485 research outputs found

    What About Interaction Geography to Evaluate Physical Learning Spaces?

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    This paper reviews and explores how interaction geography, a new approach to visualize people’s interaction over space and time, extends current approaches to evaluate physical learning spaces. This chapter begins by reviewing representations produced using interaction geography to study visitor engagement and learning in a museum. In particular, this review illustrates Mondrian Transcription, a method to map people’s movement and conversation over space and time, and the Interaction Geography Slicer (IGS), a dynamic visualisation tool that supports new forms of interaction and multi-modal analysis. Subsequently, this chapter explores how interaction geography may advance the evaluation of physical learning spaces by providing dynamic information visualisation methods that support more expansive views of learning and the evaluation of the alignment between space and pedagogy. This chapter concludes by outlining significant limitations and next steps to expand interaction geography to evaluate physical learning spaces

    The TOPSHOCK study: Effectiveness of radial shockwave therapy compared to focused shockwave therapy for treating patellar tendinopath - design of a randomised controlled trial

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    Background: Patellar tendinopathy is a chronic overuse injury of the patellar tendon that is especially prevalent in people who are involved in jumping activities. Extracorporeal Shockwave Therapy is a relatively new treatment modality for tendinopathies. It seems to be a safe and promising part of the rehabilitation program for patellar tendinopathy. Extracorporeal Shockwave Therapy originally used focused shockwaves. Several years ago a new kind of shockwave therapy was introduced: radial shockwave therapy. Studies that investigate the effectiveness of radial shockwave therapy as treatment for patellar tendinopathy are scarce. Therefore the aim of this study is to compare the effectiveness of focussed shockwave therapy and radial shockwave therapy as treatments for patellar tendinopathy. Methods/design: The TOPSHOCK study (Tendinopathy Of Patella SHOCKwave) is a two-armed randomised controlled trial in which the effectiveness of focussed shockwave therapy and radial shockwave therapy are directly compared. Outcome assessors and patients are blinded as to which treatment is given. Patients undergo three sessions of either focused shockwave therapy or radial shockwave therapy at 1-week intervals, both in combination with eccentric decline squat training. Follow-up measurements are scheduled just before treatments 2 and 3, and 1, 4, 7 and 12 weeks after the final treatment. The main outcome measure is the Dutch VISA-P questionnaire, which asks for pain, function and sports participation in subjects with patellar tendinopathy. Secondary outcome measures are pain determined with a VAS during ADL, sports and decline squats, rating of subjective improvement and overall satisfaction with the treatment. Patients will also record their sports activities, pain during and after these activities, and concurrent medical treatment on a weekly basis in a web-based diary. Results will be analysed according to the intention-to-treat principle. Discussion: The TOPSHOCK study is the first randomised controlled trial that directly compares the effectiveness of focused shockwave therapy and radial shockwave therapy, both in combination with eccentric decline squat training, for treating patellar tendinopathy. Trial registration: Trial registration number NTR2774

    F-theory and Neutrinos: Kaluza-Klein Dilution of Flavor Hierarchy

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    We study minimal implementations of Majorana and Dirac neutrino scenarios in F-theory GUT models. In both cases the mass scale of the neutrinos m_nu ~ (M_weak)^2/M_UV arises from integrating out Kaluza-Klein modes, where M_UV is close to the GUT scale. The participation of non-holomorphic Kaluza-Klein mode wave functions dilutes the mass hierarchy in comparison to the quark and charged lepton sectors, in agreement with experimentally measured mass splittings. The neutrinos are predicted to exhibit a "normal" mass hierarchy, with masses m_3,m_2,m_1 ~ .05*(1,(alpha_GUT)^(1/2),alpha_GUT) eV. When the interactions of the neutrino and charged lepton sectors geometrically unify, the neutrino mixing matrix exhibits a mild hierarchical structure such that the mixing angles theta_23 and theta_12 are large and comparable, while theta_13 is expected to be smaller and close to the Cabibbo angle: theta_13 ~ theta_C ~ (alpha_GUT)^(1/2) ~ 0.2. This suggests that theta_13 should be near the current experimental upper bound.Comment: v2: 83 pages, 10 figures, references adde

    Use of genomic DNA control features and predicted operon structure in microarray data analysis: ArrayLeaRNA – a Bayesian approach

