Optimal fermentation conditions for maximizing the ethanol production by Kluyveromyces fragilis from cheese whey powder

Cheese whey powder (CWP) is an attractive raw material for ethanol production since it is a dried and concentrated form of CW and contains lactose in addition to nitrogen, phosphate and other essential nutrients. In the present work, deproteinized CWP was utilized as fermentation medium for ethanol production by Kluyveromyces fragilis. The individual and combined effects of initial lactose concentration (50-150 kg m(-3)), temperature (25-35 degrees C) and inoculum concentration (1-3 kg m(-3)) were investigated through a 2(3) full-factorial central composite design, and the optimal conditions for maximizing the ethanol production were determined. According to the statistical analysis, in the studied range of values, only the initial lactose concentration had a significant effect on ethanol production, resulting in higher product formation as the initial substrate concentration was increased. Assays with initial lactose concentration varying from 150 to 250 kg m(-3) were thus performed and revealed that the use of 200 kg m(-3) initial lactose concentration, inoculum concentration of 1 kg m(-3) and temperature of 35 degrees C were the best conditions for maximizing the ethanol production from CWP solution. Under these conditions, 80.95 kg m(-3) of ethanol was obtained after 44 h of fermentation. (C) 2011 Elsevier Ltd. 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.

Search for optimum conditions of sugarcane bagasse hemicellulose extraction

A process has been elaborated for one-step low lignin content sugarcane bagasse hemicellulose extraction using alkaline solution of hydrogen peroxide. To maximize the hemicellulose yields several extraction conditions were examined applying the 2(4) factorial design: H(2)O(2) concentration from 2 to 6% (w/v), reaction time from 4 to 16 h, temperature from 20 to 60 degrees C, and magnesium sulfate absence or presence (0.5%, w/v). This approach allowed selection of conditions for the extraction of low and high lignin content hemicellulose. At midpoint the yield of hemicellulose was 94.5% with more than 88% of lignin removed. Lignin removal is suppressed at low extraction temperatures and in the absence of magnesium sulfate. Hemicellulose in 86% yield with low lignin content (5.9%) was obtained with 6% H(2)O(2) treatment for 4 h and 20 degrees C. This hemicellulose is much lighter in color than samples obtained at the midpoint condition and was found suitable for subsequent enzymatic hydrolysis. (C) 2009 Elsevier B.V. All rights reserved.

High-yield kraft pulping of Eucalyptus grandis Hill ex Maiden biotreated by Ceriporiopsis subvermispora under two different culture conditions

In the present study, it was evaluated how two different culture conditions for the biotreatment of Eucalyptus grandis by Ceriporiopsis subvermispora affect a subsequent high-yield kraft pulping process. Under the varied culture conditions investigated, different extracellular enzyme activities were observed. Manganese-peroxidase (MnP) secretion was 3.7 times higher in cultures supplemented with glucose plus corn-steep liquor (glucose/CSL) as compared to non-supplemented (NS) cultures. The biotreated samples underwent diverse levels of wood component degradation as losses of weight and lignin were increased in glucose/CSL cultures. Mass balances for lignin removal during kraft pulping showed that delignification was facilitated when both biotreated wood samples were cooked. Delignification efficiency did not correlate positively with MnP levels in the cultures. On the other hand, biopulps from NS and glucose/CSL cultures saved 27% and 38% beating time to achieve 288 Schopper-Riegler freeness during refining, respectively. Biopulps disposed of decreased tensile and tear resistances, thus easier refining of the biokraft pulps seems to be a consequence of less resistant fiber walls. Improved beatability of biopulps was tentatively related to short fibers and fines formation during refining. We suggest that to some extent polysaccharide depolymerization occurred during the biotreatment, which also resulted in diminished pulp yields in the case of glucose/CSL cultures.

