A study on the pretreatment of a sugarcane bagasse sample with dilute sulfuric acid

Experiments based on a 2(3) central composite full factorial design were carried out in 200-ml stainless-steel containers to study the pretreatment, with dilute sulfuric acid, of a sugarcane bagasse sample obtained from a local sugar-alcohol mill. The independent variables selected for study were temperature, varied from 112.5A degrees C to 157.5A degrees C, residence time, varied from 5.0 to 35.0 min, and sulfuric acid concentration, varied from 0.0% to 3.0% (w/v). Bagasse loading of 15% (w/w) was used in all experiments. Statistical analysis of the experimental results showed that all three independent variables significantly influenced the response variables, namely the bagasse solubilization, efficiency of xylose recovery in the hemicellulosic hydrolysate, efficiency of cellulose enzymatic saccharification, and percentages of cellulose, hemicellulose, and lignin in the pretreated solids. Temperature was the factor that influenced the response variables the most, followed by acid concentration and residence time, in that order. Although harsher pretreatment conditions promoted almost complete removal of the hemicellulosic fraction, the amount of xylose recovered in the hemicellulosic hydrolysate did not exceed 61.8% of the maximum theoretical value. Cellulose enzymatic saccharification was favored by more efficient removal of hemicellulose during the pretreatment. However, detoxification of the hemicellulosic hydrolysate was necessary for better bioconversion of the sugars to ethanol.

Characterization of commercial cellulases and their use in the saccharification of a sugarcane bagasse sample pretreated with dilute sulfuric acid

This study aimed to correlate the efficiency of enzymatic hydrolysis of the cellulose contained in a sugarcane bagasse sample pretreated with dilute H(2)SO(4) with the levels of independent variables such as initial content of solids and loadings of enzymes and surfactant (Tween 20), for two cellulolytic commercial preparations. The preparations, designated cellulase I and cellulase II, were characterized regarding the activities of total cellulases, endoglucanase, cellobiohydrolase, cellobiase, beta-glucosidase, xylanase, and phenoloxidases (laccase, manganese and lignin peroxidases), as well as protein contents. Both extracts showed complete cellulolytic complexes and considerable activities of xylanases, without activities of phenoloxidases. For the enzymatic hydrolyses, two 2(3) central composite full factorial designs were employed to evaluate the effects caused by the initial content of solids (1.19-4.81%, w/w) and loadings of enzymes (1.9-38.1 FPU/g bagasse) and Tween 20 (0.0-0.1 g/g bagasse) on the cellulose digestibility. Within 24 h of enzymatic hydrolysis, all three independent variables influenced the conversion of cellulose by cellulase I. Using cellulase II, only enzyme and surfactant loadings showed significant effects on cellulose conversion. An additional experiment demonstrated the possibility of increasing the initial content of solids to values much higher than 4.81% (w/w) without compromising the efficiency of cellulose conversion, consequently improving the glucose concentration in the hydrolysate.

Financial distress, financial constraint and investment decision: Evidence from Brazil

This paper analyses the presence of financial constraint in the investment decisions of 367 Brazilian firms from 1997 to 2004, using a Bayesian econometric model with group-varying parameters. The motivation for this paper is the use of clustering techniques to group firms in a totally endogenous form. In order to classify the firms we used a hybrid clustering method, that is, hierarchical and non-hierarchical clustering techniques jointly. To estimate the parameters a Bayesian approach was considered. Prior distributions were assumed for the parameters, classifying the model in random or fixed effects. Ordinate predictive density criterion was used to select the model providing a better prediction. We tested thirty models and the better prediction considers the presence of 2 groups in the sample, assuming the fixed effect model with a Student t distribution with 20 degrees of freedom for the error. The results indicate robustness in the identification of financial constraint when the firms are classified by the clustering techniques. (C) 2010 Elsevier B.V. All rights reserved.

Multiple random crack propagation using a boundary element formulation

This paper proposes a boundary element method (BEM) model that is used for the analysis of multiple random crack growth by considering linear elastic fracture mechanics problems and structures subjected to fatigue. The formulation presented in this paper is based on the dual boundary element method, in which singular and hyper-singular integral equations are used. This technique avoids singularities of the resulting algebraic system of equations, despite the fact that the collocation points coincide for the two opposite crack faces. In fracture mechanics analyses, the displacement correlation technique is applied to evaluate stress intensity factors. The maximum circumferential stress theory is used to evaluate the propagation angle and the effective stress intensity factor. The fatigue model uses Paris` law to predict structural life. Examples of simple and multi-fractured structures loaded until rupture are considered. These analyses demonstrate the robustness of the proposed model. In addition, the results indicate that this formulation is accurate and can model localisation and coalescence phenomena. (C) 2010 Elsevier Ltd. All rights reserved.

