Prediction of carbon monoxide in fires by conditional moment closure

Carbon monoxide is the chief killer in fires. Dangerous levels of CO can occur when reacting combustion gases are quenched by heat transfer, or by mixing of the fire plume in a cooled under- or overventilated upper layer. In this paper, carbon monoxide predictions for enclosure fires are modeled by the conditional moment closure (CMC) method and are compared with laboratory data. The modeled fire situation is a buoyant, turbulent, diffusion flame burning under a hood. The fire plume entrains fresh air, and the postflame gases are cooled considerably under the hood by conduction and radiation, emulating conditions which occur in enclosure fires and lead to the freezing of CO burnout. Predictions of CO in the cooled layer are presented in the context of a complete computational fluid dynamics solution of velocity, temperature, and major species concentrations. A range of underhood equivalence ratios, from rich to lean, are investigated. The CMC method predicts CO in very good agreement with data. In particular, CMC is able to correctly predict CO concentrations in lean cooled gases, showing its capability in conditions where reaction rates change considerably.

Finite-difference time-domain-based studies of MRI pulsed field gradient-induced eddy currents inside the human body

In modern magnetic resonance imaging (MRI), patients are exposed to strong, rapidly switching magnetic gradient fields that, in extreme cases, may be able to elicit nerve stimulation. This paper presents theoretical investigations into the spatial distribution of induced current inside human tissues caused by pulsed z-gradient fields. A variety of gradient waveforms have been studied. The simulations are based on a new, high-definition, finite-difference time-domain method and a realistic inhomogeneous 10-mm resolution human body model with appropriate tissue parameters. it was found that the eddy current densities are affected not only by the pulse sequences but by many parameters such as the position of the body inside the gradient set, the local biological material properties and the geometry of the body. The discussion contains a comparison of these results with previous results found in the literature. This study and the new methods presented herein will help to further investigate the biological effects caused by the switched gradient fields in a MRI scan. (C) 2002 Wiley Periodicals, Inc.

Estimation of crystalline phase present in the glucose crystal-solution mixture by water activity measurement

The amount of crystalline fraction present in monohydrate glucose crystal-solution mixture up to 110% crystal in relation to solution (crystal:solution=110:100) was determined by water activity measurement. It was found that the water activity had a strong linear correlation (R-2=0.994) with the amount of glucose present above saturation. Difference in the water activities of the crystal-solution mixture (a(w1)) and the supersaturated solution (a(w2)) by re-dissolving the crystalline fraction allowed calculation of the amount of crystalline phase present (DeltaG) in the mixture by an equation DeltaG=846.97(a(w1)-a(w2)). Other methods such as Raoult's, Norrish and Money-Born equations were also tested for the prediction of water activity of supersaturated glucose solution. (C) 2003 Swiss Society of Food Science and Technology. Published by Elsevier Science Ltd. All rights reserved.

Field assessment of thermal after-ripening time for dormancy release prediction in Lolium rigidum seeds

Dormancy release was studied in four populations of annual ryegrass (Lolium rigidum) seeds to determine whether loss of dormancy in the field can be predicted from temperature alone or whether seed water content (WC) must also be considered. Freshly matured seeds were after-ripened at the northern and southern extremes of the Western Australian cereal cropping region and at constant 37degreesC. Seed WC was allowed to fluctuate with prevailing humidity, but full hydration was avoided by excluding rainfall. Dormancy was measured regularly during after-ripening by germinating seeds with 12-hourly light or in darkness. Germination was lower in darkness than in light/dark and dormancy release was slower when germination was tested in darkness. Seeds were consistently drier, and dormancy release was slower, during after-ripening at 37degreesC than under field conditions. However, within each population, the rate of dormancy release in the field (north and south) in terms of thermal time was unaffected by after-ripening site. While low seed WC slowed dormancy release in seeds held at 37degreesC, dormancy release in seeds after-ripened under Western Australian field conditions was adequately described by thermal after-ripening time, without the need to account for changes in WC elicited by fluctuating environmental humidity.

Detecting sugarcane 'orange rust' disease using EO-1 Hyperion hyperspectral imagery

This Letter evaluates several narrow-band indices from EO-1 Hyperion imagery in discriminating sugarcane areas affected by 'orange rust' ( Puccinia kuehnii ) disease. Forty spectral vegetation indices (SVIs), focusing on bands related to leaf pigments, leaf internal structure, and leaf water content, were generated from an image acquired over Mackay, Queensland, Australia. Discriminant function analysis was used to select an optimum set of indices based on their correlations with the discriminant function. The predictive ability of each index was also assessed based on the accuracy of classification. Results demonstrated that Hyperion imagery can be used to detect orange rust disease in sugarcane crops. While some indices that only used visible near-infrared (VNIR) bands (e.g. SIPI and R800/R680) offer separability, the combination of VNIR bands with the moisture-sensitive band (1660 nm) yielded increased separability of rust-affected areas. The newly formulated 'Disease-Water Stress Indices' (DWSI-1=R800/R1660; DSWI-2=R1660/R550; DWSI-5=(R800+R550)/(R1660+R680)) produced the largest correlations, indicating their superior ability to discriminate sugarcane areas affected by orange rust disease.

