Improved xylitol production in media containing phenolic aldehydes: application of response surface methodology for optimization and modeling of bioprocess

BACKGROUND: The combined effects of vanillin and syringaldehyde on xylitol production by Candida guilliermondii using response surface methodology (RSM) have been studied. A 2(2) full-factorial central composite design was employed for experimental design and analysis of the results. RESULTS: Maximum xylitol productivities (Q(p) = 0.74 g L(-1) h(-1)) and yields (Y(P/S) = 0.81 g g(-1)) can be attained by adding only vanillin at 2.0 g L(-1) to the fermentation medium. These data were closely correlated with the experimental results obtained (0.69 +/- 0.04 g L(-1) h(-1) and 0.77 +/- 0.01 g g(-1)) indicating a good agreement with the predicted value. C. guilliermondii was able to convert vanillin completely after 24 h of fermentation with 94% yield of vanillyl alcohol. CONCLUSIONS: The bioconversion of xylose into xylitol by C. guilliermondii is strongly dependent on the combination of aldehydes and phenolics in the fermentation medium. Vanillin is a source of phenolic compound able to improve xylitol production by yeast. The conversion of vanillin to alcohol vanilyl reveals the potential of this yeast for medium detoxification. (C) 2009 Society of Chemical Industry

A novel electrocatalyst support with proton conductive properties for polymer electrolyte membrane fuel cell applications

The objective of this study is to graft the Surface of carbon black, by chemically introducing polymeric chains (Nafion (R) like) with proton-conducting properties. This procedure aims for a better interaction of the proton-conducting phase with the metallic catalyst particles, as well as hinders posterior support particle agglomeration. Also loss of active surface call be prevented. The proton conduction between the active electrocatalyst site and the Nafion (R) ionomer membrane should be enhanced, thus diminishing the ohmic drop ill the polymer electrolyte membrane fuel cell (PEMFC). PtRu nanoparticles were supported on different carbon materials by the impregnation method and direct reduction with ethylene glycol and characterized using amongst others FTIR, XRD and TEM. The screen printing technique was used to produce membrane electrode assemblies (MEA) for single cell tests in H(2)/air(PEMFC) and methanol operation (DMFC). In the PEMFC experiments, PtRu supported on grafted carbon shows 550 mW cm(-2) gmetal(-1) power density, which represents at least 78% improvement in performance, compared to the power density of commercial PtRu/C ETEK. The DMFC results of the grafted electrocatalyst achieve around 100% improvement. The polarization Curves results clearly show that the main Cause of the observed effect is the reduction in ohmic drop, caused by the grafted polymer. (C) 2009 Elsevier B.V. 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.

Cellulosic Films Obtained from the Treatment of Sugarcane Bagasse Fibers with N-methylmorpholine-N-oxide (NMMO)

Ethanol/water organosolv pulping was used to obtain sugarcane bagasse pulp that was bleached with sodium chlorite. This bleached pulp was used to obtain cellulosic films that were further evaluated by Fourier transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), and scanning electron microscopy (SEM). A good film formation was observed when temperature of 74 degrees C and baths of distilled water were used, which after FTIR, TGA, and SEM analysis indicated no significant difference between the reaction times. The results showed this to be an interesting and promising process, combining the prerequisites for a more efficient utilization of agro-industrial residues.

Role of brain nitric oxide in the thermoregulation of broiler chicks

Nitric oxide (NO) plays a key role in body temperature (Tb) regulation of mammals, acting on the brain to stimulate heat loss. Regarding birds, the putative participation of NO in the maintenance of Tb in thermoneutrality or during heat stress and the site of its action (periphery or brain) is unknown. Thus, we tested if NO participates in the maintenance of chicks` Tb in those conditions. We investigated the effect of intramuscular (im; 25, 50, 100 mg/kg) or intracerebroventricular (icv; 22.5, 45, 90, 180 mu g/animal) injections of the non selective NO synthase inhibitor L-NAME on Tb of 5-day-old chicks at thermoneutral zone (TNZ; 31-32 degrees C) and under heat stress (37 degrees C for 5-6 h). We also verified plasma and diencephalic nitrite/nitrate levels in non-injected chicks under both conditions. At TNZ, 100 mg/kg (im) or 45,90,180 mu g (icv) of L-NAME decreased Tb. A significant correlation between Tb and diencephalic, but not plasma, nitrite/nitrate levels was observed. Heat stress-induced hyperthermia was inhibited by all tested doses of L-NAME (im and icv). Tb was correlated neither with plasma nor with diencephalic nitrite/nitrate levels during heat stress. These results indicate the involvement of brain NO in the maintenance of Tb of chicks, an opposite action of that observed in mammals, and may modulate hyperthermia. (C) 2009 Elsevier Inc. All rights reserved.

