282 resultados para chemical extraction
Resumo:
The essential oil from the leaves of Didymocarpus tomentosa was extracted by hydrodistillation and analyzed by GC/FID and GC/MS. Twenty five constituents amounting to 81.6% of the oil were identified. The leaf oil contained 78.7% sesquiterpenes and 2.9% monoterpenes. The leaf essential oil of D. tomentosa is a unique caryophyllene-rich natural source containing beta-caryophyllene, caryophyllene oxide, alpha-humulene and humulene oxide. The cytotoxic activity of the oil was determined by the BSLT using shrimp larva and the MTT assay using HeLa tumor cell line. The oil showed significant cytotoxic activity with LC50 and IC50 values of 12.26 and 11.4 mu g/mL, respectively. This is the first report on the chemical composition and cytotoxic activity of the essential oil of D. tomentosa.
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Phase equilibria in the system Tm-Rh-O at 1200 K is established by isothermal equilibration of selected compositions and phase identification after quenching to room temperature. Six intermetallic phases (Tm3Rh, Tm7Rh3, Tm5Rh3, Tm3Rh2, TmRh, TmRh2 +/-delta) and a ternary oxide TmRhO3 are identified. Based on experimentally determined phase relations, a solid-state electrochemical cell is devised to measure the standard free energy of formation of orthorhombic perovskite TmRhO3 from cubic Tm2O3 and beta-Rh2O3 in the temperature range from (900 to 1300) K. The results can be summarized as: Delta G(f,ox)(o) +/- 104/J.mol(-1) = -46474 + 3.925(T/K). Invoking the Neumann-Kopp rule, the standard enthalpy of formation of TmRhO3 from its constituent elements at 298.15 K is estimated as -1193.89 (+/- 2.86) kJ.mol(-1). The standard entropy of TmRhO3 at 298.15 K is evaluated as 103.8 (+/- 1.6) J.mol(-1).K-1. The oxygen potential-composition diagram and three-dimensional chemical potential diagram at 1200 K and temperature-composition diagrams at constant partial pressures of oxygen are computed from thermodynamic data. The compound TmRhO3 decomposes at 1688 (+/- 2) K in pure oxygen and at 1583 (+/- 2) K in air at standard pressure.
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This paper presents computational work on the biogas early phase combustion in spark ignition (SI) engines using detailed chemical kinetics. Specifically, the early phase combustion is studied to assess the effect of various ignition parameters such as spark plug location, spark energy, and number of spark plugs. An integrated version of the KIVA-3V and CHEMKIN codes was developed and used for the simulations utilizing detailed kinetics involving 325 reactions and 53 species The results show that location of the spark plug and local flow field play an important role. A central plug configuration, which is associated with higher local flow velocities in the vicinity of the spark plug, showed faster initial combustion. Although a dual plug configuration shows the highest rate of fuel consumption, it is comparable to the rate exhibited by the central plug case. The radical species important in the initiation of combustion are identified, and their concentrations are monitored during the early phase of combustion. The concentration of these radicals is also observed to correlate very well with the above-mentioned trend.Thus, the role of these radicals in promoting faster combustion has been clearly established. It is also observed that the minimum ignition energy required to initiate a self-sustained flame depends on the flow field condition in the vicinity of the spark plug.Increasing the methane content in the biogas has shown improved combustion.
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The impact of chemical treatment on the surface morphology and other physical properties of tin monosulphide (SnS) thin films have been investigated. The SnS films treated with selected organic solvents exhibited strong improvement in their crystalline-quality and considerable decrease in electrical resistivity. Particularly, the films treated with chloroform showed very low electrical resistivity of similar to 5 Omega cm and a low optical band gap of 1.81 eV as compared to untreated and treated SnS films with other chemicals. From these studies we realized that the chemical treatment of SnS films has strong impact on their surface morphology and also on other physical properties. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
Analysis of high resolution satellite images has been an important research topic for urban analysis. One of the important features of urban areas in urban analysis is the automatic road network extraction. Two approaches for road extraction based on Level Set and Mean Shift methods are proposed. From an original image it is difficult and computationally expensive to extract roads due to presences of other road-like features with straight edges. The image is preprocessed to improve the tolerance by reducing the noise (the buildings, parking lots, vegetation regions and other open spaces) and roads are first extracted as elongated regions, nonlinear noise segments are removed using a median filter (based on the fact that road networks constitute large number of small linear structures). Then road extraction is performed using Level Set and Mean Shift method. Finally the accuracy for the road extracted images is evaluated based on quality measures. The 1m resolution IKONOS data has been used for the experiment.
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We analyze the spectral zero-crossing rate (SZCR) properties of transient signals and show that SZCR contains accurate localization information about the transient. For a train of pulses containing transient events, the SZCR computed on a sliding window basis is useful in locating the impulse locations accurately. We present the properties of SZCR on standard stylized signal models and then show how it may be used to estimate the epochs in speech signals. We also present comparisons with some state-of-the-art techniques that are based on the group-delay function. Experiments on real speech show that the proposed SZCR technique is better than other group-delay-based epoch detectors. In the presence of noise, a comparison with the zero-frequency filtering technique (ZFF) and Dynamic programming projected Phase-Slope Algorithm (DYPSA) showed that performance of the SZCR technique is better than DYPSA and inferior to that of ZFF. For highpass-filtered speech, where ZFF performance suffers drastically, the identification rates of SZCR are better than those of DYPSA.
