Clustered Archimax Copulas

When modeling multivariate phenomena, properly capturing the joint extremal behavior is often one of the many concerns. Archimax copulas appear as successful candidates in case of asymptotic dependence. In this paper, the class of Archimax copulas is extended via their stochastic representation to a clustered construction. These clustered Archimax copulas are characterized by a partition of the random variables into groups linked by a radial copula; each cluster is Archimax and therefore defined by its own Archimedean generator and stable tail dependence function. The proposed extension allows for both asymptotic dependence and independence between the clusters, a property which is sought, for example, in applications in environmental sciences and finance. The model also inherits from the ability of Archimax copulas to capture dependence between variables at pre-extreme levels. The asymptotic behavior of the model is established, leading to a rich class of stable tail dependence functions.Comment: 42 pages, 10 figure

Priority-Lasso: a simple hierarchical approach to the prediction of clinical outcome using multi-omics data

The inclusion of high-dimensional covariate data in prediction models has become a well-studied topic in the last decades. Although most of these methods do not account for possibly different types of variables in the set of covariates available in the same dataset, there are many such scenarios where the covariates can be structured in blocks of different types. To date, there exist a few computationally intensive approaches that make use of block structures of this kind. In this paper we present priority-Lasso, an intuitive and practical analysis strategy for building prediction models based on Lasso that takes such block structures into account. It requires the definition of a priority order of blocks of data. Lasso models are calculated successively for every block and the fitted values of every step are included as an offset in the fit of the next step. We apply priority-Lasso with different settings on a dataset of acute myeloid leukemia (AML) consisting of clinical variables, cytogenetics, gene mutations and expression variables, and compare its performance on an independent validation dataset to standard Lasso models. The results show that priority-Lasso is able to keep pace with Lasso in terms of prediction accuracy. Variables of blocks with higher priorities are favored over variables of blocks with lower priority, which results in an easily useable and transportable model for clinical practice

Examining the robustness of observational associations to model, measurement and sampling uncertainty with the vibration of effects framework

BACKGROUND The results of studies on observational associations may vary depending on the study design and analysis choices as well as due to measurement error. It is important to understand the relative contribution of different factors towards generating variable results, including low sample sizes, researchers' flexibility in model choices, and measurement error in variables of interest and adjustment variables. METHODS We define sampling, model and measurement uncertainty, and extend the concept of vibration of effects in order to study these three types of uncertainty in a common framework. In a practical application, we examine these types of uncertainty in a Cox model using data from the National Health and Nutrition Examination Survey. In addition, we analyse the behaviour of sampling, model and measurement uncertainty for varying sample sizes in a simulation study. RESULTS All types of uncertainty are associated with a potentially large variability in effect estimates. Measurement error in the variable of interest attenuates the true effect in most cases, but can occasionally lead to overestimation. When we consider measurement error in both the variable of interest and adjustment variables, the vibration of effects are even less predictable as both systematic under- and over-estimation of the true effect can be observed. The results on simulated data show that measurement and model vibration remain non-negligible even for large sample sizes. CONCLUSION Sampling, model and measurement uncertainty can have important consequences for the stability of observational associations. We recommend systematically studying and reporting these types of uncertainty, and comparing them in a common framework

Comparing the vibration of effects due to model, data pre-processing and sampling uncertainty on a large data set in personality psychology

Researchers have great flexibility in the analysis of observational data. If combined with selective reporting and pressure to publish, this flexibility can have devastating consequences on the validity of research findings. We extend the recently proposed vibration of effects approach to provide a framework comparing three main sources of uncertainty which lead to instability in observational associations, namely data pre-processing, model and sampling uncertainty. We analyze their behavior for varying sample sizes for two associations in personality psychology. While all types of vibration show a decrease for increasing sample sizes, data pre-processing and model vibration remain non-negligible, even for a sample of over 80000 participants. The increasing availability of large data sets that are not initially recorded for research purposes can make data pre-processing and model choices very influential. We therefore recommend the framework as a tool for the transparent reporting of the stability of research findings