Assessment of Depressive Symptoms and Cognitive Impairment in Elders From Rural Areas of the Brazilian State of Rio Grande do Sul

The main objective of this study was to examine the relationships among demographic characteristics, depressive symptoms, and cognitive impairment in oldest-old elders from rural areas of the Brazilian State of Rio Grande do Sul. A cross-sectional, descriptive correlational design was used to conduct the study. 137 Brazilian elders age 80 years or over. A target population data form, a county data form, a demographic questionnaire, the Mini-Mental State Examination, and the Depressive Cognition Scale were used to collect the data. A significant difference was found between males and females in regard to cognitive impairment. In addition, educational level and depressive symptoms were correlated with cognitive impairment. Depressive symptoms were a weak but significant predictor of cognitive impairment after controlling for the effect of age, gender, and educational level of the oldest-old elders. The findings need to be interpreted cautiously since the sample scored above the cutoff points for cognitive impairment, and had low scores on depressive symptoms. Despite several limitations, findings from this study can be a foundation for further studies, and well-designed correlational or experimental approaches, are warranted.

Power Transformer Differential Protection Based on Clarke`s Transform and Fuzzy Systems

The power transformer is a piece of electrical equipment that needs continuous monitoring and fast protection since it is very expensive and an essential element for a power system to perform effectively. The most common protection technique used is the percentage differential logic, which provides discrimination between an internal fault and different operating conditions. Unfortunately, there are some operating conditions of power transformers that can affect the protection behavior and the power system stability. This paper proposes the development of a new algorithm to improve the differential protection performance by using fuzzy logic and Clarke`s transform. An electrical power system was modeled using Alternative Transients Program (ATP) software to obtain the operational conditions and fault situations needed to test the algorithm developed. The results were compared to a commercial relay for validation, showing the advantages of the new method.

Combined heuristic with fuzzy system to transmission system expansion planning

A heuristic algorithm that employs fuzzy logic is proposed to the power system transmission expansion planning problem. The algorithm is based on the divide to conquer strategy, which is controlled by the fuzzy system. The algorithm provides high quality solutions with the use of fuzzy decision making, which is based on nondeterministic criteria to guide the search. The fuzzy system provides a self-adjusting mechanism that eliminates the manual adjustment of parameters to each system being solved. (C) 2010 Elsevier B.V. All rights reserved.

Digital frequency relaying based on the modified least mean square method

This research presents a method for frequency estimation in power systems using an adaptive filter based on the Least Mean Square Algorithm (LMS). In order to analyze a power system, three-phase voltages were converted into a complex signal applying the alpha beta-transform and the results were used in an adaptive filtering algorithm. Although the use of the complex LMS algorithm is described in the literature, this paper deals with some practical aspects of the algorithm implementation. In order to reduce computing time, a coefficient generator was implemented. For the algorithm validation, a computing simulation of a power system was carried Out using the ATP software. Many different situations were Simulated for the performance analysis of the proposed methodology. The results were compared to a commercial relay for validation, showing the advantages of the new method. (C) 2009 Elsevier Ltd. All rights reserved.

Combined solution for fault location in three-terminal lines based on wavelet transforms

This work presents the study and development of a combined fault location scheme for three-terminal transmission lines using wavelet transforms (WTs). The methodology is based on the low- and high-frequency components of the transient signals originated from fault situations registered in the terminals of a system. By processing these signals and using the WT, it is possible to determine the time of travelling waves of voltages and/or currents from the fault point to the terminals, as well as estimate the fundamental frequency components. A new approach presents a reliable and accurate fault location scheme combining some different solutions. The main idea is to have a decision routine in order to select which method should be used in each situation presented to the algorithm. The combined algorithm was tested for different fault conditions by simulations using the ATP (Alternative Transients Program) software. The results obtained are promising and demonstrate a highly satisfactory degree of accuracy and reliability of the proposed method.

