L2L_2 boosting in kernel regression

In this paper, we investigate the theoretical and empirical properties of $L_2$ boosting with kernel regression estimates as weak learners. We show that each step of $L_2$ boosting reduces the bias of the estimate by two orders of magnitude, while it does not deteriorate the order of the variance. We illustrate the theoretical findings by some simulated examples. Also, we demonstrate that $L_2$ boosting is superior to the use of higher-order kernels, which is a well-known method of reducing the bias of the kernel estimate.Comment: Published in at http://dx.doi.org/10.3150/08-BEJ160 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

Generalised additive dependency inflated models including aggregated covariates

Let us assume that X, Y and U are observed and that the conditional mean of U given X and Y can be expressed via an additive dependency of X, λ(X)Y and X + Y for some unspecified function . This structured regression model can be transferred to a hazard model or a density model when applied on some appropriate grid, and has important forecasting applications via structured marker dependent hazards models or structured density models including age-period-cohort relationships. The structured regression model is also important when the severity of the dependent variable has a complicated dependency on waiting times X, Y and the total waiting time X+Y . In case the conditional mean of U approximates a density, the regression model can be used to analyse the age-period-cohort model, also when exposure data are not available. In case the conditional mean of U approximates a marker dependent hazard, the regression model introduces new relevant age-period-cohort time scale interdependencies in understanding longevity. A direct use of the regression relationship introduced in this paper is the estimation of the severity of outstanding liabilities in non-life insurance companies. The technical approach taken is to use B-splines to capture the underlying one-dimensional unspecified functions. It is shown via finite sample simulation studies and an application for forecasting future asbestos related deaths in the UK that the B-spline approach works well in practice. Special consideration has been given to ensure identifiability of all models considered

Fermi-LAT Detection of a Break in the Gamma-Ray Spectrum of the Supernova Remnant Cassiopeia A

We report on observations of the supernova remnant Cassiopeia A in the energy range from 100 MeV to 100 GeV using 44 months of observations from the Large Area Telescope on board the Fermi Gamma-ray Space Telescope. We perform a detailed spectral analysis of this source and report on a low-energy break in the spectrum at $1.72^{+1.35}_{-0.89}$ GeV. By comparing the results with models for the gamma-ray emission, we find that hadronic emission is preferred for the GeV energy range.Comment: 18 pages, 5 figures, 2 tables, to be published in Ap

Narrow Band Chandra X-ray Analysis of Supernova Remnant 3C391

We present the narrow-band and the equivalent width (EW) images of the thermal composite supernova remnant (SNR) 3C391 for the X-ray emission lines of elements Mg, Si, & S using the Chandra ACIS Observational data. These EW images reveal the spatial distribution of the emission of the metal species Mg, Si, & S in the remnant. They have clumpy structure similar to that seen from the broadband diffuse emission, suggesting that they are largely of interstellar origin. We find an interesting finger-like feature protruding outside the southwestern radio border of the remnant, which is somewhat similar to the jet-like Si structure found in the famous SNR Cas A. This feature may possibly be the debris of the jet of ejecta which implies an asymmetrical supernova explosion of a massive progenitor star.Comment: 9 pages, 4 embedded figures, Chinese Journal of Astronomy and Astrophysics (ChJAA), in pres

Selection of Optimized Retaining Wall Technique Using Self-Organizing Maps

Construction projects in urban areas tend to be associated with high-rise buildings and are of very large-scales; hence, the importance of a project’s underground construction work is significant. In this study, a rational model based on machine learning (ML) was developed. ML algorithms are programs that can learn from data and improve from experience without human intervention. In this study, self-organizing maps (SOMs) were utilized. An SOM is an alternative to existing ML methods and involves a subjective decision-making process because a developed model is used for data training to classify and effectively recognize patterns embedded in the input data space. In addition, unlike existing methods, the SOM can easily create a feature map by mapping multidimensional data to simple two-dimensional data. The objective of this study is to develop an SOM model as a decision-making approach for selecting a retaining wall technique. N-fold cross-validation was adopted to validate the accuracy of the SOM model and evaluate its reliability. The findings are useful for decision-making in selecting a retaining wall method, as demonstrated in this study. The maximum accuracy of the SOM was 81.5%, and the average accuracy was 79.8%

Spatial Distribution of Metal Emissions in SNR 3C 397 Viewed with Chandra and XMM

We present X-ray equivalent width imaging of the supernova remnant (SNR) 3C 397 for Mg He\alpha, Si He\alpha, S He\alpha, and Fe K\alpha complex lines with the Chandra and XMM-Newton observations. The images reveal that the heavier the element is, the smaller the extent of the element distribution is. The Mg emission is evidently enhanced in the southeastern blow-out region, well along the radio boundary there, and appears to partially envelope the eastern Fe knot. Two bilateral hat-like Si line-emitting structures are along the northern and southern borders, roughly symmetric with respect to the southeast-northwest elongation axis. An S line-emitting shell is located just inner to the northern radio and IR shell, indicating of a layer of reversely shocked sulphur in the ejecta. A few enhanced Fe features are basically aligned along the diagonal of the rectangular shape of the SNR, which implicates an early asymmetric SN explosion.Comment: 4 pages, 4 figures, appears in Science China Physics, Mechanics & Astronomy, 2010, 53 (Suppl.1), 267-27

Cell cycle G2/M arrest through an S phase-dependent mechanism by HIV-1 viral protein R

<p>Abstract</p> <p>Background</p> <p>Cell cycle G2 arrest induced by HIV-1 Vpr is thought to benefit viral proliferation by providing an optimized cellular environment for viral replication and by skipping host immune responses. Even though Vpr-induced G2 arrest has been studied extensively, how Vpr triggers G2 arrest remains elusive.</p> <p>Results</p> <p>To examine this initiation event, we measured the Vpr effect over a single cell cycle. We found that even though Vpr stops the cell cycle at the G2/M phase, but the initiation event actually occurs in the S phase of the cell cycle. Specifically, Vpr triggers activation of Chk1 through Ser³⁴⁵phosphorylation in an S phase-dependent manner. The S phase-dependent requirement of Chk1-Ser³⁴⁵phosphorylation by Vpr was confirmed by siRNA gene silencing and site-directed mutagenesis. Moreover, downregulation of DNA replication licensing factors Cdt1 by siRNA significantly reduced Vpr-induced Chk1-Ser³⁴⁵phosphorylation and G2 arrest. Even though hydroxyurea (HU) and ultraviolet light (UV) also induce Chk1-Ser³⁴⁵phosphorylation in S phase under the same conditions, neither HU nor UV-treated cells were able to pass through S phase, whereas <it>vpr</it>-expressing cells completed S phase and stopped at the G2/M boundary. Furthermore, unlike HU/UV, Vpr promotes Chk1- and proteasome-mediated protein degradations of Cdc25B/C for G2 induction; in contrast, Vpr had little or no effect on Cdc25A protein degradation normally mediated by HU/UV.</p> <p>Conclusions</p> <p>These data suggest that Vpr induces cell cycle G2 arrest through a unique molecular mechanism that regulates host cell cycle regulation in an S-phase dependent fashion.</p