Laboratory and mill scale evaluation of biopulping of Eucalyptus grandis Hill ex Maiden with Phanerochaete chrysosporium RP-78 under non-aseptic conditions

Biopulping of Eucalyptus grandis wood chips with Phanerochaete chrysosporium RP-78 was evaluated under non-aseptic conditions in laboratory and mill wood-yard. The ability of P. chrysosporium to compete with indigenous fungi present in fresh wood chips was notorious under controlled laboratory experiments. A subsequent step involved an industrial test performed with 10-ton of fresh wood chips inoculated and maintained at 37 +/- 38 degrees C for 39 days in a biopulping pilot plant. Biotreated wood chips were pulped in a chemithermomechanical pulping mill. Net energy consumption during refining was 745 kWh ton(-1) and 610 kWh ton(-1) of processed pulp for control and biotreated wood chips, respectively. Accordingly, 18.5% net energy saving could be achieved. Biopulps contained lower shive content and had improved strength properties compared to control pulps. Tensile index improved from 25 +/- 1 N m g(-1) to 33.6 +/- 0.5 N m g(-1) and delamination strength from 217 +/- 19 kPa to 295 +/- 30 kPa.

Dendritic Arm Spacing Affecting Mechanical Properties and Wear Behavior of Al-Sn and Al-Si Alloys Directionally Solidified under Unsteady-State Conditions

Alloys of Al-Sn and Al-Si are widely used in tribological applications such as cylinder liners and journal bearings. Studies of the influence of the as-cast microstructures of these alloys on the final mechanical properties and wear resistance can be very useful for planning solidification conditions in order to permit a desired level of final properties to be achieved. The aim of the present study was to contribute to a better understanding about the relationship between the scale of the dendritic network and the corresponding mechanical properties and wear behavior. The Al-Sn (15 and 20 wt pct Sn) and Al-Si (3 and 5 wt pct Si) alloys were directionally solidified under unsteady-state heat flow conditions in water-cooled molds in order to permit samples with a wide range of dendritic spacings to be obtained. These samples were subjected to tensile and wear tests, and experimental quantitative expressions correlating the ultimate tensile strength (UTS), yield tensile strength, elongation, and wear volume to the primary dendritic arm spacing (DAS) have been determined. The wear resistance was shown to be significantly affected by the scale of primary dendrite arm spacing. For Al-Si alloys, the refinement of the dendritic array improved the wear resistance, while for the Al-Sn alloys, an opposite effect was observed, i.e., the increase in primary dendrite arm spacing improved the wear resistance. The effect of inverse segregation, which is observed for Al-Sn alloys, on the wear resistance is also discussed.

Influence of the slice position on chloride migration tests for concrete in marine conditions

Chloride migration tests are used to measure the concrete capacity to inhibit chloride attack. Many researchers carry out this test in a slice of concrete extracted from the central part of cylindrical specimens, discarding about 75% of the concrete used to mold the specimens. This fact generated the question: would it be possible to extract more slices from a same specimen without losing the confidence in the results? The main purpose of this work is to answer this question. Moreover, another aim of this study was to show the difference of chloride penetration between finished faces and the formwork surfaces of concrete beams and slabs. The results indicated that it is possible to use more slices of a single specimen for a chloride migration test. Moreover, it was demonstrated that there is a significant difference of chloride penetration between the finished surface and the formwork surface of the specimens. (C) 2008 Elsevier Ltd. All rights reserved.

Collaborative e-learning and Learning Objects

The Learning Object (OA) is any digital resource that can be reused to support learning with specific functions and objectives. The OA specifications are commonly offered in SCORM model without considering activities in groups. This deficiency was overcome by the solution presented in this paper. This work specified OA for e-learning activities in groups based on SCORM model. This solution allows the creation of dynamic objects which include content and software resources for the collaborative learning processes. That results in a generalization of the OA definition, and in a contribution with e-learning specifications.

Learning Profile Identification Based on the Analysis of the User Context of Interaction

One of the e-learning environment goal is to attend the individual needs of students during the learning process. The adaptation of contents, activities and tools into different visualization or in a variety of content types is an important feature of this environment, bringing to the user the sensation that there are suitable workplaces to his profile in the same system. Nevertheless, it is important the investigation of student behaviour aspects, considering the context where the interaction happens, to achieve an efficient personalization process. The paper goal is to present an approach to identify the student learning profile analyzing the context of interaction. Besides this, the learning profile could be analyzed in different dimensions allows the system to deal with the different focus of the learning.

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.

