Effects of medium supplementation and pH control on lactic acid production from brewer`s spent grain

A cellulose pulp obtained by chemical pre-treatment of brewer`s spent grain was saccharified by a commercial cellulase preparation and the produced hydrolysate (50 g/l glucose) was fermented to lactic acid by Lactobacillus delbrueckii. The effects of pH control and nutrient supplementation of the hydrolysate on fermentation performance were investigated. Addition of 5g/l yeast extract enhanced the lactic acid volumetric productivity that attained 0.53 g/l h, value 18% higher than that obtained from non-supplemented hydrolysate. Addition of the MRS broth medium components (except the carbon source) was still better, providing a productivity of 0.79 g/l h. In all the cases, the lactic acid yield factor was of 0.7 g/g glucose consumed, but the fermentations stopped after 24 h due to the pH drop from 6.0 to 4.2, resulting in large amounts of residual glucose (38-41 g/l). Fermentation runs pH-controlled at 6.0 gave better results than those where the initial pH was not further controlled. The best result, 35.54 g/l lactic acid (0.99 g/g glucose consumed) was obtained during the pH-controlled fermentation of hydrolysate medium supplemented with MRS components. The volumetric productivity at the end of this fermentation was 0.59 g/l h, with a maximum of 0.82 g/l h during the first 12 h. (c) 2008 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.

Effect of pH and oxalic acid on the reduction of Fe(3+) by a biomimetic chelator and on Fe(3+) desorption/adsorption onto wood: Implications for brown-rot decay

Fenton reaction is thought to play an important role in wood degradation by brown-rot fungi. In this context, the effect of oxalic acid and pH on iron reduction by a biomimetic fungal chelator and on the adsorption/desorption of iron to/from wood was investigated. The results presented in this work indicate that at pH 2.0 and 4.5 and in the presence of oxalic acid, the phenolate chelator 2,3-dihydroxybenzoic acid (2,3-DHBA) is capable of reducing ferric iron only when the iron is complexed with oxalate to form Fe mono-oxalate (Fe(C(2)O(4))(+)). Within the pH range tested in this work, this complex formation occurs when the oxalate:Fe(3+) molar ratio is less than 20 (pH 2.0) or less than 10 (pH 4.5). When aqueous ferric iron was passed through a column packed with milled red spruce (Picea rubens) wood equilibrated at pH 2.0 and 4.5. it was observed that ferric iron binds to wood at pH 4.5 but not at pH 2.0, and the bound iron could then be released by application of oxalic acid at pH 4.5. The release of bound iron was dependent on the amount of oxalic acid applied in the column. When the amount of oxalate was at least 20-fold greater than the amount of iron bound to the wood, all bound iron was released. When Fe-oxalate complexes were applied to the milled wood column equilibrated in the pH range of 2-4.5, iron from Fe-oxalate complexes was bound to the wood only when the pH was 3.6 or higher and the oxalate:Fe(3+) molar ratio was less than 10. When 2,3-DHBA was evaluated for its ability to release iron bound to the milled wood, it was found that 2,3-DHBA possessed a greater affinity for ferric iron than the wood as 2,3-DHBA was capable of releasing the ferric iron bound to the wood in the pH range 3.6-5.5. These results further the understanding of the mechanisms employed by brown-rot fungi in wood biodegradation processes. (C) 2009 Elsevier Ltd. All rights reserved.

Offline Detection, Identification, and Correction of Branch Parameter Errors Based on Several Measurement Snapshots

This paper proposes a three-stage offline approach to detect, identify, and correct series and shunt branch parameter errors. In Stage 1 the branches suspected of having parameter errors are identified through an Identification Index (II). The II of a branch is the ratio between the number of measurements adjacent to that branch, whose normalized residuals are higher than a specified threshold value, and the total number of measurements adjacent to that branch. Using several measurement snapshots, in Stage 2 the suspicious parameters are estimated, in a simultaneous multiple-state-and-parameter estimation, via an augmented state and parameter estimator which increases the V - theta state vector for the inclusion of suspicious parameters. Stage 3 enables the validation of the estimation obtained in Stage 2, and is performed via a conventional weighted least squares estimator. Several simulation results (with IEEE bus systems) have demonstrated the reliability of the proposed approach to deal with single and multiple parameter errors in adjacent and non-adjacent branches, as well as in parallel transmission lines with series compensation. Finally the proposed approach is confirmed on tests performed on the Hydro-Quebec TransEnergie network.

