Vitamine K et fonctions cognitives chez la personne âgée en santé : une approche épidémiologique nutritionnelle

La vitamine K fait l’objet d’un intérêt croissant en regard du rôle qu’elle peut jouer dans la santé humaine hormis celui bien établi dans la coagulation sanguine. De plus en plus d’études expérimentales lui confèrent des fonctions dans le système nerveux central, particulièrement dans la synthèse des sphingolipides, l’activation de la protéine vitamine K-dépendante Gas6 et la protection contre les dommages oxydatifs. Toutefois, il demeure beaucoup moins bien établi si la perturbation de ces fonctions peut conduire à des déficits cognitifs. L’objectif principal de cette thèse est de vérifier l’hypothèse selon laquelle le statut vitaminique K des personnes âgées en santé est un déterminant de la performance cognitive. En vue de la réalisation de cet objectif, une meilleure compréhension des indicateurs du statut vitaminique K s’avérait nécessaire. Chacune des études présentées vise donc un objectif spécifique : 1) évaluer le nombre de rappels alimentaires de 24 heures non consécutifs nécessaire pour mesurer l’apport habituel de vitamine K des personnes âgées; 2) évaluer la valeur d’une seule mesure de la concentration sérique de vitamine K comme marqueur de l’exposition à long terme; et 3) examiner l’association entre le statut vitaminique K et la performance cognitive des personnes âgées en santé de la cohorte québécoise NuAge. Trois dimensions cognitives ont été évaluées soient la mémoire épisodique verbale et non-verbale, les fonctions exécutives et la vitesse de traitement de l’information. Cette thèse présente la première étude appuyant l’hypothèse d’un rôle de la vitamine K dans la cognition chez les personnes âgées. Spécifiquement, la concentration sérique de vitamine K a été associée positivement à la performance en mémoire épisodique verbale, et plus particulièrement au processus de consolidation de la trace mnésique. En accord avec les travaux chez l’animal et l’action de la protéine Gas6 dans l’hippocampe, un rôle spécifique de la vitamine K à l’étape de consolidation est biologiquement plausible. Aucune association significative n’a été observée avec les fonctions exécutives et la vitesse de traitement de l’information. Parallèlement, il a été démontré qu’une mesure unique de la concentration sérique de vitamine K constitue une mesure adéquate de l’exposition à long terme à la vitamine K. De même, il a été établi que six à 13 rappels alimentaires de 24 heures sont nécessaires pour estimer précisément l’apport de vitamine K des personnes âgées en santé. Collectivement, les résultats de ces deux études fournissent des informations précieuses aux chercheurs permettant une meilleure interprétation des études existantes et une meilleure planification des études futures. Les résultats de cette thèse constituent une avancée importante dans la compréhension du rôle potentiel de la vitamine K dans le système nerveux central et renforce la nécessité qu’elle soit considérée en tant que facteur nutritionnel du vieillissement cognitif, en particulier chez les personnes traitées par un antagoniste de la vitamine K.

Construction of aggregation operators with noble reinforcement

This paper examines disjunctive aggregation operators used in various recommender systems. A specific requirement in these systems is the property of noble reinforcement: allowing a collection of high-valued arguments to reinforce each other while avoiding reinforcement of low-valued arguments. We present a new construction of Lipschitz-continuous aggregation operators with noble reinforcement property and its refinements.

Pointwise construction of Lippschitz aggregation operators with specific properties

This paper describes an approach to pointwise construction of general aggregation operators, based on monotone Lipschitz approximation. The aggregation operators are constructed from a set of desired values at certain points, or from empirically collected data. It establishes tight upper and lower bounds on Lipschitz aggregation operators with a number of different properties, as well as the optimal aggregation operator, consistent with the given values. We consider conjunctive, disjunctive and idempotent n-ary aggregation operators; p-stable aggregation operators; various choices of the neutral element and annihilator; diagonal, opposite diagonal and marginal sections; bipolar and double aggregation operators. In all cases we provide either explicit formulas or deterministic numerical procedures to determine the bounds. The findings of this paper are useful for construction of aggregation operators with specified properties, especially using interpolation schemata.

