Comparing Multilevel Clustering Methods on Weighted Graphs : The Case of Worldwide Air Passenger Traffic 2000-2004

Specific properties emerge from the structure of large networks, such as that of worldwide air traffic, including a highly hierarchical node structure and multi-level small world sub-groups that strongly influence future dynamics. We have developed clustering methods to understand the form of these structures, to identify structural properties, and to evaluate the effects of these properties. Graph clustering methods are often constructed from different components: a metric, a clustering index, and a modularity measure to assess the quality of a clustering method. To understand the impact of each of these components on the clustering method, we explore and compare different combinations. These different combinations are used to compare multilevel clustering methods to delineate the effects of geographical distance, hubs, network densities, and bridges on worldwide air passenger traffic. The ultimate goal of this methodological research is to demonstrate evidence of combined effects in the development of an air traffic network. In fact, the network can be divided into different levels of âeurooecohesionâeuro, which can be qualified and measured by comparative studies (Newman, 2002; Guimera et al., 2005; Sales-Pardo et al., 2007).

The evolution of helping and harming on graphs: the return of the inclusive fitness effect.

Evolutionary graph theory has been proposed as providing new fundamental rules for the evolution of co-operation and altruism. But how do these results relate to those of inclusive fitness theory? Here, we carry out a retrospective analysis of the models for the evolution of helping on graphs of Ohtsuki et al. [Nature (2006) 441, 502] and Ohtsuki & Nowak [Proc. R. Soc. Lond. Ser. B Biol. Sci (2006) 273, 2249]. We show that it is possible to translate evolutionary graph theory models into classical kin selection models without disturbing at all the mathematics describing the net effect of selection on helping. Model analysis further demonstrates that costly helping evolves on graphs through limited dispersal and overlapping generations. These two factors are well known to promote relatedness between interacting individuals in spatially structured populations. By allowing more than one individual to live at each node of the graph and by allowing interactions to vary with the distance between nodes, our inclusive fitness model allows us to consider a wider range of biological scenarios leading to the evolution of both helping and harming behaviours on graphs.

Contribution to the Development of the LHCb Vertex Locator Readout Electronics

L'expérience LHCb sera installée sur le futur accélérateur LHC du CERN. LHCb est un spectromètre à un bras consacré aux mesures de précision de la violation CP et à l'étude des désintégrations rares des particules qui contiennent un quark b. Actuellement LHCb se trouve dans la phase finale de recherche et développement et de conception. La construction a déjà commencé pour l'aimant et les calorimètres. Dans le Modèle Standard, la violation CP est causée par une phase complexe dans la matrice 3x3 CKM (Cabibbo-Kobayashi-Maskawa) de mélange des quarks. L'expérience LHCb compte utiliser les mesons B pour tester l'unitarité de cette matrice, en mesurant de diverses manières indépendantes tous les angles et côtés du "triangle d'unitarité". Cela permettra de surdéterminer le modèle et, peut-être, de mettre en évidence des incohérences qui seraient le signal de l'existence d'une physique au-delà du Modèle Standard. La reconstruction du vertex de désintégration des particules est une condition fondamentale pour l'expérience LHCb. La présence d'un vertex secondaire déplacé est une signature de la désintégration de particules avec un quark b. Cette signature est utilisée dans le trigger topologique du LHCb. Le Vertex Locator (VeLo) doit fournir des mesures précises de coordonnées de passage des traces près de la région d'interaction. Ces points sont ensuite utilisés pour reconstruire les trajectoires des particules et l'identification des vertices secondaires et la mesure des temps de vie des hadrons avec quark b. L'électronique du VeLo est une partie essentielle du système d'acquisition de données et doit se conformer aux spécifications de l'électronique de LHCb. La conception des circuits doit maximiser le rapport signal/bruit pour obtenir la meilleure performance de reconstruction des traces dans le détecteur. L'électronique, conçue en parallèle avec le développement du détecteur de silicium, a parcouru plusieurs phases de "prototyping" décrites dans cette thèse.<br/><br/>The LHCb experiment is being built at the future LHC accelerator at CERN. It is a forward single-arm spectrometer dedicated to precision measurements of CP violation and rare decays in the b quark sector. Presently it is finishing its R&D and final design stage. The construction already started for the magnet and calorimeters. In the Standard Model, CP violation arises via the complex phase of the 3 x 3 CKM (Cabibbo-Kobayashi-Maskawa) quark mixing matrix. The LHCb experiment will test the unitarity of this matrix by measuring in several theoretically unrelated ways all angles and sides of the so-called "unitary triangle". This will allow to over-constrain the model and - hopefully - to exhibit inconsistencies which will be a signal of physics beyond the Standard Model. The Vertex reconstruction is a fundamental requirement for the LHCb experiment. Displaced secondary vertices are a distinctive feature of b-hadron decays. This signature is used in the LHCb topology trigger. The Vertex Locator (VeLo) has to provide precise measurements of track coordinates close to the interaction region. These are used to reconstruct production and decay vertices of beauty-hadrons and to provide accurate measurements of their decay lifetimes. The Vertex Locator electronics is an essential part of the data acquisition system and must conform to the overall LHCb electronics specification. The design of the electronics must maximise the signal to noise ratio in order to achieve the best tracking reconstruction performance in the detector. The electronics is being designed in parallel with the silicon detector development and went trough several prototyping phases, which are described in this thesis.