Fault Detection in Power Distribution Systems Using Automated Integration of Computational Intelligence Tools

The main purpose of this paper is to present architecture of automated system that allows monitoring and tracking in real time (online) the possible occurrence of faults and electromagnetic transients observed in primary power distribution networks. Through the interconnection of this automated system to the utility operation center, it will be possible to provide an efficient tool that will assist in decisionmaking by the Operation Center. In short, the desired purpose aims to have all tools necessary to identify, almost instantaneously, the occurrence of faults and transient disturbances in the primary power distribution system, as well as to determine its respective origin and probable location. The compilations of results from the application of this automated system show that the developed techniques provide accurate results, identifying and locating several occurrences of faults observed in the distribution system.

Innovation concept for measurement gross error detection and identification in power system state estimation

In this study, the innovation approach is used to estimate the measurement total error associated with power system state estimation. This is required because the power system equations are very much correlated with each other and as a consequence part of the measurements errors is masked. For that purpose an index, innovation index (II), which provides the quantity of new information a measurement contains is proposed. A critical measurement is the limit case of a measurement with low II, it has a zero II index and its error is totally masked. In other words, that measurement does not bring any innovation for the gross error test. Using the II of a measurement, the masked gross error by the state estimation is recovered; then the total gross error of that measurement is composed. Instead of the classical normalised measurement residual amplitude, the corresponding normalised composed measurement residual amplitude is used in the gross error detection and identification test, but with m degrees of freedom. The gross error processing turns out to be very simple to implement, requiring only few adaptations to the existing state estimation software. The IEEE-14 bus system is used to validate the proposed gross error detection and identification test.

Assessment of the Performance of Acoustic and Mass Balance Methods for Leak Detection in Pipelines for Transporting Liquids

On-line leak detection is a main concern for the safe operation of pipelines. Acoustic and mass balance are the most important and extensively applied technologies in field problems. The objective of this work is to compare these leak detection methods with respect to a given reference situation, i.e., the same pipeline and monitoring signals acquired at the inlet and outlet ends. Experimental tests were conducted in a 749 m long laboratory pipeline transporting water as the working fluid. The instrumentation included pressure transducers and electromagnetic flowmeters. Leaks were simulated by opening solenoid valves placed at known positions and previously calibrated to produce known average leak flow rates. Results have clearly shown the limitations and advantages of each method. It is also quite clear that acoustics and mass balance technologies are, in fact, complementary. In general, an acoustic leak detection system sends out an alarm more rapidly and locates the leak more precisely, provided that the rupture of the pipeline occurs abruptly enough. On the other hand, a mass balance leak detection method is capable of quantifying the leak flow rate very accurately and of detecting progressive leaks.

Leak detection by inverse transient analysis in an experimental PVC pipe system

Leakage reduction in water supply systems and distribution networks has been an increasingly important issue in the water industry since leaks and ruptures result in major physical and economic losses. Hydraulic transient solvers can be used in the system operational diagnosis, namely for leak detection purposes, due to their capability to describe the dynamic behaviour of the systems and to provide substantial amounts of data. In this research work, the association of hydraulic transient analysis with an optimisation model, through inverse transient analysis (ITA), has been used for leak detection and its location in an experimental facility containing PVC pipes. Observed transient pressure data have been used for testing ITA. A key factor for the success of the leak detection technique used is the accurate calibration of the transient solver, namely adequate boundary conditions and the description of energy dissipation effects since PVC pipes are characterised by a viscoelastic mechanical response. Results have shown that leaks were located with an accuracy between 4-15% of the total length of the pipeline, depending on the discretisation of the system model.

HYBRID AND INCREMENTAL FUZZY LEARNING FOR HUMAN SKIN DETECTION

In this paper, a framework for detection of human skin in digital images is proposed. This framework is composed of a training phase and a detection phase. A skin class model is learned during the training phase by processing several training images in a hybrid and incremental fuzzy learning scheme. This scheme combines unsupervised-and supervised-learning: unsupervised, by fuzzy clustering, to obtain clusters of color groups from training images; and supervised to select groups that represent skin color. At the end of the training phase, aggregation operators are used to provide combinations of selected groups into a skin model. In the detection phase, the learned skin model is used to detect human skin in an efficient way. Experimental results show robust and accurate human skin detection performed by the proposed framework.

An Alternative Optical Method for Acoustic Resonance Detection in HID Lamps

Acoustic resonances are observed in high-pressure discharge lamps operated with ac input modulated power frequencies in the kilohertz range. This paper describes an optical resonance detection method for high-intensity discharge lamps using computer-controlled cameras and image processing software. Experimental results showing acoustic resonances in high-pressure sodium lamps are presented.

