983 resultados para processing efficiency proficiency


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The dairy industry is a global industry that provides significant nutritional benefit to many cultures. in australia the industry is especially important economically, being a large export earner, as well as a vital domestic sector. in recent years the sector has come under increased competitive pressure and has restructured to cope with the changes. the industry recently undertook an eco-efficiency project to investigate where business and environmental improvements might be found. the project involved collecting and collating previous project data and surveying 38 companies in different dairy operations, from market milk to dried products. after the survey, 10 sites in two states were visited to discuss eco-efficiency issues in detail with key players. From the surveys, visits and data compilation, a comprehensive manual was prepared to help interested companies find relevant eco-efficiency data easily and assist them in the implementation process. ten fact sheets were also produced covering the topics of water management, water recycling and re-use, refrigeration optimisation, boiler optimisation, biogas, the use of treated wastewater, yield optimisation and product recovery, optimisation of ciP systems, chemical use and membranes the project highlighted the large amount of technical and engineering expertise within the sector that could result in eco-efficiency outcomes and also identified the opportunities that exist for changes to occur in some operations to save energy, input raw materials and water.

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Tomato (Solanum lycopersicum) shows three growth habits: determinate, indeterminate and semi-determinate. These are controlled mainly by allelic variation in the SELF-PRUNING (SP) gene family, which also includes the florigen gene SINGLE FLOWER TRUSS (SFT). Determinate cultivars have synchronized flower and fruit production, which allows mechanical harvesting in the tomato processing industry, whereas indeterminate ones have more vegetative growth with continuous flower and fruit formation, being thus preferred for fresh market tomato production. The semi-determinate growth habit is poorly understood, although there are indications that it combines advantages of determinate and indeterminate growth. Here, we used near-isogenic lines (NILs) in the cultivar Micro-Tom (MT) with different growth habit to characterize semi-determinate growth and to determine its impact on developmental and productivity traits. We show that semi-determinate genotypes are equivalent to determinate ones with extended vegetative growth, which in turn impacts shoot height, number of leaves and either stem diameter or internode length. Semi-determinate plants also tend to increase the highly relevant agronomic parameter Brix×ripe yield (BRY). Water-use efficiency (WUE), evaluated either directly as dry mass produced per amount of water transpired or indirectly through C isotope discrimination, was higher in semi-determinate genotypes. We also provide evidence that the increases in BRY in semi-determinate genotypes are a consequence of an improved balance between vegetative and reproductive growth, a mechanism analogous to the conversion of the overly vegetative tall cereal varieties into well-balanced semi-dwarf ones used in the Green Revolution.

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This paper presents a rational approach to the design of a catamaran's hydrofoil applied within a modern context of multidisciplinary optimization. The approach used includes the use of response surfaces represented by neural networks and a distributed programming environment that increases the optimization speed. A rational approach to the problem simplifies the complex optimization model; when combined with the distributed dynamic training used for the response surfaces, this model increases the efficiency of the process. The results achieved using this approach have justified this publication.

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Background: Various neuroimaging studies, both structural and functional, have provided support for the proposal that a distributed brain network is likely to be the neural basis of intelligence. The theory of Distributed Intelligent Processing Systems (DIPS), first developed in the field of Artificial Intelligence, was proposed to adequately model distributed neural intelligent processing. In addition, the neural efficiency hypothesis suggests that individuals with higher intelligence display more focused cortical activation during cognitive performance, resulting in lower total brain activation when compared with individuals who have lower intelligence. This may be understood as a property of the DIPS. Methodology and Principal Findings: In our study, a new EEG brain mapping technique, based on the neural efficiency hypothesis and the notion of the brain as a Distributed Intelligence Processing System, was used to investigate the correlations between IQ evaluated with WAIS (Whechsler Adult Intelligence Scale) and WISC (Wechsler Intelligence Scale for Children), and the brain activity associated with visual and verbal processing, in order to test the validity of a distributed neural basis for intelligence. Conclusion: The present results support these claims and the neural efficiency hypothesis.

