Elsa Moreira

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.

Randomized Sample Size F Tests for the One‐Way Layout

Distributions and densities for F test statistics are obtained assuming random sample sizes, thus getting random degrees of freedom and non‐centrality parameters. Classical optimum properties are extended to this new setup as well as Scheffe Theorem for simultaneous confidence intervals.

Inference forLorthogonal models

Abstract A mixed model is orthogonal when the matrices commute. The vectors are fixed vectors and the and en are random. For these models we have very interesting results namely we have UMVUE for the relevant parameters when normality is assumed. We now intend to generalize that class of models taking with L a matrix whose column vectors are linearly independent.

Is Drought Occurrence And Severity Increasing Due to Climate Change? Analysing Drought Class Transitions With Loglinear Models

SPI time series in a 12 month time scale from 6 sites in Alentejo and Algarve, in the south of Portugal, within the period from October 1896 to September 2005, were divided into three or four periods depending on the data set length and a Loglinear modeling approach has been used to investigate differences relative to drought class transitions among these periods. Four drought severity classes were considered. The drought class transitions were computed for the different periods to form a 3-dimensional contingency table. The application of Loglinear modeling to these data allowed the comparison of the periods in terms of probabilities of transition between drought classes in order to detect a possible trend in time evolution of droughts which could be related to climate change

Integration of HIV in the Human Genome: Which Sites Are Preferential? A Genetic and Statistical Assessment

Chromosomal fragile sites (FSs) are loci where gaps and breaks may occur and are preferential integration targets for some viruses, for example, Hepatitis B, Epstein-Barr virus, HPV16, HPV18, and MLV vectors. However, the integration of the human immunodeficiency virus (HIV) in Giemsa bands and in FSs is not yet completely clear. This study aimed to assess the integration preferences of HIV in FSs and in Giemsa bands using an in silico study. HIV integration positions from Jurkat cells were used and two nonparametric tests were applied to compare HIV integration in dark versus light bands and in FS versus non-FS (NFSs). The results show that light bands are preferential targets for integration of HIV-1 in Jurkat cells and also that it integrates with equal intensity in FSs and in NFSs. The data indicates that HIV displays different preferences for FSs compared to other viruses. The aim was to develop and apply an approach to predict the conditions and constraints of HIV insertion in the human genome which seems to adequately complement empirical data.

Estimation and Orthogonal Block Structure

Estimators with good behaviors for estimable vectors and variance components are obtained for a class of models that contains the well known models with orthogonal block structure, OBS, see [15], [16] and [1], [2]. The study observations of these estimators uses commutative Jordan Algebras, CJA, and extends the one given for a more restricted class of models, the models with commutative orthogonal block structure, COBS, in which the orthogonal projection matrix on the space spanned by the means vector commute with all variance-covariance matrices, see [7].

Genetic and Statistical Study of HIV Integration in the Human Genome

Integration of the human immunodeficiency virus (HIV) DNA into human genome is essential for HIV-induced disease. The human genome is organized into chromosomes and within these we can define the chromosomal fragile sites. Our aim is to contribute to help clarifying the integration sites preferences of HIV1 and HIV2 in fragile or non-fragile regions. Here we apply statistical techniques, namely non-parametric tests and analysis of variance for analyzing two sets of data of HIV1 and HIV2 integrations in the human genome. The results show that the integrations occur significantly with more intensity in the non-fragile regions of the human genome and that the HIV1 in particular has the major contribution to this fact. This study could have implications in human disease.

Clustering of log-linear models using LRT p-values to assess homogeneous regions relative to drought class transitions

In this study, a statistical method is used aiming at finding if Alentejo, southern Portugal, could be considered a homogeneous region for drought management purposes. Time series of the standardized precipitation index (SPI) were obtained for 40 locations in the region using precipitation data for the period 1932–1999 (67 years). Contingency tables for the transitions between SPI drought classes were obtained for these time series. Log-linear models were fitted to these contingency tables to estimate the probabilities for drought class transitions. An approach of model clustering, where log-linear models were clustered using the asymptotic p-value of a likelihood ratio test (LRT) for the equality of parameters between pairs of models, was applied. Two types of LRT were performed: one considering all the parameters of the log-linear model of interest; another considering just some parameters of interest. Two p-value similarity matrices were computed to find similar models that could form clusters, however, the hypothesis of model clustering was not verified. No clustering was found, thus based on the presented technique, the Alentejo could be considered a homogeneous region relative to drought class transitions.