Pilot licensing after aortic valve surgery.

Background and aim of the study: Bicuspid aortic valve is the most common congenital heart malformation, and a high percentage of patients with this condition will develop complications over time. It is rare that pilots undergo aortic valve surgery, and the confirmation of flight-licensing requirements after aortic valve replacement (AVR) is a challenge for the patient's cardiac surgeon and, particularly, for the Aeromedical Examiner (AME). Only AMEs are able to determine the flight status of pilots. Furthermore, in military and in civil aviation (e.g., Red Bull Air Race), the high G-load environment experienced by pilots is an exceptional physiological parameter, which must be considered postoperatively. Methods: A review was conducted of the aeronautical, surgical and medical literature, and of European pilot-licensing regulations. Case studies are also reported for two Swiss Air Force pilots. Results: According to European legislation, pilots can return to flight duty from the sixth postoperative month, with the following limitations: that an aortic bioprosthesis presents no restrictions in cardiac function, requires no cardioactive medications, yet requires a flight operation with co-pilot, the avoidance of accelerations over +3 Gz and, in military aviation, restricts the pilot to non-ejection-seat aircraft. The patient follow up must include both echocardiographic and rhythm assessments every six months. Mechanical prostheses cannot be certified because the required anticoagulation therapy is a disqualifying condition for pilot licensing. Conclusion: Pilot licensing after aortic valve surgery is possible, but with restrictions. The +Gz exposition is of concern in both military and civilian aviation (aerobatics). The choice of bioprosthesis type and size is determinant. Pericardial and stentless valves seem to show better flow characteristics under high-output conditions. Repetitive cardiological controls are mandatory for the early assessment of structural valve disease and rhythm disturbances. A pre-emptive timing is recommended when reoperation is indicated, without waiting for clinical manifestations of structural valve disease.

Growth, Democracy, and Civil War

Does economic growth affect the likelihood of civil war? Answering this question requires dealing with reverse causation. Our approach exploits that international commodity prices have a significant effect on the income growth of Sub-Saharan African countries. We show that lower income growth makes civil war more likely in non-democracies. This effect is significantly weaker in democracies; as a result, we find no link between growth and civil war in these countries. Our reducedform results also indicate that lower international commodity price growth has no effect on civil war in democracies, but raises the likelihood of civil war incidence and onset in nondemocracies.

Report of Recommendations to the Iowa Civil Rights Commission, June 30, 2005

State Audit Reports

Reputation based on punishment rather than generosity allows for evolution of cooperation in sizable groups

Cooperation among unrelated individuals can arise if decisions to help others can be based on reputation. While working for dyadic interactions, reputation-use in social dilemmas involving many individuals (e.g. public goods games) becomes increasingly difficult as groups become larger and errors more frequent. Reputation is therefore believed to have played a minor role for the evolution of cooperation in collective action dilemmas such as those faced by early humans. Here, we show in computer simulations that a reputation system based on punitive actions can overcome these problems and, compared to reputation system based on generous actions, (i) is more likely to lead to the evolution of cooperation in sizable groups, (ii) more effectively sustains cooperation within larger groups, and (iii) is more robust to errors in reputation assessment. Punishment and punishment reputation could therefore have played crucial roles in the evolution of cooperation within larger groups of humans.

Les proches dans le Code civil

Le législateur du Code civil a introduit le terme « proche » dans de nombreuses dispositions, mais n'en propose aucune définition, ce qui laisse une grande marge de manoeuvre pour son interprétation et son application. La signification et la portée du terme ne seront ainsi pas les mêmes selon le domaine juridique et la situation de fait analysés. Face à cette grande diversité d'usage du terme, l'auteure de la contribution propose de l'appréhender selon les domaines et les buts dans lesquels il est utilisé par le législateur afin de réussir à tracer les contours des différents cercles de proches envisageables.

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.

Ethnic Polarization, Potential Conflict, and Civil Wars

This paper analyzes the relationship between ethnic fractionalization, polarization, and conflict. In recent years many authors have found empirical evidence that ethnic fractionalization has a negative effect on growth. One mechanism that can explain this nexus is the effect of ethnic heterogeneity on rent-seeking activities and the increase in potential conflict, which is negative for investment. However the empirical evidence supporting the effect of ethnic fractionalization on the incidence of civil conflicts is very weak. Although ethnic fractionalization may be important for growth, we argue that the channel is not through an increase in potential ethnic conflict. We discuss the appropriateness of indices of polarization to capture conflictive dimensions. We develop a new measure of ethnic heterogeneity that satisfies the basic properties associated with the concept of polarization. The empirical section shows that this index of ethnic polarization is a significant variable in the explanation of the incidence of civil wars. This result is robust to the presence of other indicators of ethnic heterogeneity, other sources of data for the construction of the index, and other data structures.