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Unfolding of a protein often proceeds through partial unfolded intermediate states (PUIS). PUIS have been detected in several experimental and simulation studies. However, complete analyses of transitions between different PUIS and the unfolding trajectory are sparse. To understand such dynamical processes, we study chemical unfolding of a small protein, chicken villin head piece (HP-36), in aqueous dimethyl sulfoxide (DMSO) solution. We carry out molecular dynamics simulations at various solution compositions under ambient conditions. In each concentration, the initial step of unfolding involves separation of two adjacent native contacts, between phenyl alanine residues (11-18 and 7-18). This first step induces, under appropriate conditions, subsequent separation among other hydrophobic contacts, signifying a high degree of cooperativity in the unfolding process. The observed sequence of structural changes in HP-36 on increasing DMSO concentration and the observed sequence of PUIS, are in approximate agreement with earlier simulation results (in pure water) and experimental observations on unfolding of HP-36. Peculiar to water-DMSO mixture, an intervening structural transformation (around 15% of DMSO) in the binary mixture solvent retards the progression of unfolding as composition is increased. This is reflected in a remarkable nonmonotonic composition dependence of RMSD, radius of gyration and the fraction of native contacts. At 30% mole fraction of DMSO, we find the extended randomly coiled structure of the unfolded protein. The molecular mechanism of DMSO induced unfolding process is attributed to the initial preferential solvation of the hydrophobic side chain atoms through the methyl groups of DMSO, followed by the hydrogen bonding of the oxygen atom of DMSO to the exposed backbone NH groups of HP-36.
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Nanosized Ce0.85M0.1Ru0.05O2-delta (M = Si, Fe) has been synthesized using a low temperature sonication method and characterized using XRD, TEM, XPS and H-2-TPR. The potential application of both the solid solutions has been explored as exhaust catalysts by performing CO oxidation. The addition of Si- and Fe-in Ce0.95Ru0.05O2-delta greatly enhanced the reducibility of Ce0.85M0.1Ru0.05O2-delta (M = Si, Fe), as indicated by the H-2-TPR study. The oxygen storage capacity has been used to correlate surface oxygen reactivity to the CO oxidation activity. Both the compounds reversibly release lattice oxygen and exhibit excellent CO oxidation activity with 99% conversion below 200 degrees C. A bifunctional reaction mechanism involving CO oxidation by the extraction of lattice oxygen and rejuvenation of oxide vacancy with gas feed O-2 has been used to correlate experimental data. The performance of both the solid solutions has also been investigated for energy application by performing the water gas shift reaction. The present catalysts are highly active and selective towards the hydrogen production and a lack of methanation activity is an important finding of present study.
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Bacteria present in natural environments such as soil have evolved multiple strategies to escape predation. We report that natural isolates of Enterobacteriaceae that actively hydrolyze plant-derived aromatic beta-glucosides such as salicin, arbutin and esculin, are able to avoid predation by the bacteriovorous amoeba Dictyostelium discoideum and nematodes of multiple genera belonging to the family Rhabditidae. This advantage can be observed under laboratory culture conditions as well as in the soil environment. The aglycone moiety released by the hydrolysis of beta-glucosides is toxic to predators and acts via the dopaminergic receptor Dop-1 in the case of Caenorhabditis elegans. While soil isolates of nematodes belonging to the family Rhabditidae are repelled by the aglycone, laboratory strains and natural isolates of Caenorhabditis sp. are attracted to the compound, mediated by receptors that are independent of Dop-1, leading to their death. The b-glucosides-positive (Bgl(+)) bacteria that are otherwise non-pathogenic can obtain additional nutrients from the dead predators, thereby switching their role from prey to predator. This study also offers an evolutionary explanation for the retention by bacteria of `cryptic' or `silent' genetic systems such as the bgl operon.
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Identifying symmetry in scalar fields is a recent area of research in scientific visualization and computer graphics communities. Symmetry detection techniques based on abstract representations of the scalar field use only limited geometric information in their analysis. Hence they may not be suited for applications that study the geometric properties of the regions in the domain. On the other hand, methods that accumulate local evidence of symmetry through a voting procedure have been successfully used for detecting geometric symmetry in shapes. We extend such a technique to scalar fields and use it to detect geometrically symmetric regions in synthetic as well as real-world datasets. Identifying symmetry in the scalar field can significantly improve visualization and interactive exploration of the data. We demonstrate different applications of the symmetry detection method to scientific visualization: query-based exploration of scalar fields, linked selection in symmetric regions for interactive visualization, and classification of geometrically symmetric regions and its application to anomaly detection.