Ultrasound, eddy current and magnetic Barkhausen noise as tools for sigma phase detection on a UNS S31803 duplex stainless steel

Sigma phase is a deleterious one which can be formed in duplex stainless steels during heat treatment or welding. Aiming to accompany this transformation, ferrite and sigma percentage and hardness were measured on samples of a UNS S31803 duplex stainless steel submitted to heat treatment. These results were compared to measurements obtained from ultrasound and eddy current techniques, i.e., velocity and impedance, respectively. Additionally, backscattered signals produced by wave propagation were acquired during ultrasonic inspection as well as magnetic Barkhausen noise during magnetic inspection. Both signal types were processed via a combination of detrended-fluctuation analysis (DFA) and principal component analysis (PCA). The techniques used were proven to be sensitive to changes in samples related to sigma phase formation due to heat treatment. Furthermore, there is an advantage using these methods since they are nondestructive. (C) 2010 Elsevier B.V. All rights reserved.

NDT flaw mapping of steel surfaces by continuous magnetic Barkhausen noise: Volumetric flaw detection case

This paper reports the use of a non-destructive, continuous magnetic Barkhausen noise (CMBN) technique to investigate the size and thickness of volumetric defects, in a 1070 steel. The magnetic behavior of the used probe was analyzed by numerical simulation, using the finite element method (FEM). Results indicated that the presence of a ferrite coil core in the probe favors MBN emissions. The samples were scanned with different speeds and probe configurations to determine the effect of the flaw on the CMBN signal amplitude. A moving smooth window, based on a second-order statistical moment, was used for analyzing the time signal. The results show the technique`s good repeatability, and high capacity for detection of this type of defect. (C) 2009 Elsevier Ltd. All rights reserved.

Corrosion Versus Mechanical Tests for Indirect Detection of Alpha Prime Phase in UNS S32520 Super Duplex Stainless Steel

Alpha prime formation leads to material embrittlement and deterioration of corrosion resistance. In the present study, the mechanical and corrosion behavior of super duplex stainless steel UNS S32520 aged at 475 degrees C from 0.5 h to 1,032 h was evaluated using microhardness measurements, Charpy impact tests, electrochemical impedance spectroscopy, and cyclic polarization curves. The sensibility of these tests to the effects of alpha prime phase was investigated. The microhardness test showed a gradual increase in hardness with aging time, whereas the impact tests revealed losses of about 80% in the energy absorption capacity for the material aged for 12 h in comparison with the solution-annealed samples. The most responsive analysis was the impact test, which indirectly revealed the presence of this deleterious phase in samples aged for 0.5 h. The electrochemical impedance spectroscopy and polarization tests were not highly sensitive to the alpha prime phase unless these are present in large amounts in the stainless steel.

Residence time distribution in holding tubes using generalized convection model and numerical convolution for non-ideal tracer detection

A procedure is proposed for the determination of the residence time distribution (RTD) of curved tubes taking into account the non-ideal detection of the tracer. The procedure was applied to two holding tubes used for milk pasteurization in laboratory scale. Experimental data was obtained using an ionic tracer. The signal distortion caused by the detection system was considerable because of the short residence time. Four RTD models, namely axial dispersion, extended tanks in series, generalized convection and PER + CSTR association, were adjusted after convolution with the E-curve of the detection system. The generalized convection model provided the best fit because it could better represent the tail on the tracer concentration curve that is Caused by the laminar velocity profile and the recirculation regions. Adjusted model parameters were well cot-related with the now rate. (C) 2010 Elsevier Ltd. All rights reserved.

On the solubility of proteins as a function of pH: Mathematical development and application

Thermodynamic relations between the solubility of a protein and the solution pH are presented in this work. The hypotheses behind the development are that the protein chemical potential in liquid phase can be described by Henry`s law and that the solid-liquid equilibrium is established only between neutral molecules. The mathematical development results in an analytical expression of the solubility curve, as a function of the ionization equilibrium constants, the pH and the solubility at the isoelectric point. It is shown that the same equation can be obtained either by directly calculating the fraction of neutral protein molecules or by integrating the curve of the protein average charge. The methodology was successfully applied to the description of the solubility of porcine insulin as a function of pH at three different temperatures and of bovine beta-lactoglobulin at four different ionic strengths. (C) 2011 Elsevier B.V. All rights reserved.