982 resultados para Extraction de structure


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As of today, opinion mining has been widely used to iden- tify the strength and weakness of products (e.g., cameras) or services (e.g., services in medical clinics or hospitals) based upon people's feed- back such as user reviews. Feature extraction is a crucial step for opinion mining which has been used to collect useful information from user reviews. Most existing approaches only find individual features of a product without the structural relationships between the features which usually exists. In this paper, we propose an approach to extract features and feature relationship, represented as tree structure called a feature hi- erarchy, based on frequent patterns and associations between patterns derived from user reviews. The generated feature hierarchy profiles the product at multiple levels and provides more detailed information about the product. Our experiment results based on some popularly used review datasets show that the proposed feature extraction approach can identify more correct features than the baseline model. Even though the datasets used in the experiment are about cameras, our work can be ap- plied to generate features about a service such as the services in hospitals or clinics.

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Changes in the molecular structure of polymer antioxidants such as hindered amine light stabilisers (HALS) is central to their efficacy in retarding polymer degradation and therefore requires careful monitoring during their in-service lifetime. The HALS, bis-(1-octyloxy-2,2,6,6-tetramethyl-4-piperidinyl) sebacate (TIN123) and bis-(1,2,2,6,6-pentamethyl-4-piperidinyl) sebacate (TIN292), were formulated in different polymer systems and then exposed to various curing and ageing treatments to simulate in-service use. Samples of these coatings were then analysed directly using liquid extraction surface analysis (LESA) coupled with a triple quadrupole mass spectrometer. Analysis of TIN123 formulated in a cross-linked polyester revealed that the polymer matrix protected TIN123 from undergoing extensive thermal degradation that would normally occur at 292 degrees C, specifically, changes at the 1- and 4-positions of the piperidine groups. The effect of thermal versus photo-oxidative degradation was also compared for TIN292 formulated in polyacrylate films by monitoring the in situ conversion of N-CH3 substituted piperidines to N-H. The analysis confirmed that UV light was required for the conversion of N-CH3 moieties to N-H - a major pathway in the antioxidant protection of polymers - whereas this conversion was not observed with thermal degradation. The use of tandem mass spectrometric techniques, including precursor-ion scanning, is shown to be highly sensitive and specific for detecting molecular-level changes in HALS compounds and, when coupled with LESA, able to monitor these changes in situ with speed and reproducibility. (C) 2013 Elsevier B. V. All rights reserved.

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Commercially viable carbon–neutral biodiesel production from microalgae has potential for replacing depleting petroleum diesel. The process of biodiesel production from microalgae involves harvesting, drying and extraction of lipids which are energy- and cost-intensive processes. The development of effective large-scale lipid extraction processes which overcome the complexity of microalgae cell structure is considered one of the most vital requirements for commercial production. Thus the aim of this work was to investigate suitable extraction methods with optimised conditions to progress opportunities for sustainable microalgal biodiesel production. In this study, the green microalgal species consortium, Tarong polyculture was used to investigate lipid extraction with hexane (solvent) under high pressure and variable temperature and biomass moisture conditions using an Accelerated Solvent Extraction (ASE) method. The performance of high pressure solvent extraction was examined over a range of different process and sample conditions (dry biomass to water ratios (DBWRs): 100%, 75%, 50% and 25% and temperatures from 70 to 120 ºC, process time 5–15 min). Maximum total lipid yields were achieved at 50% and 75% sample dryness at temperatures of 90–120 ºC. We show that individual fatty acids (Palmitic acid C16:0; Stearic acid C18:0; Oleic acid C18:1; Linolenic acid C18:3) extraction optima are influenced by temperature and sample dryness, consequently affecting microalgal biodiesel quality parameters. Higher heating values and kinematic viscosity were compliant with biodiesel quality standards under all extraction conditions used. Our results indicate that biodiesel quality can be positively manipulated by selecting process extraction conditions that favour extraction of saturated and mono-unsaturated fatty acids over optimal extraction conditions for polyunsaturated fatty acids, yielding positive effects on cetane number and iodine values. Exceeding biodiesel standards for these two parameters opens blending opportunities with biodiesels that fall outside the minimal cetane and maximal iodine values.

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It is shown that lithium can be oxidatively extracted from Li2MoO3 at room temperature using Br2 in CHCl3. The delithiated oxides, Li2â��xMoO3 (0 < x â�¤ 1.5) retain the parent ordered rocksalt structure. Complete removal of lithium from Li2MoO3 using Br2 in CH3CN results in a poorly crystalline MoO3 that transforms to the stable structure at 280�°C. Li2MoO3 undergoes topotactic ion-exchange in aqueous H2SO4 to yield a new protonated oxide, H2MoO3.

