112 research outputs found

    Determination of sodium fatty acid in soap Formulation Using Fourier Transform Infrared (FTIR) spectroscopy and multivariate calibrations.

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    Fourier Transform Infrared (FTIR) spectroscopy using an attenuated total reflectance (ATR) accessory has been investigated as a method for the determination of sodium-fatty acid (sodium-FA) in soap formulations. Multivariate calibrations namely partial least squares regression (PLS) and principle component regression (PCR) were developed for the prediction of sodium-FA using spectral ranges on the basis of relevant IR absorption bands related to sodium-FA. The sodium-FA content in soap formulations was predicted accurately at wavenumbers of 1,570–1,550 cm−1, which is specific for RCOO− Na+ vibration. The PLS method was found to be a consistently better predictor when both PLS and principal component regression (PCR) analyses were used for quantification of sodium-FA. Furthermore, FTIR spectroscopy can be an alternative technique to American oil Chemist Society methods which use a titrimetric technique because FTIR offers rapid, easy sample preparation and is friendly to the environment

    Asymmetry of Early Endosome Distribution in C. elegans Embryos

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    development, we examined the distribution and dynamics of early endosomes (EEs) in embryos.EEs are primarily found at the cell periphery with an initially uniform distribution after fertilization. Strikingly, we find that during the first cell cycle, EEA-1 positive EEs become enriched at the anterior cortex. In contrast, the Golgi compartment shows no asymmetry in distribution. Asymmetric enrichment of EEs depends on acto-myosin contractility and embryonic PAR polarity. In addition to their localization at the cortex, EEs are also found around the centrosome. These EEs move rapidly (1.3um/s) from the cortex directly to the centrosome, a speed comparable to that of the minus end directed motor dynein.We speculate that the asymmetry of early endosomes might play a role in cell asymmetries or fate decisions

    Quantitative monitoring of an activated sludge reactor using on-line UV-visible and near infrared spectroscopy

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    The performance of an activated sludge reactor can be significantly enhanced through use of continuous and real-time process-state monitoring, which avoids the need to sample for off-line analysis and to use chemicals. Despite the complexity associated with wastewater treatment systems, spectroscopic methods coupled with chemometric tools have been shown to be powerful tools for bioprocess monitoring and control. Once implemented and optimized, these methods are fast, nondestructive, user friendly, and most importantly, they can be implemented in situ, permitting rapid inference of the process state at any moment. In this work, UV-visible and NIR spectroscopy were used to monitor an activated sludge reactor using in situ immersion probes connected to the respective analyzers by optical fibers. During the monitoring period, disturbances to the biological system were induced to test the ability of each spectroscopic method to detect the changes in the system. Calibration models based on partial least squares (PLS) regression were developed for three key process parameters, namely chemical oxygen demand (COD), nitrate concentration (N-NO3−), and total suspended solids (TSS). For NIR, the best results were achieved for TSS, with a relative error of 14.1% and a correlation coefficient of 0.91. The UV-visible technique gave similar results for the three parameters: an error of ~25% and correlation coefficients of ~0.82 for COD and TSS and 0.87 for N-NO3−. The results obtained demonstrate that both techniques are suitable for consideration as alternative methods for monitoring and controlling wastewater treatment processes, presenting clear advantages when compared with the reference methods for wastewater treatment process qualification.Fundação para a Ciência e Tecnologia (FCT) - PPCDT/AMB/60141/2004, bolsa de doutoramento SFRH/BD/32614/200

    Hyperspectral Sensing Techniques Applied to Bio-masses Characterization: The Olive Husk Case

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    Olive husk (OH) quality, in respect of constituting particles characteristics (olive stones and pulp residues as result after pressing), represents an important issue. OH particles size class distribution and composition play, in fact, an important role for OH utilization as: organic amendment, bio-mass, food ingredient, plastic filler, abrasive, raw material in the cosmetic sector, dietary animal supplementation, etc. . OH is characterised by a strong variability according to olive characteristics and olive oil production process. Actually it does not exist any strategy able to quantify OH chemical-physical attributes versus its correct utilisation adopting simple, efficient and low costs analytical tools. Furthermore the possibility to perform its continuous monitoring, without any samples collection and analysis at laboratory scale, could strongly enhance OH utilization, with a great economic and environmental benefits. In this paper an analytical approach, based on HyperSpectral Imaging (HSI) is presented. HSI allows to perform, also on-line, a full quantification of OH characteristics in order to qualify this product for its further re-use, with particular reference as bio-mass. HSI was applied to different samples of OH, characterized by different moisture, different residual pulp content and different size class distributions. Results are presented and critically evaluated. © 2011 IFIP International Federation for Information Processing

    Genome-wide analysis of Sphingomonas wittichii RW1 behaviour during inoculation and growth in contaminated sand.

