994 resultados para Fluorine compounds--Spectra.
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Incoherent scatter data from non-thermal F-region ionospheric plasma are analysed, using theoretical spectra predicted by Raman et al. It is found that values of the semi-empirical drift parameter D∗, associated with deviations of the ion velocity distribution from a Maxwellian, and the plasma temperatures can be rigorously deduced (the results being independent of the path of iteration) if the angle between the line-of-sight and the geomagnetic field is larger than about 15–20 degrees. For small aspect angles, the deduced value of the average (or 3-D) ion temperature remains ambiguous and the analysis is restricted to the determination of the line-of-sight temperature because the theoretical spectrum is insensitive to non-thermal effects when the plasma is viewed along directions almost parallel to the magnetic field. This limitation is expected to apply to any realistic model of the ion velocity distribution, and its consequences are discussed. Fit strategies which allow for mixed ion composition are also considered. Examples of fits to data from various EISCAT observing programmes are presented.
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The present study compares the impact of thermal and high pressure high temperature(HPHT) processing on volatile profile (via a non-targeted headspace fingerprinting) and structural and nutritional quality parameter (via targeted approaches) of orange and yellow carrot purees. The effect of oil enrichment was also considered. Since oil enrichment affects compounds volatility, the effect of oil was not studied when comparing the volatile fraction. For the targeted part, as yellow carrot purees were shown to contain a very low amount of carotenoids, focus was given to orange carrot purees. The results of the non-targeted approach demonstrated HPHT processing exerts a distinct effect on the volatile fractions compared to thermal processing. In addition, different colored carrot varieties are characterized by distinct headspace fingerprints. From a structural point of view, limited or no difference could be observed between orange carrot purees treated with HPHT or HT processes, both for samples without and with oil. From nutritional point of view, only in samples with oil, significant isomerisation of all-trans-β-carotene occurred due to both processing. Overall, for this type of product and for the selected conditions, HPHT processing seems to have a different impact on the volatile profile but rather similar impact on the structural and nutritional attributes compared to thermal processing.
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We extend extreme learning machine (ELM) classifiers to complex Reproducing Kernel Hilbert Spaces (RKHS) where the input/output variables as well as the optimization variables are complex-valued. A new family of classifiers, called complex-valued ELM (CELM) suitable for complex-valued multiple-input–multiple-output processing is introduced. In the proposed method, the associated Lagrangian is computed using induced RKHS kernels, adopting a Wirtinger calculus approach formulated as a constrained optimization problem similarly to the conventional ELM classifier formulation. When training the CELM, the Karush–Khun–Tuker (KKT) theorem is used to solve the dual optimization problem that consists of satisfying simultaneously smallest training error as well as smallest norm of output weights criteria. The proposed formulation also addresses aspects of quaternary classification within a Clifford algebra context. For 2D complex-valued inputs, user-defined complex-coupled hyper-planes divide the classifier input space into four partitions. For 3D complex-valued inputs, the formulation generates three pairs of complex-coupled hyper-planes through orthogonal projections. The six hyper-planes then divide the 3D space into eight partitions. It is shown that the CELM problem formulation is equivalent to solving six real-valued ELM tasks, which are induced by projecting the chosen complex kernel across the different user-defined coordinate planes. A classification example of powdered samples on the basis of their terahertz spectral signatures is used to demonstrate the advantages of the CELM classifiers compared to their SVM counterparts. The proposed classifiers retain the advantages of their ELM counterparts, in that they can perform multiclass classification with lower computational complexity than SVM classifiers. Furthermore, because of their ability to perform classification tasks fast, the proposed formulations are of interest to real-time applications.
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Background: In many experimental pipelines, clustering of multidimensional biological datasets is used to detect hidden structures in unlabelled input data. Taverna is a popular workflow management system that is used to design and execute scientific workflows and aid in silico experimentation. The availability of fast unsupervised methods for clustering and visualization in the Taverna platform is important to support a data-driven scientific discovery in complex and explorative bioinformatics applications. Results: This work presents a Taverna plugin, the Biological Data Interactive Clustering Explorer (BioDICE), that performs clustering of high-dimensional biological data and provides a nonlinear, topology preserving projection for the visualization of the input data and their similarities. The core algorithm in the BioDICE plugin is Fast Learning Self Organizing Map (FLSOM), which is an improved variant of the Self Organizing Map (SOM) algorithm. The plugin generates an interactive 2D map that allows the visual exploration of multidimensional data and the identification of groups of similar objects. The effectiveness of the plugin is demonstrated on a case study related to chemical compounds. Conclusions: The number and variety of available tools and its extensibility have made Taverna a popular choice for the development of scientific data workflows. This work presents a novel plugin, BioDICE, which adds a data-driven knowledge discovery component to Taverna. BioDICE provides an effective and powerful clustering tool, which can be adopted for the explorative analysis of biological datasets.
