INTERIM REPORT IMPROVED METHODS FOR INCORPORATING RISK IN DECISION MAKING

This paper reports observations and preliminary investigations in the first phase of a research program covering methodologies for making safety-related decisions. The objective has been to gain insight into NRC perceptions of the value of formal decision methods, their possible applications, and how risk is, or may be, incorporated in decision making. The perception of formal decision making techniques, held by various decision makers, and what may be done to improve them, were explored through interviews with NRC staff. An initial survey of decision making methods, an assessment of the applicability of formal methods vis-a-vis the available information, and a review of methods of incorporating risk and uncertainty have also been conducted

Thermonuclear burn-up in deuterated methane CD4CD_4

The thermonuclear burn-up of highly compressed deuterated methane CD$_4$ is considered in the spherical geometry. The minimal required values of the burn-up parameter $x = \rho_0 \cdot r_f$ are determined for various temperatures $T$ and densities $\rho_0$. It is shown that thermonuclear burn-up in $CD_4$ becomes possible in practice if its initial density $\rho_0$ exceeds $\approx 5 \cdot 10^3$ $g \cdot cm^{-3}$. Burn-up in CD$_2$T$_2$ methane requires significantly ($\approx$ 100 times) lower compressions. The developed approach can be used in order to compute the critical burn-up parameters in an arbitrary deuterium containing fuel

Model selection in High-Dimensions: A Quadratic-risk based approach

In this article we propose a general class of risk measures which can be used for data based evaluation of parametric models. The loss function is defined as generalized quadratic distance between the true density and the proposed model. These distances are characterized by a simple quadratic form structure that is adaptable through the choice of a nonnegative definite kernel and a bandwidth parameter. Using asymptotic results for the quadratic distances we build a quick-to-compute approximation for the risk function. Its derivation is analogous to the Akaike Information Criterion (AIC), but unlike AIC, the quadratic risk is a global comparison tool. The method does not require resampling, a great advantage when point estimators are expensive to compute. The method is illustrated using the problem of selecting the number of components in a mixture model, where it is shown that, by using an appropriate kernel, the method is computationally straightforward in arbitrarily high data dimensions. In this same context it is shown that the method has some clear advantages over AIC and BIC.Comment: Updated with reviewer suggestion

Filling the Void: Bolstering Attachment Security in Committed Relationships

Attachment security has many salutary effects in adulthood, yet little is known about the specific interpersonal processes that increase attachment security over time. Using data from 134 romantically committed couples in a longitudinal study, we examined trust (whether a partner is perceived as available and dependable) and perceived goal validation (whether a partner is perceived as encouraging one’s personal goal pursuits). In concurrent analyses, trust toward a partner was uniquely associated with lower attachment anxiety, whereas perceiving one’s goal pursuits validated by a partner was uniquely associated with lower attachment avoidance. In longitudinal analyses, however, the inverse occurred: Trust toward a partner uniquely predicting reduced attachment avoidance over time and perceived goal validation uniquely predicting reduced attachment anxiety over time. These findings highlight distinct temporal paths for bolstering the security of attachment anxious versus attachment avoidant individuals

Attachment styles and personal growth following romantic breakups: The mediating roles of distress, rumination, and tendency to rebound

© 2013 Marshall et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.This article has been made available through the Brunel Open Access Publishing Fund.The purpose of this research was to examine the associations of attachment anxiety and avoidance with personal growth following relationship dissolution, and to test breakup distress, rumination, and tendency to rebound with new partners as mediators of these associations. Study 1 (N = 411) and Study 2 (N = 465) measured attachment style, breakup distress, and personal growth; Study 2 additionally measured ruminative reflection, brooding, and proclivity to rebound with new partners. Structural equation modelling revealed in both studies that anxiety was indirectly associated with greater personal growth through heightened breakup distress, whereas avoidance was indirectly associated with lower personal growth through inhibited breakup distress. Study 2 further showed that the positive association of breakup distress with personal growth was accounted for by enhanced reflection and brooding, and that anxious individuals’ greater personal growth was also explained by their proclivity to rebound. These findings suggest that anxious individuals’ hyperactivated breakup distress may act as a catalyst for personal growth by promoting the cognitive processing of breakup-related thoughts and emotions, whereas avoidant individuals’ deactivated distress may inhibit personal growth by suppressing this cognitive work

Calibrating ensemble reliability whilst preserving spatial structure

Ensemble forecasts aim to improve decision-making by predicting a set of possible outcomes. Ideally, these would provide probabilities which are both sharp and reliable. In practice, the models, data assimilation and ensemble perturbation systems are all imperfect, leading to deficiencies in the predicted probabilities. This paper presents an ensemble post-processing scheme which directly targets local reliability, calibrating both climatology and ensemble dispersion in one coherent operation. It makes minimal assumptions about the underlying statistical distributions, aiming to extract as much information as possible from the original dynamic forecasts and support statistically awkward variables such as precipitation. The output is a set of ensemble members preserving the spatial, temporal and inter-variable structure from the raw forecasts, which should be beneficial to downstream applications such as hydrological models. The calibration is tested on three leading 15-d ensemble systems, and their aggregation into a simple multimodel ensemble. Results are presented for 12 h, 1° scale over Europe for a range of surface variables, including precipitation. The scheme is very effective at removing unreliability from the raw forecasts, whilst generally preserving or improving statistical resolution. In most cases, these benefits extend to the rarest events at each location within the 2-yr verification period. The reliability and resolution are generally equivalent or superior to those achieved using a Local Quantile-Quantile Transform, an established calibration method which generalises bias correction. The value of preserving spatial structure is demonstrated by the fact that 3×3 averages derived from grid-scale precipitation calibration perform almost as well as direct calibration at 3×3 scale, and much better than a similar test neglecting the spatial relationships. Some remaining issues are discussed regarding the finite size of the output ensemble, variables such as sea-level pressure which are very reliable to start with, and the best way to handle derived variables such as dewpoint depression

A novel approach to the clustering of microarray data via nonparametric density estimation

<p>Abstract</p> <p>Background</p> <p>Cluster analysis is a crucial tool in several biological and medical studies dealing with microarray data. Such studies pose challenging statistical problems due to dimensionality issues, since the number of variables can be much higher than the number of observations.</p> <p>Results</p> <p>Here, we present a general framework to deal with the clustering of microarray data, based on a three-step procedure: (i) gene filtering; (ii) dimensionality reduction; (iii) clustering of observations in the reduced space. Via a nonparametric model-based clustering approach we obtain promising results both in simulated and real data.</p> <p>Conclusions</p> <p>The proposed algorithm is a simple and effective tool for the clustering of microarray data, in an unsupervised setting.</p

Preheat Effects on Microballoon Laser-Fusion Implosions

Nonequilibrium hydroburn simulations of early laser-driven compression experiments indicate that low energy photons from the vicinity of the ablation surface are preheating the microballoon-pushers, thereby severely limiting the compressions achieved (similar degradation may result from 1 to 4 percent energy deposition by superthermal electrons). This implies an 8- to 27-fold increase in the energy requirements for breakeven, unless radiative preheat can be drastically reduced by, say, the use of composite ablator-pushers. (auth