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This article presents an evaluation of the effects of the spouted bed design and operating conditions on system fluiddynamics and process performance during enteric coating of hard gelatine capsules. The design parameters studied were the column diameter (150 mm and 200 mm), the included angle of the conical base, gamma (60 degrees or 40 degrees) and the presence or absence of a Venturi inserted before the inlet air orifice. The process variables studied were the ratio between the feed flow rate of the coating suspension to the spouting gas flow rate (W(s)/W(g)), the mass of capsules loaded to the equipment (M(0)), and the ratio between the Spouting gas flow rate to the gas flow rate at minimum spouting condition (Q/Q(ms)). The response variables were the rate of increase of the capsules mass (K(1)), and the adhesion efficiency (eta). The linear regression equation for the dependent variable K, in terms of the independent variables adequately described the process with an r(2) value of 0.872. Analysis of variance (ANOVA) revealed that increasing of W(s)/W(g), Q/Q(ms) and gamma significantly increased the adhesion efficiency. Adhesion efficiencies higher than 90% were achieved by selecting precise coating conditions, indicating the feasibility of the process for coating of hard gelatine capsules. (C) 2008 Elsevier B.V. All rights reserved.

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This article presents an investigation of the potential of spray and spouted bed technology for the production of dried extracts of Rosmarinus officinalis Linne, popularly known as rosemary. The extractive solution was characterized by loss on drying, extractable matter and total phenolic and flavonoid compounds (chemical markers). The product was characterized by determination of loss on drying, size distribution, morphology, flow properties and thermal degradation and thermal behavior. The spray and spouted bed dryer performance were assessed through estimation of thermal efficiency, product accumulation and product recovery. The parameters studied were the inlet temperature of the spouting gas (80 and 150 degrees C) and the feed mass flow rate of concentrated extract relative to the evaporation capacity of the dryer, W-s/W-max (15 to 75%). The atomizing air flow rate was maintained at 20 l/min with a pressure of 196.1 kPa. The spouting gas flow rate used in the drying runs was 40% higher than the gas flow under the condition of minimum spouting. The spray drying gas flow rate was fixed at 0.0118 kg/s. Under the conditions studied, performance in the spray and spouted bed drying of rosemary extract was poor, causing high degradation of the marker compounds (mainly the phenolic compounds). Thus, process improvements are required before use on an industrial scale.

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Efficiency of presentation of a peptide epitope by a MHC class I molecule depends on two parameters: its binding to the MHC molecule and its generation by intracellular Ag processing. In contrast to the former parameter, the mechanisms underlying peptide selection in Ag processing are poorly understood. Peptide translocation by the TAP transporter is required for presentation of most epitopes and may modulate peptide supply to MHC class I molecules. To study the role of human TAP for peptide presentation by individual HLA class I molecules, we generated artificial neural networks capable of predicting the affinity of TAP for random sequence 9-mer peptides. Using neural network-based predictions of TAP affinity, we found that peptides eluted from three different HLA class I molecules had higher TAP affinities than control peptides with equal binding affinities for the same HLA class I molecules, suggesting that human TAP may contribute to epitope selection. In simulated TAP binding experiments with 408 HLA class I binding peptides, HLA class I molecules differed significantly with respect to TAP affinities of their ligands, As a result, some class I molecules, especially HLA-B27, may be particularly efficient in presentation of cytosolic peptides with low concentrations, while most class I molecules may predominantly present abundant cytosolic peptides.

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In this study we demonstrate a new in-fermenter chemical extraction procedure that degrades the cell wall of Escherichia coli and releases inclusion bodies (IBs) into the fermentation medium. We then prove that cross-flow microfiltration can be used to remove 91% of soluble contaminants from the released IBs. The extraction protocol, based on a combination of Triton X-100, EDTA, and intracellular T7 lysozyme, effectively released most of the intracellular soluble content without solubilising the IBs. Cross-flow microfiltration using a 0.2 mum ceramic membrane successfully recovered the granulocyte macrophagecolony stimulating factor (GM-CSF) IBs with removal of 91% of the soluble contaminants and virtually no loss of IBs to the permeate. The filtration efficiency, in terms of both flux and transmission, was significantly enhanced by infermenter Benzonase(R) digestion of nucleic acids following chemical extraction. Both the extraction and filtration methods exerted their efficacy directly on a crude fermentation broth, eliminating the need for cell recovery and re-suspension in buffer. The processes demonstrated here can all be performed using just a fermenter and a single cross-flow filtration unit, demonstrating a high level of process intensification. Furthermore, there is considerable scope to also use the microfiltration system to subsequently solubilise the IBs, to separate the denatured protein from cell debris, and to refold the protein using diafiltration. In this way refolded protein can potentially be obtained, in a relatively pure state, using only two unit operations. (C) 2004 Wiley Periodicals Inc.