The random barrier-crossing problem

This paper addresses the time-variant reliability analysis of structures with random resistance or random system parameters. It deals with the problem of a random load process crossing a random barrier level. The implications of approximating the arrival rate of the first overload by an ensemble-crossing rate are studied. The error involved in this so-called ""ensemble-crossing rate"" approximation is described in terms of load process and barrier distribution parameters, and in terms of the number of load cycles. Existing results are reviewed, and significant improvements involving load process bandwidth, mean-crossing frequency and time are presented. The paper shows that the ensemble-crossing rate approximation can be accurate enough for problems where load process variance is large in comparison to barrier variance, but especially when the number of load cycles is small. This includes important practical applications like random vibration due to impact loadings and earthquake loading. Two application examples are presented, one involving earthquake loading and one involving a frame structure subject to wind and snow loadings. (C) 2007 Elsevier Ltd. All rights reserved.

CONCENTRATION FIELDS NEAR AIR-WATER INTERFACES DURING INTERFACIAL MASS TRANSPORT: OXYGEN TRANSPORT AND RANDOM SQUARE WAVE ANALYSIS

Mass transfer across a gas-liquid interface was studied theoretically and experimentally, using transfer of oxygen into water as the gas-liquid system. The experimental results support the conclusions of a theoretical description of the concentration field that uses random square waves approximations. The effect of diffusion over the concentration records was quantified. It is shown that the peak of the normalized rills concentration fluctuation profiles must be lower than 0.5, and that the position of the peak of the rms value is an adequate measure of the thickness of the diffusive layer. The position of the peak is the boundary between the regions more subject to molecular diffusion or to turbulent transport of dissolved mass.

Simulation of the Barkhausen Noise using random field Ising model with long-range interaction

We present a method to simulate the Magnetic Barkhausen Noise using the Random Field Ising Model with magnetic long-range interaction. The method allows calculating the magnetic flux density behavior in particular sections of the lattice reticule. The results show an internal demagnetizing effect that proceeds from the magnetic long-range interactions. This demagnetizing effect induces the appearing of a magnetic pattern in the region of magnetic avalanches. When compared with the traditional method, the proposed numerical procedure neatly reduces computational costs of simulation. (c) 2008 Published by Elsevier B.V.

Methodological analysis of gamma tomography system for large random packed columns

Gamma ray tomography experiments have been carried out to detect spatial patterns in the porosity in a 0.27 m diameter column packed with steel Rashig rings of different sizes: 12.6, 37.9, and 76 mm. using a first generation CT system (Chen et al., 1998). A fast Fourier transform tomographic reconstruction algorithm has been used to calculate the spatial variation over the column cross section. Cross-sectional gas porosity and solid holdup distribution were determinate. The values of cross-sectional average gas porosity were epsilon=0.849, 0.938 and 0.966 for the 12.6, 37.9, and 76 mm rings, respectively. Radial holdup variation within the packed bed has been determined. The variation of the circumferentially averaged gas holdup in the radial direction indicates that the porosity in the column wall region is a somewhat higher than that in the bulk region, due to the effect of the column wall. (C) 2009 Elsevier Ltd. All rights reserved.

Exploring the random genesis of co-occurrence networks

Using the network random generation models from Gustedt (2009)[23], we simulate and analyze several characteristics (such as the number of components, the degree distribution and the clustering coefficient) of the generated networks. This is done for a variety of distributions (fixed value, Bernoulli, Poisson, binomial) that are used to control the parameters of the generation process. These parameters are in particular the size of newly appearing sets of objects, the number of contexts in which new elements appear initially, the number of objects that are shared with `parent` contexts, and, the time period inside which a context may serve as a parent context (aging). The results show that these models allow to fine-tune the generation process such that the graphs adopt properties as can be found in real world graphs. (C) 2011 Elsevier B.V. All rights reserved.

