Testing linear hypotheses in high-dimensional regressions

For a multivariate linear model, Wilk's likelihood ratio test (LRT) constitutes one of the cornerstone tools. However, the computation of its quantiles under the null or the alternative requires complex analytic approximations and more importantly, these distributional approximations are feasible only for moderate dimension of the dependent variable, say $p\le 20$. On the other hand, assuming that the data dimension $p$ as well as the number $q$ of regression variables are fixed while the sample size $n$ grows, several asymptotic approximations are proposed in the literature for Wilk's \bLa including the widely used chi-square approximation. In this paper, we consider necessary modifications to Wilk's test in a high-dimensional context, specifically assuming a high data dimension $p$ and a large sample size $n$. Based on recent random matrix theory, the correction we propose to Wilk's test is asymptotically Gaussian under the null and simulations demonstrate that the corrected LRT has very satisfactory size and power, surely in the large $p$ and large $n$ context, but also for moderately large data dimensions like $p=30$ or $p=50$. As a byproduct, we give a reason explaining why the standard chi-square approximation fails for high-dimensional data. We also introduce a new procedure for the classical multiple sample significance test in MANOVA which is valid for high-dimensional data.Comment: Accepted 02/2012 for publication in "Statistics". 20 pages, 2 pages and 2 table

Multipartite entanglement in four-qubit cluster-class states

Based on quantitative complementarity relations (QCRs), we analyze the multipartite correlations in four-qubit cluster-class states. It is proven analytically that the average multipartite correlation $E_{ms}$ is entanglement monotone. Moreover, it is also shown that the mixed three-tangle is a correlation measure compatible with the QCRs in this kind of quantum states. More arrestingly, with the aid of the QCRs, a set of hierarchy entanglement measures is obtained rigorously in the present system.Comment: 7 pages, 3 figs, version 3, some refs. are adde

Parametrization of the Driven Betatron Oscillation

An AC dipole is a magnet which produces a sinusoidally oscillating dipole field and excites coherent transverse beam motion in a synchrotron. By observing this coherent motion, the optical parameters can be directly measured at the beam position monitor locations. The driven oscillation induced by an AC dipole will generate a phase space ellipse which differs from that of the free oscillation. If not properly accounted for, this difference can lead to a misinterpretation of the actual optical parameters, for instance, of 6% or more in the cases of the Tevatron, RHIC, or LHC. The effect of an AC dipole on the linear optics parameters is identical to that of a thin lens quadrupole. By introducing a new amplitude function to describe this new phase space ellipse, the motion produced by an AC dipole becomes easier to interpret. Beam position data taken under the influence of an AC dipole, with this new interpretation in mind, can lead to more precise measurements of the normal Courant-Snyder parameters. This new parameterization of the driven motion is presented and is used to interpret data taken in the FNAL Tevatron using an AC dipole.Comment: 8 pages, 8 figures, and 1 tabl

Scanning tunneling microscopy investigation of 2H-MoS_2: A layered semiconducting transition‐metal dichalcogenide

Scanning tunneling microscopy (STM) has been enormously successful in solving several important problems in the geometric and electronic structure of homogeneous metallic and semiconducting surfaces. A central question which remains to be answered with respect to the study of compound surfaces, however, is the extent to which the chemical identity of constituent atoms may be established. Recently, progress in this area was made by Feenstra et al. who succeeded in selectively imaging either Ga or As atoms on the GaAs (110) surface. So far this is the only case where such selectivity has been achieved. In an effort to add to our understanding of compound surface imaging we have undertaken a vacuum STM study of 2H-MoS_2, a material which has two structurally and electronically different atomic species at its surface

Quantum state redistribution based on a generalized decoupling

We develop a simple protocol for a one-shot version of quantum state redistribution, which is the most general two-terminal source coding problem. The protocol is simplified from a combination of protocols for the fully quantum reverse Shannon and fully quantum Slepian-Wolf problems, with its time-reversal symmetry being apparent. When the protocol is applied to the case where the redistributed states have a tensor power structure, more natural resource rates are obtained

Learning associations between clinical information and motion-based descriptors using a large scale MR-derived cardiac motion atlas

The availability of large scale databases containing imaging and non-imaging data, such as the UK Biobank, represents an opportunity to improve our understanding of healthy and diseased bodily function. Cardiac motion atlases provide a space of reference in which the motion fields of a cohort of subjects can be directly compared. In this work, a cardiac motion atlas is built from cine MR data from the UK Biobank (~ 6000 subjects). Two automated quality control strategies are proposed to reject subjects with insufficient image quality. Based on the atlas, three dimensionality reduction algorithms are evaluated to learn data-driven cardiac motion descriptors, and statistical methods used to study the association between these descriptors and non-imaging data. Results show a positive correlation between the atlas motion descriptors and body fat percentage, basal metabolic rate, hypertension, smoking status and alcohol intake frequency. The proposed method outperforms the ability to identify changes in cardiac function due to these known cardiovascular risk factors compared to ejection fraction, the most commonly used descriptor of cardiac function. In conclusion, this work represents a framework for further investigation of the factors influencing cardiac health.Comment: 2018 International Workshop on Statistical Atlases and Computational Modeling of the Hear

Synthesis of 2-Substituted 9-Oxa-Guanines {5-Aminooxazolo 5,4-D Pyrimidin-7(6H)-Ones} and 9-Oxa-2-Thio-Xanthines{5-Mercaptooxazolo 5,4-D Pyrimidin-7(6H)-Ones}

Oxazolo[5,4-d] pyrimidines can be considered as 9-oxa-purine analogs of naturally occurring nucleic acid bases. Interest in this ring system has increased due to recent reports of biologically active derivatives. In particular, 5-aminooxazolo[5,4-d]pyrimidine-7(6H)-ones (9-oxa-guanines) have been shown to inhibit ricin. The preparation of a series of 2-substituted 5-aminooxazolo[5,4-d] pyrimidin-7(6H)-ones and related 5-thio-oxazolo[5,4-d] pyrimidines is described, including analogs suitable for further elaboration employing "click" chemistry utilizing copper-catalyzed Huisgen 1,3-dipolar cycloadditions. Two of the compounds prepared were found to inhibit ricin with IC(50) ca. 1-3 mM.Pharmac

Stratified decision forests for accurate anatomical landmark localization in cardiac images

Accurate localization of anatomical landmarks is an important step in medical imaging, as it provides useful prior information for subsequent image analysis and acquisition methods. It is particularly useful for initialization of automatic image analysis tools (e.g. segmentation and registration) and detection of scan planes for automated image acquisition. Landmark localization has been commonly performed using learning based approaches, such as classifier and/or regressor models. However, trained models may not generalize well in heterogeneous datasets when the images contain large differences due to size, pose and shape variations of organs. To learn more data-adaptive and patient specific models, we propose a novel stratification based training model, and demonstrate its use in a decision forest. The proposed approach does not require any additional training information compared to the standard model training procedure and can be easily integrated into any decision tree framework. The proposed method is evaluated on 1080 3D highresolution and 90 multi-stack 2D cardiac cine MR images. The experiments show that the proposed method achieves state-of-theart landmark localization accuracy and outperforms standard regression and classification based approaches. Additionally, the proposed method is used in a multi-atlas segmentation to create a fully automatic segmentation pipeline, and the results show that it achieves state-of-the-art segmentation accuracy