996 resultados para Dispersion Stabilization


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Toll plazas are particularly susceptible to build-ups of vehicle-emitted pollutants because vehicles pass through in low gear. To look at this, three-dimensional computational fluid dynamics simulations of pollutant dispersion are used on the standard k e turbulence model. The effects of wind speed, wind direction and topography on pollutant dispersion were discussed. The Wuzhuang toll plaza on the Hefei-Nanjing expressway is considered, and the effects of the retaining walls along both sides of the plaza on pollutant dispersion is analysed. There are greater pollutant concentrations near the tollbooths as the angle between the direction of the wind and traffic increases implying that retaining walls impede dispersion. The slope of the walls has little influence on the variations in pollutant concentration.

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The crystal structure of the hydrated proton-transfer compound of the drug quinacrine [rac-N'-(6-chloro-2-methoxyacridin-9-yl)-N,N-diethylpentane-1,4-diamine] with 4,5-dichlorophthalic acid, C23H32ClN3O2+ . 2(C8H3Cl2O4-).4H2O (I), has been determined at 200 K. The four labile water molecules of solvation form discrete ...O--H...O--H... hydrogen-bonded chains parallel to the quinacrine side chain, the two N--H groups of which act as hydrogen-bond donors for two of the water acceptor molecules. The other water molecules, as well as the acridinium H atom, also form hydrogen bonds with the two anion species and extend the structure into two-dimensional sheets. Between these sheets there are also weak cation--anion and anion--anion pi-pi aromatic ring interactions. This structure represents only the third example of a simple quinacrine derivative for which structural data are available but differs from the other two in that it is unstable in the X-ray beam due to efflorescence, probably associated with the destruction of the unusual four-membered water chain structures.

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Difference and Dispersion is the fourth in a series of annual research papers produced by doctoral students from The Graduate School of Education, The University of Queensland, following their presentation at the School’s annual Postgraduate Research Conference in Education. The work featured herein celebrates the diversity of cultural and disciplinary backgrounds of education researchers who come from as far afield as Germany, Hong Kong, China, Nigeria, Russia, Singapore, Thailand and of course different parts of Australia. In keeping with a postmodern epistemology, ‘difference’ and ‘dispersion’ are key themes in apprehending the multiplicity of their research topics, methodologies, methods and speaking/writing positions. From widely differing contexts and situations, these writers address the consequences, implications and possibilities for education at the beginning of the third millennium. Their interest ranges from location-specific issues in schools and classrooms, change in learning contexts and processes, educational discourses and relations of power in diverse geographical settings, and the differing articulations of the local and the global in situated policy contexts. Conceived and developed in a spirit of ongoing dialogue with and insight to alternative views and visions of education and society, this edited collection exemplifies the quality in diversity and the high levels of scholarship and supervision at one of Australia’s finest Graduate Schools of Education.

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The crystal structure of the 2:1 proton-transfer compound of brucine with biphenyl-4,4’-disulfonate, bis(2,3-dimethoxy-10-oxostrychnidinium) biphenyl-4,4'-disulfonate hexahydrate (1) has been determined at 173 K. Crystals are monoclinic, space group P21 with Z = 2 in a cell with a = 8.0314(2), b = 29.3062(9), c = 12.2625(3) Å, β = 101.331(2)o. The crystallographic asymmetric unit comprises two brucinium cations, a biphenyl-4,4'-disulfonate dianion and six water molecules of solvation. The brucinium cations form a variant of the common undulating and overlapping head-to-tail sheet sub-structure. The sulfonate dianions are also linked head-to-tail by hydrogen bonds into parallel zig-zag chains through clusters of six water molecules of which five are inter-associated, featuring conjoint cyclic eight-membered hydrogen-bonded rings [graph sets R33(8) and R34(8)], comprising four of the water molecules and closed by sulfonate O-acceptors. These chain structures occupy the cavities between the brucinium cation sheets and are linked to them peripherally through both brucine N+-H...Osulfonate and Ocarbonyl…H-Owater to sulfonate O bridging hydrogen bonds, forming an overall three-dimensional framework structure. This structure determination confirms the importance of water in the stabilization of certain brucine compounds which have inherent crystal instability.