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The East China Sea is a hot area for typhoon waves to occur. A wave spectra assimilation model has been developed to predict the typhoon wave more accurately and operationally. This is the first time where wave data from Taiwan have been used to predict typhoon wave along the mainland China coast. The two-dimensional spectra observed in Taiwan northeast coast modify the wave field output by SWAN model through the technology of optimal interpolation (OI) scheme. The wind field correction is not involved as it contributes less than a quarter of the correction achieved by assimilation of waves. The initialization issue for assimilation is discussed. A linear evolution law for noise in the wave field is derived from the SWAN governing equations. A two-dimensional digital low-pass filter is used to obtain the initialized wave fields. The data assimilation model is optimized during the typhoon Sinlaku. During typhoons Krosa and Morakot, data assimilation significantly improves the low frequency wave energy and wave propagation direction in Taiwan coast. For the far-field region, the assimilation model shows an expected ability of improving typhoon wave forecast as well, as data assimilation enhances the low frequency wave energy. The proportion of positive assimilation indexes is over 81% for all the periods of comparison. The paper also finds that the impact of data assimilation on the far-field region depends on the state of the typhoon developing and the swell propagation direction.
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The feasibility to synthesize, in large quantity, pure and non-toxic tetrahedrite compounds using high-energy mechanical-alloying from only elemental precursors is reported in the present paper for the first time. Our processing technique allows a better control of the final product composition and leads to high thermoelectric performances (ZT of 0.75 at 700 K), comparable to that reported on sealed tube synthesis samples. Combined with spark plasma sintering, the production of highly pure and dense samples is achieved in a very short time, at least 8 times shorter than in conventional liquid-solid-vapor synthesis process. The process described in this paper is a promising way to produce high performance tetrahedrite materials for cost-effective and large-scale thermoelectric applications.
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Background, aim and scope Soil organic matter (SOM) is known to increase with time as landscapes recover after a major disturbance; however, little is known about the evolution of the chemistry of SOM in reconstructed ecosystems. In this study, we assessed the development of SOM chemistry in a chronosequence (space for time substitution) of restored Jarrah forest sites in Western Australia. Materials and methods Replicated samples were taken at the surface of the mineral soil as well as deeper in the profile at sites of 1, 3, 6, 9, 12, and 17 years of age. A molecular approach was developed to distinguish and quantify numerous individual compounds in SOM. This used accelerated solvent extraction in conjunction with gas chromatography mass spectrometry. A novel multivariate statistical approach was used to assess changes in accelerated solvent extraction (ASE)-gas chromatography-mass spectrometry (GCMS) spectra. This enabled us to track SOM developmental trajectories with restoration time. Results Results showed total carbon concentrations approached that of native forests soils by 17 years of restoration. Using the relate protocol in PRIMER, we demonstrated an overall linear relationship with site age at both depths, indicating that changes in SOM chemistry were occurring. Conclusions The surface soils were seen to approach native molecular compositions while the deeper soil retained a more stable chemical signature, suggesting litter from the developing diverse plant community has altered SOM near the surface. Our new approach for assessing SOM development, combining ASE-GCMS with illuminating multivariate statistical analysis, holds great promise to more fully develop ASE for the characterisation of SOM.
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Bulk polycrystalline samples in the series Ti1−xNbxS2 (0 ≤ x ≤ 0.075) were prepared using mechanical alloying synthesis and spark plasma sintering. X-ray diffraction analysis coupled with high resolution transmission electron microscopy indicates the formation of trigonal TiS2 by high energy ball-milling. The as-synthesized particles consist of pseudo-ordered TiS2 domains of around 20–50 nm, joined by bent atomic planes. This bottom-up approach leads, after spark plasma sintering, to homogeneous solid solutions, with a niobium solubility limit of x = 0.075. Microstructural observations evidence the formation of small crystallites in the bulk compounds with a high density of stacking faults. The large grain boundary concentration coupled with the presence of planar defects, leads to a substantial decrease in the thermal conductivity to 1.8 W/mK at 700 K. This enables the figure of merit to reach ZT = 0.3 at 700 K for x = 0.05, despite the lower electron mobility in mechanically alloyed samples due to small crystallite/grain size and structural defects.
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The present research explores the degree of morphological structure of compound words in the native and nonnative lexicons, and provides additional data on the access to these representations. Native and nonnative speakers (L1 Spanish) of English were tested using a lexical decision task with masked priming of the compound’s constituents in isolation, including two orthographic conditions to control for a potential orthographic locus of effects. Both groups displayed reliable priming effects, unmediated by semantics, for the morphological but not the orthographic conditions as compared to an unrelated baseline. Results contribute further evidence of morphological structure in the lexicon of native speakers, and suggest that lexical representation and access in a second language are qualitatively comparable at relatively advanced levels of proficiency.