Dynamical modeling and analysis of large cellular regulatory networks.

The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

Recombinant human insulin-like growth factor I (rhIGF-I) for the treatment of amyotrophic lateral sclerosis/motor neuron disease.

BACKGROUND: Recombinant human insulin-like growth factor I (rhIGF-I) is a possible disease modifying therapy for amyotrophic lateral sclerosis (ALS, which is also known as motor neuron disease (MND)). OBJECTIVES: To examine the efficacy of rhIGF-I in affecting disease progression, impact on measures of functional health status, prolonging survival and delaying the use of surrogates (tracheostomy and mechanical ventilation) to sustain survival in ALS. Occurrence of adverse events was also reviewed. SEARCH METHODS: We searched the Cochrane Neuromuscular Disease Group Specialized Register (21 November 2011), CENTRAL (2011, Issue 4), MEDLINE (January 1966 to November 2011) and EMBASE (January 1980 to November 2011) and sought information from the authors of randomised clinical trials and manufacturers of rhIGF-I. SELECTION CRITERIA: We considered all randomised controlled clinical trials involving rhIGF-I treatment of adults with definite or probable ALS according to the El Escorial Criteria. The primary outcome measure was change in Appel Amyotrophic Lateral Sclerosis Rating Scale (AALSRS) total score after nine months of treatment and secondary outcome measures were change in AALSRS at 1, 2, 3, 4, 5, 6, 7, 8, 9 months, change in quality of life (Sickness Impact Profile scale), survival and adverse events. DATA COLLECTION AND ANALYSIS: Each author independently graded the risk of bias in the included studies. The lead author extracted data and the other authors checked them. We generated some missing data by making ruler measurements of data in published graphs. We collected data about adverse events from the included trials. MAIN RESULTS: We identified three randomised controlled trials (RCTs) of rhIGF-I, involving 779 participants, for inclusion in the analysis. In a European trial (183 participants) the mean difference (MD) in change in AALSRS total score after nine months was -3.30 (95% confidence interval (CI) -8.68 to 2.08). In a North American trial (266 participants), the MD after nine months was -6.00 (95% CI -10.99 to -1.01). The combined analysis from both RCTs showed a MD after nine months of -4.75 (95% CI -8.41 to -1.09), a significant difference in favour of the treated group. The secondary outcome measures showed non-significant trends favouring rhIGF-I. There was an increased risk of injection site reactions with rhIGF-I (risk ratio 1.26, 95% CI 1.04 to 1.54). . A second North American trial (330 participants) used a novel primary end point involving manual muscle strength testing. No differences were demonstrated between the treated and placebo groups in this study. All three trials were at high risk of bias. AUTHORS' CONCLUSIONS: Meta-analysis revealed a significant difference in favour of rhIGF-I treatment; however, the quality of the evidence from the two included trials was low. A third study showed no difference between treatment and placebo. There is no evidence for increase in survival with IGF1. All three included trials were at high risk of bias.

