Controlling Restricted Random Testing: An Examination of the Exclusion Ratio Parameter

In Restricted Random Testing (RRT), the main control parameter is the Target Exclusion Ratio (R), the proportion of the input domain to be excluded from test case generation at each iteration. Empirical investigations have consistently indicated that best failure-finding performance is achieved when the value for the Target Exclusion Ratio is maximised, i.e. close to 100%. This paper explains an algorithm to calculate the Actual Exclusion Ratio for RRT, and applies the algorithm to several simulations, confirming that previous empirically determined values for the Maximum Target Exclusion Ratio do give Actual Exclusion Ratios close to 100%. Previously observed trends of improvement in failure-finding efficiency of RRT corresponding to increases in Target Exclusion Ratios are also identified for Actual Exclusion Ratios.published_or_final_versio

Using the Thermal Work Limit (TWL) as an environmental determinant of heat stress for construction workers

2012-2013 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Photoinduced Dehydrogenation of Defects in Undoped a-Si:H Using Positron Annihilation Spectroscopy

We report changes in variable-energy positron annihilation spectroscopy measurements on undoped hydrogenated amorphous silicon films after light soaking. The change, seen predominantly in the high momentum band of the annihilation radiation, is not reversed by thermal annealing. We suggest, following recent models of the Staebler-Wronski effect, that light exposure induces hydrogen trapped in vacancylikc detects to become mobile in the Si network. The observations place constraints on models of hydrogen motion fitting macroscopic Staebler-Wronski effect kinetics and may help to achieve a definitive description of metastability in a-Si:H.published_or_final_versio

Rare Germline Genetic Variants and the Risks of Epithelial Ovarian Cancer.

A family history of ovarian or breast cancer is the strongest risk factor for epithelial ovarian cancer (EOC). Germline deleterious variants in the BRCA1 and BRCA2 genes confer EOC risks by age 80, of 44% and 17% respectively. The mismatch repair genes, particularly MSH2 and MSH6, are also EOC susceptibility genes. Several other DNA repair genes, BRIP1, RAD51C, RAD51D, and PALB2, have been identified as moderate risk EOC genes. EOC has five main histotypes; high-grade serous (HGS), low-grade serous (LGS), clear cell (CCC), endometrioid (END), and mucinous (MUC). This review examines the current understanding of the contribution of rare genetic variants to EOC, focussing on providing frequency data for each histotype. We provide an overview of frequency and risk for pathogenic variants in the known susceptibility genes as well as other proposed genes. We also describe the progress to-date to understand the role of missense variants and the different breast and ovarian cancer risks for each gene. Identification of susceptibility genes have clinical impact by reducing disease-associated mortality through improving risk prediction, with the possibility of prevention strategies, and developing new targeted treatments and these clinical implications are also discussed

Can Foreign Policy Make a Difference to Health?

As part of the PLoS Medicine series on Global Health Diplomacy, Sigrun Møgedal and Benedikte Alveberg provide a diplomatic perspective on how foreign policy can make a difference to global health challenges

Online unit clustering in higher dimensions

We revisit the online Unit Clustering and Unit Covering problems in higher dimensions: Given a set of $n$ points in a metric space, that arrive one by one, Unit Clustering asks to partition the points into the minimum number of clusters (subsets) of diameter at most one; while Unit Covering asks to cover all points by the minimum number of balls of unit radius. In this paper, we work in $\mathbb{R}^d$ using the $L_\infty$ norm. We show that the competitive ratio of any online algorithm (deterministic or randomized) for Unit Clustering must depend on the dimension $d$. We also give a randomized online algorithm with competitive ratio $O(d^2)$ for Unit Clustering}of integer points (i.e., points in $\mathbb{Z}^d$, $d\in \mathbb{N}$, under $L_{\infty}$ norm). We show that the competitive ratio of any deterministic online algorithm for Unit Covering is at least $2^d$. This ratio is the best possible, as it can be attained by a simple deterministic algorithm that assigns points to a predefined set of unit cubes. We complement these results with some additional lower bounds for related problems in higher dimensions.Comment: 15 pages, 4 figures. A preliminary version appeared in the Proceedings of the 15th Workshop on Approximation and Online Algorithms (WAOA 2017

Relationship between FEV1 change and patient-reported outcomes in randomised trials of inhaled bronchodilators for stable COPD: a systematic review.

BACKGROUND: Interactions between spirometry and patient-reported outcomes in COPD are not well understood. This systematic review and study-level analysis investigated the relationship between changes in FEV1 and changes in health status with bronchodilator therapy. METHODS: Six databases (to October 2009) were searched to identify studies with long-acting bronchodilator therapy reporting FEV1 and health status, dyspnoea or exacerbations. Mean and standard deviations of treatment effects were extracted for each arm of each study. Relationships between changes in trough FEV1 and outcomes were assessed using correlations and random-effects regression modelling. The primary outcome was St George's Respiratory Questionnaire (SGRQ) total score. RESULTS: Thirty-six studies (≥ 3 months) were included. Twenty-two studies (23,654 patients) with 49 treatment arms each contributing one data point provided SGRQ data. Change in trough FEV1 and change in SGRQ total score were negatively correlated (r = -0.46, p < 0.001); greater increases in FEV1 were associated with greater reductions (improvements) in SGRQ. The correlation strengthened with increasing study duration from 3 to 12 months. Regression modelling indicated that 100 mL increase in FEV1 (change at which patients are more likely to report improvement) was associated with a statistically significant reduction in SGRQ of 2.5 (95% CI 1.9, 3.1), while a clinically relevant SGRQ change (4.0) was associated with 160.6 (95% CI 129.0, 211.6) mL increase in FEV1. The association between change in FEV1 and other patient-reported outcomes was generally weak. CONCLUSIONS: Our analyses indicate, at a study level, that improvement in mean trough FEV1 is associated with proportional improvements in health status