The emergence of biofuels and the co-movement between crude oil and agricultural prices

Biofuels are becoming an alternative to non-renewable energy sources but we know little about the economic mechanisms influencing their prices. This paper studies the interrelationships between the spot prices of oil and those of agricultural commodities used as biofuel feedstocks. Using daily data since 1988, we identify a co-movement after 2005 that does not appear for other food-related commodities and is not due to general economic variables. We also find traces of the co-movement in the prices of a large biofuel stock. The results amount to the first systematic piece of empirical evidence linking spot oil and agricultural markets via the emergence of biofuels.

The Lincoln Highway Association’s “Object Lesson:” The Seedling Mile in Linn County Iowa,

The Seedling Mile in Linn County, Iowa, was part of the Lincoln Highway Association’s so-called “object lesson” program that sought to graphically demonstrate, in the paving of selected one-mile demonstration sections, the benefits of concrete paving to improving road travel across the nation. Constructed in 1918-19, this Seedling Mile became much more than an object lesson and served as something of a battleground between two municipalities—Marion and Cedar Rapids—in their struggle over the county seat and their place on the Lincoln Highway. The Seedling Mile eventually became part of a continuously paved section of the Lincoln Highway between Chicago and Cedar Rapids, with the whole of the Lincoln Highway in Iowa paved in some fashion by the 1930s. In 2002, Linn County reconstructed Mt. Vernon Road from the City of Mt. Vernon to the west end of the Seedling Mile impacting the historic road section. An agreement between concerned government agencies resulted in this publication in partial mitigation of the impact to this historic road section under the guidelines of the National Historic Preservation Act.

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.

Epidemiological characterization of Plasmodium falciparum in the Republic of Cabo Verde: implications for potential large-scale re-emergence of malaria

Background: Malaria has come near eradication at archipelago of Cabo Verde in 1970. Infections are now only observed in Santiago, where outbreaks occur. In these islands, malaria is considered by the international community as being of limited risk and, therefore, no prophylaxis is recommended. Since the understanding of factors that determine malaria outbreaks are crucial for controlling the disease, the present study aimed to investigate if the malaria infections observed in Santiago Island are maintained in isolated foci and in asymptomatic individuals.

Negativity effect and the emergence of ideologies

``Negativity effect'' refers to the psychological phenomenon that peopletend to attach greater weight to negative information than to equallyextreme and equally likely positive information in a variety of informationprocessing tasks. Numerous studies of impression formation have found thatnegative information is weighted more heavily than positive information asimpressions of others are formed. There is empirical evidence in politicalscience that shows the importance of the negativity effect in the informationprocessing of the voters. This effect can explain the observed decreaseof popularity for a president the longer he is in office. \\We construct a dynamic model of political competition, incorporating thenegativity effect in the decision rule of the voters and allowing their preferencesto change over time, according to the past performance of the candidateswhile in office. Our model may explain the emergence of ideologies out ofthe competition for votes of myopic candidates freely choosing policypositions. This result gives rise to the formation of political parties,as infinitely--lived agents with a certain ideology. Furthermore, in thismodel some voters may start out by switching among parties associated withdifferent policies, but find themselves supporting one of the parties fromsome point on. Thus, the model describes a process by which some votersbecome identified with a ``right'' or ``left'' bloc, while others ``swing''between the two parties.

In vitro prevention of the emergence of daptomycin resistance in Staphylococcus aureus and enterococci following combination with amoxicillin/clavulanic acid or ampicillin.

Daptomycin is bactericidal against meticillin-resistant Staphylococcus aureus (MRSA), glycopeptide-intermediate-resistant S. aureus (GISA) and vancomycin-susceptible and -resistant enterococci. However, selection for daptomycin-resistant derivatives has occasionally been reported during therapy in humans. Here we evaluate whether selection for daptomycin-resistant S. aureus or enterococci could be prevented in vitro by combining daptomycin with amoxicillin/clavulanic acid, ampicillin, gentamicin or rifampicin. Six strains of S. aureus (four MRSA and two GISA) and four strains of enterococci (two Enterococcus faecalis and two Enterococcus faecium) were serially exposed in broth to two-fold stepwise increasing concentrations of daptomycin alone or in combination with a fixed concentration [0.25x minimum inhibitory concentration (MIC)] of either of the second agents. The daptomycin MIC was examined after each cycle. Exposure to daptomycin alone gradually selected for S. aureus and enterococci with an increased MIC. Gentamicin did not prevent the emergence of daptomycin-resistant bacteria. Rifampicin was also unable to prevent daptomycin resistance, although resistance was slightly delayed. In contrast, amoxicillin/clavulanic acid or ampicillin prevented or greatly delayed the selection of daptomycin-resistant mutants in S. aureus and enterococci, respectively. Addition of amoxicillin/clavulanic acid or ampicillin to daptomycin prevents, or greatly delays, daptomycin resistance in vitro. Future studies in animal models are needed to predict the utility of these combinations in humans.

Emergence of Cooperation on Static and Dynamic Networks

Game theory is a branch of applied mathematics used to analyze situation where two or more agents are interacting. Originally it was developed as a model for conflicts and collaborations between rational and intelligent individuals. Now it finds applications in social sciences, eco- nomics, biology (particularly evolutionary biology and ecology), engineering, political science, international relations, computer science, and philosophy. Networks are an abstract representation of interactions, dependencies or relationships. Net- works are extensively used in all the fields mentioned above and in many more. Many useful informations about a system can be discovered by analyzing the current state of a network representation of such system. In this work we will apply some of the methods of game theory to populations of agents that are interconnected. A population is in fact represented by a network of players where one can only interact with another if there is a connection between them. In the first part of this work we will show that the structure of the underlying network has a strong influence on the strategies that the players will decide to adopt to maximize their utility. We will then introduce a supplementary degree of freedom by allowing the structure of the population to be modified along the simulations. This modification allows the players to modify the structure of their environment to optimize the utility that they can obtain.

Émergence du moi cérébral de Theodor Meynert à Antonio Damasio = Emergence of the cerebral self, from Theodor Meynert to Antonio Damasio

Antonio Damasio's works have brought emotions into line with current trends in neuroscience. They are conceived as the addition, to a perception, of the somatic effects it has induced. Nevertheless, this continuous and relatively steady process of body perception has also led to the less-known hypothesis of the "neural self." Behind the explicit and apparently contradictory reference to William James and Sigmund Freud, there lies a common source: Theodor Meynert's conception of a "cortical self." Our aim is to enlight a stream unified around what we call here "cerebral self." The Self is thus considered as the cerebral projection or presentation of the body. The specificity of this notion is particularly highlighted by its confrontation to the closely, yet disembodied, notion of "cerebral subject.". Pour citer cette revue : Psychiatr. Sci. Hum. Neurosci. 9 (2011).