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When genome sections of wild Solanum species are bred into the cultivated potato (S. tuberosum L.) to obtain improved potato cultivars, the new cultivars must be evaluated for their beneficial and undesirable traits. Glycoalkaloids present in Solanum species are known for their toxic as well as for beneficial effects on mammals. On the other hand, glycoalkaloids in potato leaves provide natural protection against pests. Due to breeding, glycoalkaloid profile of the plant is affected. In addition, the starch properties in potato tubers can be affected as a result of breeding, because the crystalline properties are determined by the botanical source of the starch. Starch content and composition affect the texture of cooked and processed potatoes. In order to determine glycoalkaloid contents in Solanum species, simultaneous separation of glycoalkaloids and aglycones using reversed-phase high-performance liquid chromatography (HPLC) was developed. Clean-up of foliage samples was improved using a silica-based strong cation exchanger instead of octadecyl phases in solid-phase extraction. Glycoalkaloids alpha-solanine and alpha-chaconine were detected in potato tubers of cvs. Satu and Sini. The total glycoalkaloid concentration of non-peeled and immature tubers was at an acceptable level (under 20 mg/100 g of FW) in the cv. Satu, whereas concentration in cv. Sini was 23 mg/100 g FW. Solanum species (S. tuberosum, S. brevidens, S. acaule, and S. commersonii) and interspecific somatic hybrids (brd + tbr, acl + tbr, cmm + tbr) were analyzed for their glycoalkaloid contents using liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS). The concentrations in the tubers of the brd + tbr and acl + tbr hybrids remained under 20 mg/100 g FW. Glycoalkaloid concentration in the foliage of the Solanum species was between 110 mg and 890 mg/100 g FW. However, the concentration in the foliage of S. acaule was as low as 26 mg/100 g FW. The total concentrations of brd + tbr, acl + tbr, and cmm + tbr hybrid foliages were 88 mg, 180 mg, and 685 mg/100 g FW, respectively. Glycoalkaloids of both parental plants as well as new combinations of aglycones and saccharides were detected in somatic hybrids. The hybrids contained mainly spirosolanes, and glycoalkaloid structures having no 5,6-double bond in the aglycone. Based on these results, the glycoalkaloid profiles of the hybrids may represent a safer and more beneficial spectrum of glycoalkaloids than that found in currently cultivated varieties. Starch nanostructure of three different cultivars (Satu, Saturna, and Lady Rosetta), a wild species S. acaule, and interspecific somatic hybrids were examined by wide-angle and small-angle X-ray scattering (WAXS, SAXS). For the first time, the measurements were conducted on fresh potato tuber samples. Crystallinity of starch, average crystallite size, and lamellar distance were determined from the X-ray patterns. No differences in the starch nanostructure between the three different cultivars were detected. However, tuber immaturity was detected by X-ray scattering methods when large numbers of immature and mature samples were measured and the results were compared. The present study shows that no significant changes occurred in the nanostructures of starches resulting from hybridizations of potato cultivars.

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The increasing use of 3D modeling of Human Face in Face Recognition systems, User Interfaces, Graphics, Gaming and the like has made it an area of active study. Majority of the 3D sensors rely on color coded light projection for 3D estimation. Such systems fail to generate any response in regions covered by Facial Hair (like beard, mustache), and hence generate holes in the model which have to be filled manually later on. We propose the use of wavelet transform based analysis to extract the 3D model of Human Faces from a sinusoidal white light fringe projected image. Our method requires only a single image as input. The method is robust to texture variations on the face due to space-frequency localization property of the wavelet transform. It can generate models to pixel level refinement as the phase is estimated for each pixel by a continuous wavelet transform. In cases of sparse Facial Hair, the shape distortions due to hairs can be filtered out, yielding an estimate for the underlying face. We use a low-pass filtering approach to estimate the face texture from the same image. We demonstrate the method on several Human Faces both with and without Facial Hairs. Unseen views of the face are generated by texture mapping on different rotations of the obtained 3D structure. To the best of our knowledge, this is the first attempt to estimate 3D for Human Faces in presence of Facial hair structures like beard and mustache without generating holes in those areas.