Structural Analysis of Networks

Network analysis naturally relies on graph theory and, more particularly, on the use of node and edge metrics to identify the salient properties in graphs. When building visual maps of networks, these metrics are turned into useful visual cues or are used interactively to filter out parts of a graph while querying it, for instance. Over the years, analysts from different application domains have designed metrics to serve specific needs. Network science is an inherently cross-disciplinary field, which leads to the publication of metrics with similar goals; different names and descriptions of their analytics often mask the similarity between two metrics that originated in different fields. Here, we study a set of graph metrics and compare their relative values and behaviors in an effort to survey their potential contributions to the spatial analysis of networks.

Properties of ideal composite knots.

The shortest tube of constant diameter that can form a given knot represents the 'ideal' form of the knot. Ideal knots provide an irreducible representation of the knot, and they have some intriguing mathematical and physical features, including a direct correspondence with the time-averaged shapes of knotted DNA molecules in solution. Here we describe the properties of ideal forms of composite knots-knots obtained by the sequential tying of two or more independent knots (called factor knots) on the same string. We find that the writhe (related to the handedness of crossing points) of composite knots is the sum of that of the ideal forms of the factor knots. By comparing ideal composite knots with simulated configurations of knotted, thermally fluctuating DNA, we conclude that the additivity of writhe applies also to randomly distorted configurations of composite knots and their corresponding factor knots. We show that composite knots with several factor knots may possess distinct structural isomers that can be interconverted only by loosening the knot.

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The paper spells out five different accounts of the relationship between objects and relations three of which are versions of ontic structural realism (OSR). We argue that the distinction between objects and properties, including relations, is merely a conceptual one by contrast to an ontological one: properties, including relations, are modes, that is the concrete, particular ways in which objects exist. We then set out moderate OSR as the view according to which irreducible relations are central ways in which the fundamental physical objects exist. Physical structures thus consist in objects for whom it is essential that they are related in certain ways. There hence are objects, but they do not possess an intrinsic identity. This view can also admit intrinsic properties as ways in which objects exist provided that these do not amount to identity conditions for the objects. Finally, we indicate how this view can take objective modality into account.

Language Regression Associated With Autistic Regression and Electroencephalographic (EEG) Abnormalities: A Prospective Study.

We report a boy, referred at 25 months following a dramatic isolated language regression antedating autistic-like symptomatology. His sleep electroencephalogram (EEG) showed persistent focal epileptiform activity over the left parietal and vertex areas never associated with clinical seizures. He was started on adrenocorticotropic hormone (ACTH) with a significant improvement in language, behavior, and in EEG discharges in rapid eye movement (REM) sleep. Later course was characterized by fluctuations/regressions in language and behavior abilities, in phase with recrudescence of EEG abnormalities prompting additional ACTH courses that led to remarkable decrease in EEG abnormalities, improvement in language, and to a lesser degree, in autistic behavior. The timely documentation of regression episodes suggesting an "atypical" autistic regression, striking therapy-induced improvement, fluctuation of symptomatology over time could be ascribed to recurrent and persisting EEG abnormalities.

Error and attack tolerance of layered complex networks.

Many complex systems may be described by not one but a number of complex networks mapped on each other in a multi-layer structure. Because of the interactions and dependencies between these layers, the state of a single layer does not necessarily reflect well the state of the entire system. In this paper we study the robustness of five examples of two-layer complex systems: three real-life data sets in the fields of communication (the Internet), transportation (the European railway system), and biology (the human brain), and two models based on random graphs. In order to cover the whole range of features specific to these systems, we focus on two extreme policies of system's response to failures, no rerouting and full rerouting. Our main finding is that multi-layer systems are much more vulnerable to errors and intentional attacks than they appear from a single layer perspective.

Evolutionary games on complex networks : the emergence and maintenance of cooperation