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The radiation food processing has been demonstrating great effectiveness in the attack of pathogenic agents, while little compromising nutritional value and sensorial properties of foods. The mate (Ilex paraguariensis), widely consumed product in South America, generally in the form of infusions with hot or cold water, calls of chimarrao or terere, it is cited in literature as one of the best sources phenolic compounds. The antioxidants action of these constituent has been related to the protection of the organism against the free radicals, generated in alive, currently responsible for the sprouting of some degenerative illness as cancer, arteriosclerosis, rheumatic arthritis and cardiovascular clutters among others. The objective of that work was to evaluate the action of the processing for gamma radiation in phenolic compounds of terere beverage in the doses of 0, 3, 5, 7 and 10 kGy. The observed results do not demonstrate significant alterations in phenolic compounds of terere beverage processed by gamma radiation. Crown Copyright (C) 2009 Published by Elsevier Ltd. All rights reserved.
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A method for the determination of volatile organic compounds (VOCs) in recycled polyethylene terephthalate and high-density polyethylene using headspace sampling by solid-phase microextraction and gas chromatography coupled to mass spectrometry detection is presented. This method was used to evaluate the efficiency of cleaning processes for VOC removal from recycled PET. In addition, the method was also employed to evaluate the level of VOC contamination in multilayer packaging material containing recycled HDPE material. The optimisation of the extraction procedure for volatile compounds was performed and the best extraction conditions were found using a 75 mu m carboxen-polydimethylsiloxane (CAR-PDMS) fibre for 20 min at 60 degrees C. The validation parameters for the established method were linear range, linearity, sensitivity, precision (repeatability), accuracy (recovery) and detection and quantification limits. The results indicated that the method could easily be used in quality control for the production of recycled PET and HDPE. (C) 2011 Elsevier B.V. All rights reserved.
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Different extraction processes were employed to extract the polyphenolic compounds from pitanga (Eugenia uniflora L) leaves: a one-step process using water, ethanol or supercritical CO(2) as solvents, and a two-step process using supercritical CO(2) followed by either water or ethanol. The total polyphenolic compounds, total flavonoids and antioxidant activity were determined in all the extracts obtained. The process performance was evaluated with respect to three variables: global extraction yield, concentration and yield of both polyphenols and flavonoids in the extracts. For the one-step extraction, the results showed that the extraction yield increased with solvent polarity. For the two-step process, the results suggested that water was more efficient in extracting the phenolic compounds from E. uniflora when the matrix was previously extracted with scCO(2). With respect to the antioxidant activity, the ethanolic extracts obtained from both processes, using either the DPPH radical scavenging method or the beta-carotene bleaching method, presented high antioxidant activities. (C) 2010 Elsevier B.V. All rights reserved.
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Supercritical carbon dioxide (SC-CO(2)) extractions of Brazilian cherry (Eugenia uniflora L.) were carried out under varied conditions of pressure and temperature, according to a central composite 2(2) experimental design, in order to produce flavour-rich extracts. The composition of the extracts was evaluated by gas chromatography coupled with mass spectrometry (GC/MS). The abundance of the extracted compounds was then related to sensory analysis results, assisted by principal component and factorial discriminant analysis (PCA and FDA, respectively). The identified sesquiterpenes and ketones were found to strongly contribute to the characteristic flavour of the Brazilian cherry. The extracts also contained a variety of other volatile compounds, and part of the fruit wax contained long-chain hydrocarbons that according to multivariate analysis, contributed to the yield of the extracts, but not the flavour. Volatile phenolic compounds, to which antioxidant properties are attributed, were also present in the extracts in high proportion, regardless of the extraction conditions. (C) 2010 Elsevier Ltd. All rights reserved.
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In the present work, a group contribution method is proposed for the estimation of viscosity of fatty compounds and biodiesel esters as a function of the temperature. The databank used for regression of the group contribution parameters (1070 values for 65 types of substances) included fatty compounds, such as fatty acids, methyl and ethyl esters and alcohols, tri- and diacylglycerols, and glycerol. The inclusion of new experimental data for fatty esters, a partial acylglycerol, and glycerol allowed for a further refinement in the performance of this methodology in comparison to a prior group contribution equation (Ceriani, R.; Goncalves, C. B.; Rabelo, J.; Caruso, M.; Cunha, A. C. C.; Cavaleri, F. W.; Batista, E. A. C.; Meirelles, A. J. A. Group contribution model for predicting viscosity of fatty compounds. J. Chem. Eng. Data 2007, 52, 965-972) for all classes of fatty compounds. Besides, the influence of small concentrations of partial acylglycerols, intermediate compounds in the transesterification reaction, in the viscosity of biodiesels was also investigated.