On the use of correlated beta random variables with animal population modelling

We give reasons why demographic parameters such as survival and reproduction rates are often modelled well in stochastic population simulation using beta distributions. In practice, it is frequently expected that these parameters will be correlated, for example with survival rates for all age classes tending to be high or low in the same year. We therefore discuss a method for producing correlated beta random variables by transforming correlated normal random variables, and show how it can be applied in practice by means of a simple example. We also note how the same approach can be used to produce correlated uniform triangular, and exponential random variables. (C) 2008 Elsevier B.V. All rights reserved.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil

A total of 152,145 weekly test-day milk yield records from 7317 first lactations of Holstein cows distributed in 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of DIM. The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable, linear and quadratic effects. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM. Additive genetic and permanent environmental random effects were estimated by random regression on orthogonal Legendre polynomials. Residual variances were modeled using third to seventh-order variance functions or a step function with 1, 6,13,17 and 44 variance classes. Results from Akaike`s and Schwarz`s Bayesian information criterion suggested that a model considering a 7th-order Legendre polynomial for additive effect, a 12th-order polynomial for permanent environment effect and a step function with 6 classes for residual variances, fitted best. However, a parsimonious model, with a 6th-order Legendre polynomial for additive effects and a 7th-order polynomial for permanent environmental effects, yielded very similar genetic parameter estimates. (C) 2008 Elsevier B.V. All rights reserved.

Simultaneous determination of rosiglitazone and its metabolites in rat liver microsomal fraction using hollow-fiber liquid-phase microextraction for sample preparation

A three-phase hollow-fiber liquid-phase microextraction method for the analysis of rosiglitazone and its metabolites N-desmethyl rosiglitazone and p-hydroxy rosiglitazone in microsomal preparations is described for the first time. The drug and metabolites HPLC determination was carried out using an X-Terra RP-18 column, at 22 degrees C. The mobile phase was composed of water, acetonitrile and acetic acid (85:15:0.5, v/v/v) and the detection was performed at 245 nm. The hollow-fiber liquid-phase microextraction procedure was optimized using multifactorial experiments and the following optimal condition was established: sample agitation at 1750 rpm, extraction for 30 min, hydrochloric acid 0.01 mol/L as acceptor phase, 1-octanol as organic phase, and donor phase pH adjustment to 8.0. The recovery rates, obtained by using 1 mL of microsomal preparation, were 47-70%. The method presented LOQs of 50 ng/mL and it was linear over the concentration range of 50-6000 ng/mL, with correlation coefficients (r) higher than 0.9960, for all analytes. The validated method was employed to study the in vitro biotransformation of rosiglitazone using rat liver microsomal fraction.

Sudden onset of log-periodicity and superdiffusion in non-Markovian random walks with amnestically induced persistence: exact results

Random walks can undergo transitions from normal diffusion to anomalous diffusion as some relevant parameter varies, for instance the L,vy index in L,vy flights. Here we derive the Fokker-Planck equation for a two-parameter family of non-Markovian random walks with amnestically induced persistence. We investigate two distinct transitions: one order parameter quantifies log-periodicity and discrete scale invariance in the first moment of the propagator, whereas the second order parameter, known as the Hurst exponent, describes the growth of the second moment. We report numerical and analytical results for six critical exponents, which together completely characterize the properties of the transitions. We find that the critical exponents related to the diffusion-superdiffusion transition are identical in the positive feedback and negative feedback branches of the critical line, even though the former leads to classical superdiffusion whereas the latter gives rise to log-periodic superdiffusion.

Methylmercury and inorganic mercury determination in blood by using liquid chromatography with inductively coupled plasma mass spectrometry and a fast sample preparation procedure

Despite the necessity to differentiate chemical species of mercury in clinical specimens, there area limited number of methods for this purpose. Then, this paper describes a simple method for the determination of methylmercury and inorganic mercury in blood by using liquid chromatography with inductively coupled mass spectrometry (LC-ICP-MS) and a fast sample preparation procedure. Prior to analysis, blood (250 mu L) is accurately weighed into 15-mL conical tubes. Then, an extractant solution containing mercaptoethanol, L-cysteine and HCI was added to the samples following sonication for 15 min. Quantitative mercury extraction was achieved with the proposed procedure. Separation of mercury species was accomplished in less than 5 min on a C18 reverse-phase column with a mobile phase containing 0.05% (v/v) mercaptoethanol, 0.4% (m/v) L-cysteine, 0.06 mol L(-1) ammonium acetate and 5% (v/v) methanol. The method detection limits were found to be 0.25 mu g L(-1) and 0.1 mu Lg L(-1) for inorganic mercury and methylmercury, respectively. Method accuracy is traceable to Standard Reference Material (SRM) 966 Toxic Metals in Bovine Blood from the National Institute of Standards and Technology (NIST). The proposed method was also applied to the speciation of mercury in blood samples collected from fish-eating communities and from rats exposed to thimerosal. With the proposed method there is a considerable reduction of the time of sample preparation prior to speciation of Hg by LC-ICP-MS. Finally, after the application of the proposed method, we demonstrated an interesting in vivo ethylmercury conversion to inorganic mercury. (C) 2009 Elsevier B.V. All rights reserved.