Efficiency of arsenic oxidizing bacterial biofilms for arsenic contaminated drinking water treatment

In drinking water supplies, arsenic exists mostly as two inorganic forms, arsenite [As(III)] and arsenate [As(V)] which are toxic to living organisms . According to WHO recommendations, the drinking water standard was reduced from 50 to 10 µg/L and many regulatory agencies have recently accepted this new standard. Most of the existing treatment processes are effective only on arsenic anionic forms [As(V)] and not on neutral and mobile arsenic complexes. To overcome this lack of efficiency, a first oxidation step of As(III) form is necessary and is usually performed using strong oxidant or binding materials that are costly for small drinking water treatment units. An alternative to theses physico-chemical treatments is the biological treatment using As(III)-oxidising bacteria. Numerous autotrophic bacteria are able to oxidise arsenic. Among them, Thiomonas arsenivorans [4-6] is able to oxidise As(III) up to 100 mg As(III)/L and appears to be a good candidate for its known capacity to use As(III) as an energy source and carbon dioxide or carbonates as carbon source. An As(III)-oxidizing biological treatment pilot unit coupled to trapping units for As(V) removal at the outflow of the biological bioreactor was performed on site in order to study the strength of the biological process in real operating conditions. The bioreactor was previously inoculated with the autotrophic As(III)-oxidizing Thiomonas arsenivorans. Then, it has been intermittently fed with contaminated water from the drinking water well, at site temperature (15-17°C) and under downstream mode. As(III)-oxidizing biofilm development has been followed during the pilot functioning using CE-SSCP-16S (targeting the global community) and PCR-DGGE-aoxB (targeting As(III) oxidizers) fingerprinting techniques. Results showed a complete colonization of the mineral support (i.e. pozzolana) by indigenous bacteria of the groundwater to be treated. Moreover, the oxidation yield of the biological step was in the range of 54 to 100 % depending on the residence time (from 30 to 7 minutes) and the residual As concentration at the end of the complete treatment process (biological oxidation and trapping) was below 2 µg As/L. These results are thus very encouraging for an industrial application in regard to the strength and its absence of nutrients supply, except for the low amount of oxygen needed if it is not in sufficient concentration in the site water.

Archives et création : nouvelles perspectives sur l'archivistique. Cahier 1

Ce cahier de recherche fait état des travaux menés au cours de la première étape (2013-2014) du projet « Archives et création : nouvelles perspectives sur l’archivistique ». Il comprend les textes suivants : Yvon Lemay et Anne Klein, « Introduction », p. 4-6; Yvon Lemay, « Archives et création : nouvelles perspectives sur l’archivistique », p. 7-19; Anne-Marie Lacombe, « Exploitation des archives à des fins de création : un aperçu de la littérature », p. 20-59; Simon Côté-Lapointe, « Archives sonores et création : une pratique à la croisée des chemins », p. 60-83; Hélène Brousseau, « Fibres, archives et société », p. 84-104; Annie Lecompte-Chauvin, « Comment les archives entrent dans nos vies par le biais de la littérature », p. 105-120; Aude Bertrand, « Valeurs, usages et usagers des archives », p. 121-150; Laure Guitard, « Indexation, émotions, archives », p. 151-168; Anne Klein, Denis Lessard et Anne-Marie Lacombe, « Archives et mise en archives dans le champ culturel. Synthèse du colloque « Archives et création, regards croisés : tournant archivistique, courant artistique », p. 169-178. De plus, dans le but de situer le projet dans un contexte plus large, le cahier inclut une bibliographie des travaux effectués sur les archives et la création depuis 2007, p. 179-182.Le projet de recherche est financé par le Conseil de recherches en sciences humaines du Canada (Programme Savoir, 2013-2016)

