Técnicas composicionales para concentraciones geoquímicas por debajo del límite de detección

In most geochemical analyses log-ratio techniques are required to analyse compositional data sets. When a chemical element is present at a low concentration in is usally identified as a value below the detection límit and added to the data set either as zero or simply by attaching a less-than label. In any case, the occirrence of such concentration prevents us from applying the log-ratio approach. We review here the tehoretical bases of the most recent proposals for dealing with these types of observation, give some advice on their practical application and illustrate their performance throgh some examples using geochemical data

Partial correlation : Network analysis

The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.

Estudio de la distribución espacial de Cydia pomonella (L.) y Pandemis heparana (Denis & Schiffermüller) en Torregrossa (Lleida) mediante métodos geoestadísticos

El estudio de la distribución espacial de una especie por me'todos geoestadísticos se realiza mediante el conocimiento de la función semivariograma. Después de calcular el semivariograma se procede a la estimación de la variable regionalizada en cualquier punto de la zona de estudio. Esta estimación se realiza mediante técnicas de interpolación lineal llamadas «krigeado», en honor a Krige y Matheron, fundadores de la geoestadística. El «krigeado» se basa en la minimización de la varianza del error en cada punto de estudio, previamente localizado en el espacio por sus coordenadas de situación. Cydia pomonella (L.) y Pandemis heparana (Denis & Schiffermüller) son dos tortrícidos plaga del manzano y del peral. La estimación de sus poblaciones se realiza mediante trampas de feromona y es posible disponer de una amplia base de datos. El objetivo de este trabajo fue analizar la idoneidad de los métodos geoestadísticos para el estudio de poblaciones de insectos y aplicarlas al caso concreto de C. pomonella y P. heparana. Se utilizaron las capturas en 55 estaciones con trampas de feromonas (difusor de origen Wageningen) colocadas en parcelas comerciales de manzano y peral en 1996 y 1997 en el término municipal de Torregrossa (Lleida). La idoneidad de los métodos geoestadísticos quedó demostrada por el hecho de que la variable número acumulado de machos por trampa fue regionalizable. Una vez calculadas las funciones semivariograma para cada especie y año, se han dibujado los mapas de distribución mediante el uso de isolíneas. En el futuro, se plantea la posibilidad de ampliar la zona de estudio a toda la zona frutera de Lleida y analizar la influencia de variables independientes (climáticas ...) sobre la distribución espacial mediante métodos de «co-krigeado».

Effect of selective recording on estimates of heritability

En este trabajo se analiza el efecto de la selección de datos sobre las estimaciones de heredabilidad. Se estimó el valor de heredabilidad del tamaño de camada en una población porcina en la que los datos correspondientes a las cerdas más viejas eran una muestra seleccionada. Las estimaciones se obtuvieron usando distintos conjuntos de datos derivados de toda la información disponible. Esos conjunto de datos se compararon evaluando su capacidad predictiva. Se vio que las estimaciones de heredabilidad obtenidas utilizando todos los datos disponibles correspondían a valores infraestimados. También se simuló un carácter materno y se generó un conjunto de datos seleccionados eliminando aquellos correspondientes a las hembras sin padres conocidos. Distintos modelos, habitualmente empleados cuando no existe selección de registros, se consideraron para estimar el valor de heredabilidad. Los resultados mostraron que ninguno de esos modelos ofrecía estimaciones insesgadas. Sólo los modelos que tenían en cuenta el efecto de la selección sobre la media residual y la media y varianza genéticas ofrecían estimaciones poco sesgadas. Sin embargo, para poder aplicarlos se debe conocer la selección realizada. El problema de la selección de datos es difícil de abordar cuando se desconoce cual es el proceso de selección que se ha realizado en una población.

The 2010 May Flaring Episode of Cygnus X-3 in Radio, X-rays, and γ-rays

In 2009, Cygnus X-3 (Cyg X-3) became the first microquasar to be detected in the GeV γ-ray regime, via the satellites Fermi and AGILE. The addition of this new band to the observational toolbox holds promise for building a more detailed understanding of the relativistic jets of this and other systems. We present a rich data set of radio, hard and soft X-ray, and γ-ray observations of Cyg X-3 made during a flaring episode in 2010 May. We detect a ~3 day softening and recovery of the X-ray emission, followed almost immediately by a ~1 Jy radio flare at 15 GHz, followed by a 4.3σ γ-ray flare (E > 100 MeV) ~1.5 days later. The radio sampling is sparse, but we use archival data to argue that it is unlikely the γ-ray flare was followed by any significant unobserved radio flares. In this case, the sequencing of the observed events is difficult to explain in a model in which the γ-ray emission is due to inverse Compton scattering of the companion star's radiation field. Our observations suggest that other mechanisms may also be responsible for γ-ray emission from Cyg X-3.

