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High salinity and natural organic matter are both known to facilitate migration of toxic or radioactive metals in geochemical systems, but little is known on their combined effect. We investigated complexation of Tb(III) and Eu(III) (as analogues for trivalent actinides) with fulvic acid and their adsorption onto a natural clay in the presence of NaCl, MgCl 2 and CaCl 2 up to very high ionic strengths. 160 Tb, 152 Eu and 14 C-labelled fulvic acid were employed as radiotracers, allowing investigations at very low concentrations according to probable conditions in far-field scenarios of nuclear waste repositories. A combined K d approach (Linear Additive Model) was tested for suitability in predicting solid–liquid distribution of metals in the presence of organic matter based on the interactions in the constituent subsystems. In this analysis, it could be shown that high ionic strength does not further enhance the mobilizing potential of humic matter. A quantitative reproduction of the influence of fulvic acid failed for most systems under study. Assumptions and limitations of the model are discussed. [ABSTRACT FROM AUTHOR]

Abstract: Sorption of technetium by alumina has been studied in absence as well as in presence of humic acid using 95Tcm as a tracer. Measurements were carried out at fixed ionic strength (0.1M NaClO4) under varying pH (3–10) as well as redox (aerobic and reducing anaerobic) conditions. Under aerobic conditions, negligible sorption of technetium was observed onto alumina both in absence and in presence of humic acid. However, under reducing conditions (simulated with [Sn(II)]=10−6 M), presence of humic acid enhanced the sorption of technetium in the low pH region significantly and decreased at higher pH with respect to that in absence of humic acid. Linear additive as well as surface complexation modeling of Tc(IV) sorption in presence of humic acid indicated the predominant role of sorbed humic acid in deciding technetium sorption onto alumina. [Copyright &y& Elsevier]

Safety assessments for radioactive waste disposal require estimations of the migration of radionuclides in soils. The influence of humic acid (HA) on the sorption of uranium in its +4 oxidation state to kaolin has been examined from pH 4 to 8, with HA concentrations of 15-200 ppm. In the absence of HA, 20-40% of the U(IV) was in solution, with more sorption occurring at higher pH. The presence of HA solubilised up to 90% of the uranium with higher solubilities at higher HA concentrations and higher pH values. Uranium sorption was mapped against HA sorption, and it was found that there was a lower level of U(IV) sorption than can be accounted for by just measuring HA sorption. However, this effect got less marked as the pH rose. Sensitivity analysis indicated that the fraction of surface-bound HA is the controlling parameter for modelling in these systems. [ABSTRACT FROM AUTHOR]

A typical microarray experiment attempts to ascertain which genes display differential expression in different samples. We model the data by using a two-component mixture model and develop an empirical Bayesian thresholding procedure, which was originally introduced for thresholding wavelet coefficients, as an alternative to the existing methods for determining differential expression across thousands of genes. The method is built on sound theoretical properties and has easy computer implementation in the R statistical package. Furthermore, we consider improvements to the standard empirical Bayesian procedure when replication is present, to increase the robustness and reliability of the method. We provide an introduction to microarrays for those who are unfamilar with the field and the proposed procedure is demonstrated with applications to two-channel complementary DNA microarray experiments. [ABSTRACT FROM AUTHOR]

This paper proposes the use of more than one clustering method to improve clustering performance. Clustering is an optimization procedure based on a specific clustering criterion. Clustering combination can be regarded as a technique that constructs and processes multiple clustering criteria. Since the global and local clustering criteria are complementary rather than competitive, combining these two types of clustering criteria may enhance the clustering performance. In our past work, a multi-objective programming based simultaneous clustering combination algorithm has been proposed, which incorporates multiple criteria into an objective function by a weighting method, and solves this problem with constrained nonlinear optimization programming. But this algorithm has high computational complexity. Here a sequential combination approach is investigated, which first uses the global criterion based clustering to produce an initial result, then uses the local criterion based information to improve the initial result with a probabilistic relaxation algorithm or linear additive model. Compared with the simultaneous combination method, sequential combination has low computational complexity. results on some simulated data and standard test data are reported. It appears that clustering performance improvement can be achieved at low cost through sequential combination. [ABSTRACT FROM AUTHOR]

The weighted linear choice model is one of the most popular models in the social sciences. In this model the utility of a choice object is represented as a weighted sum of attribute-level desirabilities, where the weights are attribute importances. In many empirical contexts the choice objects are such that individuals are highly correlated in terms of their desirability ordering of levels within attribute (e.g., price levels, durability levels, etc.) but may differ appreciably in terms of their evaluations of each attribute's importance. In this paper we address the problem of how dissimilar two individuals may be, in a rank correlation sense, given that they agree completely on the desirability ordering of levels within attributes, but may disagree considerably regarding the importance they attach to the attributes themselves. The problem has interesting implications regarding the potential value of clustering individuals' utility functions for market segmentation or other such purposes. [ABSTRACT FROM AUTHOR]