759 resultados para Calabi-Yau manifold


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The first edition of this new multi-authored publication entitled ‘Migration Panorama’ focuses on the consequences of the refugee and migration crisis on the Schengen area and the concept of a borderless union. Several external and EPC authors have contributed to building a comprehensive picture on the manifold challenges and possible consequences of maintaining and/or returning to internal border controls among Schengen countries. How does a signatory of the Schengen agreement see the current developments? What would be the impact of the reintroduction of physical borders on Europe’s digital economy? In what way do the V4 countries envisage to solve the ‘Schengen crisis’? How dangerous are the empty threats to expel Greece out of the Schengen area? What is the symbolic meaning of the Belgian border controls following the French decision to dismantle parts of the Calais ‘jungle’? Is saving Schengen only a question of national sovereignty or a matter of shared European responsibility? All these questions and many others are tackled in this first issue of the ‘Migration Panorama’ produced by EPC’ s Migration and Diversity Programme.

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The EU Summit and the separate meeting of the EU27 without the UK on 28/29 June 2016 demonstrated that the EU is in limbo. Following the initial shock, frustration and anger after the unexpected result of the UK ‘in/out’ referendum, the future relationship between the European Union (EU) and the United Kingdom (UK) monopolised the meetings of EU leaders. The EU has entered uncharted waters and leaders are struggling to figure out how exactly to deal with the manifold (potential) consequences of the ‘Brexit crisis’. Despite the many uncertainties, the EU27 managed to reach some common lines, trying to convey four key messages, although the final outcome of the crisis and its effects on the Union’s overall future are still very unclear:

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Mode of access: Internet.

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Mode of access: Internet.

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Vita.

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Thesis (Ph.D.)--University of Washington, 2016-06

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A two-component mixture regression model that allows simultaneously for heterogeneity and dependency among observations is proposed. By specifying random effects explicitly in the linear predictor of the mixture probability and the mixture components, parameter estimation is achieved by maximising the corresponding best linear unbiased prediction type log-likelihood. Approximate residual maximum likelihood estimates are obtained via an EM algorithm in the manner of generalised linear mixed model (GLMM). The method can be extended to a g-component mixture regression model with the component density from the exponential family, leading to the development of the class of finite mixture GLMM. For illustration, the method is applied to analyse neonatal length of stay (LOS). It is shown that identification of pertinent factors that influence hospital LOS can provide important information for health care planning and resource allocation. (C) 2002 Elsevier Science B.V. All rights reserved.

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The modelling of inpatient length of stay (LOS) has important implications in health care studies. Finite mixture distributions are usually used to model the heterogeneous LOS distribution, due to a certain proportion of patients sustaining-a longer stay. However, the morbidity data are collected from hospitals, observations clustered within the same hospital are often correlated. The generalized linear mixed model approach is adopted to accommodate the inherent correlation via unobservable random effects. An EM algorithm is developed to obtain residual maximum quasi-likelihood estimation. The proposed hierarchical mixture regression approach enables the identification and assessment of factors influencing the long-stay proportion and the LOS for the long-stay patient subgroup. A neonatal LOS data set is used for illustration, (C) 2003 Elsevier Science Ltd. All rights reserved.

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What is the minimal size quantum circuit required to exactly implement a specified n-qubit unitary operation, U, without the use of ancilla qubits? We show that a lower bound on the minimal size is provided by the length of the minimal geodesic between U and the identity, I, where length is defined by a suitable Finsler metric on the manifold SU(2(n)). The geodesic curves on these manifolds have the striking property that once an initial position and velocity are set, the remainder of the geodesic is completely determined by a second order differential equation known as the geodesic equation. This is in contrast with the usual case in circuit design, either classical or quantum, where being given part of an optimal circuit does not obviously assist in the design of the rest of the circuit. Geodesic analysis thus offers a potentially powerful approach to the problem of proving quantum circuit lower bounds. In this paper we construct several Finsler metrics whose minimal length geodesics provide lower bounds on quantum circuit size. For each Finsler metric we give a procedure to compute the corresponding geodesic equation. We also construct a large class of solutions to the geodesic equation, which we call Pauli geodesics, since they arise from isometries generated by the Pauli group. For any unitary U diagonal in the computational basis, we show that: (a) provided the minimal length geodesic is unique, it must be a Pauli geodesic; (b) finding the length of the minimal Pauli geodesic passing from I to U is equivalent to solving an exponential size instance of the closest vector in a lattice problem (CVP); and (c) all but a doubly exponentially small fraction of such unitaries have minimal Pauli geodesics of exponential length.

