901 resultados para L71 - Mining, Extraction, and Refining:
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Includes bibliography
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Includes bibliography
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Several cements are used as biomaterials. Biopolymers such as chitosan and collagen exhibit excellent biocompatibility and can be used in the remodeling of bone tissue. The cement must have high mechanical strength and compatibility with original tissue. In this context, the objective of this study was to extract, characterize and cross-link collagen from bovine tendon, forlater associate it with chitosan and calcium phosphate to obtain cements for bone regeneration. Glutaraldehyde was used as cross-linker in 0.1, 0.5, 1.0 and 10% concentration. Infrared analysis confirmed the presence of functional groups characteristic of collagen, whereas the capacity of water absorption decreased with the increasing of cross-linking degree. Denaturation temperatures of collagen samples were obtained by Differential Scanning Calorimetry and Scanning Electron Microscopy showed the fiber structure characteristics of collagen, which were more organized for high degree of cross-linking samples.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The liquid-liquid equilibria of systems composed of rice bran oil, free fatty acids, ethanol and water were investigated at temperatures ranging from 10 to 60 degrees C. The results of the present study indicated that the mutual solubility of the compounds decreased with an increase in the water content of the solvent and a decrease in the temperature of the solution. The experimental data set was correlated by applying the UNIQUAC model. The average variance between the experimental and calculated compositions was 0.35%, indicating that the model can accurately predict behavior of the compounds at different temperatures and degrees of hydration. The adjustment of interaction parameters enables both the simulation of liquid-liquid extractors for deacidification of vegetable oil and the prediction of phase compositions for the oil and alcohol-rich phases that are generated during cooling of the stream exiting the extractor (when using ethanol as the solvent). (C) 2012 Elsevier Ltd. All rights reserved.
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Seaweeds are photosynthetic organisms important to their ecosystem and constitute a source of compounds with several different applications in the pharmaceutical, cosmetic and biotechnology industries, such as triacylglycerols, which can be converted to fatty acid methyl esters that make up biodiesel, an alternative source of fuel applied in economic important areas. This study evaluates the fatty acid profiles and concentrations of three Brazilian seaweed species, Hypnea musciformis (Wulfen) J.V. Lamouroux (Rhodophya), Sargassum cymosum C. Agardh (Heterokontophyta), and Ulva lactuca L. (Chlorophyta), comparing three extraction methods (Bligh & Dyer - B&D; AOAC Official Methods - AOM; and extraction with methanol and ultrasound - EMU) and two transesterification methods (7% BF3 in methanol - BF3; and 5% HCl in methanol - HCl). The fatty acid contents of the three species of seaweeds were significantly different when extracted and transesterified by the different methods. Moreover, the best method for one species was not the same for the other species. The best extraction and transesterification methods for H. musciformis, S. cymosum and U. lactuca were, respectively, AOM-HCl, B&D-BF3 and B&D-BF3/B&D-HCl. These results point to a matrix effect and the method used for the analysis of the fatty acid content of different organisms should be selected carefully.
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The identification of people by measuring some traits of individual anatomy or physiology has led to a specific research area called biometric recognition. This thesis is focused on improving fingerprint recognition systems considering three important problems: fingerprint enhancement, fingerprint orientation extraction and automatic evaluation of fingerprint algorithms. An effective extraction of salient fingerprint features depends on the quality of the input fingerprint. If the fingerprint is very noisy, we are not able to detect a reliable set of features. A new fingerprint enhancement method, which is both iterative and contextual, is proposed. This approach detects high-quality regions in fingerprints, selectively applies contextual filtering and iteratively expands like wildfire toward low-quality ones. A precise estimation of the orientation field would greatly simplify the estimation of other fingerprint features (singular points, minutiae) and improve the performance of a fingerprint recognition system. The fingerprint orientation extraction is improved following two directions. First, after the introduction of a new taxonomy of fingerprint orientation extraction methods, several variants of baseline methods are implemented and, pointing out the role of pre- and post- processing, we show how to improve the extraction. Second, the introduction of a new hybrid orientation extraction method, which follows an adaptive scheme, allows to improve significantly the orientation extraction in noisy fingerprints. Scientific papers typically propose recognition systems that integrate many modules and therefore an automatic evaluation of fingerprint algorithms is needed to isolate the contributions that determine an actual progress in the state-of-the-art. The lack of a publicly available framework to compare fingerprint orientation extraction algorithms, motivates the introduction of a new benchmark area called FOE (including fingerprints and manually-marked orientation ground-truth) along with fingerprint matching benchmarks in the FVC-onGoing framework. The success of such framework is discussed by providing relevant statistics: more than 1450 algorithms submitted and two international competitions.
