Graphical Modeling for High Dimensional Data

With advances in science and information technologies, many scientific fields are able to meet the challenges of managing and analyzing high-dimensional data. A so-called large p small n problem arises when the number of experimental units, n, is equal to or smaller than the number of features, p. A methodology based on probability and graph theory, termed graphical models, is applied to study the structure and inference of such high-dimensional data

Energy consumption and capacity utilization of galvanizing furnaces

An explicit equation leading to a method for improving furnace efficiency is presented. This equation is dimensionless and can be applied to furnaces of any size and fuel type for the purposes of comparison. The implications for current furnace design are discussed. Currently the technique most commonly used to reduce energy consumption in galvanizing furnaces is to increase burner turndown. This is shown by the analysis presented here actually to worsen the thermal efficiency of the furnace, particularly at low levels of capacity utilization. Galvanizing furnaces are different to many furnaces used within industry, as a quantity of material (in this case zinc) is kept molten within the furnace at all times, even outside production periods. The dimensionless analysis can, however, be applied to furnaces with the same operational function as a galvanizing furnace, such as some furnaces utilized within the glass industry. © IMechE 2004

Lipid droplet detection by the cavity perturbation method

There are currently no point-of-care diagnosis strategies available to indicate the presence of neoplasmic growth. This research aims to develop a novel diagnostic strategy based on detecting TAG accumulation in cells. This element of the research is a preliminary experiment to prove the concept of detecting TAG lipid droplets in YEPD media. It was found that a change in mono-unsaturated concentration can be detected by the frequency shift in a resonant cavity. The dielectric constant of TAG vegetable oils was calculated at 2.34-2.39. It was also found that concentrations of lipid droplet can be differentiated up to 5% (v/v)

Anxiety sensitivity as a predictor of outcome in the treatment of obsessive-compulsive disorder

BACKGROUND AND OBJECTIVES: To address the fact that not all individuals who receive cognitive-behavioral therapy (CBT) for obsessive-compulsive disorder (OCD) exhibit complete symptom reduction, research has examined factors that predict outcome; however, no studies have examined anxiety sensitivity (AS) as a predictor of outcome of CBT for OCD. AS refers to the fear of anxious arousal that results from mistaken beliefs about the dangerousness of anxiety-related body sensations. It is important to understand whether AS influences OCD treatment outcome, considering that (a) some obsessions directly relate to AS, and (b) OCD patients with high AS may be reluctant to engage in anxiety-provoking components of CBT for OCD. METHODS: Patients (N = 187) with a primary diagnosis of OCD who received residential CBT for OCD participated in this study, which involved completing a self-report battery at pre- and post-treatment. RESULTS: Results supported study hypotheses, in that (a) baseline AS positively correlated with baseline OCD severity, and (b) greater baseline AS prospectively predicted higher posttreatment OCD symptom severity even after controlling for pretreatment OCD and depression severity. LIMITATIONS: The study was limited by its use of an older measure of AS, reliance on self-report measures, and nonstandardized treatment across participants. CONCLUSIONS: Findings highlight the importance of AS in the nature and treatment of OCD. Clinical implications and future directions are discussed