Diagnosis of Alzheimer’s Disease from EEG by Means of Synchrony Measures in Optimized Frequency Bands

Several clinical studies have reported that EEG synchrony is affected by Alzheimer’s disease (AD). In this paper a frequency band analysis of AD EEG signals is presented, with the aim of improving the diagnosis of AD using EEG signals. In this paper, multiple synchrony measures are assessed through statistical tests (Mann–Whitney U test), including correlation, phase synchrony and Granger causality measures. Moreover, linear discriminant analysis (LDA) is conducted with those synchrony measures as features. For the data set at hand, the frequency range (5-6Hz) yields the best accuracy for diagnosing AD, which lies within the classical theta band (4-8Hz). The corresponding classification error is 4.88% for directed transfer function (DTF) Granger causality measure. Interestingly, results show that EEG of AD patients is more synchronous than in healthy subjects within the optimized range 5-6Hz, which is in sharp contrast with the loss of synchrony in AD EEG reported in many earlier studies. This new finding may provide new insights about the neurophysiology of AD. Additional testing on larger AD datasets is required to verify the effectiveness of the proposed approach.

Defining ecologically relevant water quality targets for lakes in Europe

1. The implementation of the Water Framework Directive requires EU member states to establish and harmonize ecological status class boundaries for biological quality elements. In this paper, we describe an approach for defining ecological class boundaries that delineates shifts in lake ecosystem functioning and, therefore, provides ecologically meaningful targets for water policy in Europe. 2. We collected an extensive data set of 810 lake-years from nine Central European countries, and we used phytoplankton chlorophyll a, a metric widely used to measure the impact of eutrophication in lakes. Our approach establishes chlorophyll a target values in relation to three significant ecological effects of eutrophication: the decline of aquatic macrophytes, the dominance of potentially harmful cyanobacteria and the major functional switch from a clear water to a turbid state. 3. Ranges of threshold chlorophyll a concentrations are given for the two most common lake types in lowland Central Europe: for moderately deep lakes (mean depth 3–15 m), the greatest ecological shifts occur in the range 10–12 lg L 1 chlorophyll a, and for shallow lakes (<3 m mean depth), in the range 21–23 lg L 1 chlorophyll a. 4. Synthesis and applications. Our study provides class boundaries for determining the ecological status of lakes, which have robust ecological consequences for lake functioning and which, therefore, provide strong and objective targets for sustainable water management in Europe. The results have been endorsed by all participant member states and adopted in the European Commission legislation, marking the first attempt in international water policy to move from physico-chemical quality standards to harmonized ecologically based quality targets.

A hybrid feature selection approach for the early diagnosis of Alzheimer's disease

Objective. Recently, significant advances have been made in the early diagnosis of Alzheimer’s disease from EEG. However, choosing suitable measures is a challenging task. Among other measures, frequency Relative Power and loss of complexity have been used with promising results. In the present study we investigate the early diagnosis of AD using synchrony measures and frequency Relative Power on EEG signals, examining the changes found in different frequency ranges. Approach. We first explore the use of a single feature for computing the classification rate, looking for the best frequency range. Then, we present a multiple feature classification system that outperforms all previous results using a feature selection strategy. These two approaches are tested in two different databases, one containing MCI and healthy subjects (patients age: 71.9 ± 10.2, healthy subjects age: 71.7 ± 8.3), and the other containing Mild AD and healthy subjects (patients age: 77.6 ± 10.0; healthy subjects age: 69.4± 11.5). Main Results. Using a single feature to compute classification rates we achieve a performance of 78.33% for the MCI data set and of 97.56 % for Mild AD. Results are clearly improved using the multiple feature classification, where a classification rate of 95% is found for the MCI data set using 11 features, and 100% for the Mild AD data set using 4 features. Significance. The new features selection method described in this work may be a reliable tool that could help to design a realistic system that does not require prior knowledge of a patient's status. With that aim, we explore the standardization of features for MCI and Mild AD data sets with promising results.

