983 resultados para Extraction techniques


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The current study aims to verify the best method for a rapid and efficient extraction of flavonoids from Alpinia zerumbet. Dried leaves were extracted using distillated water and ethanol 70% by extraction methods of shaking maceration, ultrasonic, microwave and stirring. By the application of TLC and reversed-phase HPLC techniques the rutin and kaempferol-3-O-glucuronide were detected. Ethanol 70% was more efficient for flavonoids extraction than water. No significant yielding variation was verified for ultrasonic, microwave and stirring methods using ethanol 70% (11 to 14%). The relative concentration of rutin and kaempferol-3-O-glucuronide, respectively, was higher by ultrasonic (1.5 and 5.62 mg g-1 dried leaves, respectively) and by microwave (1.0 and 6.64 mg g-1 dried leaves) methods using ethanol. Rapid and simplified extraction proceeding optimize phytochemical work and acquisition of secondary metabolites.

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La documentation des programmes aide les développeurs à mieux comprendre le code source pendant les tâches de maintenance. Toutefois, la documentation n’est pas toujours disponible ou elle peut être de mauvaise qualité. Le recours à la redocumentation s’avère ainsi nécessaire. Dans ce contexte, nous proposons de faire la redocumentation en générant des commentaires par application de techniques de résumé par extraction. Pour mener à bien cette tâche, nous avons commencé par faire une étude empirique pour étudier les aspects quantitatifs et qualitatifs des commentaires. En particulier, nous nous sommes intéressés à l’étude de la distribution des commentaires par rapport aux différents types d’instructions et à la fréquence de documentation de chaque type. Aussi, nous avons proposé une taxonomie de commentaires pour classer les commentaires selon leur contenu et leur qualité. Suite aux résultats de l’étude empirique, nous avons décidé de résumer les classes Java par extraction des commentaires des méthodes/constructeurs. Nous avons défini plusieurs heuristiques pour déterminer les commentaires les plus pertinents à l’extraction. Ensuite, nous avons appliqué ces heuristiques sur les classes Java de trois projets pour en générer les résumés. Enfin, nous avons comparé les résumés produits (les commentaires produits) à des résumés références (les commentaires originaux) en utilisant la métrique ROUGE.

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Cerebral glioma is the most prevalent primary brain tumor, which are classified broadly into low and high grades according to the degree of malignancy. High grade gliomas are highly malignant which possess a poor prognosis, and the patients survive less than eighteen months after diagnosis. Low grade gliomas are slow growing, least malignant and has better response to therapy. To date, histological grading is used as the standard technique for diagnosis, treatment planning and survival prediction. The main objective of this thesis is to propose novel methods for automatic extraction of low and high grade glioma and other brain tissues, grade detection techniques for glioma using conventional magnetic resonance imaging (MRI) modalities and 3D modelling of glioma from segmented tumor slices in order to assess the growth rate of tumors. Two new methods are developed for extracting tumor regions, of which the second method, named as Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA) can also extract white matter and grey matter from T1 FLAIR an T2 weighted images. The methods were validated with manual Ground truth images, which showed promising results. The developed methods were compared with widely used Fuzzy c-means clustering technique and the robustness of the algorithm with respect to noise is also checked for different noise levels. Image texture can provide significant information on the (ab)normality of tissue, and this thesis expands this idea to tumour texture grading and detection. Based on the thresholds of discriminant first order and gray level cooccurrence matrix based second order statistical features three feature sets were formulated and a decision system was developed for grade detection of glioma from conventional T2 weighted MRI modality.The quantitative performance analysis using ROC curve showed 99.03% accuracy for distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant glioma. The developed brain texture analysis techniques can improve the physician’s ability to detect and analyse pathologies leading to a more reliable diagnosis and treatment of disease. The segmented tumors were also used for volumetric modelling of tumors which can provide an idea of the growth rate of tumor; this can be used for assessing response to therapy and patient prognosis.