Some averaging functions in image reduction

In this work we propose a definition of weak local reduction operators and an algorithm that uses such operators to reduce images. We show how to construct local reduction operators by means of different aggregation functions. We also present several experimental results obtained using these aggregation functions-based reduction operators.

Aggregation of preferences in recommender systems

This chapter gives an overview of aggregation functions toward their use in recommender systems. Simple aggregation functions such as the arithmetic mean are often employed to aggregate user features, item ratings, measures of similarity, etc., however many other aggregation functions exist which could deliver increased accuracy and flexibility to many systems. We provide definitions of some important families and properties, sophisticated methods of construction, and various examples of aggregation functions in the domain of recommender systems.

Color image reduction by minimizing penalty functions

In image processing, particularly in image reduction, averaging aggregation functions play an important role. In this work we study the aggregation of color values (RGB) and we present an image reduction algorithm for RGB color images. For this purpose, we define and study aggregation functions and penalty functions in product lattices. We show how the arithmetic mean and the median can be obtained by minimizing specific penalty functions. Moreover, we study other penalty functions and we show that, in general, aggregation functions on product lattices do not coincide with the cartesian product of the corresponding aggregation functions. Finally, we make an experimental study where we test our reduction algorithm and we analyze the stability of the penalty functions in images affected by noise.

On the use of restricted dissimilarity and dissimilarity-like functions for defining penalty functions

In this work we study the relation between restricted dissimilarity functions-and, more generally, dissimilarity-like functions- and penalty functions and the possibility of building the latter using the former. Several results on convexity and quasiconvexity are also considered.

Image reduction operators based on non-monotonic averaging functions

Image reduction is a crucial task in image processing, underpinning many practical applications. This work proposes novel image reduction operators based on non-monotonic averaging aggregation functions. The technique of penalty function minimisation is used to derive a novel mode-like estimator capable of identifying the most appropriate pixel value for representing a subset of the original image. Performance of this aggregation function and several traditional robust estimators of location are objectively assessed by applying image reduction within a facial recognition task. The FERET evaluation protocol is applied to confirm that these non-monotonic functions are able to sustain task performance compared to recognition using nonreduced images, as well as significantly improve performance on query images corrupted by noise. These results extend the state of the art in image reduction based on aggregation functions and provide a basis for efficiency and accuracy improvements in practical computer vision applications.

A penalty-based aggregation operator for non-convex intervals

In the case of real-valued inputs, averaging aggregation functions have been studied extensively with results arising in fields including probability and statistics, fuzzy decision-making, and various sciences. Although much of the behavior of aggregation functions when combining standard fuzzy membership values is well established, extensions to interval-valued fuzzy sets, hesitant fuzzy sets, and other new domains pose a number of difficulties. The aggregation of non-convex or discontinuous intervals is usually approached in line with the extension principle, i.e. by aggregating all real-valued input vectors lying within the interval boundaries and taking the union as the final output. Although this is consistent with the aggregation of convex interval inputs, in the non-convex case such operators are not idempotent and may result in outputs which do not faithfully summarize or represent the set of inputs. After giving an overview of the treatment of non-convex intervals and their associated interpretations, we propose a novel extension of the arithmetic mean based on penalty functions that provides a representative output and satisfies idempotency.

