1,656 research outputs found

    Ten simple rules for reporting voxel-based morphometry studies

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    Voxel-based morphometry [Ashburner, J. and Friston, K.J., 2000. Voxel-based morphometry—the methods. NeuroImage 11(6 Pt 1), 805–821] is a commonly used tool for studying patterns of brain change in development or disease and neuroanatomical correlates of subject characteristics. In performing a VBM study, many methodological options are available; if the study is to be easily interpretable and repeatable, the processing steps and decisions must be clearly described. Similarly, unusual methods and parameter choices should be justified in order to aid readers in judging the importance of such options or in comparing the work with other studies. This editorial suggests core principles that should be followed and information that should be included when reporting a VBM study in order to make it transparent, replicable and useful

    A Generic Agent Organisation Framework For Autonomic Systems

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    Autonomic computing is being advocated as a tool for managing large, complex computing systems. Specifically, self-organisation provides a suitable approach for developing such autonomic systems by incorporating self-management and adaptation properties into large-scale distributed systems. To aid in this development, this paper details a generic problem-solving agent organisation framework that can act as a modelling and simulation platform for autonomic systems. Our framework describes a set of service-providing agents accomplishing tasks through social interactions in dynamically changing organisations. We particularly focus on the organisational structure as it can be used as the basis for the design, development and evaluation of generic algorithms for self-organisation and other approaches towards autonomic systems

    Studies of RF Noise Induced Bunch Lengthening at the LHC

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    Radio Frequency noise induced bunch lengthening can strongly affect the Large Hadron Collider performance through luminosity reduction, particle loss, and other effects. Models and theoretical formalisms demonstrating the dependence of the LHC longitudinal bunch length on the RF station noise spectral content have been presented*,**. Initial measurements validated these studies and determined the performance limiting RF components. For the existing LHC LLRF implementation the bunch length increases with a rate of 1 mm/hr, which is higher than the intrabeam scattering diffusion and leads to a 27% bunch length increase over a 20 hour store. This work presents measurements from the LHC that better quantify the relationship between the RF noise and longitudinal emittance blowup. Noise was injected at specific frequency bands and with varying amplitudes at the LHC accelerating cavities. The experiments presented in this paper confirmed the predicted effects on the LHC bunch length due to both the noise around the synchrotron frequency resonance and the noise in other frequency bands aliased down to the synchrotron frequency by the periodic beam sampling of the accelerating voltage

    Relative performance of four midge-resistant wheat varietal blends in western Canada

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    Non-Peer ReviewedOrange wheat blossom midge, Sitodiplosis mosellana (Géhin), causes significant yield losses to spring wheat in western Canada in severe infestations. To mitigate losses, midge-resistant wheat varietal blends, consisting of cultivars carrying the Sm1 midge resistance gene and 10% interspersed midge susceptible refuge, have been made available to farmers. To test their performance relative to conventional midge-susceptible cultivars, four varietal blends were grown during four consecutive years, at eight locations in the provinces of Manitoba Saskatchewan and Alberta, in comparison to four conventional, midge-susceptible cultivars. Midge damage was higher in 2007 and 2010 than in 2008 and 2009. In general, the varietal blends, as a group, yielded more grain than the susceptible cultivars, especially when grown in environments with high midge pressure (5.5 - 35% seed damage). In environments with low midge pressure (0 – 2.6% seed damage), the varietal blend average yield advantage was smaller but still significant, indicating that some of the varietal blends had additional superior attributes, in addition to midge resistance

    The effect of incorporating the midge resistance (Sm1) gene in wheat

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    Non-Peer ReviewedOrange wheat blossom midge, Sitodiplosis mosellana (Géhin), was first detected in Manitoba in 1901, but now is present in all three prairie provinces of western Canada. In severe infestations, this insect may cause significant yield losses to spring wheat. To mitigate losses, midge-resistant wheat varietal blends, consisting of cultivars carrying the Sm1 midge resistance gene and 10% interspersed midge susceptible refuge, are now available to farmers. The refuge prevents this resistance to be overcome by the insect. To test the field performance of these varietal blends, relative to conventional midge-susceptible cultivars, four varietal blends were grown during four consecutive years, at eight locations in the provinces of Manitoba Saskatchewan and Alberta, in comparison to four conventional, midge-susceptible cultivars. Midge damage was higher in 2007 and 2010, than in 2008 and 2009. In general, the varietal blends, as a group, yielded more grain than the susceptible cultivars, especially when grown in environments with high midge pressure (5.5 - 35% seed damage). In environments with low midge pressure (0 – 2.6% seed damage), the varietal blend average yield advantage was smaller but still significant, indicating that some of the varietal blends had additional superior attributes, in addition to midge resistance. Significant differences in midge damage were observed within the resistant and the susceptible groups of the cultivars tested. Midge resistance did not protect wheat against loss of market grade

    Mathematical Models of Feedback Systems for Control of Intra-Bunch Instabilities Driven by E-Clouds and TMCI

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    The feedback control of intra-bunch instabilities driven by electron-clouds or strong head-tail coupling (transverse mode coupled instabilities TMCI) requires bandwidth sufficient to sense the vertical position and apply correction fields to multiple sections of a nanosecond-scale bunch. These requirements impose challenges and limits in the design and implementation of the feedback control channel. This paper presents different models for the feedback subsystems: receiver, processing channel, amplifier and kicker, that take into account their frequency response and limits. These models are included in reduced mathematical models of the bunch dynamics and multi-particle simulation codes (WARP / C-MAD / HEADTAIL) to evaluate the impact of the subsystem limitations in the bunch stabilization and emittance improvement. With this realistic model of the hardware, it is possible to analyze and design the feedback system. This research is crucial to evaluate the boundary in the performance of the feedback control system due to technological limitations. Additionally, these models define the impact of parameter variations or mismatching and the effect of spurious perturbation and noise in the performance of the feedback system

    Core Mass Estimates in Strong Lensing Galaxy Clusters: A Comparison between Masses Obtained from Detailed Lens Models, Single-halo Lens Models, and Einstein Radii

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    The core mass of galaxy clusters is both an important anchor of the radial mass distribution profile and a probe of structure formation. With thousands of strong lensing galaxy clusters being discovered by current and upcoming surveys, timely, efficient, and accurate core mass estimates are needed. We assess the results of two efficient methods to estimate the core mass of strong lensing clusters: the mass enclosed by the Einstein radius (M(<θE), where θE is approximated from arc positions, and a single-halo lens model (MSHM), compared with measurements from publicly available detailed lens models (MDLM) of the same clusters. We use data from the Sloan Giant Arc Survey, the Reionization Lensing Cluster Survey, the Hubble Frontier Fields, and the Cluster Lensing and Supernova Survey with Hubble. We find a scatter of 18.1% (8.2%) with a bias of −7.1% (1.0%) between Mcorr(<θarcs){M}_{\mathrm{corr}}\left(\lt {\theta }_{\mathrm{arcs}}\right) (MSHM) and MDLM. Last, we compare the statistical uncertainties measured in this work to those from simulations. This work demonstrates the successful application of these methods to observational data. As the effort to efficiently model the mass distribution of strong lensing galaxy clusters continues, we need fast, reliable methods to advance the field
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