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The accurate solution of 3D full-wave Method of Moments (MoM) on an arbitrary mesh of a package-board structure does not guarantee accuracy, since the discretizations may not be fine enough to capture rapid spatial changes in the solution variable. At the same time, uniform over-meshing on the entire structure generates large number of solution variables and therefore requires an unnecessarily large matrix solution. In this work, a suitable refinement criterion for MoM based electromagnetic package-board extraction is proposed and the advantages of the adaptive strategy are demonstrated from both accuracy and speed perspectives.

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3-D full-wave method of moments (MoM) based electromagnetic analysis is a popular means toward accurate solution of Maxwell's equations. The time and memory bottlenecks associated with such a solution have been addressed over the last two decades by linear complexity fast solver algorithms. However, the accurate solution of 3-D full-wave MoM on an arbitrary mesh of a package-board structure does not guarantee accuracy, since the discretization may not be fine enough to capture spatial changes in the solution variable. At the same time, uniform over-meshing on the entire structure generates a large number of solution variables and therefore requires an unnecessarily large matrix solution. In this paper, different refinement criteria are studied in an adaptive mesh refinement platform. Consequently, the most suitable conductor mesh refinement criterion for MoM-based electromagnetic package-board extraction is identified and the advantages of this adaptive strategy are demonstrated from both accuracy and speed perspectives. The results are also compared with those of the recently reported integral equation-based h-refinement strategy. Finally, a new methodology to expedite each adaptive refinement pass is proposed.

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Background: Understanding channel structures that lead to active sites or traverse the molecule is important in the study of molecular functions such as ion, ligand, and small molecule transport. Efficient methods for extracting, storing, and analyzing protein channels are required to support such studies. Further, there is a need for an integrated framework that supports computation of the channels, interactive exploration of their structure, and detailed visual analysis of their properties. Results: We describe a method for molecular channel extraction based on the alpha complex representation. The method computes geometrically feasible channels, stores both the volume occupied by the channel and its centerline in a unified representation, and reports significant channels. The representation also supports efficient computation of channel profiles that help understand channel properties. We describe methods for effective visualization of the channels and their profiles. These methods and the visual analysis framework are implemented in a software tool, CHEXVIS. We apply the method on a number of known channel containing proteins to extract pore features. Results from these experiments on several proteins show that CHEXVIS performance is comparable to, and in some cases, better than existing channel extraction techniques. Using several case studies, we demonstrate how CHEXVIS can be used to study channels, extract their properties and gain insights into molecular function. Conclusion: CHEXVIS supports the visual exploration of multiple channels together with their geometric and physico-chemical properties thereby enabling the understanding of the basic biology of transport through protein channels. The CHEXVIS web-server is freely available at http://vgl.serc.iisc.ernet.in/chexvis/. The web-server is supported on all modern browsers with latest Java plug-in.

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In the present paper, we present the structure and composition of tropical evergreen and deciduous forests in the Western Ghats monitored under a long-term programme involving Indian Institute of Science, Earthwatch and volunteer investigators from HSBC. Currently, there is limited evidence on the status and dynamics of tropical forests in the context of human disturbance and climate change. Observations made in this study show that the `more disturbed' evergreen and one of the deciduous plots have low species diversity compared to the less-disturbed forests. There are also variations in the size class structure in the more and `less disturbed' forests of all the locations. The variation is particularly noticeable in the DBH size class 10 - 15 cm category. When biomass stock estimates are considered, there was no significant difference between evergreen and deciduous forests. The difference in biomass stocks between `less disturbed' and `more disturbed' forests within a forest type is also low. Thus, the biomass and carbon stock has not been impacted despite the dependence of communities on the forests. Periodic and long-term monitoring of the status and dynamics of the forests is necessary in the context of potential increased human pressure and climate change. There is, therefore, a need to inform the communities of the impact of extraction and its effect on regeneration so as to motivate them to adopt what may be termed as ``adaptive resource management'', so as to sustain the flow of forest products.

