A Parametric Framework for the Comparison of Methods of Very Robust Regression

There are several methods for obtaining very robust estimates of regression parameters that asymptotically resist 50% of outliers in the data. Differences in the behaviour of these algorithms depend on the distance between the regression data and the outliers. We introduce a parameter $\lambda$ that defines a parametric path in the space of models and enables us to study, in a systematic way, the properties of estimators as the groups of data move from being far apart to close together. We examine, as a function of $\lambda$, the variance and squared bias of five estimators and we also consider their power when used in the detection of outliers. This systematic approach provides tools for gaining knowledge and better understanding of the properties of robust estimators.Comment: Published in at http://dx.doi.org/10.1214/13-STS437 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Sub-horizon Perturbation Behavior in Extended Quintessence

In the general context of scalar-tensor theories, we consider a model in which a scalar field coupled to the Ricci scalar in the gravitational sector of the Lagrangian, is also playing the role of an ``Extended Quintessence'' field, dominating the energy content of the Universe at the present time. In this framework, we study the linear evolution of the perturbations in the Quintessence energy density, showing that a new phenomenon, named here ``gravitational dragging'', can enhance the scalar field density perturbations as much as they reach the non-linear regime. The possibility of dark energy clumps formation is thus discussed.Comment: Proceedings of the 5th International UCLA Symposium on Sources and Detection of Dark Matter and Dark Energy in the Universe (Dark Matter 2002), Marina del Rey, California, USA, 20-22 February 200

La pesca costera en la Argentina

Se aborda el estudio de la pesca costera en la Argentina (océano Atlántico sudoccidental) teniendo en cuenta los factores económicos, sociales y políticos que promovieron su retraso o desarrollo. Para comprenderlo se analizan las diversas etapas históricas desde la época de la conquista (1580) hasta nuestros días. Se detalla sobre la actualidad de las artes de pesca en pequeña escala, las características de los pescadores, el manejo de las pesquerías costeras y el conflicto por los recursos y perspectivas

Scalar field dark energy and Cosmic Microwave Background

A dynamical scalar field represents the simplest generalization of a pure Cosmological Constant as a candidate to explain the recent evidence in favour of the accelerated cosmic expansion. We review the dynamical properties of such a component, and argue that, even if the background expectation value of this field is fixed and the equation of state is the same as a Cosmological Constant, scalar field fluctuations can still be used to distinguish the two components. We compare predicted spectra of Cosmic Microvave Background (CMB) anisotropies in tracking scalar field cosmologies with the present CMB data, in order to get constraints on the amount and equation of state of dark energy. High precision experiments like SNAP, {\sc Planck} and {\sc SNfactory}, together with the data on Large Scale Structure, are needed to probe this issue with the necessary accuracy. Here we show the intriguing result that, with a strong prior on the value of the Hubble constant today, the assumption of a flat universe, and consistency relations between amplitude and spectral index of primordial gravitational waves, the present CMB data at $1\sigma$ give indication of a dark energy equation of state larger than -1, while the ordinary Cosmological Constant is recovered at $2\sigma$.Comment: 4 pages including 2 figures, Dark Matter 2002 proceedings, Nucl.Phys.B in pres

Numerical study of halo concentrations in dark-energy cosmologies

We study the concentration parameters, their mass dependence and redshift evolution, of dark-matter halos in different dark-energy cosmologies with constant and time-variable equation of state, and compare them with "standard'' Lambda-CDM and OCDM models. We find that previously proposed algorithms for predicting halo concentrations can be well adapted to dark-energy models. When centred on the analytically expected values, halo concentrations show a log-normal distribution with a uniform standard deviation of ~0.2. The dependence of averaged halo concentrations on mass and redshift permits a simple fit of the form (1+z) c=c0 (M/M0)^a, with a~-0.1 throughout. We find that the cluster concentration depends on the dark energy equation of state at the cluster formation redshift z_{coll} through the linear growth factor D_+(z_{coll}). As a simple correction accounting for dark-energy cosmologies, we propose scaling c0 from Lambda-CDM with the ratio of linear growth factors, c0 -> c0 D_+(z_{coll})/D_{+,Lambda-CDM}(z_{coll}).Comment: 11 pages, submitted to Astronomy & Astrophysic