Accelerating autonomous learning by using heuristic selection of actions

This paper investigates how to make improved action selection for online policy learning in robotic scenarios using reinforcement learning (RL) algorithms. Since finding control policies using any RL algorithm can be very time consuming, we propose to combine RL algorithms with heuristic functions for selecting promising actions during the learning process. With this aim, we investigate the use of heuristics for increasing the rate of convergence of RL algorithms and contribute with a new learning algorithm, Heuristically Accelerated Q-learning (HAQL), which incorporates heuristics for action selection to the Q-Learning algorithm. Experimental results on robot navigation show that the use of even very simple heuristic functions results in significant performance enhancement of the learning rate.

Unsaturated Infinite Slope Stability Considering Surface Flux Conditions

A slope stability model is derived for an infinite slope subjected to unsaturated infiltration flow above a phreatic surface. Closed form steady state solutions are derived for the matric suction and degree of saturation profiles. Soil unit weight, consistent with the degree of saturation profile, is also directly calculated and introduced into the analyzes, resulting in closed-form solutions for typical soil parameters and an infinite series solution for arbitrary soil parameters. The solutions are coupled with the infinite slope stability equations to establish a fully realized safety factor function. In general, consideration of soil suction results in higher factor of safety. The increase in shear strength due to the inclusion of soil suction is analogous to making an addition to the cohesion, which, of course, increases the factor of safety against sliding. However, for cohesive soils, the results show lower safety factors for slip surfaces approaching the phreatic surface compared to those produced by common safety factor calculations. The lower factor of safety is due to the increased soil unit weight considered in the matric suction model but not usually accounted for in practice wherein the soil is treated as dry above the phreatic surface. The developed model is verified with a published case study, correctly predicting stability under dry conditions and correctly predicting failure for a particular storm.

Learning about knowledge management for improving environmental impact assessment in a government agency: The Western Australian experience

How does knowledge management (KM) by a government agency responsible for environmental impact assessment (EIA) potentially contribute to better environmental assessment and management practice? Staff members at government agencies in charge of the EIA process are knowledge workers who perform judgement-oriented tasks highly reliant on individual expertise, but also grounded on the agency`s knowledge accumulated over the years. Part of an agency`s knowledge can be codified and stored in an organizational memory, but is subject to decay or loss if not properly managed. The EIA agency operating in Western Australia was used as a case study. Its KM initiatives were reviewed, knowledge repositories were identified and staff surveyed to gauge the utilisation and effectiveness of such repositories in enabling them to perform EIA tasks. Key elements of KM are the preparation of substantive guidance and spatial information management. It was found that treatment of cumulative impacts on the environment is very limited and information derived from project follow-up is not properly captured and stored, thus not used to create new knowledge and to improve practice and effectiveness. Other opportunities for improving organizational learning include the use of after-action reviews. The learning about knowledge management in EIA practice gained from Western Australian experience should be of value to agencies worldwide seeking to understand where best to direct their resources for their own knowledge repositories and environmental management practice. (C) 2011 Elsevier Ltd. All rights reserved.

Optimal conditions for the wetting balance test

Wetting balance tests of copper sheets submerged in tin solder baths were carried out in a completely automatic wetting balance. Wetting curves were examined for three different values of sheet thickness and four different solder bath temperatures. Most of the wetting curves showed a distorted shape relative to that of a standard curve, preventing calculation of important wetting parameters, such as the wetting rate and the wetting force. The wetting tests showed that the distortion increased for a thicker sheet thickness and a lower solder bath temperature, being the result of solder bath solidification around the submerged sheet substrate. (C) 2008 Elsevier B.V. All rights reserved.

Effect of the processing conditions and the addition of trans-polyoctenylene rubber on the properties of natural rubber/styrene-butadiene rubber blends

In this study, the influence of the processing conditions and the addition of trans-polyoctenylene rubber (TOR) on Mooney viscosity, tensile properties, hardness, tearing resistance, and resilience of natural rubber/styrene-butadiene rubber blends was investigated. The results obtained are explained in light of dynamic mechanical and morphological analyses. Increasing processing time produced a finer blend morphology, which resulted in an improvement in the mechanical properties. The addition of TOR involved an increase in hardness, a decrease in tear resistance, and no effect on the resilience. It resulted in a large decrease in the Mooney viscosity and a slight decrease in the tensile properties if the components of the compounds were not properly mixed. The results indicate that TOR acted more as a plasticizer than a compatibilizer. (c) 2008 Wiley Periodicals, Inc.