Direct strain and elastic energy evaluation in rolled-up semiconductor tubes by x-ray micro-diffraction

We depict the use of x-ray diffraction as a tool to directly probe the strain status in rolled-up semiconductor tubes. By employing continuum elasticity theory and a simple model we are able to simulate quantitatively the strain relaxation in perfect crystalline III-V semiconductor bi- and multilayers as well as in rolled-up layers with dislocations. The reduction in the local elastic energy is evaluated for each case. Limitations of the technique and theoretical model are discussed in detail.Comment: 32 pages (single column), 9 figures, 39 reference

Light response of pure CsI calorimeter crystals painted with wavelength-shifting lacquer

We have measured scintillation properties of pure CsI crystals used in the shower calorimeter built for a precise determination of the pi+ -> pi0 e+ nu decay rate at the Paul Scherrer Institute (PSI). All 240 individual crystals painted with a special wavelength-shifting solution were examined in a custom-build detection apparatus (RASTA=radioactive source tomography apparatus) that uses a 137Cs radioactive gamma source, cosmic muons and a light emitting diode as complementary probes of the scintillator light response. We have extracted the total light output, axial light collection nonuniformities and timing responses of the individual CsI crystals. These results predict improved performance of the 3 pi sr PIBETA calorimeter due to the painted lateral surfaces of 240 CsI crystals. The wavelength-shifting paint treatment did not affect appreciably the total light output and timing resolution of our crystal sample. The predicted energy resolution for positrons and photons in the energy range of 10-100 MeV was nevertheless improved due to the more favorable axial light collection probability variation. We have compared simulated calorimeter ADC spectra due to 70 MeV positrons and photons with a Monte Carlo calculation of an ideal detector light response.Comment: Elsevier LaTeX, 35 pages in e-print format, 15 Postscript Figures and 4 Tables, also available at http://pibeta.phys.virginia.edu/~pibeta/subprojects/csipro/tomo/rasta.p

Joint optimization and variable selection of high-dimensional gaussian processes.

Abstract Maximizing high-dimensional, non-convex functions through noisy observations is a notoriously hard problem, but one that arises in many applications. In this paper, we tackle this challenge by modeling the unknown function as a sample from a high-dimensional Gaussian process (GP) distribution. Assuming that the unknown function only depends on few relevant variables, we show that it is possible to perform joint variable selection and GP optimization. We provide strong performance guarantees for our algorithm, bounding the sample complexity of variable selection, and as well as providing cumulative regret bounds. We further provide empirical evidence on the effectiveness of our algorithm on several benchmark optimization problems

Coresets for Nonparametric Estimation -the Case of DP-Means

Abstract Scalable training of Bayesian nonparametric models is a notoriously difficult challenge. We explore the use of coresets -a data summarization technique originating from computational geometry -for this task. Coresets are weighted subsets of the data such that models trained on these coresets are provably competitive with models trained on the full dataset. Coresets sublinear in the dataset size allow for fast approximate inference with provable guarantees. Existing constructions, however, are limited to parametric problems. Using novel techniques in coreset construction we show the existence of coresets for DP-Means -a prototypical nonparametric clustering problem -and provide a practical construction algorithm. We empirically demonstrate that our algorithm allows us to efficiently trade off computation time and approximation error and thus scale DP-Means to large datasets. For instance, with coresets we can obtain a computational speedup of 45× at an approximation error of only 2.4% compared to solving on the full data set. In contrast, for the same subsample size, the "naive" approach of uniformly subsampling the data incurs an approximation error of 22.5%

A detailed analysis of a multi-agent diverse team

In an open system we can have many different kinds of agents. However, it is a challenge to decide which agents to pick when forming multi-agent teams. In some scenarios, agents coordinate by voting continuously. When forming such teams, should we focus on the diversity of the team or on the strength of each member? Can a team of diverse (and weak) agents outperform a uniform team of strong agents? We propose a new model to address these questions. Our key contributions include: (i) we show that a diverse team can overcome a uniform team and we give the necessary conditions for it to happen; (ii) we present optimal voting rules for a diverse team; (iii) we perform synthetic experiments that demonstrate that both diversity and strength contribute to the performance of a team; (iv) we show experiments that demonstrate the usefulness of our model in one of the most difficult challenges for Artificial Intelligence: Computer Go

Toward Perfection: Kapellasite, Cu3Zn(OH)6Cl2, a New Model S = 1/2 Kagome Antiferromagnet

The search for the resonating valence bond (RVB) state continues to underpin many areas of condensed matter research. The RVB is made from the dimerisation of spins on different sites into fluctuating singlets, and was proposed by Anderson to be the reference state from which the transition to BCS superconductivity occurs. Little is known about the state experimentally, due to the scarcity of model materials. Theoretical work has put forward the S = 1/2 kagome antiferromagnet (KAFM) as a good candidate for the realization of the RVB state. In this paper we introduce a new model system, the S = 1/2 KAFM Kapellasite, Cu3Zn(OH)6Cl2. We show that its crystal structure is a good approximation to a 2-dimensional kagome antiferromagnet and that susceptibility data indicate a collapse of the magnetic moment below T = 25 K that is compatible with the spins condensing into the non-magnetic RVB state.Comment: Communication, 3 pages, 3 figure

Cognitive function, social integration and mortality in a U.S. national cohort study of older adults

<p>Abstract</p> <p>Background</p> <p>Prior research suggests an interaction between social networks and Alzheimer's disease pathology and cognitive function, all predictors of survival in the elderly. We test the hypotheses that both social integration and cognitive function are independently associated with subsequent mortality and there is an interaction between social integration and cognitive function as related to mortality in a national cohort of older persons.</p> <p>Methods</p> <p>Data were analyzed from a longitudinal follow-up study of 5,908 American men and women aged 60 years and over examined in 1988–1994 followed an average 8.5 yr. Measurements at baseline included self-reported social integration, socio-demographics, health, body mass index, C-reactive protein and a short index of cognitive function (SICF).</p> <p>Results</p> <p>Death during follow-up occurred in 2,431. In bivariate analyses indicators of greater social integration were associated with higher cognitive function. Among persons with SICF score of 17, 22% died compared to 54% of those with SICF score of 0–11 (p < 0.0001). After adjusting for confounding by baseline socio-demographics and health status, the hazards ratio (HR) (95% confidence limits) for low SICF score was 1.43 (1.13–1.80, p < 0.001). After controlling for health behaviors, blood pressure and body mass, C-reactive protein and social integration, the HR was 1.36 (1.06–1.76, p = 0.02). Further low compared to high social integration was also independently associated with increased risk of mortality: HR 1.24 (1.02–1.52, p = 0.02).</p> <p>Conclusion</p> <p>In a cohort of older Americans, analyses demonstrated a higher risk of death independent of confounders among those with low cognitive function and low social integration with no significant interaction between them.</p