89 research outputs found

    How to Use Data and Assessment to Automate Collections Workflows and Decisions

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    On solving trust-region and other regularised subproblems in optimization

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    The solution of trust-region and regularisation subproblems which arise in unconstrained optimization is considered. Building on the pioneering work of Gay, Mor´e and Sorensen, methods which obtain the solution of a sequence of parametrized linear systems by factorization are used. Enhancements using high-order polynomial approximation and inverse iteration ensure that the resulting method is both globally and asymptotically at least superlinearly convergent in all cases, including in the notorious hard case. Numerical experiments validate the effectiveness of our approach. The resulting software is available as packages TRS and RQS as part of the GALAHAD optimization library, and is especially designed for large-scale problems

    Erratum: Non-collinear generation of angularly isolated circularly polarized high harmonics.

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    [EN]In the version of this Article originally published the blue dashed line was mislabelled in the legend in Fig. 3d and the label should have read i Evert. This has now been corrected in the online versions of the Article

    Observation and control of shock waves in individual nanoplasmas

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    In a novel experiment that images the momentum distribution of individual, isolated 100-nm-scale plasmas, we make the first experimental observation of shock waves in nanoplasmas. We demonstrate that the introduction of a heating pulse prior to the main laser pulse increases the intensity of the shock wave, producing a strong burst of quasi-monochromatic ions with an energy spread of less than 15%. Numerical hydrodynamic calculations confirm the appearance of accelerating shock waves, and provide a mechanism for the generation and control of these shock waves. This observation of distinct shock waves in dense plasmas enables the control, study, and exploitation of nanoscale shock phenomena with tabletop-scale lasers.Comment: 8 pages of manuscript, 9 pages of supplemental information, total 17 page

    From Poverty to Disaster and Back: a Review of the Literature

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    Poor people are disproportionally affected by natural hazards and disasters. This paper provides a review of the multiple factors that explain why this is the case. It explores the role of exposure (often, but not always, poor people are more likely to be affected by hazards), vulnerability (when they are affected, poor people tend to lose a larger fraction of their wealth), and socio-economic resilience (poor people have a lower ability to cope with and recover from disaster impacts). Finally, the paper highlights the vicious circle between poverty and disaster losses: poverty is a major driver of people’s vulnerability to natural disasters, which in turn increase poverty in a measurable and significant way. The main policy implication is that poverty reduction can be considered as disaster risk management, and disaster risk management can be considered as poverty reduction

    Uncovering a Macrophage Transcriptional Program by Integrating Evidence from Motif Scanning and Expression Dynamics

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    Macrophages are versatile immune cells that can detect a variety of pathogen-associated molecular patterns through their Toll-like receptors (TLRs). In response to microbial challenge, the TLR-stimulated macrophage undergoes an activation program controlled by a dynamically inducible transcriptional regulatory network. Mapping a complex mammalian transcriptional network poses significant challenges and requires the integration of multiple experimental data types. In this work, we inferred a transcriptional network underlying TLR-stimulated murine macrophage activation. Microarray-based expression profiling and transcription factor binding site motif scanning were used to infer a network of associations between transcription factor genes and clusters of co-expressed target genes. The time-lagged correlation was used to analyze temporal expression data in order to identify potential causal influences in the network. A novel statistical test was developed to assess the significance of the time-lagged correlation. Several associations in the resulting inferred network were validated using targeted ChIP-on-chip experiments. The network incorporates known regulators and gives insight into the transcriptional control of macrophage activation. Our analysis identified a novel regulator (TGIF1) that may have a role in macrophage activation
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