A BAYESIAN SHRINKAGE MODEL FOR INCOMPLETE LONGITUDINAL BINARY DATA WITH APPLICATION TO THE BREAST CANCER PREVENTION TRIAL

We consider inference in randomized studies, in which repeatedly measured outcomes may be informatively missing due to drop out. In this setting, it is well known that full data estimands are not identified unless unverified assumptions are imposed. We assume a non-future dependence model for the drop-out mechanism and posit an exponential tilt model that links non-identifiable and identifiable distributions. This model is indexed by non-identified parameters, which are assumed to have an informative prior distribution, elicited from subject-matter experts. Under this model, full data estimands are shown to be expressed as functionals of the distribution of the observed data. To avoid the curse of dimensionality, we model the distribution of the observed data using a Bayesian shrinkage model. In a simulation study, we compare our approach to a fully parametric and a fully saturated model for the distribution of the observed data. Our methodology is motivated and applied to data from the Breast Cancer Prevention Trial

Sclerosponges: Primary framework constructors on the Jamaican deep fore-reef

Sclerosponges grow on hard substrates in areas protected from high rates of sediment accumulation to depths of about 200 m at Discovery Bay, Jamaica. Here they are primary framework builders on the deep fore-reef between 70 m and 105 m

Lamb Wave Modes in Coal-Tar-Coated Steel Plates

In order to study the feasibility of using ultrasonic Lamb wave modes for detection and sizing of corrosion-related flaws in buried steel pipelines, we have calculated Lamb wave modes and performed numerous experiments on steel plates coated on one side with coal-tar enamel. The purpose of this paper is to discuss these theoretical and experimental results

Joint Learning of Intrinsic Images and Semantic Segmentation

Semantic segmentation of outdoor scenes is problematic when there are variations in imaging conditions. It is known that albedo (reflectance) is invariant to all kinds of illumination effects. Thus, using reflectance images for semantic segmentation task can be favorable. Additionally, not only segmentation may benefit from reflectance, but also segmentation may be useful for reflectance computation. Therefore, in this paper, the tasks of semantic segmentation and intrinsic image decomposition are considered as a combined process by exploring their mutual relationship in a joint fashion. To that end, we propose a supervised end-to-end CNN architecture to jointly learn intrinsic image decomposition and semantic segmentation. We analyze the gains of addressing those two problems jointly. Moreover, new cascade CNN architectures for intrinsic-for-segmentation and segmentation-for-intrinsic are proposed as single tasks. Furthermore, a dataset of 35K synthetic images of natural environments is created with corresponding albedo and shading (intrinsics), as well as semantic labels (segmentation) assigned to each object/scene. The experiments show that joint learning of intrinsic image decomposition and semantic segmentation is beneficial for both tasks for natural scenes. Dataset and models are available at: https://ivi.fnwi.uva.nl/cv/intrinsegComment: ECCV 201

Footprints of Statistical Anisotropies

We propose and develop a formalism to describe and constrain statistically anisotropic primordial perturbations. Starting from a decomposition of the primordial power spectrum in spherical harmonics, we find how the temperature fluctuations observed in the CMB sky are directly related to the coefficients in this harmonic expansion. Although the angular power spectrum does not discriminate between statistically isotropic and anisotropic perturbations, it is possible to define analogous quadratic estimators that are direct measures of statistical anisotropy. As a simple illustration of our formalism we test for the existence of a preferred direction in the primordial perturbations using full-sky CMB maps. We do not find significant evidence supporting the existence of a dipole component in the primordial spectrum.Comment: 26 pages, 5 double figures. Uses RevTeX

Zero Energy of Plane-Waves for ELKOs

We consider the ELKO field in interaction through contorsion with its own spin density, and we investigate the form of the consequent autointeractions; to do so we take into account the high-density limit and find plane wave solutions: such plane waves give rise to contorsional autointeractions for which the Ricci metric curvature vanishes and therefore the energy density is equal to zero identically. Consequences are discussed.Comment: 7 page

Cosmic Microwave Background, Accelerating Universe and Inhomogeneous Cosmology

We consider a cosmology in which a spherically symmetric large scale inhomogeneous enhancement or a void are described by an inhomogeneous metric and Einstein's gravitational equations. For a flat matter dominated universe the inhomogeneous equations lead to luminosity distance and Hubble constant formulas that depend on the location of the observer. For a general inhomogeneous solution, it is possible for the deceleration parameter to differ significantly from the FLRW result. The deceleration parameter $q_0$ can be interpreted as $q_0 > 0$ ($q_0=1/2$ for a flat matter dominated universe) in a FLRW universe and be $q_0 < 0$ as inferred from the inhomogeneous enhancement that is embedded in a FLRW universe. A spatial volume averaging of local regions in the backward light cone has to be performed for the inhomogeneous solution at late times to decide whether the decelerating parameter $q$ can be negative for a positive energy condition. The CMB temperature fluctuations across the sky can be unevenly distributed in the northern and southern hemispheres in the inhomogeneous matter dominated solution, in agreement with the analysis of the WMAP power spectrum data by several authors. The model can possibly explain the anomalous alignment of the quadrupole and octopole moments observed in the WMAP data.Comment: 20 pages, no figures, LaTex file. Equations and typos corrected and references added. Additional material and some conclusions changed. Final published versio

The New ‘Hidden Abode’: Reflections on Value and Labour in the New Economy

In a pivotal section of Capital, volume 1, Marx (1976: 279) notes that, in order to understand the capitalist production of value, we must descend into the ‘hidden abode of production’: the site of the labour process conducted within an employment relationship. In this paper we argue that by remaining wedded to an analysis of labour that is confined to the employment relationship, Labour Process Theory (LPT) has missed a fundamental shift in the location of value production in contemporary capitalism. We examine this shift through the work of Autonomist Marxists like Hardt and Negri, Lazaratto and Arvidsson, who offer theoretical leverage to prize open a new ‘hidden abode’ outside employment, for example in the ‘production of organization’ and in consumption. Although they can open up this new ‘hidden abode’, without LPT's fine-grained analysis of control/resistance, indeterminacy and structured antagonism, these theorists risk succumbing to empirically naive claims about the ‘new economy’. Through developing an expanded conception of a ‘new hidden abode’ of production, the paper demarcates an analytical space in which both LPT and Autonomist Marxism can expand and develop their understanding of labour and value production in today's economy. </jats:p