1,337 research outputs found

    Predictability of large future changes in a competitive evolving population

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    The dynamical evolution of many economic, sociological, biological and physical systems tends to be dominated by a relatively small number of unexpected, large changes (`extreme events'). We study the large, internal changes produced in a generic multi-agent population competing for a limited resource, and find that the level of predictability actually increases prior to a large change. These large changes hence arise as a predictable consequence of information encoded in the system's global state.Comment: 10 pages, 3 figure

    Book Reviews

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    Reviews of the following books: Joe Scott, The Woodsman-Songmaker by Edward D. Ives; Legacy of a Lifetime: The Story of Baxter State Park by John W. Hakola; General William King: Merchant, Shipbuilder, and Maine\u27s First Governor by Marion Jaques Smith; Picture History of New England Passenger Vessels by W. Bartlett Cram; Colonial Massachusetts: A History by Benjamin Labaree

    Generating functional analysis of Minority Games with real market histories

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    It is shown how the generating functional method of De Dominicis can be used to solve the dynamics of the original version of the minority game (MG), in which agents observe real as opposed to fake market histories. Here one again finds exact closed equations for correlation and response functions, but now these are defined in terms of two connected effective non-Markovian stochastic processes: a single effective agent equation similar to that of the `fake' history models, and a second effective equation for the overall market bid itself (the latter is absent in `fake' history models). The result is an exact theory, from which one can calculate from first principles both the persistent observables in the MG and the distribution of history frequencies.Comment: 39 pages, 5 postscript figures, iop styl

    Gene network effects on brain microstructure and intellectual performance identified in 472 twins

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    A major challenge in neuroscience is finding which genes affect brain integrity, connectivity, and intellectual function. Discovering influential genes holds vast promise for neuroscience, but typical genome-wide searches assess approximately one million genetic variants one-by-one, leading to intractable false positive rates, even with vast samples of subjects. Even more intractable is the question of which genes interact and how they work together to affect brain connectivity. Here, we report a novel approach that discovers which genes contribute to brain wiring and fiber integrity at all pairs of points in a brain scan. We studied genetic correlations between thousands of points in human brain images from 472 twins and their nontwin siblings (mean age: 23.7 ± 2.1 SD years; 193 male/279 female). We combined clustering with genome-wide scanning to find brain systems with common genetic determination. We then filtered the image in a new way to boost power to find causal genes. Using network analysis, we found a network of genes that affect brain wiring in healthy young adults. Our new strategy makes it computationally more tractable to discover genes that affect brain integrity. The gene network showed small-world and scale-free topologies, suggesting efficiency in genetic interactions and resilience to network disruption. Genetic variants at hubs of the network influence intellectual performance by modulating associations between performance intelligence quotient and the integrity of major white matter tracts, such as the callosal genu and splenium, cingulum, optic radiations, and the superior longitudinal fasciculus

    Capacitance and effective area of flush monopole probes.

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    Approximate formulas are constructed and numerical simulations are carried out for electric field derivative probes that have the form of flush mounted monopoles. Effects such as rounded edges are included. A method is introduced to make results from two-dimensional conformal mapping analyses accurately apply to the three-dimensional axisymmetric probe geometr

    Regulation of the let-7a-3 Promoter by NF-κB

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    Changes in microRNA expression have been linked to a wide array of pathological states. However, little is known about the regulation of microRNA expression. The let-7 microRNA is a tumor suppressor that inhibits cellular proliferation and promotes differentiation, and is frequently lost in tumors. We investigated the transcriptional regulation of two let-7 family members, let-7a-3 and let-7b, which form a microRNA cluster and are located 864 bp apart on chromosome 22q13.31. Previous reports present conflicting data on the role of the NF-κB transcription factor in regulating let-7. We cloned three fragments upstream of the let-7a-3/let-7b miRNA genomic region into a plasmid containing a luciferase reporter gene. Ectopic expression of subunits of NF-κB (p50 or p65/RelA) significantly increased luciferase activity in HeLa, 293, 293T and 3T3 cells, indicating that the let-7a-3/let-7b promoter is highly responsive to NF-κB. Mutation of a putative NF-κB binding site at bp −833 reduced basal promoter activity and decreased promoter activity in the presence of p50 or p65 overexpression. Mutation of a second putative binding site, at bp −947 also decreased promoter activity basally and in response to p65 induction, indicating that both sites contribute to NF-κB responsiveness. While the levels of the endogenous primary let-7a and let-7b transcript were induced in response to NF-κB overexpression in 293T cells, the levels of fully processed, mature let-7a and let-7b miRNAs did not increase. Instead, levels of Lin-28B, a protein that blocks let-7 maturation, were induced by NF-κB. Increased Lin-28B levels could contribute to the lack of an increase in mature let-7a and let-7b. Our results suggest that the final biological outcome of NF-κB activation on let-7 expression may vary depending upon the cellular context. We discuss our results in the context of NF-κB activity in repressing self-renewal and promoting differentiation

    Automatic Network Fingerprinting through Single-Node Motifs

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    Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs---a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.Comment: 16 pages (4 figures) plus supporting information 8 pages (5 figures

    Towards a framework for critical citizenship education

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    Increasingly countries around the world are promoting forms of "critical" citizenship in the planned curricula of schools. However, the intended meaning behind this term varies markedly and can range from a set of creative and technical skills under the label "critical thinking" to a desire to encourage engagement, action and political emancipation, often labelled "critical pedagogy". This paper distinguishes these manifestations of the "critical" and, based on an analysis of the prevailing models of critical pedagogy and citizenship education, develops a conceptual framework for analysing and comparing the nature of critical citizenship
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