Deakin University

About: Deakin University is a education organization based out in Burwood, Victoria, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 12118 authors who have published 46470 publications receiving 1188841 citations. The organization is also known as: Deakin.

Concentrations of Volatile Organic Compounds in Indoor Air – A Review

Abstract: A review is presented of investigations of volatile organic compound (VOC) concentrations in indoor air of buildings of different classifications (dwellings, offices, schools, hospitals) and categories (established, new and complaint buildings). Measured concentrations obtained from the published literature and from research in progress overseas were pooled so that VOC concentration profiles could be derived for each building classification/category. Mean concentrations of individual compounds in established buildings were found to be generally below 50 μg/m3, with most below 5 μg/m3. Concentrations in new buildings were much greater, often by an order of magnitude or more, and appeared to arise from construction materials and building contents. The nature of these sources and approaches to reduce indoor air concentrations by limiting source VOC emissions is discussed. Total VOC (TVOC) concentrations were substantially higher than concentrations of any individual VOCs in all situations, reflecting the large number of compounds present, but interpretation of such measurements was limited by the lack of a common definition for TVOC relevant to occupant exposure.

Manipulation of dietary short chain carbohydrates alters the pattern of gas production and genesis of symptoms in irritable bowel syndrome

Abstract: Background and Aim: Reduction of short-chain poorly absorbed carbohydrates (FODMAPs) in the diet reduces symptoms of irritable bowel syndrome (IBS). In the present study, we aimed to compare the patterns of breath hydrogen and methane and symptoms produced in response to diets that differed only in FODMAP content. Methods: Fifteen healthy subjects and 15 with IBS (Rome III criteria) undertook a single-blind, crossover intervention trial involving consuming provided diets that were either low (9 g/day) or high (50 g/day) in FODMAPs for 2 days. Food and gastrointestinal symptom diaries were kept and breath samples collected hourly over 14 h on day 2 of each diet. Results: Higher levels of breath hydrogen were produced over the entire day with the high FODMAP diet for healthy volunteers (181 77 ppm.14 h vs 43 18; mean SD P < 0.0001) and patients with IBS (242 79 vs 62 23; P < 0.0001), who had higher levels during each dietary period than the controls (P < 0.05). Breath methane, produced by 10 subjects within each group, was reduced with the high FODMAP intake in healthy subjects (47 29 vs 109 77; P = 0.043), but was not different in patients with IBS (126 153 vs 86 72). Gastrointestinal symptoms and lethargy were significantly induced by the high FODMAP diet in patients with IBS, while only increased flatus production was reported by healthy volunteers. Conclusions: Dietary FODMAPs induce prolonged hydrogen production in the intestine that is greater in IBS, influence the amount of methane produced, and induce gastrointes- tinal and systemic symptoms experienced by patients with IBS. The results offer mecha- nisms underlying the efficacy of the low FODMAP diet in IBS.

Complex interventions or complex systems? Implications for health economic evaluation

Abstract: Although guidelines exist for evaluating complex interventions, they may be of little help in dealing with the multiple effects of interventions in complex systems such as hospitals. Alan Shiell, Penelope Hawe, and Lisa Gold explain why it is important to distinguish the two types of complexity

Short-Term Load and Wind Power Forecasting Using Neural Network-Based Prediction Intervals

Abstract: Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.