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In recent years, advanced metering infrastructure (AMI) has been the main research focus due to the traditional power grid has been restricted to meet development requirements. There has been an ongoing effort to increase the number of AMI devices that provide real-time data readings to improve system observability. Deployed AMI across distribution secondary networks provides load and consumption information for individual households which can improve grid management. Significant upgrade costs associated with retrofitting existing meters with network-capable sensing can be made more economical by using image processing methods to extract usage information from images of the existing meters. This thesis presents a new solution that uses online data exchange of power consumption information to a cloud server without modifying the existing electromechanical analog meters. In this framework, application of a systematic approach to extract energy data from images replaces the manual reading process. One case study illustrates the digital imaging approach is compared to the averages determined by visual readings over a one-month period.

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We present a case of successful interventional laser-assisted extraction of an endovascularly trapped long-term implanted ventriculoatrial shunt in a patient with shunt-associated septicemia. This approach is based on modified techniques for explantation of pacemaker leads and might be considered an additional option for extraction of otherwise nonremovable trapped endovascular catheters in experienced centers.

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A Pergamon Press Book.

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La richiesta di allergeni puri è in continuo aumento per scopi diagnostici, come standard per metodi di rilevamento e di quantificazione, per l'immunoterapia e per lo studio a livello molecolare dei meccanismi delle reazioni allergiche, al fine di facilitare lo sviluppo di possibili cure. In questa tesi di dottorato sono descritte diverse strategie per l’ottenimento di forme pure di non-specific Lipid Transfer Proteins (nsLTPs), le quali sono state riconosciute essere rilevanti allergeni alimentari in molti frutti e verdure comunemente consumati e sono state definite come modello di veri allergeni alimentari. Una LTP potenzialmente allergenica, non nota in precedenza, è stata isolata dalle mandorle, mentre una LTP dall’allergenicità nota contenuta nelle noci è stata prodotta mediante tecniche di DNA ricombinante. Oltre a questi approcci classici, metodi per la sintesi chimica totale di proteine sono stati applicati per la prima volta alla produzione di un allergene, utilizzando Pru p 3, la LTP prototipica e principale allergene della pesca nell'area mediterranea, come modello. La sintesi chimica totale di proteinepermette di controllarne completamente la sequenza e di studiare la loro funzione a livello atomico. La sua applicazione alla produzione di allergeni costituisce perciò un importante passo avanti nel campo della ricerca sulle allergie alimentari. La proteina Pru p 3 è stata prodotta nella sua intera lunghezza e sono necessari solo due passaggi finali di deprotezione per ottenere il target nella sua forma nativa. Le condizioni sperimentali per tali deprotezioni sono state messe a punto durante la produzione dei peptidi sPru p 3 (1-37) e sPru p 3 (38-91), componenti insieme l'intera proteina. Tecniche avanzate di spettrometria di massa sono state usate per caratterizzare tutti i composti ottenuti, mentre la loro allergenicità è stata studiata attraverso test immunologici o approcci in silico.

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PURPOSE: To evaluate theoretically three previously published formulae that use intra-operative aphakic refractive error to calculate intraocular lens (IOL) power, not necessitating pre-operative biometry. The formulae are as follows: IOL power (D) = Aphakic refraction x 2.01 [Ianchulev et al., J. Cataract Refract. Surg.31 (2005) 1530]; IOL power (D) = Aphakic refraction x 1.75 [Mackool et al., J. Cataract Refract. Surg.32 (2006) 435]; IOL power (D) = 0.07x(2) + 1.27x + 1.22, where x = aphakic refraction [Leccisotti, Graefes Arch. Clin. Exp. Ophthalmol.246 (2008) 729]. METHODS: Gaussian first order calculations were used to determine the relationship between intra-operative aphakic refractive error and the IOL power required for emmetropia in a series of schematic eyes incorporating varying corneal powers, pre-operative crystalline lens powers, axial lengths and post-operative IOL positions. The three previously published formulae, based on empirical data, were then compared in terms of IOL power errors that arose in the same schematic eye variants. RESULTS: An inverse relationship exists between theoretical ratio and axial length. Corneal power and initial lens power have little effect on calculated ratios, whilst final IOL position has a significant impact. None of the three empirically derived formulae are universally accurate but each is able to predict IOL power precisely in certain theoretical scenarios. The formulae derived by Ianchulev et al. and Leccisotti are most accurate for posterior IOL positions, whereas the Mackool et al. formula is most reliable when the IOL is located more anteriorly. CONCLUSION: Final IOL position was found to be the chief determinant of IOL power errors. Although the A-constants of IOLs are known and may be accurate, a variety of factors can still influence the final IOL position and lead to undesirable refractive errors. Optimum results using these novel formulae would be achieved in myopic eyes.

