Biological detoxification of different hemicellulosic hydrolysates using Issatchenkia occidentalis CCTCC M 206097 yeast

This work had as its main objective to contribute to the development of a biological detoxification of hemicellulose hydrolysates obtained from different biomass plants using Issatchenkia occidentalis CCTCC M 206097 yeast. Tests with hemicellulosic hydrolysate of sugarcane bagasse in different concentrations were carried out to evaluate the influence of the hydrolysate concentration on the inhibitory compounds removal from the sugarcane bagasse hydrolysate, without reduction of sugar concentration. The highest reduction values of inhibitors concentration and less sugar losses were observed when the fivefold concentrated hydrolysate was treated by the evaluated yeast. In these experiments it was found that the high sugar concentrations favored lower sugar consumption by the yeast. The highest concentration reduction of syringaldehyde (66.67%), ferulic acid (73.33%), furfural (62%), and 5-HMF (85%) was observed when the concentrated hydrolysate was detoxified by using this yeast strain after 24 h of experimentation. The results obtained in this work showed the potential of the yeast Issatchenkia occidentalis CCTCC M 206097 as detoxification agent of hemicellulosic hydrolysate of different biomass plants.

Novel Isolates for Biological Detoxification of Lignocellulosic Hydrolysate

In this paper, two new strians, Issatchenkia occidentalis (Lj-3, CCTCC M 2006097) and Issatchenkia orienalis (S-7, CCTCC M 2006098), isolated from different environments on solid media, were used in the detoxification process of the hemicellulosic hydrolysate of sugarcane bagasse. High-pressure liquid chromatography elution curve of UV-absorption compounds represented by acetic acid, furfural, and guaiacol (toxic compounds found in the hemicellulosic hydrolysate) showed that several chromatographic peaks were evidently diminished for the case of detoxified hydrolysate with isolate strains compared to the high peaks resulted for no detoxified hydrolysate. It was clear that these inhibitors were degraded by the two new isolates during their cultivation process. Fermentation results for the biodetoxified hydrolysate showed an increase in xylitol productivity (Q (p)) by 1.97 and 1.95 times (2.03 and 2.01 g l(-1) h(-1)) and in xylitol yield (Y (p)) by 1.72 and 1.65 times (0.93 and 0.89 g xylitol per gram xylose) for hydrolysate treated with S-7 and Lj-3, respectively, in comparison with no detoxified hydrolysate (1.03 g l(-1) h(-1) and 0.54 g xylitol per gram xylose). This present work demonstrated the importance of Issatchenkia yeast in providing an effective biological detoxification approach to remove inhibitors and improve hydrolysate fermentability, leading to a high xylitol productivity and yield.

Analysis of Bacteria, Parasites, and Heavy Metals in Lettuce (Lactuca sativa) and Rocket Salad (Eruca sativa L.) Irrigated with Treated Effluent from a Biological Wastewater Treatment Plant

This study aimed to evaluate the viability of using treated residuary water from the Biological Wastewater Treatment Plant of Ribeiro Preto to grow vegetables, through the characterization and quantification of parasites, coliforms, and heavy metals. Three equal cultivation areas were prepared. The first was irrigated with treated/chlorinated (0.2 mg L(-1)) wastewater, the second one with treated wastewater without chlorination, and the third site with potable water, which was the control group. The presence of Hymenolepis nana, Enterobius vermicularis, nematode larvae, and Entamoeba coli was verified in lettuce (Lactuca sativa) samples. Although nematode larvae were observed in rocket salad (Eruca sativa L.), no significant differences were found between the number of parasites and type of irrigation water used. No significant differences were found between the number of fecal coliforms in vegetables and the different types of irrigation. However, the vegetables irrigated with treated effluent without chlorination showed higher levels of fecal coliforms. The risk of pathogens is reduced with bleach addition to the treated effluent at 0.2 mg/L. Concentration of heavy metals in vegetables does not mean significant risks to human health, according with the parameters recommended by the World Health Organization.

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.

A novel aerobic-anoxic biological filter for nitrogen removal from UASB effluent using biogas compounds as electron donors for denitrification

The performance of a new trickling filter (TF) configuration composed of an upper compartment for nitrification and a lower compartment for denitrification of effluent from a UASB reactor treating domestic sewage was evaluated. The TF was packed with new plastic material characterized by its durability and high percentage of void spaces. The feasibility of using the reduced compounds present in the biogas produced by a UASB reactor as electron donor for denitrification was also evaluated. Efficient nitrification and denitrification was achieved for the mean hydraulic (5.6 m(3) m(-2) d(-1)) organic (0.26 kg COD m(-3) d(-1)) and ammonia-N (0.08 kg m(-3) d(-1)) loading rates applied, resulting in ammonia-N removal ranging from 60 to 74%. The final effluent presented ammonia-N lower than 13 mg L(-1). Despite the presence of dissolved oxygen (DO) in the denitrification compartment, its performance was considered quite satisfactory and final nitrate concentrations were lower than 10 mg L(-1). The results indicate that methane was the main electron donor used for denitrification. Additionally, denitrification can probably be improved by avoiding high DO concentration in the denitrification compartment and by enhancing biogas transfer in the anoxic zone.

Removal of ammonium via simultaneous nitrification-denitrification nitrite-shortcut in a single packed-bed batch reactor

A polyurethane packed-bed-biofilm sequential batch reactor was fed with synthetic substrate simulating the composition of UASB reactor effluents. Two distinct ammonia nitrogen concentrations (125 and 250 mg l(-1)) were supplied during two sequential long-term experiments of 160 days each (320 total). Cycles of 24 h under intermittent aeration for periods of 1 h were applied, and ethanol was added as a carbon source at the beginning of each anoxic period. Nitrite was the main oxidized nitrogen compound which accumulated only during the aerated phases of the batch cycle. A consistent decrease of nitrite concentration started always immediately after the interruption of oxygen supply and addition of the electron donor. Removal to below detection limits of all nitrogen soluble forms was always observed at the end of the 24 h cycles for both initial concentrations. Polyurethane packed-bed matrices and ethanol amendments conferred high process stability. Microbial investigation by cloning suggested that nitrification was carried out by Nitrosomonas-like species whereas denitrification was mediated by unclassified species commonly observed in denitrifying environments. The packed-bed batch bioreactor favored the simultaneous colonization of distinct microbial groups within the immobilized microbial biomass. The biofilm was capable of actively oxidizing ammonium and denitrification at high ratios in intermittent intervals within 24 h cycles. (c) 2008 Elsevier Ltd. All rights reserved.

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.

BIOLOGICAL NITROGEN REMOVAL OVER NITRITATION/DENITRITATION USING PHENOL AS CARBON SOURCE

A laboratory scale activated sludge sequencing batch reactor was operated in order to obtain total removal of influent ammonia (200; 300 and 500 mg NH(3)-N.L(-1)) with sustained nitrite accumulation at the end of the aerobic stages with phenol (1,000 mg C(6)H(5)OH.L(-1)) as the carbon source for denitrifying microorganisms during the anoxic stages. Ammonia removal above 95% and ratios of (NO(2)(-)-N / (NO(2)(-)-N + NO(3)(-)-N)) ranging from 89 to 99% were obtained by controlling the dissolved oxygen concentration (1.0 mg O(2).L(-1)) and the pH value of 8.3 during the aerobic stages. Phenol proved to be an adequate source of carbon for nitrogen removal via nitrite with continuous feeding throughout part of the anoxic stage. Nitrite concentrations greater than 70.0 mg NO(2)(-)-N.L(-1) inhibited the biological denitritation process.

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.