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This paper deals with the thermo-physical changes that a droplet undergoes when it is radiatively heated in a levitated environment. The heat and mass transport model has been developed along with chemical kinetics within a cerium nitrate droplet. The chemical transformation of cerium nitrate to ceria during the process is predicted using Kramers' reaction mechanism which justifies the formation of ceria at a very low temperature as observed in experiments. The rate equation modeled by Kramers is modified suitably to be applicable within the framework of a droplet, and predicts experimental results well in both bulk form of cerium nitrate and in aqueous cerium nitrate droplet. The dependence of dissociation reaction rate on droplet size is determined and the transient mass concentration of unreacted cerium nitrate is reported. The model is validated with experiments both for liquid phase vaporization and chemical reaction. Vaporization and chemical conversion are simulated for different ambient conditions. The competitive effects of sensible heating rate and the rate of vaporization with diffusion of cerium nitrate is seen to play a key role in determining the mass fraction of ceria formed within the droplet. Spatially resolved modeling of the droplet enables the understanding of the conversion of chemical species in more detail.
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Flood is one of the detrimental hydro-meteorological threats to mankind. This compels very efficient flood assessment models. In this paper, we propose remote sensing based flood assessment using Synthetic Aperture Radar (SAR) image because of its imperviousness to unfavourable weather conditions. However, they suffer from the speckle noise. Hence, the processing of SAR image is applied in two stages: speckle removal filters and image segmentation methods for flood mapping. The speckle noise has been reduced with the help of Lee, Frost and Gamma MAP filters. A performance comparison of these speckle removal filters is presented. From the results obtained, we deduce that the Gamma MAP is reliable. The selected Gamma MAP filtered image is segmented using Gray Level Co-occurrence Matrix (GLCM) and Mean Shift Segmentation (MSS). The GLCM is a texture analysis method that separates the image pixels into water and non-water groups based on their spectral feature whereas MSS is a gradient ascent method, here segmentation is carried out using spectral and spatial information. As test case, Kosi river flood is considered in our study. From the segmentation result of both these methods are comprehensively analysed and concluded that the MSS is efficient for flood mapping.
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Room temperature operation, low detection limit and fast response time are highly desirable for a wide range of gas sensing applications. However, the available gas sensors suffer mainly from high temperature operation or external stimulation for response/recovery. Here, we report an ultrasensitive-flexible-silver-nanoparticle based nanocomposite resistive sensor for ammonia detection and established the sensing mechanism. We show that the nanocomposite can detect ammonia as low as 500 parts-per-trillion at room temperature in a minute time. Furthermore, the evolution of ammonia from different chemical reactions has been demonstrated using the nanocomposite sensor as an example. Our results demonstrate the proof-of-concept for the new detector to be used in several applications including homeland security, environmental pollution and leak detection in research laboratories and many others.
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This paper presents classification, representation and extraction of deformation features in sheet-metal parts. The thickness is constant for these shape features and hence these are also referred to as constant thickness features. The deformation feature is represented as a set of faces with a characteristic arrangement among the faces. Deformation of the base-sheet or forming of material creates Bends and Walls with respect to a base-sheet or a reference plane. These are referred to as Basic Deformation Features (BDFs). Compound deformation features having two or more BDFs are defined as characteristic combinations of Bends and Walls and represented as a graph called Basic Deformation Features Graph (BDFG). The graph, therefore, represents a compound deformation feature uniquely. The characteristic arrangement of the faces and type of bends belonging to the feature decide the type and nature of the deformation feature. Algorithms have been developed to extract and identify deformation features from a CAD model of sheet-metal parts. The proposed algorithm does not require folding and unfolding of the part as intermediate steps to recognize deformation features. Representations of typical features are illustrated and results of extracting these deformation features from typical sheet metal parts are presented and discussed. (C) 2013 Elsevier Ltd. All rights reserved.
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This paper reports on the characterization of an integrated micro-fluidic platform for controlled electrical lysis of biological cells and subsequent extraction of intracellular biomolecules. The proposed methodology is capable of high throughput electrical cell lysis facilitated by nano-composite coated electrodes. The nano-composites are synthesized using Carbon Nanotube and ZnO nanorod dispersion in polymer. Bacterial cells are used to demonstrate the lysis performance of these nanocomposite electrodes. Investigation of electrical lysis in the microchannel is carried out under different parameters, one with continuous DC application and the other under DC biased AC electric field. Lysis in DC field is dependent on optimal field strength and governed by the cell type. By introducing the AC electrical field, the electrokinetics is controlled to prevent cell clogging in the micro-channel and ensure uniform cell dispersion and lysis. Lysis mechanism is analyzed with time-resolved fluorescence imaging which reveal the time scale of electrical lysis and explain the dynamic behavior of GFP-expressing E. coli cells under the electric field induced by nanocomposite electrodes. The DNA and protein samples extracted after lysis are compared with those obtained from a conventional chemical lysis method by using a UV-Visible spectroscopy and fluorimetry. The paper also focuses on the mechanistic understanding of the nano-composite coating material and the film thickness on the leakage charge densities which lead to differential lysis efficiency.