137 resultados para sequential extraction

em Queensland University of Technology - ePrints Archive


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Assessment of heavy metal bioavailability in sediments is complex because of the number of partial extraction methods available for the assessment and the general lack of certified reference materials. This study evaluates five different extraction methodologies to ascertain the relative strengths and weaknesses of each method. The results are then compared to previously published work to ascertain the most effective partial extraction technique, which was established to be dilute (0.75 – 1 M) nitric acid solutions. These results imply that single reagent; weak acid extractions provide a better assessment of potentially bioavailable metals than the chelating agents used in sequential extraction methods.

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Successive alkalinity producing systems (SAPSs) are widely used for treating acid mine drainage (AMD) and alleviating clogging commonly occurring in limestone systems due to an amorphous ferric precipitate. In this study, iron dust, bone char, micrite and their admixtures were used to treat arseniccontaining AMD. A particular interest was devoted to arsenic removal performance, mineralogical constraints on arsenic retention ability and permeability variation during column experiment for 140 days. The results showed that the sequence of the arsenic removal capacity was as follows: bone char > micrite > iron dust. The combination of 20% v/v iron dust and 80% v/v bone char/micrite columns can achieve better hydraulic conductivity and phosphorus-retention capacity than single micrite and bone char columns. The addition of iron dust created reductive environment and resulted in the transformation of coating material from colloidal phase to secondary mineral phase, such as green rust and phosphoerrite, which obviously ameliorates hydraulic conductivity of systems. The sequential extraction experiments indicated that the stable fractions of arsenic in columns were enhanced with help of iron dust compared to single bone char and micrite columns. A combination of iron dust and micrite/bone char represented a potential SAPS for treating As-containing AMD.

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The computation of compact and meaningful representations of high dimensional sensor data has recently been addressed through the development of Nonlinear Dimensional Reduction (NLDR) algorithms. The numerical implementation of spectral NLDR techniques typically leads to a symmetric eigenvalue problem that is solved by traditional batch eigensolution algorithms. The application of such algorithms in real-time systems necessitates the development of sequential algorithms that perform feature extraction online. This paper presents an efficient online NLDR scheme, Sequential-Isomap, based on incremental singular value decomposition (SVD) and the Isomap method. Example simulations demonstrate the validity and significant potential of this technique in real-time applications such as autonomous systems.

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The one-dimensional propagation of a combustion wave through a premixed solid fuel for two-stage kinetics is studied. We re-examine the analysis of a single reaction travelling-wave and extend it to the case of two-stage reactions. We derive an expression for the travelling wave speed in the limit of large activation energy for both reactions. The analysis shows that when both reactions are exothermic, the wave structure is similar to the single reaction case. However, when the second reaction is endothermic, the wave structure can be significantly different from single reaction case. In particular, as might be expected, a travelling wave does not necessarily exist in this case. We establish conditions in the limiting large activation energy limit for the non-existence, and for monotonicity of the temperature profile in the travelling wave.

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The Automated Estimator and LCADesign are two early examples of nD modelling software which both rely on the extraction of quantities from CAD models to support their further processing. The issues of building information modelling (BIM), quantity takeoff for different purposes and automating quantity takeoff are discussed by comparing the aims and use of the two programs. The technical features of the two programs are also described. The technical issues around the use of 3D models is described together with implementation issues and comments about the implementation of the IFC specifications. Some user issues that emerged through the development process are described, with a summary of the generic research tasks which are necessary to fully support the use of BIM and nD modelling.

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Monitoring unused or dark IP addresses offers opportunities to extract useful information about both on-going and new attack patterns. In recent years, different techniques have been used to analyze such traffic including sequential analysis where a change in traffic behavior, for example change in mean, is used as an indication of malicious activity. Change points themselves say little about detected change; further data processing is necessary for the extraction of useful information and to identify the exact cause of the detected change which is limited due to the size and nature of observed traffic. In this paper, we address the problem of analyzing a large volume of such traffic by correlating change points identified in different traffic parameters. The significance of the proposed technique is two-fold. Firstly, automatic extraction of information related to change points by correlating change points detected across multiple traffic parameters. Secondly, validation of the detected change point by the simultaneous presence of another change point in a different parameter. Using a real network trace collected from unused IP addresses, we demonstrate that the proposed technique enables us to not only validate the change point but also extract useful information about the causes of change points.