Present-day deformation of the Pyrenees revealed by GPS surveying and earthquake focal mechanisms until 2011

The Pyrenean mountain range is a slowly deforming belt with continuous and moderate seismic activity. To quantify its deformation field, we present the velocity field estimated from a GPS survey of the Pyrenees spanning 18 yr. The PotSis and ResPyr networks, including a total of 85 GPS sites, were installed and first measured in 1992 and 1995 1997, respectively, and remeasured in 2008 and 2010. We obtain a deformation field with velocities less than 1 mm yr−1 across the range. The estimated velocities for individual stations do not differ significantly from zero with 95 per cent confidence. Even so, we estimate a maximum extensional horizontal strain rate of 2.0 ± 1.7 nanostrain per year in a N S direction in the western part of the range. We do not interpret the vertical displacements due to their large uncertainties. In order to compare the horizontal strain rates with the seismic activity, we analyse a set of 194 focal mechanisms using three methods: (i) the 'r' factor relating their P and T axes, (ii) the stress tensors obtained by fault slip inversion and (iii) the strain-rate tensors. Stress and strain-rate tensors are estimated for: (i) the whole data set, (ii) the eastern and western parts of the range separately, and (iii) eight zones, which are defined based on the seismicity and the tectonic patterns of the Pyrenees. Each of these analyses reveals a lateral variation of the deformation style from compression and extension in the east to extension and strike-slip in the west of the range. Although the horizontal components of the strain-rate tensors estimated from the seismic data are slightly smaller in magnitude than those computed from the GPS velocity field, they are consistent within the 2σ uncertainties. Furthermore, the orientations of their principal axes agree with the mapped active faults.

Photometric and Halpha observations of LSI+61·303: detection of a 26 day V and JHK band modulation

We present new optical and infrared photometric observations and high resolution H α spectra of the periodic radio star LSI+61◦303. The optical photometric data set covers the time interval 1985-1993 and amounts to about a hundred nights. A period of ∼26 days is found in the V band. The infrared data also present evidence for a similar periodicity, but with higher amplitude of variation ((0.m 2). The spectroscopic observations include 16 intermediate and high dispersion spectra of LSI+61◦303 collected between January 1989 and February 1993. The H α emission line profile and its variations are analyzed. Several emission line parameters -- among them the H α EW and the width of the H α red hump -- change strongly at or close to radio maximum, and may exhibit periodic variability. We also observe a significant change in the peak separation. The H α profile of LSI+61◦303 does not seem peculiar for a Be star. However, several of the observed variations of the H α profile can probably be associated with the presence of the compact, secondary star.

Análisis composicional de datos en Ciencias Geoambientales

Compositional data (concentrations) are common in geosciences. Neglecting its character mey lead to erroneous conclusions. Spurious correlation (K. Pearson, 1897) has disastrous consequences. On the basis of the pioneering work by J. Aitchison in the 1980s, a methodology free of these drawbacks is now available. The geometry of the símplex allows the representation of compositions using orthogonal co-ordinares, to which usual statistical methods can be applied, thus facilating computation ans analysis. The use of (log) ratios precludes the interpretation of single concentrations disregarding their relative character. A hydro-chemical data set is used to illustrate the point

Assigning and combining probabilities in single-case designs: A second study

The present study builds on a previous proposal for assigning probabilities to the outcomes computed using different primary indicators in single-case studies. These probabilities are obtained comparing the outcome to previously tabulated reference values and reflect the likelihood of the results in case there was no intervention effect. The current study explores how well different metrics are translated into p values in the context of simulation data. Furthermore, two published multiple baseline data sets are used to illustrate how well the probabilities could reflect the intervention effectiveness as assessed by the original authors. Finally, the importance of which primary indicator is used in each data set to be integrated is explored; two ways of combining probabilities are used: a weighted average and a binomial test. The results indicate that the translation into p values works well for the two nonoverlap procedures, with the results for the regression-based procedure diverging due to some undesirable features of its performance. These p values, both when taken individually and when combined, were well-aligned with the effectiveness for the real-life data. The results suggest that assigning probabilities can be useful for translating the primary measure into the same metric, using these probabilities as additional evidence on the importance of behavioral change, complementing visual analysis and professional's judgments.

Productivity, Technical eficiency and internationalisation of the Spanish chemical sector

relationship between productivity and international position of Spanish chemical firms in the period 2005-2011. The goal is to determine whether companies that follow and international strategy, either with exports or by investment in foreign countries obtain greater productivity growth than these that do not operate in global market. For this purpose a panel data set with microdata has been created. A preliminary analysis of the evolution of productivity growth in the sector is carried out. The measurement of Total Factor Productivity is performed. With the estimated TFP we analyze the differentials in productivity growth, comparing the effects of export and investment behavior with non-international firms.