João T. Mexia

A dynamic model for the electrokinetic removal of copper from a polluted soil

The electrokinetic process is a promising decontamination technique for removal of heavy metals from polluted sites. The authors have studied the removal of copper (Cu) from an industrially heavy-metal-contaminated soil, using the application of electric current. A sequential extraction procedure was used to monitor changes in the chemical associations of Cu during the electrokinetic treatment of the soil. A dynamic model is presented for the removal of Cu by electrokinetic decontamination. This model, based on a biregressional design, enables a joint analysis of the experiments which were carried out in a laboratory cell. The removal of Cu was found to be a local phenomenon, dependent on the release of metal by different soil fractions, cumulative and controlled by time as well as pH.

Assessing the diurnal variability of pharmaceutical and personal care products in a full-scale activated sludge plant

An intensive sampling campaign has been carried out in a municipal wastewater treatment plant (WWTP) to assess the dynamics of the influent pharmaceutical active compounds (PhAC) and musks. The mass loadings of these compounds in wastewater influents displayed contrasting diurnal variations depending on the compound. The musks and some groups of PhACs tended to follow a similar diurnal trend as compared to macropollutants, while the majority of PhACs followed either the opposite trend or no repeatable trend. The total musk loading to the WWTP was 0.74 ± 0.25 g d(-1), whereas the total PhAC mass loading was 84.7 ± 63.8 g d(-1). Unlike the PhACs, the musks displayed a high repeatability from one sampling day to the next. The range of PhAC loadings in the influent to WWTPs can vary several orders of magnitude from one day or week to the next, representing a challenge in obtaining data for steady-state modelling purposes.

Best linear unbiased estimates, duality of f tests and the Scheffe´ multiple comparison method in the presence of controlled heterosecdasticity

Abstract The main purpose of this paper is the use of best linear unbiased estimates in order to build F tests with duality properties. The relationship between those properties and the Scheffe multiple comparison method is analyzed. A situation of controlled heteroscedasticity, in which the vector of observations has a variance-covariance matrix σ2C, with C known and regular, is considered and full-rank is not assumed. The paper comprises, besides an introduction, four sections. In the first of these, Moore—Pemrose inverses are used to obtain orthogonal projection matrices. These orthogonal projection matrices are then used, in the following section, to obtain best linear unbiased estimates of estimable vectors. In obtaining these estimates the reduction of the controlled heteroscedasticity of the vector of observations is carried through. Once obtained the best linear unbiased estimates the construction of the F tests is performed. The F tests that are obtained are unbiased and possess duality. In a final section the relation between the duality of the F tests and the Scheffe multiple comparisons method is considered.

Jordan algebras, generating pivot variables and orthogonal normal models

Abstract Jordan algebras are used to present normal orthogonal models in a canonical form. It is shown that the usual factor based formulation of such models may, many times, be obtained imposing restrictions on the parameters of the canonical formulation, and examples are presented. The canonical model formulation is interesting since it leads to complete sufficient statistics. These statistics may be used to obtain pivot variables that induce probability measures in the parameter space. Monte Carlo generated samples, of arbitrary size, may be obtained having the induced probability measures. These samples may be screened so that the restrictions corresponding to the direct model formulations hold. Inference is presented using such samples.

Oxidative stress in familial adenomatous polyposis.

The prooxidant/antioxidant imbalance in familial adenomatous polyposis (FAP) is suggested by (i) the intimate connection between APC and prostaglandin H synthase-2 genes, (ii) the increase of the free radical-generating enzyme xanthine oxidase, and (iii) the decrease of antioxidant defences. In this research work we evaluated lipid peroxidation measuring the thiobarbituric acid (TBA) reactive products and we studied the activities of superoxide dismutase (SOD) and catalase as well as the levels of ascorbate and tocopherols in the peripheral blood cells from a total of 27 FAP patients and 83 normal controls. TBA-reactive products were determined according to a previously published method. SOD and catalase activities were determined by the spectrophotometric monitoring of the inhibition of pyrogallol autoxidation and the hydrogen peroxide decomposition rate, respectively. Ascorbate levels were determined by a modified 2,4-dinitrophenylhydrazine method and tocopherol levels by a modified Emmerie-Engle method. The levels of TBA-reactive products were higher in FAP patients than in normal controls. Although no statistically significant differences in SOD and catalase activities were observed between FAP patients and normal controls, we found that ascorbate and tocopherol levels were significantly lower in FAP patients than in normal controls, as assessed by the Mann-Whitney test. Hence, this finding of an imbalance in the prooxidant/antioxidant status may contribute towards new strategies for prevention and therapy in FAP patients.

