4,563 research outputs found

    On explicit results at the intersection of the Z_2 and Z_4 orbifold subvarieties in K3 moduli space

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    We examine the recently found point of intersection between the Z_2 and Z_4 orbifold subvarieties in the K3 moduli space more closely. First we give an explicit identification of the coordinates of the respective Z_2 and Z_4 orbifold theories at this point. Secondly we construct the explicit identification of conformal field theories at this point and show the orthogonality of the two subvarieties.Comment: Latex, 23 page

    Numerical Ricci-flat metrics on K3

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    We develop numerical algorithms for solving the Einstein equation on Calabi-Yau manifolds at arbitrary values of their complex structure and Kahler parameters. We show that Kahler geometry can be exploited for significant gains in computational efficiency. As a proof of principle, we apply our methods to a one-parameter family of K3 surfaces constructed as blow-ups of the T^4/Z_2 orbifold with many discrete symmetries. High-resolution metrics may be obtained on a time scale of days using a desktop computer. We compute various geometric and spectral quantities from our numerical metrics. Using similar resources we expect our methods to practically extend to Calabi-Yau three-folds with a high degree of discrete symmetry, although we expect the general three-fold to remain a challenge due to memory requirements.Comment: 38 pages, 10 figures; program code and animations of figures downloadable from http://schwinger.harvard.edu/~wiseman/K3/ ; v2 minor corrections, references adde

    Efficient Modal Design Variables for Optimization of Aero-Elastic Wing

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    A Statistical Model for Simultaneous Template Estimation, Bias Correction, and Registration of 3D Brain Images

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    Template estimation plays a crucial role in computational anatomy since it provides reference frames for performing statistical analysis of the underlying anatomical population variability. While building models for template estimation, variability in sites and image acquisition protocols need to be accounted for. To account for such variability, we propose a generative template estimation model that makes simultaneous inference of both bias fields in individual images, deformations for image registration, and variance hyperparameters. In contrast, existing maximum a posterori based methods need to rely on either bias-invariant similarity measures or robust image normalization. Results on synthetic and real brain MRI images demonstrate the capability of the model to capture heterogeneity in intensities and provide a reliable template estimation from registration

    TVL<sub>1</sub> Planarity Regularization for 3D Shape Approximation

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    The modern emergence of automation in many industries has given impetus to extensive research into mobile robotics. Novel perception technologies now enable cars to drive autonomously, tractors to till a field automatically and underwater robots to construct pipelines. An essential requirement to facilitate both perception and autonomous navigation is the analysis of the 3D environment using sensors like laser scanners or stereo cameras. 3D sensors generate a very large number of 3D data points when sampling object shapes within an environment, but crucially do not provide any intrinsic information about the environment which the robots operate within. This work focuses on the fundamental task of 3D shape reconstruction and modelling from 3D point clouds. The novelty lies in the representation of surfaces by algebraic functions having limited support, which enables the extraction of smooth consistent implicit shapes from noisy samples with a heterogeneous density. The minimization of total variation of second differential degree makes it possible to enforce planar surfaces which often occur in man-made environments. Applying the new technique means that less accurate, low-cost 3D sensors can be employed without sacrificing the 3D shape reconstruction accuracy

    Perfectionism, achievement motives, and attribution of success and failure in female soccer players

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    While some researchers have identified adaptive perfectionism as a key characteristic to achieving elite performance in sport, others see perfectionism as a maladaptive characteristic that undermines, rather than helps, athletic performance. Arguing that perfectionism in sport contains both adaptive and maladaptive facets, the present article presents a study of N 5 74 female soccer players investigating how two facets of perfectionism—perfectionistic strivings and negative reactions to imperfection (Stoeber, Otto, Pescheck, Becker, & Stoll, 2007)—are related to achievement motives and attributions of success and failure. Results show that striving for perfection was related to hope of success and self-serving attributions (internal attribution of success). Moreover, once overlap between the two facets of perfectionism was controlled for, striving for perfection was inversely related to fear of failure and self-depreciating attributions (internal attribution of failure). In contrast, negative reactions to imperfection were positively related to fear of failure and self-depreciating attributions (external attribution of success) and inversely related to self-serving attributions (internal attribution of success and external attribution of failure). It is concluded that striving for perfection in sport is associated with an adaptive pattern of positive motivational orientations and self-serving attributions of success and failure, which may help athletic performance. In contrast, negative reactions to imperfection are associated with a maladaptive pattern of negative motivational orientations and self-depreciating attributions, which is likely to undermine athletic performance. Consequently, perfectionism in sport may be adaptive in those athletes who strive for perfection, but can control their negative reactions when performance is less than perfect

    Objectives and Constraints for Transonic Wing Optimization

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    Transfinite thin plate spline interpolation

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    Duchon's method of thin plate splines defines a polyharmonic interpolant to scattered data values as the minimizer of a certain integral functional. For transfinite interpolation, i.e. interpolation of continuous data prescribed on curves or hypersurfaces, Kounchev has developed the method of polysplines, which are piecewise polyharmonic functions of fixed smoothness across the given hypersurfaces and satisfy some boundary conditions. Recently, Bejancu has introduced boundary conditions of Beppo Levi type to construct a semi-cardinal model for polyspline interpolation to data on an infinite set of parallel hyperplanes. The present paper proves that, for periodic data on a finite set of parallel hyperplanes, the polyspline interpolant satisfying Beppo Levi boundary conditions is in fact a thin plate spline, i.e. it minimizes a Duchon type functional

    Monitoramento da variabilidade patogĂȘnica de Colletotrichum lindemuthianum em regiĂ”es produtoras de feijĂŁo no Brasil.

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    Com o objetivo monitorar a variabilidade patogĂȘnica de C. lindemuthianum nos Ășltimos seis anos, 664 amostras de feijoeiro com sintomas da doença, coletadas em regiĂ”es produtoras de feijĂŁo no Brasil, foram utilizadas para isolamento e identificação de patĂłtipos
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