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This work reports on the effect of initial substrate concentration on COD consumption, pH, and H(2) production during cassava processing wastewater fermentation by Clostridium acetobutylicum ATCC 824. Five initial COD wastewater concentrations, namely 5.0, 7.5, 10.7, 15.0, and 30.0 g/L, were used. The results showed that higher substrate concentrations (30.0 and 15.0 COD/L) led to lower H(2) yield as well as less efficient substrate conversion into H(2). On the other hand, initial COD concentrations of 10.7, 7.5 and 5 g/L furnished 1.34, 1.2 and 2.41 mol H(2)/mol glucose, with efficiency of glucose conversion into H(2) of 34, 30, and 60% (mol/mol), respectively. These results demonstrate that cassava processing wastewater, a highly polluting effluent, can be successfully employed as substrate for H(2) production by C acetobutylicum at lower COD concentrations. (C) 2011 Elsevier Ltd. All rights reserved.

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The settling characteristics of cell debris and inclusion bodies prior to, and following, fractionation in a disc-stack centrifuge were measured using Cumulative Sedimentation Analysis (CSA) and Centrifugal Disc photosedimentation (CDS). The impact of centrifuge feedrate and repeated homogenisation on both cell debris and inclusion body collection efficiency was investigated. Increasing the normalised centrifuge feedrate (Q/Sigma) from 1.32 x 10(-9) m s(-1) to 3.97 x 10(-9) m s(-1) leads to a 36% increase in inclusion body paste purity. Purity may also be improved by repeated homogenisation. Increasing the number of homogeniser passes results in smaller cell debris size whilst leaves inclusion body size unaltered. At a normalised centrifuge feedrate of 2.65 x 10(-9) m s(-1), increasing the number of homogeniser passes from two (2) to ten (10) improved overall inclusion body paste purity by 58%. Grade-efficiency curves for both the cell debris and inclusion bodies have also been generated in this study. The data are described using an equation developed by Mannweiler (1989) with parameters of k = 0.15-0.26 and n = 2.5-2.6 for inclusion bodies, and k = 0.12-0.14 and n = 2.0-2.2 for cell debris. This is the first accurate experimentally-determined grade efficiency curve for cell debris. Previous studies have simply estimated debris grade efficiency curves using an approximate debris size distribution and grade efficiency curves determined with 'ideal particles' (e.g. spherical PVA particles). The findings of this study may be used to simulate and optimise the centrifugal fractionation of inclusion bodies from cell debris.

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In this paper, we propose a method based on association rule-mining to enhance the diagnosis of medical images (mammograms). It combines low-level features automatically extracted from images and high-level knowledge from specialists to search for patterns. Our method analyzes medical images and automatically generates suggestions of diagnoses employing mining of association rules. The suggestions of diagnosis are used to accelerate the image analysis performed by specialists as well as to provide them an alternative to work on. The proposed method uses two new algorithms, PreSAGe and HiCARe. The PreSAGe algorithm combines, in a single step, feature selection and discretization, and reduces the mining complexity. Experiments performed on PreSAGe show that this algorithm is highly suitable to perform feature selection and discretization in medical images. HiCARe is a new associative classifier. The HiCARe algorithm has an important property that makes it unique: it assigns multiple keywords per image to suggest a diagnosis with high values of accuracy. Our method was applied to real datasets, and the results show high sensitivity (up to 95%) and accuracy (up to 92%), allowing us to claim that the use of association rules is a powerful means to assist in the diagnosing task.