Forward-looking versus recursive-dynamic modeling in climate policy analysis: A comparison

This paper develops a multi-regional general equilibrium model for climate policy analysis based on the latest version of the MIT Emissions Prediction and Policy Analysis (EPPA) model. We develop two versions so that we can solve the model either as a fully inter-temporal optimization problem (forward-looking, perfect foresight) or recursively. The standard EPPA model on which these models are based is solved recursively, and it is necessary to simplify some aspects of it to make inter-temporal solution possible. The forward-looking capability allows one to better address economic and policy issues such as borrowing and banking of GHG allowances, efficiency implications of environmental tax recycling, endogenous depletion of fossil resources, international capital flows, and optimal emissions abatement paths among others. To evaluate the solution approaches, we benchmark each version to the same macroeconomic path, and then compare the behavior of the two versions under a climate policy that restricts greenhouse gas emissions. We find that the energy sector and CO(2) price behavior are similar in both versions (in the recursive version of the model we force the inter-temporal theoretical efficiency result that abatement through time should be allocated such that the CO(2) price rises at the interest rate.) The main difference that arises is that the macroeconomic costs are substantially lower in the forward-looking version of the model, since it allows consumption shifting as an additional avenue of adjustment to the policy. On the other hand, the simplifications required for solving the model as an optimization problem, such as dropping the full vintaging of the capital stock and fewer explicit technological options, likely have effects on the results. Moreover, inter-temporal optimization with perfect foresight poorly represents the real economy where agents face high levels of uncertainty that likely lead to higher costs than if they knew the future with certainty. We conclude that while the forward-looking model has value for some problems, the recursive model produces similar behavior in the energy sector and provides greater flexibility in the details of the system that can be represented. (C) 2009 Elsevier B.V. All rights reserved.

Increased rates of ENT surgery among young children: Have clinical guidelines made a difference?

Objectives: To examine the association between introduction of paediatric ear, nose and throat (ENT) surgery guidelines and population procedure rates. To determine changes in children's risk of undergoing ENT surgery. Methods: Trend analysis of incidence of myringotomy, tonsillectomy and adenoidectomy among New South Wales (NSW) children aged 0-14 between 1981 and mid 1999. Poisson regression models were used to estimate annual rates of change pre and postguidelines introduction and age/gender specific rates, and lifetable methods to determine risk of undergoing an ENT procedure by age 15. Results: ENT surgery rates increased by 21% over the study period. Children's risk of surgery increased from 17.9% in 1981 to 20.2% in 1998/99. Guideline introduction was associated with moderate short-term decreases in rates. For tonsillectomy, rates decreased between 1981 and 1983, but then rose continually until the introduction of myringotomy guidelines in 1993, when they fell, only to recommence rising until the end of the study period. For myringotomy, rates rose annually from 1981 to 1992/93 and fell in the 3 years following guideline introduction, after which they rose again. Increases were almost exclusively restricted to children aged 0-4 and correspond with increased use of formal childcare. The prevalence of myringotomy by the age of 5 years rose from 5.6% of children born in 1988/89 to 6.4% of those born in 1994/95, and the prevalence of tonsillectomy from 2.4% to 2.7%. Conclusions: The risk of young Australian children undergoing ENT surgery increased significantly over the last two decades despite the introduction of guidelines and no evidence of an increase in otitis media, one condition prompting surgery. Surgery increased most among the very young. We hypothesize this is related to increasing use of childcare.

Visible and near-infrared luminescent Eu(3+) or Er(3+) doped laponite-derived xerogels and thick films: Structural and spectroscopic properties