Glutathione S transferase mu polymorphism and gastric cancer in the Portuguese population

The glutathione S-transferases appear to form part of a protective mechanism against the development of cancer where environmental chemical carcinogens are involved. In humans one member of the mu class gene family (GSTM1) has been shown to be polymorphic and is only expressed in ~50% of individuals. Previous studies have shown a possible link between the null phenotype and susceptibility to cancer but have been equivocal regarding stomach cancer. To evaluate any association in Portuguese gastric cancer individuals with GSTM1 variability, we performed GST M 1 polymorphism by PCR amplification in 148 gastric cancer patients and in 84 healthy control individuals. We found no statistical differences between the gastric cancer and control populations (wild type phenotype: 52%, 48%; null phenotype: 48%, 52%, respectively). A subset analysis into site of tumour also revealed no significant differences between the groups, although we found a slight increase of the wild type phenotype in the samples of the antrum compared with the control population (57% vs 48%, respectively; 2= 1.18; p 0.28) and a slight increase of the null phenotype in the signet ring cells/mucocellular group (2= 1.05; p 0.3). However, in both cases it did not reach statistical significance. A subset analysis of the histological groups following the WHO criteria revealed a statistically significant difference (2= 3.704; p 0.05) between the moderately differentiated gastric adenocarcinoma and the presence of the wild type phenotype. These results do not support the hypothesis that the GSTM1 null phenotype predisposes to gastric cancer in the Portuguese population and the moderately differentiated gastric adenocarcinoma seems to be associated with the presence of the G STM 1 wild type phenotype.

Regressional modeling of electrodialytic removal of Cu, Cr and as from CCA treated timber waste : application to sawdust

Waste of wood treated with chromated copper arsenate (CCA) is expected to increase in volume over the next decades. Alternative disposal options to landfilling are becoming more attractive to study, especially those that promote re-use. The authors have studied and modeled the electrodialytic (ED) removal of Cu, Cr and As from CCA treated timber waste. The method uses a low-level direct current as the “cleaning agent”, combining the electrokinetic movement of ions in the matrix with the principle of electrodialysis. The technique was tested in eight experiments using a laboratory cell on sawdust of out-of-service CCA treated Pinus pinaster Ait. poles. The experiments differ because the sawdust was saturated with different assisting agents and different percentages of them. In order to select the best assisting agent in jointly removing the three metals and subsequently the best percentage of the selected assistant agent, a statistical analysis was made. First, three experiments were selected as being the best. Second, for the selected experiments, a polynomial model was found to describe the time evolution of the total concentrations of each metal in the electrolytes. Based on this modeling, a multi-treatment regression approach was further used to select the final range of experiments.

A comparison between Joint Regression Analysis and the Additive Main and Multiplicative Interaction model: the robustness with increasing amounts of missing data

This paper joins the main properties of joint regression analysis (JRA), a model based on the Finlay-Wilkinson regression to analyse multi-environment trials, and of the additive main effects and multiplicative interaction (AMMI) model. The study compares JRA and AMMI with particular focus on robustness with increasing amounts of randomly selected missing data. The application is made using a data set from a breeding program of durum wheat (Triticum turgidum L., Durum Group) conducted in Portugal. The results of the two models result in similar dominant cultivars (JRA) and winner of mega-environments (AMMI) for the same environments. However, JRA had more stable results with the increase in the incidence rates of missing values.

Modelling series of studies with a common structure

Consider the situation where the Structuration des Tableaux a Trois Indices de la Statistique (STATIS) methodology is applied to a series of studies, each study being represented by data and weight matrices. Relations between studies may be captured by the Hilbert-Schmidt product of these matrices. Specifically, the eigenvalues and eigenvectors of the Hilbert-Schmidt matrix S may be used to obtain a geometrical representation of the studies. The studies in a series may further be considered to have a common structure whenever their corresponding points lie along the first axis. The matrix S can be expressed as the sum of a rank 1 matrix @luu^T with an error matrix E. Therefore, the components of the vector @lu are sufficient to locate the points associated to the studies. Former models for S where vec(E) are mathematically tractable and yet do not take into account the symmetry of the matrix S. Thus a new symmetric model is proposed as well as the corresponding tests for a common structure. It is further shown how to assess the goodness of fit of such models. An application to the human immunodeficiency virus (HIV) infection is used for assessing the proposed model.

Using confidence bands for parallel texts alignment

This paper describes a language independent method for alignment of parallel texts that makes use of homograph tokens for each pair of languages. In order to filter out tokens that may cause misalignment, we use confidence bands of linear regression lines instead of heuristics which are not theoretically supported. This method was originally inspired on work done by Pascale Fung and Kathleen McKeown, and Melamed, providing the statistical support those authors could not claim.