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The detailed understanding of the electronic properties of carbon-based materials requires the determination of their electronic structure and more precisely the calculation of their joint density of states (JDOS) and dielectric constant. Low electron energy loss spectroscopy (EELS) provides a continuous spectrum which represents all the excitations of the electrons within the material with energies ranging between zero and about 100 eV. Therefore, EELS is potentially more powerful than conventional optical spectroscopy which has an intrinsic upper information limit of about 6 eV due to absorption of light from the optical components of the system or the ambient. However, when analysing EELS data, the extraction of the single scattered data needed for Kramers Kronig calculations is subject to the deconvolution of the zero loss peak from the raw data. This procedure is particularly critical when attempting to study the near-bandgap region of materials with a bandgap below 1.5 eV. In this paper, we have calculated the electronic properties of three widely studied carbon materials; namely amorphous carbon (a-C), tetrahedral amorphous carbon (ta-C) and C60 fullerite crystal. The JDOS curve starts from zero for energy values below the bandgap and then starts to rise with a rate depending on whether the material has a direct or an indirect bandgap. Extrapolating a fit to the data immediately above the bandgap in the stronger energy loss region was used to get an accurate value for the bandgap energy and to determine whether the bandgap is direct or indirect in character. Particular problems relating to the extraction of the single scattered data for these materials are also addressed. The ta-C and C60 fullerite materials are found to be direct bandgap-like semiconductors having a bandgaps of 2.63 and 1.59eV, respectively. On the other hand, the electronic structure of a-C was unobtainable because it had such a small bandgap that most of the information is contained in the first 1.2 eV of the spectrum, which is a region removed during the zero loss deconvolution.

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'Learning to learn' phenomena have been widely investigated in cognition, perception and more recently also in action. During concept learning tasks, for example, it has been suggested that characteristic features are abstracted from a set of examples with the consequence that learning of similar tasks is facilitated-a process termed 'learning to learn'. From a computational point of view such an extraction of invariants can be regarded as learning of an underlying structure. Here we review the evidence for structure learning as a 'learning to learn' mechanism, especially in sensorimotor control where the motor system has to adapt to variable environments. We review studies demonstrating that common features of variable environments are extracted during sensorimotor learning and exploited for efficient adaptation in novel tasks. We conclude that structure learning plays a fundamental role in skill learning and may underlie the unsurpassed flexibility and adaptability of the motor system.

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A study was conducted in Tebuwana Wathurana Wetland ecosystem to understand its vegetation structure and faunal composition in order to assess its conservation needs. As there are no published records on the flora and fauna of Wathurana Wetlands in Tebuwana, it is necessary to understand the ecological and other relevant features in order to develop strategies to conserve this wetland. These objectives were pursued by surveying the vegetation of the wetland and by identifying fish and bird species present. A total of 66 species of flora and 61 species of fauna were identified in the survey. Of the 27 fish species recorded from the Tebuwana Wetland, 9 species were endemic and 17 species belonged to the indigenous category. With regard to the flora in the wetlands, the dominant families were Rubaceae, Fabaceae and Arecaceae. The 66 species belonged to 39 families and 61 genera while 12 species were endemic and 4 species were considered highly threatened. These flora were found in four layers. Of the 22 species of birds recorded, two species were endemic. This study revealed that these Wathurana Wetlands have a high species diversity but that they face many threats including encroachments, extraction of forest products mainly as timber, land filling, mining and occurrence of invasive species. It is essential to minimize the exploitation of natural resources from this wetland in the future and in particular to mark the boundary, conduct awareness programmes and continue research.

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Green tiger prawn, Penaeus sentisulcatus is one of the commercial species of Persian Gulf, which is distributed from north to Strait of I Iormoze. Concerning its role in fisheries economic, various research projects on stock assessment, biology and aquaculture has been conducted. This research is targeted the identification of various populations of green tiger prawn in northern waters of Persian Gulf. The area has been divided to five regions from north to south named; Bahrakan, Boushehr, Tangestan, Motaaf and Strait of Hormoz. In each region, numbers of sampling stations trawled, and live shrimp species carried in containers equipped with air pump, to coastal laboratories in Boushehr and Bandar Abbass Fisheries Research Centers. Biometeric, morphometeric and merestic measures for 45 factars done, and peices of muscles, eye and ovary tissues dissected, and stored in liquid nitrogen. Protein extraction, and polyacrylamid gel electrophoresis by SDS-PAGE technique for tissues samples conducted. Data of 45 morphometeric and merestic characteristics analyzed by principal component analysis (PCA), and clustering analysis methods. The results of analysis showed that, the populations of Bahrakan and Mota.af regions are differentiated, while population of Boushehr and Tangestan regions were mixed, and named as a single population. The analysis of electrophoretic data also confirmed this result, and showed a distinct population in Strait of Hormoz. Therefore, this research illustrated four distinct populations for P. semisulcatus in northern area of Persian Gulf, named Bahrakan (north of Boushehr), Boushehr and Tangesta.n (adjacent), Motaaf and it's south, and Strait of Hormoz. Study of morphometeric characteristics of carapace factors, genital organs, antenna and life cycle of samples of different regions resulting identification of a subspecies, which is named Penaeus seinisuleatus persicus.