted RLS, by allowing for time-varying regularization matrices with generic structure. Simulations in finite precision show the algorithm`s superiority as compared to alternative algorithms in the context of adaptive beamforming.

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.

Generalized Coupled Algebraic Riccati Equations for Discrete-time Markov Jump with Multiplicative Noise Systems

In this paper we consider the existence of the maximal and mean square stabilizing solutions for a set of generalized coupled algebraic Riccati equations (GCARE for short) associated to the infinite-horizon stochastic optimal control problem of discrete-time Markov jump with multiplicative noise linear systems. The weighting matrices of the state and control for the quadratic part are allowed to be indefinite. We present a sufficient condition, based only on some positive semi-definite and kernel restrictions on some matrices, under which there exists the maximal solution and a necessary and sufficient condition under which there exists the mean square stabilizing solution fir the GCARE. We also present a solution for the discounted and long run average cost problems when the performance criterion is assumed be composed by a linear combination of an indefinite quadratic part and a linear part in the state and control variables. The paper is concluded with a numerical example for pension fund with regime switching.

Formulating Mixed Models for Experiments, Including Longitudinal Experiments

Mixed models have become important in analyzing the results of experiments, particularly those that require more complicated models (e.g., those that involve longitudinal data). This article describes a method for deriving the terms in a mixed model. Our approach extends an earlier method by Brien and Bailey to explicitly identify terms for which autocorrelation and smooth trend arising from longitudinal observations need to be incorporated in the model. At the same time we retain the principle that the model used should include, at least, all the terms that are justified by the randomization. This is done by dividing the factors into sets, called tiers, based on the randomization and determining the crossing and nesting relationships between factors. The method is applied to formulate mixed models for a wide range of examples. We also describe the mixed model analysis of data from a three-phase experiment to investigate the effect of time of refinement on Eucalyptus pulp from four different sources. Cubic smoothing splines are used to describe differences in the trend over time and unstructured covariance matrices between times are found to be necessary.

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

On estimation and influence diagnostics for zero-inflated negative binomial regression models

The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 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.

Development and In Vitro Evaluation of Propranolol Hydrochloride Controlled Release Tablets Using HPMC as Matrix Former

The purpose of this paper was to produce controlled-release matrices with 120 mg of propranolol hydrochloride (PHCl) employing hydroxypropyl methylcellulose (HPMC, Methocel (R) K100) as the gel forming barrier. Although this class of polymers has been commonly used for direct compression, with the intent of use reduced polymer concentrations to achieve controlled drug release, in this study tablets were produced by the wet granulation process. HPMC percentages ranged from 15-34 % and both soluble and non soluble diluents were tested in the 10 proposed tablet compositions. Dissolution testing of matrices was performed over a 12 h period in 1.2 pH medium (the first 2 h) and in pH 6.8 (10 h). Dissolution kinetic analysis was performed by applying Zero-order, First-order and Higuchi models with the aim of elucidating the drug release mechanism. All physical-chemical characteristics such as average weight, friability, hardness, diameter, height, and drug content were in accordance to the pharmacopeial specifications. Taking into account that PHCl is a very soluble drug, low concentrations (15 %) of HPMC were sufficient to reduce the drug release and to promote controlled release of PHCl, presenting good dissolution efficiencies, between 50 % and 63 %. The Higuchi model has presented the best fit to the 15 % HPMC formulations, indicating that the main release mechanism was diffusion. It could be concluded that the application of the wet granulation method reduced matrices erosion and promoted controlled release of the drug at low HPMC percentages.

Enantioselective Analysis of Fluoxetine and Norfluoxetine by LC in Culture Medium for Application in Biotransformation Studies Employing Fungi

A liquid chromatography method is described for the analysis of fluoxetine and norfluoxetine enantiomers in fungi cultures. The analytes were separated simultaneously by LC employing a serial system. The resolution was performed using a mobile phase of ethanol: 15 mM ammonium acetate buffer solution, pH 5.9: acetonitrile (77.5:17.5:5, v/v/v). UV detection was at 227 nm. Hexane: isoamyl alcohol (98:2, v/v) was used as extractor solvent. The calibration curves were linear over the concentration range of 12.5-3,750 ng mL(-1) (r a parts per thousand yen 0.996). The values for intra- and inter-day precision and accuracy were a parts per thousand currency sign10% for all analytes. The validated method was used to evaluate fluoxetine biotransformation to its mammalian metabolite, norfluoxetine, by selected endophytic fungi. Although the desired biotransformation was not observed in the conditions used here, the method could be used to evaluate the biotransformation of fluoxetine by other fungi or to be extended to other matrices with adequate procedures for sample preparation.