Penrose type inequalities for asymptotically hyperbolic graphs

In this paper we study asymptotically hyperbolic manifolds given as graphs of asymptotically constant functions over hyperbolic space \bH^n. The graphs are considered as subsets of \bH^{n+1} and carry the induced metric. For such manifolds the scalar curvature appears in the divergence of a 1-form involving the integrand for the asymptotically hyperbolic mass. Integrating this divergence we estimate the mass by an integral over an inner boundary. In case the inner boundary satisfies a convexity condition this can in turn be estimated in terms of the area of the inner boundary. The resulting estimates are similar to the conjectured Penrose inequality for asymptotically hyperbolic manifolds. The work presented here is inspired by Lam's article concerning the asymptotically Euclidean case.Comment: 29 pages, no figure, includes a proof of the equality cas

The analysis of bridging constructs with hierarchical clustering methods: An application to identity

When analyzing psychometric surveys, some design and sample size limitations challenge existing approaches. Hierarchical clustering, with its graphics (heat maps, dendrograms, means plots), provides a nonparametric method for analyzing factorially-designed survey data, and small samples data. In the present study, we demonstrated the advantages of using hierarchical clustering (HC) for the analysis of non-higher-order measures, comparing the results of HC against those of exploratory factor analysis. As a factorially-designed survey, we used the Identity Labels and Life Contexts Questionnaire (ILLCQ), a novel measure to assess identity as a bridging construct for the intersection of identity domains and life contexts. Results suggest that, when used to validate factorially-designed measures, HC and its graphics are more stable and consistent compared to EFA

A Classroom Activity for Teaching Kohlberg’s Theory of Moral Development

In two studies, we demonstrate an engaging classroom activity that facilitates student learning about Kohlberg’s theory of moral development by using digital resources to foster active, experiential learning. In addition to hearing a standard lecture about moral development, students watched a video of a morally provocative incident, then worked in small groups to classify user comments posted in response to the video according to Kohlberg’s six stages. Students in both studies found the activity enjoyable and useful. Moreover, students’ scores on a moral development quiz improved after completing the activity (Study 1), and students who completed the activity in addition to receiving a lecture performed better on the quiz than students who received lecture alone (Study 2)

Moving Through Cancer: Setting the Agenda to Make Exercise Standard in Oncology Practice

International evidence?based guidelines support the prescription of exercise for all individuals living with and beyond cancer.This article describes the agenda of the newly formed Moving Through Cancer initiative, which has a primary objective of making exercise standard practice in oncology by 2029

Distributionally Robust Deep Learning using Hardness Weighted Sampling

Limiting failures of machine learning systems is vital for safety-critical applications. In order to improve the robustness of machine learning systems, Distributionally Robust Optimization (DRO) has been proposed as a generalization of Empirical Risk Minimization (ERM)aiming at addressing this need. However, its use in deep learning has been severely restricted due to the relative inefficiency of the optimizers available for DRO in comparison to the wide-spread variants of Stochastic Gradient Descent (SGD) optimizers for ERM. We propose SGD with hardness weighted sampling, a principled and efficient optimization method for DRO in machine learning that is particularly suited in the context of deep learning. Similar to a hard example mining strategy in essence and in practice, the proposed algorithm is straightforward to implement and computationally as efficient as SGD-based optimizers used for deep learning, requiring minimal overhead computation. In contrast to typical ad hoc hard mining approaches, and exploiting recent theoretical results in deep learning optimization, we prove the convergence of our DRO algorithm for over-parameterized deep learning networks with ReLU activation and finite number of layers and parameters. Our experiments on brain tumor segmentation in MRI demonstrate the feasibility and the usefulness of our approach. Using our hardness weighted sampling leads to a decrease of 2% of the interquartile range of the Dice scores for the enhanced tumor and the tumor core regions. The code for the proposed hard weighted sampler will be made publicly available

Vitamin D supplementation and breast cancer prevention : a systematic review and meta-analysis of randomized clinical trials

In recent years, the scientific evidence linking vitamin D status or supplementation to breast cancer has grown notably. To investigate the role of vitamin D supplementation on breast cancer incidence, we conducted a systematic review and meta-analysis of randomized controlled trials comparing vitamin D with placebo or no treatment. We used OVID to search MEDLINE (R), EMBASE and CENTRAL until April 2012. We screened the reference lists of included studies and used the “Related Article” feature in PubMed to identify additional articles. No language restrictions were applied. Two reviewers independently extracted data on methodological quality, participants, intervention, comparison and outcomes. Risk Ratios and 95% Confident Intervals for breast cancer were pooled using a random-effects model. Heterogeneity was assessed using the I2 test. In sensitivity analysis, we assessed the impact of vitamin D dosage and mode of administration on treatment effects. Only two randomized controlled trials fulfilled the pre-set inclusion criteria. The pooled analysis included 5372 postmenopausal women. Overall, Risk Ratios and 95% Confident Intervals were 1.11 and 0.74–1.68. We found no evidence of heterogeneity. Neither vitamin D dosage nor mode of administration significantly affected breast cancer risk. However, treatment efficacy was somewhat greater when vitamin D was administered at the highest dosage and in combination with calcium (Risk Ratio 0.58, 95% Confident Interval 0.23–1.47 and Risk Ratio 0.93, 95% Confident Interval 0.54–1.60, respectively). In conclusions, vitamin D use seems not to be associated with a reduced risk of breast cancer development in postmenopausal women. However, the available evidence is still limited and inadequate to draw firm conclusions. Study protocol code: FARM8L2B5L

The personal norm of reciprocity

Reciprocity is here considered as an internalized social norm, and a questionnaire to measure individual differences in the internalized norm of reciprocity is presented. The questionnaire, Personal Norm of Reciprocity (PNR), measures three aspects of reciprocity: positive reciprocity, negative reciprocity, and beliefs in reciprocity. The PNR has been developed and tested in two cultures, British and Italian, for a total of 951 participants. A cross-cultural study provides evidence of good psychometric properties and generalizability of the PNR. Data provide evidence for criterion validity and show that positive and negative reciprocators behave in different ways as a function of the valence (positive or negative) of the other's past behaviour, the type of feasible reaction (reward versus punishment), and the fairness of their reaction. Copyright (C) 2002 John Wiley Sons, Ltd

High frequency oscillations during magnetar flares

The recent discovery of high frequency oscillations during giant flares from the Soft Gamma Repeaters SGR 1806-20 and SGR 1900+14 may be the first direct detection of vibrations in a neutron star crust. If this interpretation is correct it offers a novel means of testing the neutron star equation of state, crustal breaking strain, and magnetic field configuration. We review the observational data on the magnetar oscillations, including new timing analysis of the SGR 1806-20 giant flare using data from the Ramaty High Energy Solar Spectroscopic Imager (RHESSI) and the Rossi X-ray Timing Explorer (RXTE). We discuss the implications for the study of neutron star structure and crust thickness, and outline areas for future investigation.Comment: 5 pages, 1 figure, to appear in the proceedings of the conference "Isolated Neutron Stars: from the Interior to the Surface" (April 2006, London), eds. D. Page, R. Turolla, & S. Zane, Astrophysics & Space Science in pres