22 resultados para Garbage compound

em Deakin Research Online - Australia


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The synthesis of the first example of an organotin double ladder (6) containing a functional group within the spacer is reported. In the solid state, compound 6 shows an interlaminar cavity whose size and shape suggest the possibility of host–guest chemistry. 119Sn-NMR and ESMS show that compound 6 undergoes extensive dissociation in solution. ESMS of compound 6 to which have been added Li+, Na+, Mg2+ or Cu2+ show only minimal interaction.


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The aim of this study was to determine if taste interactions occur when bitter stimuli are mixed. Eight bitter stimuli were employed: denatonium benzoate (DB), quinine-HCl (QHCl), sucrose octaacetate (SOA), urea, L-tryptophan (L-trp), L-phenylalanine (L-phe), ranitidine-HCl, and Tetralone. The first experiment constructed individual psychophysical curves for each subject (n = 19) for each compound to account for individual differences in sensitivities when presenting bitter compounds in experiment 2. Correlation analysis revealed two groupings of bitter compounds at low intensity (1, L-trp, L-phe, and ranitidine; 2, SOA and QHCl), but the correlations within each group decreased as the perceived intensity increased. In experiment 2, intensity ratings and two-alternative forced-choice discrimination tasks showed that bitter compounds generally combine additively in mixture and do not show interactions with a few specific exceptions. The methods employed detected synergy among sweeteners, but could not detect synergy among these eight bitter compounds. In general, the perceived bitterness of these binary bitter-compound mixtures was an additive function of the total bitter-inducing stimuli in the mouth.

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The chemical senses have been underutilised as analytical instruments, although as detectors of chemicals our senses are highly specialised biological machines. This paper reviews the current state of knowledge of the chemical senses. A novel technique was used to isolate and identify a flavour-active non-steroidal antiinflammatory compound in virgin olive oil.

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The thesis shows that a plant extract favourably affects glucose utilisation and production in vitro, and identifies genes/biological pathways involved in its actions. The extract underwent fractionation and screening for effects observed. Chemical studies of active fractions led to the isolation of a compound shown to have potential anti-diabetic properties.

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Describes the development of a cell to hold loose wool fibre, fabric and yarn samples for the collection of Fourier Transform Raman spectra. Then follows a detailed study of reactions of Lanasol (Ciba) dyes with wool, the dyes forming covalent bonds with various amino acids in the fibres.

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The present paper describes processing of a lotus-structured porous Ti-Al/Ti composite by SHS with Ti powder and Al rods. Ti-Al intermetallic compound was formed in a range of 200-300μm around the pore by SHS of reaction between Ti and Al, resulting in formation of a lotus-structured porous Ti-Al/Ti composite.

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Recent research on the olive oil phenolic, oleo canthal has led to speculation that it may confer some of the health benefits associated with a traditional Mediterranean diet. Oleocanthal produces a peppery, stinging sensation at the back of the throat similar to that of the non-steroidal anti-inflammatory drug (NSAID), ibuprofen. This led to the hypothesis that the perceptual similarity between oleocanthal and ibuprofen may indicate similar pharmacological properties. Subsequent studies have proved the hypothesis and oleocanthal was shown not only to inhibit inflammation in the same way as ibuprofen does, but it was found to be substantially more potent than this NSAID. It is important to note that inflammation has been demonstrated to playa significant role in the development of a number of chronic diseases, such as cardiovascular disease (CVD) and certain types of cancers. Therefore, as a result of dietary feeding with olive oil as a part of the traditional Mediterranean diet, a reduction in inflammation produced by oleocanthal is speculated to be the potential mechanism that is partially responsible for the health benefits associated with this dietary pattern. This review summarizes the current knowledge on oleocanthal, in tenns of its physiological and sensory properties, as well as a discussion on the factors that have the ability to affect oleocanthal concentrations in extra virgin olive oils (EVOOs).

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Chronic inflammation is a critical factor in the pathogenesis of many inflammatory disease states including cardiovascular disease, cancer, diabetes, degenerative joint diseases and neurodegenerative diseases. Chronic inflammatory states are poorly understood, however it is known that dietary habits can evoke or attenuate inflammatory responses. Popular methods to deal with inflammation and its associated symptoms involve the use of non steroidal anti-inflammatory drugs, however the use of these drugs are associated with severe side effects. Therefore, investigations concerned with natural methods of inflammatory control are warranted. A traditional Mediterranean diet has been shown to confer some protection against the pathology of chronic diseases through the attenuation of proinflammatory mediators and this has been partially attributed to the high intake of virgin olive oil accompanying this dietary regime. Virgin olive oil contains numerous phenolic compounds that exert potent anti-inflammatory actions. Of interest to this paper is the recently discovered phenolic compound oleocanthal. Oleocanthal is contained in virgin olive oil and possesses similar anti-inflammatory properties to ibuprofen. This pharmacological similarity has provoked interest in oleocanthal and the few studies conducted thus far have verified its anti-inflammatory and potential therapeutic actions. A review of the health benefits of the Mediterranean diet and antiinflammatory properties of virgin olive oil is presented with the additional emphasis on the pharmacological and anti-inflammatory properties of the phenolic compound oleocanthal.

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To improve the accuracy of access prediction, a prefetcher for web browsing should recognize the fact that a web page is a compound. By this term we mean that a user request for a single web page may require the retrieval of several multimedia items. Our prediction algorithm builds an access graph that captures the dynamics of web navigation rather than merely attaching probabilities to hypertext structure. When it comes to making prefetch decisions, most previous studies in speculative prefetching resort to simple heuristics, such as prefetching an item with access probabilities larger than a manually tuned threshold. The paper takes a different approach. Specifically, it models the performance of the prefetcher and develops a prefetch policy based on a theoretical analysis of the model. In the analysis, we derive a formula for the expected improvement in access time when prefetch is performed in anticipation for a compound request. We then develop an algorithm that integrates prefetch and cache replacement decisions so as to maximize this improvement. We present experimental results to demonstrate the effectiveness of compound-based prefetching in low bandwidth networks.

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A preliminary study showed that the inhibitor lanthanum 4-hydroxy cinnamate ((La4OHcin)3) at a concentration of 400 ppm prevented the hydrogen embrittlement (HE) of SAE 4340 steel tensile specimens when tested under slow strain rate conditions in a 0.01M NaCl. In the presence of the inhibitor, a complex film formed on the surface of specimens during the slow strain rate test (SSRT), and no corrosion pits were detected. Electrochemical polarization studies indicated that the La(4OHcin)3 acted as an anodic inhibitor in the NaCl solution. This article also discusses the mechanism of HE inhibition by La(4OHcin)3.

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This paper presents a new semi-supervised method to effectively improve traffic classification performance when few supervised training data are available. Existing semi supervised methods label a large proportion of testing flows as unknown flows due to limited supervised information, which severely affects the classification performance. To address this problem, we propose to incorporate flow correlation into both training and testing stages. At the training stage, we make use of flow correlation to extend the supervised data set by automatically labeling unlabeled flows according to their correlation to the pre-labeled flows. Consequently, the traffic classifier has better performance due to the extended size and quality of the supervised data sets. At the testing stage, the correlated flows are identified and classified jointly by combining their individual predictions, so as to further boost the classification accuracy. The empirical study on the real-world network traffic shows that the proposed method outperforms the state-of-the-art flow statistical feature based classification methods.