Francesca Torti

Membrane phosphorylation leads to the partial detachment of the chlorophyll a/b protein from photosystem II

Abstract The hypothesis that the chlorophyll fluorescence decline due to membrane phosphorylation is caused principally by the detachment and removal of LHCP from the LHCP-PS II matrix is examined. It is demonstrated that when membranes are phosphorylated in the dark (a) the fluorescence decline is greater when excited by light enriched in wavelengths absorbed mainly by LHCP (475 nm) than when excited by light absorbed to a large extent also by the PS II complex (435 nm), (b) titration with different artificial quenchers of chlorophyll fluorescence is unchanged after the phosphorylation-induced fluorescence decline, and (c) the F v / F m ratio does not change after the phosphorylation-induced fluorescence decline. These data indicate that it is indeed principally LHCP that interacts with the quencher (PS I presumably). This interaction involves a small fraction of the total PS II-coupled LHCP, which becomes functionally detached from the LHCP-PS II matrix.

Benchmark testing of algorithms for very robust regression: FS, LMS and LTS

The methods of very robust regression resist up to 50% of outliers. The algorithms for very robust regression rely on selecting numerous subsamples of the data. New algorithms for LMS and LTS estimators that have increased computational efficiency due to improved combinatorial sampling are proposed. These and other publicly available algorithms are compared for outlier detection. Timings and estimator quality are also considered. An algorithm using the forward search (FS) has the best properties for both size and power of the outlier tests.

New robust dynamic plots for regression mixture detection

The forward search is a powerful general method for detecting multiple masked outliers and for determining their effect on inferences about models fitted to data. From the monitoring of a series of statistics based on subsets of data of increasing size we obtain multiple views of any hidden structure. One of the problems of the forward search has always been the lack of an automatic link among the great variety of plots which are monitored. Usually it happens that a lot of interesting features emerge unexpectedly during the progression of the forward search only when a specific combination of forward plots is inspected at the same time. Thus, the analyst should be able to interact with the plots and redefine or refine the links among them. In the absence of dynamic linking and interaction tools, the analyst risks to miss relevant hidden information. In this paper we fill this gap and provide the user with a set of new robust graphical tools whose power will be demonstrated on several regression problems. Through the analysis of real and simulated data we give a series of examples where dynamic interaction with different “robust plots” is used to highlight the presence of groups of outliers and regression mixtures and appraise the effect that these hidden groups exert on the fitted model.

Detecting Price Outliers in European Trade Data with the Forward Search

We describe empirical work in the domain of clustering and outlier detection, for the analysis of European trade data. It is our first attempt to evaluate benefits and limitations of the forward search approach for regression and multivariate analysis Atkinson and Riani (Robust diagnostic regression analysis, Springer, 2000), Atkinson et al. (Exploring multivariate data with the forward search, Springer, 2004), within a concrete application scenario and in relation to a comparable backward method developed in the JRC by Arsenis et al. (Price outliers in eu external trade data, Enlargement and Integration Workshop 2005, 2005). Our findings suggest that the automatic clustering based on Mahalanobis distances may be inappropriate in presence of a high-density area in the dataset. Follow up work is discussed extensively in Riani et al. (Fitting mixtures of regression lines with the forward search, Mining massive data sets for security, IOS, 2008).

Discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample”

We contribute to the discussion of an article where Andrea Cerioli, Marco Riani, Anthony Atkinson and Aldo Corbellini review the advantages of analyzing multivariate data by monitoring how the estimated model parameters change as the estimation parameters vary. The focus is on robust methods and their sensitivity to the nominal efficiency and breakdown point. In congratulating with the authors for the clear and stimulating exposition, we contribute to its discussion with an overview of what we experienced in applying the monitoring in our application domain.

Heteroscedasticity, Multiple Populations and Outliers in Trade Data

International trade data are often affected by multiple linear populations and heteroscedasticity. An immediate consequence is the false declaration of outliers. We propose the monitoring of the White test statistic through the Forward Search as a new robust tool to test the presence of heteroscedasticity. We briefly describe how the regression estimates change when considering a heteroscedastic regression model. We finally show that, if the data are analyzed on a monthly basis, the heteroscedastic problem can be often bypassed.

Use of Interactive Plots and Tables for Robust Analysis of International Trade Data

This contribution is about the analysis of international trade data through a robust approach for the identification of outliers and regression mixtures called Forward Search. The focus is on interactive tools that we have developed to dynamically connect the information which comes from different robust plots and from the trade flows in the input datasets. The work originated from the need to provide the statistician with new robust exploratory data analysis tools and the end-user with an instrument to simplify the production and interpretation of the results. We argue that with the proposed interactive graphical tools the end-user can combine effectively subject matter knowledge with information provided by the statistical method and draw conclusions of relevant operational value.

Energy Coupling between Protein-chlorophyll Complexes in Chloroplasts. The Effect of Membrane Phosphorylation

Published data relating to the effects of membrane phosphorylation on the fluorescence induction parameters are conflicting. Arntzen and co-workers have consistently reported a decrease in the ratio Fv/Fm (Bennett et al., 1980; Kyle et al., 1982, 1983), whereas other authors have reported that this ratio does not change (Horton, Black, 1981; Krause, Behrend, 1983).