Host lifestyle affects human microbiota on daily timescales

Background: Disturbance to human microbiota may underlie several pathologies. Yet, we lack a comprehensive understanding of how lifestyle affects the dynamics of human-associated microbial communities. Results: Here, we link over 10,000 longitudinal measurements of human wellness and action to the daily gut and salivary microbiota dynamics of two individuals over the course of one year. These time series show overall microbial communities to be stable for months. However, rare events in each subjects’ life rapidly and broadly impacted microbiota dynamics. Travel from the developed to the developing world in one subject led to a nearly two-fold increase in the Bacteroidetes to Firmicutes ratio, which reversed upon return. Enteric infection in the other subject resulted in the permanent decline of most gut bacterial taxa, which were replaced by genetically similar species. Still, even during periods of overall community stability, the dynamics of select microbial taxa could be associated with specific host behaviors. Most prominently, changes in host fiber intake positively correlated with next-day abundance changes among 15% of gut microbiota members. Conclusions: Our findings suggest that although human-associated microbial communities are generally stable, they can be quickly and profoundly altered by common human actions and experiences.National Science Foundation (U.S.) (Grant 0821391

A machine learning approach for the estimation of fuel consumption related to road pavement rolling resistance for large fleets of trucks

There remains a level of uncertainty concerning the methodological assumptions and parameters to consider in the estimation of road vehicle fuel consumption due to the condition of road pavements. In fact, recent studies highlighted how existing models can lead to very different results and that because of this, they are not fully ready to be implemented as standard in the life-cycle assessment (LCA) framework. This study presents an innovative approach, based on the application of the Boruta algorithm (BA) and neural networks (NN), for the assessment and calculation of the fuel consumption of a large fleet of truck, which can be used to estimate the use phase emissions of road pavements. The study shows that neural networks are suitable to analyse the large quantities of data, coming from fleet and road asset management databases, effectively and that the developed NN model is able to estimate the impact of rolling resistance-related parameters (pavement roughness and macrotexture) on truck fuel consumption

Genetic characterization of the Bardigiano horse using microsatellite markers

The study was aimed at investigating the genetic structure of the Bardigiano horse and its relationships with the Haflinger, Maremmano and Arabian breeds using 11 microsatellite markers. A total of 94 alleles were detected across the breeds, with a mean of 8.5 alleles per locus and a mean observed heterozygosity of 0.69. Compared to the other breeds, the Bardigiano horse showed quite a high genetic variability, as indicated by the mean number of alleles (7.0 vs 6.1÷7.6) and by the observed heterozygosity (0.72 vs 0.66÷0.71). Moreover, the genotype distributions in the Bardigiano groups of different sex and age were not significantly different. The overall FST value showed that the genetic differences among breeds accounted for 7.8% (P=0.001) of the total variation, and the pairwise FST values were all significant. The assignment test allocated between 96.8 and 98.9% of the individuals to the population they were collected from, with a mean probability of assignment of about 97% for all breeds, except for the Arabian, where it approached 100%. The results have highlighted that the Bardigiano breed has a high within and between breed variability, which is considerably more than could be expected by looking at its evolution history. This justifies the need for the development of additional breeding strategies to preserve the existing genetic variability

Robust regression with density power divergence: theory, comparisons, and data analysis

Minimum density power divergence estimation provides a general framework for robust statistics, depending on a parameter α , which determines the robustness properties of the method. The usual estimation method is numerical minimization of the power divergence. The paper considers the special case of linear regression. We developed an alternative estimation procedure using the methods of S-estimation. The rho function so obtained is proportional to one minus a suitably scaled normal density raised to the power α . We used the theory of S-estimation to determine the asymptotic efficiency and breakdown point for this new form of S-estimation. Two sets of comparisons were made. In one, S power divergence is compared with other S-estimators using four distinct rho functions. Plots of efficiency against breakdown point show that the properties of S power divergence are close to those of Tukey's biweight. The second set of comparisons is between S power divergence estimation and numerical minimization. Monitoring these two procedures in terms of breakdown point shows that the numerical minimization yields a procedure with larger robust residuals and a lower empirical breakdown point, thus providing an estimate of α leading to more efficient parameter estimates