Weakly monotone averaging functions

Averaging behaviour of aggregation functions depends on the fundamental property of monotonicity with respect to all arguments. Unfortunately this is a limiting property that ensures that many important averaging functions are excluded from the theoretical framework. We propose a definition for weakly monotone averaging functions to encompass the averaging aggregation functions in a framework with many commonly used non-monotonic means. Weakly monotonic averages are robust to outliers and noise, making them extremely important in practical applications. We show that several robust estimators of location are actually weakly monotone and we provide sufficient conditions for weak monotonicity of the Lehmer and Gini means and some mixture functions. In particular we show that mixture functions with Gaussian kernels, which arise frequently in image and signal processing applications, are actually weakly monotonic averages. Our concept of weak monotonicity provides a sound theoretical and practical basis for understanding both monotone and non-monotone averaging functions within the same framework. This allows us to effectively relate these previously disparate areas of research and gain a deeper understanding of averaging aggregation methods. © Springer International Publishing Switzerland 2014.

Three types of monotonicity of averaging functions

Monotonicity with respect to all arguments is fundamental to the definition of aggregation functions, which are one of the basic tools in knowledge-based systems. The functions known as means (or averages) are idempotent and typically are monotone, however there are many important classes of means that are non-monotone. Weak monotonicity was recently proposed as a relaxation of the monotonicity condition for averaging functions. In this paper we discuss the concepts of directional and cone monotonicity, and monotonicity with respect to majority of inputs and coalitions of inputs. We establish the relations between various kinds of monotonicity, and illustrate it on various examples. We also provide a construction method for cone monotone functions.

Weakly monotonic averaging functions

Monotonicity with respect to all arguments is fundamental to the definition of aggregation functions. It is also a limiting property that results in many important nonmonotonic averaging functions being excluded from the theoretical framework. This work proposes a definition for weakly monotonic averaging functions, studies some properties of this class of functions, and proves that several families of important nonmonotonic means are actually weakly monotonic averaging functions. Specifically, we provide sufficient conditions for weak monotonicity of the Lehmer mean and generalized mixture operators. We establish weak monotonicity of several robust estimators of location and conditions for weak monotonicity of a large class of penalty-based aggregation functions. These results permit a proof of the weak monotonicity of the class of spatial-tonal filters that include important members such as the bilateral filter and anisotropic diffusion. Our concept of weak monotonicity provides a sound theoretical and practical basis by which (monotonic) aggregation functions and nonmonotonic averaging functions can be related within the same framework, allowing us to bridge the gap between these previously disparate areas of research.

On weak monotonicity of some mixture functions

Monotonicity with respect to all arguments is fundamental to the definition of aggregation functions. Here we study means that are not necessarily monotone. Weak monotonicity was recently proposed as a relaxation of the monotonicity condition for averaging functions. We provide results for the weak monotonicity of some importantclasses of mixture functions. With these results we are able to extend and improve the understanding of this very important class of functions.

Biased experts and similarity based weights in preferences aggregation

In a group decision making setting, we consider the potential impact an expert can have on the overall ranking by providing a biased assessment of the alternatives that differs substantially from the majority opinion. In the framework of similarity based averaging functions, we show that some alternative approaches to weighting the experts' inputs during the aggregation process can minimize the influence the biased expert is able to exert.

(KsKs0)-K-0 correlations in pp collisions at root s=7 TeV from the LHC ALICE experiment

Identical neutral kaon pair correlations are measured in root s = 7 TeV pp collisions in the ALICE experiment. One-dimensional (KsKs0)-K-0 correlation functions in terms of the invariant momentum difference of kaon pairs are formed in two multiplicity and two transverse momentum ranges. The femtoscopic parameters for the radius and correlation strength of the kaon source are extracted. The fit includes quantum statistics and final-state interactions of the a(0)/f(0) resonance. (KsKs0)-K-0 correlations show an increase in radius for increasing multiplicity and a slight decrease in radius for increasing transverse mass, mT, as seen in pi pi correlations in pp collisions and in heavy-ion collisions. Transverse mass scaling is observed between the (KsKs0)-K-0 and pi pi radii. Also, the first observation is made of the decay of the f(2)'(1525) meson into the (KsKs0)-K-0 channel in pp collisions. (C) 2012 CERN. Published by Elsevier B.V. All rights reserved.