Abstract The object of game theory lies in the analysis of situations where different social actors have conflicting requirements and where their individual decisions will all influence the global outcome. In this framework, several games have been invented to capture the essence of various dilemmas encountered in many common important socio-economic situations. Even though these games often succeed in helping us understand human or animal behavior in interactive settings, some experiments have shown that people tend to cooperate with each other in situations for which classical game theory strongly recommends them to do the exact opposite. Several mechanisms have been invoked to try to explain the emergence of this unexpected cooperative attitude. Among them, repeated interaction, reputation, and belonging to a recognizable group have often been mentioned. However, the work of Nowak and May (1992) showed that the simple fact of arranging the players according to a spatial structure and only allowing them to interact with their immediate neighbors is sufficient to sustain a certain amount of cooperation even when the game is played anonymously and without repetition. Nowak and May's study and much of the following work was based on regular structures such as two-dimensional grids. Axelrod et al. (2002) showed that by randomizing the choice of neighbors, i.e. by actually giving up a strictly local geographical structure, cooperation can still emerge, provided that the interaction patterns remain stable in time. This is a first step towards a social network structure. However, following pioneering work by sociologists in the sixties such as that of Milgram (1967), in the last few years it has become apparent that many social and biological interaction networks, and even some technological networks, have particular, and partly unexpected, properties that set them apart from regular or random graphs. Among other things, they usually display broad degree distributions, and show small-world topological structure. Roughly speaking, a small-world graph is a network where any individual is relatively close, in terms of social ties, to any other individual, a property also found in random graphs but not in regular lattices. However, in contrast with random graphs, small-world networks also have a certain amount of local structure, as measured, for instance, by a quantity called the clustering coefficient. In the same vein, many real conflicting situations in economy and sociology are not well described neither by a fixed geographical position of the individuals in a regular lattice, nor by a random graph. Furthermore, it is a known fact that network structure can highly influence dynamical phenomena such as the way diseases spread across a population and ideas or information get transmitted. Therefore, in the last decade, research attention has naturally shifted from random and regular graphs towards better models of social interaction structures. The primary goal of this work is to discover whether or not the underlying graph structure of real social networks could give explanations as to why one finds higher levels of cooperation in populations of human beings or animals than what is prescribed by classical game theory. To meet this objective, I start by thoroughly studying a real scientific coauthorship network and showing how it differs from biological or technological networks using divers statistical measurements. Furthermore, I extract and describe its community structure taking into account the intensity of a collaboration. Finally, I investigate the temporal evolution of the network, from its inception to its state at the time of the study in 2006, suggesting also an effective view of it as opposed to a historical one. Thereafter, I combine evolutionary game theory with several network models along with the studied coauthorship network in order to highlight which specific network properties foster cooperation and shed some light on the various mechanisms responsible for the maintenance of this same cooperation. I point out the fact that, to resist defection, cooperators take advantage, whenever possible, of the degree-heterogeneity of social networks and their underlying community structure. Finally, I show that cooperation level and stability depend not only on the game played, but also on the evolutionary dynamic rules used and the individual payoff calculations. Synopsis Le but de la théorie des jeux réside dans l'analyse de situations dans lesquelles différents acteurs sociaux, avec des objectifs souvent conflictuels, doivent individuellement prendre des décisions qui influenceront toutes le résultat global. Dans ce cadre, plusieurs jeux ont été inventés afin de saisir l'essence de divers dilemmes rencontrés dans d'importantes situations socio-économiques. Bien que ces jeux nous permettent souvent de comprendre le comportement d'êtres humains ou d'animaux en interactions, des expériences ont montré que les individus ont parfois tendance à coopérer dans des situations pour lesquelles la théorie classique des jeux prescrit de faire le contraire. Plusieurs mécanismes ont été invoqués pour tenter d'expliquer l'émergence de ce comportement coopératif inattendu. Parmi ceux-ci, la répétition des interactions, la réputation ou encore l'appartenance à des groupes reconnaissables ont souvent été mentionnés. Toutefois, les travaux de Nowak et May (1992) ont montré que le simple fait de disposer les joueurs selon une structure spatiale en leur permettant d'interagir uniquement avec leurs voisins directs est suffisant pour maintenir un certain niveau de coopération même si le jeu est joué de manière anonyme et sans répétitions. L'étude de Nowak et May, ainsi qu'un nombre substantiel de travaux qui ont suivi, étaient basés sur des structures régulières telles que des grilles à deux dimensions. Axelrod et al. (2002) ont montré qu'en randomisant le choix des voisins, i.e. en abandonnant une localisation géographique stricte, la coopération peut malgré tout émerger, pour autant que les schémas d'interactions restent stables au cours du temps. Ceci est un premier pas en direction d'une structure de réseau social. Toutefois, suite aux travaux précurseurs de sociologues des années soixante, tels que ceux de Milgram (1967), il est devenu clair ces dernières années qu'une grande partie des réseaux d'interactions sociaux et biologiques, et même quelques réseaux technologiques, possèdent des propriétés particulières, et partiellement inattendues, qui les distinguent de graphes réguliers ou aléatoires. Entre autres, ils affichent en général une distribution du degré relativement large ainsi qu'une structure de "petit-monde". Grossièrement parlant, un graphe "petit-monde" est un réseau où tout individu se trouve relativement près de tout autre individu en termes de distance sociale, une propriété également présente dans les graphes aléatoires mais absente des grilles régulières. Par contre, les réseaux "petit-monde" ont, contrairement aux graphes aléatoires, une certaine structure de localité, mesurée par exemple par une quantité appelée le "coefficient de clustering". Dans le même esprit, plusieurs situations réelles de conflit en économie et sociologie ne sont pas bien décrites ni par des positions géographiquement fixes des individus en grilles régulières, ni par des graphes aléatoires. De plus, il est bien connu que la structure même d'un réseau peut passablement influencer des phénomènes dynamiques tels que la manière qu'a une maladie de se répandre à travers une population, ou encore la façon dont des idées ou une information s'y propagent. Ainsi, durant cette dernière décennie, l'attention de la recherche s'est tout naturellement déplacée des graphes aléatoires et réguliers vers de meilleurs modèles de structure d'interactions sociales. L'objectif principal de ce travail est de découvrir si la structure sous-jacente de graphe de vrais réseaux sociaux peut fournir des explications quant aux raisons pour lesquelles on trouve, chez certains groupes d'êtres humains ou d'animaux, des niveaux de coopération supérieurs à ce qui est prescrit par la théorie classique des jeux. Dans l'optique d'atteindre ce but, je commence par étudier un véritable réseau de collaborations scientifiques et, en utilisant diverses mesures statistiques, je mets en évidence la manière dont il diffère de réseaux biologiques ou technologiques. De plus, j'extrais et je décris sa structure de communautés en tenant compte de l'intensité d'une collaboration. Finalement, j'examine l'évolution temporelle du réseau depuis son origine jusqu'à son état en 2006, date à laquelle l'étude a été effectuée, en suggérant également une vue effective du réseau par opposition à une vue historique. Par la suite, je combine la théorie évolutionnaire des jeux avec des réseaux comprenant plusieurs modèles et le réseau de collaboration susmentionné, afin de déterminer les propriétés structurelles utiles à la promotion de la coopération et les mécanismes responsables du maintien de celle-ci. Je mets en évidence le fait que, pour ne pas succomber à la défection, les coopérateurs exploitent dans la mesure du possible l'hétérogénéité des réseaux sociaux en termes de degré ainsi que la structure de communautés sous-jacente de ces mêmes réseaux. Finalement, je montre que le niveau de coopération et sa stabilité dépendent non seulement du jeu joué, mais aussi des règles de la dynamique évolutionnaire utilisées et du calcul du bénéfice d'un individu.