Priority-Lasso: a simple hierarchical approach to the prediction of clinical outcome using multi-omics data

BACKGROUND The inclusion of high-dimensional omics data in prediction models has become a well-studied topic in the last decades. Although most of these methods do not account for possibly different types of variables in the set of covariates available in the same dataset, there are many such scenarios where the variables can be structured in blocks of different types, e.g., clinical, transcriptomic, and methylation data. To date, there exist a few computationally intensive approaches that make use of block structures of this kind. RESULTS In this paper we present priority-Lasso, an intuitive and practical analysis strategy for building prediction models based on Lasso that takes such block structures into account. It requires the definition of a priority order of blocks of data. Lasso models are calculated successively for every block and the fitted values of every step are included as an offset in the fit of the next step. We apply priority-Lasso in different settings on an acute myeloid leukemia (AML) dataset consisting of clinical variables, cytogenetics, gene mutations and expression variables, and compare its performance on an independent validation dataset to the performance of standard Lasso models. CONCLUSION The results show that priority-Lasso is able to keep pace with Lasso in terms of prediction accuracy. Variables of blocks with higher priorities are favored over variables of blocks with lower priority, which results in easily usable and transportable models for clinical practice

Reduced Self-Perception of Fatigue after Intake of Panax ginseng Root Extract (G115®) Formulated with Vitamins and Minerals An Open-Label Study

Background: Unexplained fatigue is a common complaint. When underlying disease causes have been eliminated, lifestyle measures and supplementation can be indicated. Elaborating on clinical findings that G115®, a dry extract from the root of Panax ginseng, combined with vitamins and minerals could alleviate fatigue, this open label study aimed at assessing its effect on perceived fatigue and energy. Methods: Healthy adults self-reporting fatigue (n = 103) completed the Multidimensional Fatigue Inventory questionnaire. They rated their perceptions of mental and physical fatigue, energy, performance, and stress at baseline and 15, 30, 60 and 90 days after a daily intake of 40 mg G115® formulated with vitamins and minerals. Results: Compared with baseline values, mean self-perception of general fatigue was reduced by −7.55 units [95% CI: −8.44; −6.66] (−41.8%, p < 0.0001) at 90 days. All assessed perception ratings (mental and physical fatigue, reduced activity and motivation, performance, and stress) were significantly and steadily improved from two weeks after supplementation up to study's end. Overall satisfaction with the ability of the product to reduce fatigue reached 85% at Day 90. Conclusion: Daily intake with G115® extract formulated with vitamins and minerals suggests an improvement of self-perception of fatigue and energy in a fatigued adult population

Chemical and structural investigations on uranium oxide-based microparticles as reference materials for analytical measurements

The analysis of individual micrometre- and submicrometre-sized particles collected by IAEA’s safeguards inspectors on swipe samples during in-field verification activities requires the implementation of a sustainable quality control system such as suitable microparticulate reference materials. To this end, pure and neodymium-doped uranium oxide-based microparticles utilising an aerosol-based particle production process were prepared. SEM/EDX measurements confirmed the monodispersity of the produced microspheres as well as the incorporation of 15 mol% Nd into the compound particles. The timeline of structural investigations mirror the ongoing alteration of particles being stored under laboratory atmosphere. While results from in-SEM Raman (CEA, DAM) on microparticles after two years storage time point to the formation of U3O8 and a minor fraction of schoepite phase (hydrated UO3), in U L3-edge XAFS after four months storage time and U M4-edge HR-XANES after ten months storage time spectra (INE-Beamline and ACT station @ KIT synchrotron radiation source) mainly U(IV) and U(V), respectively, was observed. These results provide new insight into ageing mechanism of the microparticles after preparation. From these results important conclusions with respect to storage conditions and shelf life of the reference particles can be drawn. The first batch of pure U-oxide microparticles produced in Juelich was successfully certified regarding the isotopic composition and the U amount per particle and applied in an international laboratory exercise NUSIMEP-9