337 research outputs found

    The microbiology of cheese-like flavors in unsalted butter

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    This archival publication may not reflect current scientific knowledge or recommendations

    A Retrospective Database Analysis of Neonatal Morbidities to Evaluate a Composite Endpoint for Use in Preterm Labor Clinical Trials

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    Objective To propose and assess a composite endpoint (CE) of neonatal benefit based on neonatal mortality and morbidities by gestational age (GA) for use in preterm labor clinical trials. Study Design A descriptive, retrospective analysis of the Medical University of South Carolina Perinatal Information System database was conducted. Neonatal morbidities were assessed for inclusion in the CE based on clinical significance/risk of childhood neurodevelopmental impairment, frequency, and association with GA in a mother– neonate linked cohort, comprising women with uncomplicated singleton pregnancies delivered at !24 weeks’ GA. Results Among 17,912 mother–neonate pairs, neonates were at a risk of numerous severe but infrequent morbidities. Clinically important, predominantly rare events were combined into a CE comprising neonatal mortality and morbidities, which decreased in frequency with increasing GA. The highest CE frequency occurred at \u3c31 weeks. High frequency of respiratory distress syndrome, bronchopulmonary dysplasia, and sepsis drove the CE. Median length of hospital stay was longer at all GAs in those with the CE compared with those without. Conclusions Descriptive epidemiological assessment and clinical input were used to develop a CE to measure neonatal benefit, comprising clinically meaningful outcomes. These empirical data and CE allowed trials investigating tocolytics to be sized appropriately

    Cooperation, Norms, and Revolutions: A Unified Game-Theoretical Approach

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    Cooperation is of utmost importance to society as a whole, but is often challenged by individual self-interests. While game theory has studied this problem extensively, there is little work on interactions within and across groups with different preferences or beliefs. Yet, people from different social or cultural backgrounds often meet and interact. This can yield conflict, since behavior that is considered cooperative by one population might be perceived as non-cooperative from the viewpoint of another. To understand the dynamics and outcome of the competitive interactions within and between groups, we study game-dynamical replicator equations for multiple populations with incompatible interests and different power (be this due to different population sizes, material resources, social capital, or other factors). These equations allow us to address various important questions: For example, can cooperation in the prisoner's dilemma be promoted, when two interacting groups have different preferences? Under what conditions can costly punishment, or other mechanisms, foster the evolution of norms? When does cooperation fail, leading to antagonistic behavior, conflict, or even revolutions? And what incentives are needed to reach peaceful agreements between groups with conflicting interests? Our detailed quantitative analysis reveals a large variety of interesting results, which are relevant for society, law and economics, and have implications for the evolution of language and culture as well

    Spatial interactions in agent-based modeling

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    Agent Based Modeling (ABM) has become a widespread approach to model complex interactions. In this chapter after briefly summarizing some features of ABM the different approaches in modeling spatial interactions are discussed. It is stressed that agents can interact either indirectly through a shared environment and/or directly with each other. In such an approach, higher-order variables such as commodity prices, population dynamics or even institutions, are not exogenously specified but instead are seen as the results of interactions. It is highlighted in the chapter that the understanding of patterns emerging from such spatial interaction between agents is a key problem as much as their description through analytical or simulation means. The chapter reviews different approaches for modeling agents' behavior, taking into account either explicit spatial (lattice based) structures or networks. Some emphasis is placed on recent ABM as applied to the description of the dynamics of the geographical distribution of economic activities, - out of equilibrium. The Eurace@Unibi Model, an agent-based macroeconomic model with spatial structure, is used to illustrate the potential of such an approach for spatial policy analysis.Comment: 26 pages, 5 figures, 105 references; a chapter prepared for the book "Complexity and Geographical Economics - Topics and Tools", P. Commendatore, S.S. Kayam and I. Kubin, Eds. (Springer, in press, 2014

    Communication Research

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    Contains reports on seven research projects.Carnegie Foundatio

    Communication Research

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    Contains reports on seven research projects.Rockefeller FoundationCarnegie Foundatio

    Individual strategy update and emergence of cooperation in social networks

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    In this paper, we critically study whether social networks can explain the emergence of cooperative behavior. We carry out an extensive simulation program in which we study the most representative social dilemmas. For the Prisoner’s Dilemma, it turns out that the emergence of cooperation is very dependent on the micro-dynamics. On the other hand, network clustering mostly facilitates global cooperation in the Stag Hunt game, whereas degree heterogeneity promotes cooperation in Snowdrift dilemmas. Thus, social networks do not promote cooperation in general, because the macrooutcome is not robust under change of dynamics. Therefore, having specific applications of interest in mind is crucial to include the appropriate microdetails in a good model.This work has been supported by Ministerio de Ciencia e Innovación (Spain) through grant MOSAICO, and by Comunidad de Madrid (Spain) through grant MODELICO-CM.Publicad

    Magnetic Field Generation in Stars

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    Enormous progress has been made on observing stellar magnetism in stars from the main sequence through to compact objects. Recent data have thrown into sharper relief the vexed question of the origin of stellar magnetic fields, which remains one of the main unanswered questions in astrophysics. In this chapter we review recent work in this area of research. In particular, we look at the fossil field hypothesis which links magnetism in compact stars to magnetism in main sequence and pre-main sequence stars and we consider why its feasibility has now been questioned particularly in the context of highly magnetic white dwarfs. We also review the fossil versus dynamo debate in the context of neutron stars and the roles played by key physical processes such as buoyancy, helicity, and superfluid turbulence,in the generation and stability of neutron star fields. Independent information on the internal magnetic field of neutron stars will come from future gravitational wave detections. Thus we maybe at the dawn of a new era of exciting discoveries in compact star magnetism driven by the opening of a new, non-electromagnetic observational window. We also review recent advances in the theory and computation of magnetohydrodynamic turbulence as it applies to stellar magnetism and dynamo theory. These advances offer insight into the action of stellar dynamos as well as processes whichcontrol the diffusive magnetic flux transport in stars.Comment: 41 pages, 7 figures. Invited review chapter on on magnetic field generation in stars to appear in Space Science Reviews, Springe
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