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not only for isolated shapes or words, but also for com-plex visual displays (Chun & Jiang, 1999; Fiser & Aslin, 2001). When asked to count an array of random dots, ob-servers are faster at counting a display presented before (Lassaline & Logan, 1993), even when they do not have explicit memory

Knowledge partitioning is a theoretical construct holding that knowledge is not always integrated and homogeneous but may be separated into independent parcels containing mutually contradictory information. Knowledge partitioning has been observed in research on expertise, categorization, and function learning. This article presents a theory of function learning (the population of linear experts model— POLE) that assumes people partition their knowledge whenever they are presented with a complex task. The authors show that POLE is a general model of function learning that accommodates both benchmark results and recent data on knowledge partitioning. POLE also makes the counterintuitive prediction that a person’s distribution of responses to repeated test stimuli should be multimodal. The authors report 3 experiments that support this prediction. The learning of concepts by induction from examples is fundamental to cognition and “...basic to all of our intellectual activities” (Estes, 1994, p. 4). Many concepts are categorical: for example, when a paleontologist learns to classify dinosaurs as birdhipped or lizard-hipped, when an infant learns to label furry four-legged animals as cats or dogs, or when a physician learns to

Learning to recognize the contrasts of a language-specific phonemic repertoire can be viewed as forming categories in a multidimensional psychophysical space. Research on the learning of distributionally defined visual categories has shown that categories defined over 1 dimension are easy to learn and that learning multidimensional categories is more difficult but tractable under specific task conditions. In 2 experiments, adult participants learned either a unidimensional or a multidimensional category distinction with or without supervision (feedback) during learning. The unidimensional distinctions were readily learned and supervision proved beneficial, especially in maintaining category learning beyond the learning phase. Learning the multidimensional category distinction proved to be much more difficult and supervision was not nearly as beneficial as with unidimensionally defined categories. Maintaining a learned multidimensional category distinction was only possible when the distributional information that identified the categories remained present throughout the testing phase. We conclude that listeners are sensitive to both trial-by-trial feedback and the distributional information in the stimuli. Even given limited exposure, listeners learned to use 2 relevant dimensions, albeit with considerable difficulty.

Abstract Recent years have seen a substantial increase in alternative agrifood initiatives that attempt to use the market to curtail the negative social and environmental effects of production and trade in a globalized food system. These alternatives pose a challenge to capital accumulation and the externalization of environmental costs by large agribusiness, trading and retail firms. Yet the success of these alternatives also makes them an inviting target for corporate participa-tion. This article examines these dynamics through a case study of the two most significant such food system alterna-tives—organics and fair trade—focusing on corporate involvement in establishing and renegotiating the standards undergirding these initiatives. We compare the development of and contestation over the standards for both certified organic and certified fair trade, with particular attention to the U.S. context. We provide a brief history of their parallel processes of rapid growth and market mainstreaming. We examine claims of cooptation by movement participants, as well as the divergences and similarities between the organic and fair trade cases. Analyzing these two cases provides useful insights into the strategic approaches that corporate firms have deployed to further capital accumulation and to defuse threats to their profit margins and to status quo pro-duction, pricing, labor, trading and retailing practices. It can also offer valuable lessons regarding the most effective means of responding to such counter-reforms and of protecting or reasserting the more transformative elements at the heart of these alternative systems.

and many precious advices he gave me all along my thesis work. I learned a lot from his experience and his broad scientific knowledge. It has been a pleasure collaborating with him and his team on many different projects. I would like to thank as well Daniel Shulz and Thierry Bal for the great

Abstract not found

Both adults and young children possess powerful statistical computation capabilities—they can infer the referent of a word from highly ambiguous contexts involving many words and many referents by aggregating cross-situational statistical information across contexts. This ability has been explained by models of hypothesis testing and by models of associative learning. This article describes a series of simulation studies and analyses designed to understand the different learning mechanisms posited by the 2 classes of models and their relation to each other. Variants of a hypothesis-testing model and a simple or dumb associative mechanism were examined under different specifications of information selection, computation, and decision. Critically, these 3 components of the models interact in complex ways. The models illustrate a fundamental tradeoff between amount of data input and powerful computations: With the selection of more information, dumb associative models can mimic the powerful learning that is accomplished by hypothesis-testing models with fewer data. However, because of the interactions among the component parts of the models, the associative model can mimic various hypothesis-testing models, producing the same learning patterns but through different internal components. The simulations argue for the importance of a compositional approach to human statistical learning: the experimental decomposition of the processes that contribute to statistical learning in human learners and models with the

ABSTRACT An analysis is presented on how structural cores modify their shape across homologous proteins, and whether or not a relationship exists between these structural changes and the vibrational normal modes that proteins experience as a result of the topological constraints imposed by the fold. A set of 35 representative, well-populated protein families is studied. The evolutionary directions of deformation are obtained by using multiple structural alignments to superimpose the structures and extract a conserved core, together with principal components analysis to extract the main deformation modes from the threedimensional superimposition. In parallel, a low-resolution normal mode analysis technique is employed to study the properties of the mechanical core plasticity of these same families. We show that the evolutionary deformations span a low dimensional space of 4–5 dimensions on average. A statistically significant correspondence exists between these principal deformations and the;20 slowest vibrational modes accessible to a particular topology. We conclude that, to a significant extent, the structural response of a protein topology to sequence changes takes place by means of collective deformations along combinations of a small number of low-frequency modes. The findings have implications in structure prediction by homology modeling.

Copyright © 2015 Ron A. Adelman et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The paper entitled “Strategy for the Management of Macular Edema in Retinal Vein Occlusion: the European VitreoReti-nal Society Macular Edema Study ” [1] was missing EVRS Macular Edema Study Group as coauthors, and it was added as shown above. The members of this group are listed in Acknowledgments. Acknowledgments The authors are thankful for the European VitreoRetinal Society (EVRS) Macular Edema Study Group. EVRS Mac-