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.

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.

The relationship between prepulse inhibition and perceived intensity of the blink-eliciting stimulus: Stimulus intensity and lead interval effects

The hypothesis that prepulse inhibition of the blink reflex reflects a transient process that protects preattentive processing of the prepulse was investigated. Participants were presented with pairs of blink-eliciting noises, with some noises preceded by a prepulse, and were asked to rate the intensity of the second noise relative to the first. Inhibition of blink amplitude was greater for a 110 dB(A) noise than for a 95 dB(A) noise with a 120 ms lead interval, whereas there was no difference with a 30 ms lead interval. The reduction in perceived intensity was greater for the 110 dB(A) noise than for the 95 dB(A) noise with the 120 ms lead interval, but not with the 30 ms lead interval. The parallel results support an association between prepulse inhibition and perceived intensity. However, the prepulse did not reduce intensity ratings relative to control trials in some conditions, suggesting that prepulse inhibition is not always associated with an attenuation of the impact of the blink-eliciting stimulus.

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.

Prognostic Value of Dobutamine Stress Echocardiography With Early Injection of Atropine With Versus Without Chronic Beta-Blocker Therapy in Patients With Known or Suspected Coronary Heart Disease

Although a new protocol of dobutamine stress echocardiography with the early injection of atropine (EA-DSE) has been demonstrated to be useful in reducing adverse effects and increasing the number of effective tests and to have similar accuracy for detecting coronary artery disease (CAD) compared with conventional protocols, no data exist regarding its ability to predict long-term events. The aim of this study was to determine the prognostic value of EA-DSE and the effects of the long-term use of beta blockers on it. A retrospective evaluation of 844 patients who underwent EA-DSE for known or suspected CAD was performed; 309 (37%) were receiving beta blockers. During a median follow-up period of 24 months, 102 events (12%) occurred. On univariate analysis, predictors of events were the ejection fraction (p <0.001), male gender (p <0.001), previous myocardial infarction (p <0.001), angiotensin-converting enzyme inhibitor therapy (p = 0.021), calcium channel blocker therapy (p = 0.034), and abnormal results on EA-DSE (p <0.001). On multivariate analysis, the independent predictors of events were male gender (relative risk [RR] 1.78, 95% confidence interval [CI] 1.13 to 2.81, p = 0.013) and abnormal results on EA-DSE (RR 4.45, 95% CI 2.84 to 7.01, p <0.0001). Normal results on EA-DSE with P blockers were associated with a nonsignificant higher incidence of events than normal results on EA-DSE without beta blockers (RR 1.29, 95% CI 0.58 to 2.87, p = 0.54). Abnormal results on EA-DSE with beta blockers had an RR of 4.97 (95% CI 2.79 to 8.87, p <0.001) compared with normal results, while abnormal results on EA-DSE without beta blockers had an RR of 5.96 (95% CI 3.41 to 10.44, p <0.001) for events, with no difference between groups (p = 0.36). In conclusion, the detection of fixed or inducible wall motion abnormalities during EA-DSE was an independent predictor of long-term events in patients with known or suspected CAD. The prognostic value of EA-DSE was not affected by the long-term use of beta blockers. (C) 2008 Elsevier Inc. All rights reserved. (Am J Cardiol 2008;102:1291-1295)

Relation of Aortic Valve Calcium Detected by Cardiac Computed Tomography to All-Cause Mortality

