Psychological Impact of Significantly Short Stature

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142466/1/apa199180s37714.pd

On the sequential massart algorithm for statistical model checking

Several schemes have been provided in Statistical Model Checking (SMC) for the estimation of property occurrence based on predefined confidence and absolute or relative error. Simulations might be however costly if many samples are required and the usual algorithms implemented in statistical model checkers tend to be conservative. Bayesian and rare event techniques can be used to reduce the sample size but they can not be applied without prerequisite or knowledge about the system under scrutiny. Recently, sequential algorithms based on Monte Carlo estimations and Massart bounds have been proposed to reduce the sample size while providing guarantees on error bounds which has been shown to outperform alternative frequentist approaches [15]. In this work, we discuss some features regarding the distribution and the optimisation of these algorithms.No Full Tex

Rapid Diagnostic Algorithms as a Screening Tool for Tuberculosis: An Assessor Blinded Cross-Sectional Study

Background: A major obstacle to effectively treat and control tuberculosis is the absence of an accurate, rapid, and low-cost diagnostic tool. A new approach for the screening of patients for tuberculosis is the use of rapid diagnostic classification algorithms. Methods: We tested a previously published diagnostic algorithm based on four biomarkers as a screening tool for tuberculosis in a Central European patient population using an assessor-blinded cross-sectional study design. In addition, we developed an improved diagnostic classification algorithm based on a study population at a tertiary hospital in Vienna, Austria, by supervised computational statistics. Results: The diagnostic accuracy of the previously published diagnostic algorithm for our patient population consisting of 206 patients was 54% (CI: 47%–61%). An improved model was constructed using inflammation parameters and clinical information. A diagnostic accuracy of 86% (CI: 80%–90%) was demonstrated by 10-fold cross validation. An alternative model relying solely on clinical parameters exhibited a diagnostic accuracy of 85% (CI: 79%–89%). Conclusion: Here we show that a rapid diagnostic algorithm based on clinical parameters is only slightly improved by inclusion of inflammation markers in our cohort. Our results also emphasize the need for validation of new diagnostic algorithms in different settings and patient populations

Sequential schemes for frequentist estimation of properties in statistical model checking

National Research Foundation (NRF) Singapor

Galaxy Zoo: CANDELS barred discs and bar fractions

The formation of bars in disc galaxies is a tracer of the dynamical maturity of the population. Previous studies have found that the incidence of bars in discs decreases from the local Universe to z ~ 1, and by z > 1 simulations predict that bar features in dynamically mature discs should be extremely rare. Here, we report the discovery of strong barred structures in massive disc galaxies at z ~ 1.5 in deep rest-frame optical images from the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey. From within a sample of 876 disc galaxies identified by visual classification in Galaxy Zoo, we identify 123 barred galaxies. Selecting a subsample within the same region of the evolving galaxy luminosity function (brighter than L*), we find that the bar fraction across the redshift range 0.5 ≤ z ≤ 2 (fbar = 10.7+6.3 -3.5 per cent after correcting for incompleteness) does not significantly evolve.We discuss the implications of this discovery in the context of existing simulations and our current understanding of the way disc galaxies have evolved over the last 11 billion yearsPeer reviewedFinal Accepted Versio

About Low DFR for QC-MDPC Decoding

International audienceMcEliece-like code-based key exchange mechanisms using QC-MDPC codes can reach IND-CPA security under hardness assumptions from coding theory, namely quasi-cyclic syndrome decoding and quasi-cyclic codeword finding. To reach higher security requirements, like IND-CCA security, it is necessary in addition to prove that the decoding failure rate (DFR) is negligible, for some decoding algorithm and a proper choice of parameters. Getting a formal proof of a low DFR is a difficult task. Instead, we propose to ensure this low DFR under some additional security assumption on the decoder. This assumption relates to the asymptotic behavior of the decoder and is supported by several other works. We define a new decoder, Backflip, which features a low DFR. We evaluate the Backflip decoder by simulation and extrapolate its DFR under the decoder security assumption. We also measure the accuracy of our simulation data, in the form of confidence intervals, using standard techniques from communication systems