Laponite-derived materials represent promising materials for optical applications. In this work, Eu(3+)- or Er(3+)-doped laponite xerogels and films were prepared from colloidal dispersion. Homogeneous, crack-free and transparent single layers were deposited on soda-lime substrates with a thickness of 10 mu m. Structural and spectroscopic properties were analyzed by thermal analyses, X-ray diffractometry, transmission electron microscopy, infrared spectroscopy, and luminescence spectroscopy. The addition of a rare earth ion to the laponite does not promote any changes in thermal stability or phase transition. Laponite clay was identified after annealing up to 500 degrees C, with a decrease in basal spacing when the annealing temperature is changed from 100 degrees C to 500 degrees C. Enstatite polymorphs and amorphous silicate phases were observed after heat treatment at 700 degrees C and 900 degrees C. Stationary and time-dependent luminescence spectra in the visible region for Eu(3+), and (5)D(0) lifetime are discussed in terms of thermal treatment and structural evolution. In the layered host, the Eu(3+) ions are distributed in many different local environments. However, Eu(3+) ions were found to occupy at least two symmetry sites, and the ions are preferentially incorporated into the crystalline enstatite for the materials annealed at 700 degrees C and 900 degrees C. A (5)D(0) lifetime of 1.3 ms and 3.1 ms was obtained for Eu(3+) ions in an amorphous silicate and crystalline MgSiO(3) local environment, respectively. Strong Er(3+) emission at the 1550 nm region was observed for the materials annealed at 900 degrees C, with a bandwidth of 44 nm. (C) 2008 Elsevier B.V. All rights reserved.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.

ANNA: A new prediction method for bioassessment programs

1. Cluster analysis of reference sites with similar biota is the initial step in creating River Invertebrate Prediction and Classification System (RIVPACS) and similar river bioassessment models such as Australian River Assessment System (AUSRIVAS). This paper describes and tests an alternative prediction method, Assessment by Nearest Neighbour Analysis (ANNA), based on the same philosophy as RIVPACS and AUSRIVAS but without the grouping step that some people view as artificial. 2. The steps in creating ANNA models are: (i) weighting the predictor variables using a multivariate approach analogous to principal axis correlations, (ii) calculating the weighted Euclidian distance from a test site to the reference sites based on the environmental predictors, (iii) predicting the faunal composition based on the nearest reference sites and (iv) calculating an observed/expected (O/E) analogous to RIVPACS/AUSRIVAS. 3. The paper compares AUSRIVAS and ANNA models on 17 datasets representing a variety of habitats and seasons. First, it examines each model's regressions for Observed versus Expected number of taxa, including the r(2), intercept and slope. Second, the two models' assessments of 79 test sites in New Zealand are compared. Third, the models are compared on test and presumed reference sites along a known trace metal gradient. Fourth, ANNA models are evaluated for western Australia, a geographically distinct region of Australia. The comparisons demonstrate that ANNA and AUSRIVAS are generally equivalent in performance, although ANNA turns out to be potentially more robust for the O versus E regressions and is potentially more accurate on the trace metal gradient sites. 4. The ANNA method is recommended for use in bioassessment of rivers, at least for corroborating the results of the well established AUSRIVAS- and RIVPACS-type models, if not to replace them.

PREDBALB/c: a system for the prediction of peptide binding to H2(d) molecules, a haplotype of the BALB/c mouse

PREDBALB/c is a computational system that predicts peptides binding to the major histocompatibility complex-2 (H2(d)) of the BALB/c mouse, an important laboratory model organism. The predictions include the complete set of H2(d) class I ( H2-K-d, H2-L-d and H2-D-d) and class II (I-E-d and I-A(d)) molecules. The prediction system utilizes quantitative matrices, which were rigorously validated using experimentally determined binders and non-binders and also by in vivo studies using viral proteins. The prediction performance of PREDBALB/c is of very high accuracy. To our knowledge, this is the first online server for the prediction of peptides binding to a complete set of major histocompatibility complex molecules in a model organism (H2(d) haplotype). PREDBALB/c is available at http://antigen.i2r.a-star.edu.sg/predBalbc/.

Axial Young's modulus prediction of single-walled carbon nanotube arrays with diameters from nanometer to meter scales

Based on a self-similar array model, we systematically investigated the axial Young's modulus (Y-axis) of single-walled carbon nanotube (SWNT) arrays with diameters from nanometer to meter scales by an analytical approach. The results show that the Y-axis of SWNT arrays decreases dramatically with the increases of their hierarchy number (s) and is not sensitive to the specific size and constitution when s is the same, and the specific Young's modulus Y-axis(s) is independent of the packing configuration of SWNTs. Our calculations also show that the Y-axis of SWNT arrays with diameters of several micrometers is close to that of commercial high performance carbon fibers (CFs), but the Y-axis(s) of SWNT arrays is much better than that of high performance CFs. (C) 2005 American Institute of Physics.

Physiologic parameters that affect pulse transit time difference between the upper and lower limbs in children

Pulse wave velocity (PWV) is a known parameter that is related to arterial distensibility. However, its potential is hampered by the absence of appropriate techniques to estimate it noninvasively. PWV can be used as an assessment of increased arterial stiffness that is linked to systolic hypertension, excess cardiovascular morbidity and mortality.(1,2)