Power quality analysis applying a hybrid methodology with wavelet transforms and neural networks

A hybrid system to automatically detect, locate and classify disturbances affecting power quality in an electrical power system is presented in this paper. The disturbances characterized are events from an actual power distribution system simulated by the ATP (Alternative Transients Program) software. The hybrid approach introduced consists of two stages. In the first stage, the wavelet transform (WT) is used to detect disturbances in the system and to locate the time of their occurrence. When such an event is flagged, the second stage is triggered and various artificial neural networks (ANNs) are applied to classify the data measured during the disturbance(s). A computational logic using WTs and ANNs together with a graphical user interface (GU) between the algorithm and its end user is then implemented. The results obtained so far are promising and suggest that this approach could lead to a useful application in an actual distribution system. (C) 2009 Elsevier Ltd. All rights reserved.

Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop

This paper describes the modeling of a weed infestation risk inference system that implements a collaborative inference scheme based on rules extracted from two Bayesian network classifiers. The first Bayesian classifier infers a categorical variable value for the weed-crop competitiveness using as input categorical variables for the total density of weeds and corresponding proportions of narrow and broad-leaved weeds. The inferred categorical variable values for the weed-crop competitiveness along with three other categorical variables extracted from estimated maps for the weed seed production and weed coverage are then used as input for a second Bayesian network classifier to infer categorical variables values for the risk of infestation. Weed biomass and yield loss data samples are used to learn the probability relationship among the nodes of the first and second Bayesian classifiers in a supervised fashion, respectively. For comparison purposes, two types of Bayesian network structures are considered, namely an expert-based Bayesian classifier and a naive Bayes classifier. The inference system focused on the knowledge interpretation by translating a Bayesian classifier into a set of classification rules. The results obtained for the risk inference in a corn-crop field are presented and discussed. (C) 2009 Elsevier Ltd. All rights reserved.

A classification methodology for the risk of weed infestation using fuzzy logic

Despite modern weed control practices, weeds continue to be a threat to agricultural production. Considering the variability of weeds, a classification methodology for the risk of infestation in agricultural zones using fuzzy logic is proposed. The inputs for the classification are attributes extracted from estimated maps for weed seed production and weed coverage using kriging and map analysis and from the percentage of surface infested by grass weeds, in order to account for the presence of weed species with a high rate of development and proliferation. The output for the classification predicts the risk of infestation of regions of the field for the next crop. The risk classification methodology described in this paper integrates analysis techniques which may help to reduce costs and improve weed control practices. Results for the risk classification of the infestation in a maize crop field are presented. To illustrate the effectiveness of the proposed system, the risk of infestation over the entire field is checked against the yield loss map estimated by kriging and also with the average yield loss estimated from a hyperbolic model.

Effect of bituminous impregnation on nonwoven geotextiles tensile and permeability properties

Geosynthetics interlayer systems are effective techniques to control reflective cracking in damaged pavements. It comprises the inclusion of nonwoven geotextiles between the damaged layer and the new overlay of the pavement to reduce the propagation of cracks and to extend pavement life. However, the success of this technique depends directly on the understanding of the geotextile`s behavior when impregnated with asphalt This paper evaluates different nonwoven geotextiles frequently used in anti-reflective cracking systems, focusing on initial stiffness gain and permeability reduction after asphalt impregnation. Fresh and impregnated samples of polyester and polypropylene nonwoven geotextiles were tested. Cationic rapid setting emulsified asphalt was used as asphalt binder. Wide-width tensile tests were carried out based on the specification of ABNT - NBR 12824 (1993). Water vapor transmission tests were conducted according to ASTM E 96M (2005). Results of tensile tests on impregnated geotextiles showed a significant increase on tensile strength values, probably due to the inter contact of the fibers. Results also showed high increase in strength values at strain levels less than 0.05% and decrease on stiffness gains with increase of strains. Water vapor transmission tests demonstrated that cationic asphalt emulsion applied on nonwoven geotextiles allows a drastic reduction in permeability values to turn nonwoven geotextiles into a low permeability barrier. (C) 2010 Elsevier Ltd. All rights reserved.

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.