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    <p>Abstract</p> <p>Background</p> <p>Microarrays are widely used for the study of gene expression; however deciding on whether observed differences in expression are significant remains a challenge.</p> <p>Results</p> <p>A computing tool (ArrayLeaRNA) has been developed for gene expression analysis. It implements a Bayesian approach which is based on the Gumbel distribution and uses printed genomic DNA control features for normalization and for estimation of the parameters of the Bayesian model and prior knowledge from predicted operon structure. The method is compared with two other approaches: the classical LOWESS normalization followed by a two fold cut-off criterion and the OpWise method (Price, et al. 2006. BMC Bioinformatics. 7, 19), a published Bayesian approach also using predicted operon structure. The three methods were compared on experimental datasets with prior knowledge of gene expression. With ArrayLeaRNA, data normalization is carried out according to the genomic features which reflect the results of equally transcribed genes; also the statistical significance of the difference in expression is based on the variability of the equally transcribed genes. The operon information helps the classification of genes with low confidence measurements.</p> <p>ArrayLeaRNA is implemented in Visual Basic and freely available as an Excel add-in at <url>http://www.ifr.ac.uk/safety/ArrayLeaRNA/</url></p> <p>Conclusion</p> <p>We have introduced a novel Bayesian model and demonstrated that it is a robust method for analysing microarray expression profiles. ArrayLeaRNA showed a considerable improvement in data normalization, in the estimation of the experimental variability intrinsic to each hybridization and in the establishment of a clear boundary between non-changing and differentially expressed genes. The method is applicable to data derived from hybridizations of labelled cDNA samples as well as from hybridizations of labelled cDNA with genomic DNA and can be used for the analysis of datasets where differentially regulated genes predominate.</p

    Constraints from muon g-2 and LFV processes in the Higgs Triplet Model

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    Constraints from the muon anomalous magnetic dipole moment and lepton flavor violating processes are translated into lower bounds on v_Delta*m_H++ in the Higgs Triplet Model by considering correlations through the neutrino mass matrix. The discrepancy of the sign of the contribution to the muon anomalous magnetic dipole moment between the measurement and the prediction in the model is clarified. It is shown that mu to e gamma, tau decays (especially, tau to mu e e), and the muonium conversion can give a more stringent bound on v_Delta*m_H++ than the bound from mu to eee which is expected naively to give the most stringent one.Comment: 18 pages, 16 figure

    Lazy Lasso for local regression

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    Locally weighted regression is a technique that predicts the response for new data items from their neighbors in the training data set, where closer data items are assigned higher weights in the prediction. However, the original method may suffer from overfitting and fail to select the relevant variables. In this paper we propose combining a regularization approach with locally weighted regression to achieve sparse models. Specifically, the lasso is a shrinkage and selection method for linear regression. We present an algorithm that embeds lasso in an iterative procedure that alternatively computes weights and performs lasso-wise regression. The algorithm is tested on three synthetic scenarios and two real data sets. Results show that the proposed method outperforms linear and local models for several kinds of scenario

    Beyond the standard seesaw: neutrino masses from Kahler operators and broken supersymmetry

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    We investigate supersymmetric scenarios in which neutrino masses are generated by effective d=6 operators in the Kahler potential, rather than by the standard d=5 superpotential operator. First, we discuss some general features of such effective operators, also including SUSY-breaking insertions, and compute the relevant renormalization group equations. Contributions to neutrino masses arise at low energy both at the tree level and through finite threshold corrections. In the second part we present simple explicit realizations in which those Kahler operators arise by integrating out heavy SU(2)_W triplets, as in the type II seesaw. Distinct scenarios emerge, depending on the mechanism and the scale of SUSY-breaking mediation. In particular, we propose an appealing and economical picture in which the heavy seesaw mediators are also messengers of SUSY breaking. In this case, strong correlations exist among neutrino parameters, sparticle and Higgs masses, as well as lepton flavour violating processes. Hence, this scenario can be tested at high-energy colliders, such as the LHC, and at lower energy experiments that measure neutrino parameters or search for rare lepton decays.Comment: LaTeX, 34 pages; some corrections in Section

    Liquid metal nanodroplet dynamics inside nanocontainers

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    Here we report direct observations of spatial movements of nanodroplets of Pb metal trapped inside sealed carbon nanocontainers. We find drastic changes in the mobility of the liquid droplets as the particle size increases from a few to a few ten nanometers. In open containers the droplet becomes immobile and readily evaporates to the vacuum environment. The particle mobility strongly depends on confinement, particle size, and wetting on the enclosed surface. The collisions between droplets increase mobility but the tendency is reversed if collisions lead to droplet coalescence. The dynamics of confined nanodroplets could provide new insights into the activity of nanostructures in spatially constrained geometries

    An efficient approach to BAC based assembly of complex genomes

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    Background: There has been an exponential growth in the number of genome sequencing projects since the introduction of next generation DNA sequencing technologies. Genome projects have increasingly involved assembly of whole genome data which produces inferior assemblies compared to traditional Sanger sequencing of genomic fragments cloned into bacterial artificial chromosomes (BACs). While whole genome shotgun sequencing using next generation sequencing (NGS) is relatively fast and inexpensive, this method is extremely challenging for highly complex genomes, where polyploidy or high repeat content confounds accurate assembly, or where a highly accurate ‘gold’ reference is required. Several attempts have been made to improve genome sequencing approaches by incorporating NGS methods, to variable success. Results: We present the application of a novel BAC sequencing approach which combines indexed pools of BACs, Illumina paired read sequencing, a sequence assembler specifically designed for complex BAC assembly, and a custom bioinformatics pipeline. We demonstrate this method by sequencing and assembling BAC cloned fragments from bread wheat and sugarcane genomes. Conclusions: We demonstrate that our assembly approach is accurate, robust, cost effective and scalable, with applications for complete genome sequencing in large and complex genomes
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