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The aim of this study was to compare the performance of the following techniques on the isolation of volatiles of importance for the aroma/flavor of fresh cashew apple juice: dynamic headspace analysis using PorapakQ(®) as trap, solvent extraction with and without further concentration of the isolate, and solid-phase microextraction (fiber DVB/CAR/PDMS). A total of 181 compounds were identified, from which 44 were esters, 20 terpenes, 19 alcohols, 17 hydrocarbons, 15 ketones, 14 aldehydes, among others. Sensory evaluation of the gas chromatography effluents revealed esters (n = 24) and terpenes (n = 10) as the most important aroma compounds. The four techniques were efficient in isolating esters, a chemical class of high impact in the cashew aroma/flavor. However, the dynamic headspace methodology produced an isolate in which the analytes were in greater concentration, which facilitates their identification (gas chromatography-mass spectrometry) and sensory evaluation in the chromatographic effluents. Solvent extraction (dichloromethane) without further concentration of the isolate was the most efficient methodology for the isolation of terpenes. Because these two techniques also isolated in greater concentration the volatiles from other chemical classes important to the cashew aroma, such as aldehydes and alcohols, they were considered the most advantageous for the study of cashew aroma/flavor.

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Molecular characterization of Cryptosporidium spp.oocysts in clinical samples is useful for public health since it allows the study of sources of contamination as well as the transmission in different geographical regions. Although widely used in developed countries, in Brazil it is restricted to academic studies, mostly using commercial kits for the extraction of genomic DNA, or in collaboration with external reference centers, rendering the method expensive and limited. The study proposes the application of the modifications recently introduced in the method improving feasibility with lower cost. This method was efficient for clinical samples preserved at -20 °C for up to six years and the low number of oocysts may be overcomed by repetitions of extraction.

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The ascorbate oxidase is the enzyme used to determine the content of ascorbic acid in the pharmaceutical and food industries and clinics analyses. The techniques currently used for the purification of this enzyme raise its production cost. Thus, the development of alternative processes and with the potential to reduce costs is interesting. The application of aqueous two-phase system is proposed as an alternative to purification because it enables good separation of biomolecules. The objective of this study was to determine the conditions to continuously pre-purify the enzyme ascorbate oxidase by an aqueous two-phase system (PEG/citrate) using rotating column provided with perforated discs. Under the best conditions (20,000 g/mol PEG molar mass, 10% PEG concentration, and 25% citrate concentration), the system showed satisfactory results (partition coefficient, 3.35; separation efficiency, 54.98%; and purification factor, 1.46) and proved suitable for the pre-purification of ascorbate oxidase in continuous process.

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With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.

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PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

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Magnetic resonance (MR) imaging has been used to analyse and evaluate the vocal tract shape through different techniques and with promising results in several fields. Our purpose is to demonstrate the relevance of MR and image processing for the vocal tract study. The extraction of contours of the air cavities allowed the set - up of a number of 3D reconstruction image stacks by means of the combination of orthogonally oriented sets of slices for e ach articulatory gesture, as a new approach to solve the expected spatial under sampling of the imaging process. In result these models give improved information for the visualization of morphologic and anatomical aspects and are useful for partial measure ments of the vocal tract shape in different situations. Potential use can be found in Medical and therapeutic applications as well as in acoustic articulatory speech modelling.