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Liquid-liquid extraction (LLE) is a method used to separate compounds based on their relative activity in two immiscible phases. By significantly reducing the scale of liquid-liquid extraction to the micro- and milli-fluidic levels, this separation process can bemade suitable for low volume, high value materials.
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In this thesis, I study skin lesion detection and its applications to skin cancer diagnosis. A skin lesion detection algorithm is proposed. The proposed algorithm is based color information and threshold. For the proposed algorithm, several color spaces are studied and the detection results are compared. Experimental results show that YUV color space can achieve the best performance. Besides, I develop a distance histogram based threshold selection method and the method is proven to be better than other adaptive threshold selection methods for color detection. Besides the detection algorithms, I also investigate GPU speed-up techniques for skin lesion extraction and the results show that GPU has potential applications in speeding-up skin lesion extraction. Based on the skin lesion detection algorithms proposed, I developed a mobile-based skin cancer diagnosis application. In this application, the user with an iPhone installed with the proposed application can use the iPhone as a diagnosis tool to find the potential skin lesions in a persons' skin and compare the skin lesions detected by the iPhone with the skin lesions stored in a database in a remote server.
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This lecture discusses monitoring activities of the Berkeley Pit for the past 31 years at the Montana Bureau of Mines and Geology in Butte, Montana.
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Abstract to be posted.
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In this study, the development of a new sensitive method for the analysis of alpha-dicarbonyls glyoxal (G) and methylglyoxal (MG) in environmental ice and snow is presented. Stir bar sorptive extraction with in situ derivatization and liquid desorption (SBSE-LD) was used for sample extraction, enrichment, and derivatization. Measurements were carried out using high-performance liquid chromatography coupled to electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS). As part of the method development, SBSE-LD parameters such as extraction time, derivatization reagent, desorption time and solvent, and the effect of NaCl addition on the SBSE efficiency as well as measurement parameters of HPLC-ESI-MS/MS were evaluated. Calibration was performed in the range of 1–60 ng/mL using spiked ultrapure water samples, thus incorporating the complete SBSE and derivatization process. 4-Fluorobenzaldehyde was applied as internal standard. Inter-batch precision was <12 % RSD. Recoveries were determined by means of spiked snow samples and were 78.9 ± 5.6 % for G and 82.7 ± 7.5 % for MG, respectively. Instrumental detection limits of 0.242 and 0.213 ng/mL for G and MG were achieved using the multiple reaction monitoring mode. Relative detection limits referred to a sample volume of 15 mL were 0.016 ng/mL for G and 0.014 ng/mL for MG. The optimized method was applied for the analysis of snow samples from Mount Hohenpeissenberg (close to the Meteorological Observatory Hohenpeissenberg, Germany) and samples from an ice core from Upper Grenzgletscher (Monte Rosa massif, Switzerland). Resulting concentrations were 0.085–16.3 ng/mL for G and 0.126–3.6 ng/mL for MG. Concentrations of G and MG in snow were 1–2 orders of magnitude higher than in ice core samples. The described method represents a simple, green, and sensitive analytical approach to measure G and MG in aqueous environmental samples.