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The relationship between soil structure and the ability of soil to stabilize soil organic matter (SOM) is a key element in soil C dynamics that has either been overlooked or treated in a cursory fashion when developing SOM models. The purpose of this paper is to review current knowledge of SOM dynamics within the framework of a newly proposed soil C saturation concept. Initially, we distinguish SOM that is protected against decomposition by various mechanisms from that which is not protected from decomposition. Methods of quantification and characteristics of three SOM pools defined as protected are discussed. Soil organic matter can be: (1) physically stabilized, or protected from decomposition, through microaggregation, or (2) intimate association with silt and clay particles, and (3) can be biochemically stabilized through the formation of recalcitrant SOM compounds. In addition to behavior of each SOM pool, we discuss implications of changes in land management on processes by which SOM compounds undergo protection and release. The characteristics and responses to changes in land use or land management are described for the light fraction (LF) and particulate organic matter (POM). We defined the LF and POM not occluded within microaggregates (53-250 mum sized aggregates as unprotected. Our conclusions are illustrated in a new conceptual SOM model that differs from most SOM models in that the model state variables are measurable SOM pools. We suggest that physicochemical characteristics inherent to soils define the maximum protective capacity of these pools, which limits increases in SOM (i.e. C sequestration) with increased organic residue inputs.

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Statistical modeling of traffic crashes has been of interest to researchers for decades. Over the most recent decade many crash models have accounted for extra-variation in crash counts—variation over and above that accounted for by the Poisson density. The extra-variation – or dispersion – is theorized to capture unaccounted for variation in crashes across sites. The majority of studies have assumed fixed dispersion parameters in over-dispersed crash models—tantamount to assuming that unaccounted for variation is proportional to the expected crash count. Miaou and Lord [Miaou, S.P., Lord, D., 2003. Modeling traffic crash-flow relationships for intersections: dispersion parameter, functional form, and Bayes versus empirical Bayes methods. Transport. Res. Rec. 1840, 31–40] challenged the fixed dispersion parameter assumption, and examined various dispersion parameter relationships when modeling urban signalized intersection accidents in Toronto. They suggested that further work is needed to determine the appropriateness of the findings for rural as well as other intersection types, to corroborate their findings, and to explore alternative dispersion functions. This study builds upon the work of Miaou and Lord, with exploration of additional dispersion functions, the use of an independent data set, and presents an opportunity to corroborate their findings. Data from Georgia are used in this study. A Bayesian modeling approach with non-informative priors is adopted, using sampling-based estimation via Markov Chain Monte Carlo (MCMC) and the Gibbs sampler. A total of eight model specifications were developed; four of them employed traffic flows as explanatory factors in mean structure while the remainder of them included geometric factors in addition to major and minor road traffic flows. The models were compared and contrasted using the significance of coefficients, standard deviance, chi-square goodness-of-fit, and deviance information criteria (DIC) statistics. The findings indicate that the modeling of the dispersion parameter, which essentially explains the extra-variance structure, depends greatly on how the mean structure is modeled. In the presence of a well-defined mean function, the extra-variance structure generally becomes insignificant, i.e. the variance structure is a simple function of the mean. It appears that extra-variation is a function of covariates when the mean structure (expected crash count) is poorly specified and suffers from omitted variables. In contrast, when sufficient explanatory variables are used to model the mean (expected crash count), extra-Poisson variation is not significantly related to these variables. If these results are generalizable, they suggest that model specification may be improved by testing extra-variation functions for significance. They also suggest that known influences of expected crash counts are likely to be different than factors that might help to explain unaccounted for variation in crashes across sites