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    The efficacy of inoculation of single pure bacterial cultures into complex microbiomes, for example, in order to achieve increased pollutant degradation rates in contaminated material (that is, bioaugmentation), has been frustrated by insufficient knowledge on the behaviour of the inoculated bacteria under the specific abiotic and biotic boundary conditions. Here we present a comprehensive analysis of genome-wide gene expression of the bacterium Sphingomonas wittichii RW1 in contaminated non-sterile sand, compared with regular suspended batch growth in liquid culture. RW1 is a well-known bacterium capable of mineralizing dibenzodioxins and dibenzofurans. We tested the reactions of the cells both during the immediate transition phase from liquid culture to sand with or without dibenzofuran, as well as during growth and stationary phase in sand. Cells during transition show stationary phase characteristics, evidence for stress and for nutrient scavenging, and adjust their primary metabolism if they were not precultured on the same contaminant as found in the soil. Cells growing and surviving in sand degrade dibenzofuran but display a very different transcriptome signature as in liquid or in liquid culture exposed to chemicals inducing drought stress, and we obtain evidence for numerous 'soil-specific' expressed genes. Studies focusing on inoculation efficacy should test behaviour under conditions as closely as possible mimicking the intended microbiome conditions

    Membrane Protein Location-Dependent Regulation by PI3K (III) and Rabenosyn-5 in Drosophila Wing Cells

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    The class III phosphatidylinositol-3 kinase (PI3K (III)) regulates intracellular vesicular transport at multiple steps through the production of phosphatidylinositol-3-phosphate (PI(3)P). While the localization of proteins at distinct membrane domains are likely regulated in different ways, the roles of PI3K (III) and its effectors have not been extensively investigated in a polarized cell during tissue development. In this study, we examined in vivo functions of PI3K (III) and its effector candidate Rabenosyn-5 (Rbsn-5) in Drosophila wing primordial cells, which are polarized along the apical-basal axis. Knockdown of the PI3K (III) subunit Vps15 resulted in an accumulation of the apical junctional proteins DE-cadherin and Flamingo and also the basal membrane protein β-integrin in intracellular vesicles. By contrast, knockdown of PI3K (III) increased lateral membrane-localized Fasciclin III (Fas III). Importantly, loss-of-function mutation of Rbsn-5 recapitulated the aberrant localization phenotypes of β-integrin and Fas III, but not those of DE-cadherin and Flamingo. These results suggest that PI3K (III) differentially regulates localization of proteins at distinct membrane domains and that Rbsn-5 mediates only a part of the PI3K (III)-dependent processes

    Systolic peak detection in acceleration photoplethysmograms measured from emergency responders in tropical conditions

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    Photoplethysmogram (PPG) monitoring is not only essential for critically ill patients in hospitals or at home, but also for those undergoing exercise testing. However, processing PPG signals measured after exercise is challenging, especially if the environment is hot and humid. In this paper, we propose a novel algorithm that can detect systolic peaks under challenging conditions, as in the case of emergency responders in tropical conditions. Accurate systolic-peak detection is an important first step for the analysis of heart rate variability. Algorithms based on local maxima-minima, first-derivative, and slope sum are evaluated, and a new algorithm is introduced to improve the detection rate. With 40 healthy subjects, the new algorithm demonstrates the highest overall detection accuracy (99.84% sensitivity, 99.89% positive predictivity). Existing algorithms, such as Billauer's, Li's and Zong's, have comparable although lower accuracy. However, the proposed algorithm presents an advantage for real-time applications by avoiding human intervention in threshold determination. For best performance, we show that a combination of two event-related moving averages with an offset threshold has an advantage in detecting systolic peaks, even in heat-stressed PPG signals.Mohamed Elgendi, Ian Norton, Matt Brearley, Derek Abbott, Dale Schuurman

    Classification of Camellia (Theaceae) Species Using Leaf Architecture Variations and Pattern Recognition Techniques

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    Leaf characters have been successfully utilized to classify Camellia (Theaceae) species; however, leaf characters combined with supervised pattern recognition techniques have not been previously explored. We present results of using leaf morphological and venation characters of 93 species from five sections of genus Camellia to assess the effectiveness of several supervised pattern recognition techniques for classifications and compare their accuracy. Clustering approach, Learning Vector Quantization neural network (LVQ-ANN), Dynamic Architecture for Artificial Neural Networks (DAN2), and C-support vector machines (SVM) are used to discriminate 93 species from five sections of genus Camellia (11 in sect. Furfuracea, 16 in sect. Paracamellia, 12 in sect. Tuberculata, 34 in sect. Camellia, and 20 in sect. Theopsis). DAN2 and SVM show excellent classification results for genus Camellia with DAN2's accuracy of 97.92% and 91.11% for training and testing data sets respectively. The RBF-SVM results of 97.92% and 97.78% for training and testing offer the best classification accuracy. A hierarchical dendrogram based on leaf architecture data has confirmed the morphological classification of the five sections as previously proposed. The overall results suggest that leaf architecture-based data analysis using supervised pattern recognition techniques, especially DAN2 and SVM discrimination methods, is excellent for identification of Camellia species
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