Aortic valve calcium (AVC) can be quantified on the same computed tomographic scan as coronary artery calcium (CAC). Although CAC is an established predictor of cardiovascular events, limited evidence is available for an independent predictive value for AVC. We studied a cohort of 8,401 asymptomatic subjects (mean age 53 10 years, 69% men), who were free of known coronary heart disease and were undergoing electron beam computed tomography for assessment of subclinical atherosclerosis. The patients were followed for a median of 5 years (range 1 to 7) for the occurrence of mortality from any cause. Multivariate Cox regression models were developed to predict all-cause mortality according to the presence of AVC. A total of 517 patients (6%) had AVC on electron beam computed tomography. During follow-up, 124 patients died (1.5%), for an overall survival rate of 96.1% and 98.7% for those with and without AVC, respectively (hazard ratio 3.39, 95% confidence interval 2.09 to 5.49). After adjustment for age, gender, hypertension, dyslipidemia, diabetes mellitus, smoking, and a family history of premature coronary heart disease, AVC remained a significant predictor of mortality (hazard ratio 1.82, 95% confidence interval 1.11 to 2.98). Likelihood ratio chi-square statistics demonstrated that the addition of AVC contributed significantly to the prediction of mortality in a model adjusted for traditional risk factors (chi-square = 5.03, p = 0.03) as well as traditional risk factors plus the presence of CAC (chi-square = 3.58, p = 0.05). In conclusion, AVC was associated with increased all-cause mortality, independent of the traditional risk factors and the presence of CAC. (C) 2010 Published by Elsevier Inc. (Am J Cardiol 2010;106:1787-1791)

Prediction of impact forces in a vibratory ball mill using an inverse technique

To understand the dynamic mechanisms of the mechanical milling process in a vibratory mill, it is necessary to determine the characteristics of the impact forces associated with the collision events. However, it is difficult to directly measure the impact force in an operating mill. This paper describes an inverse technique for the prediction of impact forces from acceleration measurements on a vibratory ball mill. The characteristics of the vibratory mill have been investigated by the modal testing technique, and its system modes have been identified. In the modelling of the system vibration response to the impact forces, two modal equations have been used to describe the modal responses. The superposition of the modal responses gives rise to the total response of the system. A method based on an optimisation approach has been developed to predict the impact forces by minimising the difference between the measured acceleration of the vibratory ball mill and the predicted acceleration from the solution of the modal equations. The predicted and measured impact forces are in good agreement. Copyright (C) 1996 Elsevier Science Ltd.

Effects of high-intensity aerobic interval training vs. moderate exercise on hemodynamic, metabolic and neuro-humoral abnormalities of young normotensive women at high familial risk for hypertension

Exercise training has an important role in the prevention and treatment of hypertension, but its effects on the early metabolic and hemodynamic abnormalities observed in normotensive offspring of hypertensive parents (FH+) have not been studied. We compared high-intensity interval (aerobic interval training, AIT) and moderate-intensity continuous exercise training (CMT) with regard to hemodynamic, metabolic and hormonal variables in FH+ subjects. Forty-four healthy FH+ women (25.0+/-4.4 years) randomized to control (ConFH+) or to a three times per week equal-volume AIT (80-90% of VO(2MAX)) or CMT (50-60% of VO(2MAX)) regimen, and 15 healthy women with normotensive parents (ConFH-; 25.3+/-3.1 years) had their hemodynamic, metabolic and hormonal variables analyzed at baseline and after 16 weeks of follow-up. Ambulatorial blood pressure (ABP), glucose and cholesterol levels were similar among all groups, but the FH+ groups showed higher insulin, insulin sensitivity, carotid-femoral pulse wave velocity (PWV), norepinephrine and endothelin-1 (ET-1) levels and lower nitrite/ nitrate (NOx) levels than ConFH- subjects. AIT and CMT were equally effective in improving ABP (P<0.05), insulin and insulin sensitivity (P<0.001); however, AIT was superior in improving cardiorespiratory fitness (15 vs. 8%; P<0.05), PWV (P<0.01), and BP, norepinephrine, ET-1 and NOx response to exercise (P<0.05). Exercise intensity was an important factor in improving cardiorespiratory fitness and reversing hemodynamic, metabolic and hormonal alterations involved in the pathophysiology of hypertension. These findings may have important implications for the exercise training programs used for the prevention of inherited hypertensive disorder. Hypertension Research (2010) 33, 836-843; doi:10.1038/hr.2010.72; published online 7 May 2010