Improved fault diagnosis in multivariate systems using regression-based reconstruction

Subspace monitoring has recently been proposed as a condition monitoring tool that requires considerably fewer variables to be analysed compared to dynamic principal component analysis (PCA). This paper analyses subspace monitoring in identifying and isolating fault conditions, which reveals that the existing work suffers from inherent limitations if complex fault senarios arise. Based on the assumption that the fault signature is deterministic while the monitored variables are stochastic, the paper introduces a regression-based reconstruction technique to overcome these limitations. The utility of the proposed fault identification and isolation method is shown using a simulation example and the analysis of experimental data from an industrial reactive distillation unit.

Developing NGO competencies in post-disaster reconstruction: a theoretical framework

In the aftermath of recent natural disasters, NGOs have become increasingly involved in the permanent reconstruction of affected communities. These organizations, often operating well outside their expertise, encounter significant barriers as they implement reconstruction programmes. This paper presents the theoretical bedrock of a current research project, the overall goal of which is to design a competency-based framework model that can be used by NGOs in post-disaster reconstruction projects. Drawing on established theories of management, a unique perspective has been developed from which a competency-based reconstruction theory emerges. This theoretical framework brings together three distinct fields; Disaster Management, Strategic Management and Project Management, each vital to the success of the model. This theoretical study will incorporate a critical review of literature within each field. It is imperative that NGOs involved in post-disaster reconstruction familiarize themselves with concepts and strategies. It is hoped that the competence-based frame-work model that is produced on the basis of this theory will help define the standard of best practice to which future NGO projects might align themselves.

Dietary patterns and breast cancer risk: a systematic review and meta-analysis

Background: Dietary patterns, which represent whole-diet and possible food and nutrient interactions, have been linked to the risk of various cancers. However, the associations of these dietary patterns with breast cancer remain unclear. Objective: We critically appraised the literature and conducted meta-analyses to pool the results of studies to clarify the relation between dietary patterns and breast cancer risk.
Design: MEDLINE and EMBASE were searched for relevant articles that identified common dietary patterns published up to November 2009. Multivariable-adjusted odds ratios (ORs) comparing highest and lowest categories of dietary pattern scores and multi-variable-adjusted ORs for a 20th-percentile increase in dietary pattern scores were combined by using random-effects meta-analyses. Results: Case-control and cohort studies were retrieved that identified prudent/healthy (n = 18), Western/unhealthy (n = 17), and drinker (n = 4) dietary patterns. There was evidence of a decrease in the risk of breast cancer in the highest compared with the lowest categories of prudent/healthy dietary patterns (OR = 0.89; 95% CI: 0.82, 0.99; P = 0.02) in all studies and in pooled cohort studies alone. An increase in the risk of breast cancer was shown for the highest compared with the lowest categories of a drinker dietary pattern (OR = 1.21; 95% CI: 1.04, 1.41; P = 0.01). There was no evidence of a difference in the risk of breast cancer between the highest and the lowest categories of Western/unhealthy dietary patterns (OR = 1.09; 95% CI: 0.98, 1.22; P = 0.12). Conclusion: The results of this systematic review and meta-analysis indicate that some dietary patterns may be associated with breast cancer risk.