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To account for the preponderance of zero counts and simultaneous correlation of observations, a class of zero-inflated Poisson mixed regression models is applicable for accommodating the within-cluster dependence. In this paper, a score test for zero-inflation is developed for assessing correlated count data with excess zeros. The sampling distribution and the power of the test statistic are evaluated by simulation studies. The results show that the test statistic performs satisfactorily under a wide range of conditions. The test procedure is further illustrated using a data set on recurrent urinary tract infections. Copyright (c) 2005 John Wiley & Sons, Ltd.

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Transgenic tobacco plants, carrying a Potato virus Y (PVY)-NIa hairpin sequence separated by a unique unrelated spacer sequence were specifically silenced and highly resistant to PVY infection. In such plants neither PVY-NIa nor spacer transgene transcripts were detectable by specific quantitative real time reverse transcriptase PCR (RT-qPCR) assays of similar relative efficiencies developed for direct comparative analysis. However, small interfering RNAs (siRNAs) specific for the PVY sequence of the transgene and none specific for the LNYV spacer sequence were detected. Following infection with Cucumber mosaic virus (CMV), which suppresses dsRNA-induced RNA silencing, transcript levels of PVY-NIa as well as spacer sequence increased manifold with the same time course. The cellular abundance of the single-stranded (ss) spacer sequence was consistently higher than that of PVY dsRNA in all cases. The results show that during RNA silencing and its suppression of a hairpin transcript in transgenic tobacco, the ssRNA spacer sequence is affected differently than the dsRNA. In PVY-silenced plants. the spacer is efficiently degraded by a mechanism not involving the accumulation of siRNAs, while following suppression of RNA silencing by CMV, the spacer appears protected from degradation. Crown Copyright (c) 2006 Published by Elsevier B.V. All rights reserved.

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Count data with excess zeros relative to a Poisson distribution are common in many biomedical applications. A popular approach to the analysis of such data is to use a zero-inflated Poisson (ZIP) regression model. Often, because of the hierarchical Study design or the data collection procedure, zero-inflation and lack of independence may occur simultaneously, which tender the standard ZIP model inadequate. To account for the preponderance of zero counts and the inherent correlation of observations, a class of multi-level ZIP regression model with random effects is presented. Model fitting is facilitated using an expectation-maximization algorithm, whereas variance components are estimated via residual maximum likelihood estimating equations. A score test for zero-inflation is also presented. The multi-level ZIP model is then generalized to cope with a more complex correlation structure. Application to the analysis of correlated count data from a longitudinal infant feeding study illustrates the usefulness of the approach.

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We prove upper and lower bounds relating the quantum gate complexity of a unitary operation, U, to the optimal control cost associated to the synthesis of U. These bounds apply for any optimal control problem, and can be used to show that the quantum gate complexity is essentially equivalent to the optimal control cost for a wide range of problems, including time-optimal control and finding minimal distances on certain Riemannian, sub-Riemannian, and Finslerian manifolds. These results generalize the results of [Nielsen, Dowling, Gu, and Doherty, Science 311, 1133 (2006)], which showed that the gate complexity can be related to distances on a Riemannian manifold.

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We present existence results for a Neumann problem involving critical Sobolev nonlinearities both on the right hand side of the equation and at the boundary condition.. Positive solutions are obtained through constrained minimization on the Nehari manifold. Our approach is based on the concentration 'compactness principle of P. L. Lions and M. Struwe.