Relative and absolute reliability of the clinical version of the Narrow Path Walking Test (NPWT) under single and dual task conditions.

Decline in gait stability has been associated with increased fall risk in older adults. Reliable and clinically feasible methods of gait instability assessment are needed. This study evaluated the relative and absolute reliability and concurrent validity of the testing procedure of the clinical version of the Narrow Path Walking Test (NPWT) under single task (ST) and dual task (DT) conditions. Thirty independent community-dwelling older adults (65-87 years) were tested twice. Participants were instructed to walk within the 6-m narrow path without stepping out. Trial time, number of steps, trial velocity, number of step errors, and number of cognitive task errors were determined. Intraclass correlation coefficients (ICCs) were calculated as indices of agreement, and a graphic approach called "mountain plot" was applied to help interpret the direction and magnitude of disagreements between testing procedures. Smallest detectable change and smallest real difference (SRD) were computed to determine clinically relevant improvement at group and individual levels, respectively. Concurrent validity was assessed using Performance Oriented Mobility Assessment Tool (POMA) and the Short Physical Performance Battery (SPPB). Test-retest agreement (ICC1,2) varied from 0.77 to 0.92 in ST and from 0.78 to 0.92 in DT conditions, with no apparent systematic differences between testing procedures demonstrated by the mountain plot graphs. Smallest detectable change and smallest real change were small for motor task performance and larger for cognitive errors. Significant correlations were observed for trial velocity and trial time with POMA and SPPB. The present results indicate that the NPWT testing procedure is highly reliable and reproducible.