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Ratio Model (ratio + model)

Distribution by Scientific Domains

Chemistry	28%

Selected Abstracts

A Semiparametric Odds Ratio Model for Measuring Association

BIOMETRICS, Issue 2 2007
Hua Yun Chen
Summary We propose a semiparametric odds ratio model to measure the association between two variables taking discrete values, continuous values, or a mixture of both. Methods for estimation and inference with varying degrees of robustness to model assumptions are studied. Semiparametric efficient estimation and inference procedures are also considered. The estimation methods are compared in a simulation study and applied to the study of associations among genital tract bacterial counts in HIV infected women. [source]

Dysautonomia after severe traumatic brain injury

EUROPEAN JOURNAL OF NEUROLOGY, Issue 9 2010
H. T. Hendricks
Background:, Dysautonomia after traumatic brain injury (TBI) is characterized by episodes of increased heart rate, respiratory rate, temperature, blood pressure, muscle tone, decorticate or decerebrate posturing, and profuse sweating. This study addresses the incidence of dysautonomia after severe TBI, the clinical variables that are associated with dysautonomia, and the functional outcome of patients with dysautonomia. Methods:, A historic cohort study in patients with severe TBI [Glasgow Coma Scale (GCS) , 8 on admission]. Results:, Seventy-six of 119 patients survived and were eligible for follow-up. The incidence of dysautonomia was 11.8%. Episodes of dysautonomia were prevalent during a mean period of 20.1 days (range 3,68) and were often initiated by discomfort. Patients with dysautonomia showed significant longer periods of coma (24.78 vs. 7.99 days) and mechanical ventilation (22.67 vs. 7.21 days). Dysautonomia was associated with diffuse axonal injury (DAI) [relative risk (RR) 20.83, CI 4.92,83.33] and the development of spasticity (RR 16.94, CI 3.96,71.42). Patients with dysautonomia experienced more secondary complications. They tended to have poorer outcome. Conclusions:, Dysautonomia occurs in approximately 10% of patients surviving severe TBI and is associated with DAI and the development of spasticity at follow-up. The initiation of dysautonomia by discomfort supports the Excitatory: Inhibitory Ratio model as pathophysiological mechanism. [source]

Compositional effects on electrophoretic and chromatographic figures of merit in electrokinetic chromatography with cetyltrimethylammonium bromide/sodium octyl sulfate vesicles as the pseudostationary phase.

ELECTROPHORESIS, Issue 5 2008
Part 1: Effect of the phase ratio
Abstract The effect of the phase ratio on the electrophoretic and chromatographic properties of unilamellar vesicles comprised of cetyltrimethylammonium bromide (CTAB) and sodium octyl sulfate (SOS) was investigated in EKC. The surfactant concentration of the vesicles was 0.9, 1.2, 1.5, and 1.8% w/v, with a mole ratio of 1:3.66 (CTAB/SOS). Results were compared to those obtained using SDS micelles at concentrations of 1.0% (w/v, 35,mM) and 1.5% (52,mM). The CTAB/SOS vesicles (0.9,1.8% w/v) provided a significantly larger elution range (5.7,,,tves/t0,,,8.7) and greater hydrophobic (methylene) selectivity (2.8,,,,CH2,,,3.1) than SDS micelles (3.1,,,tmc/t0,,,3.3; ,CH2,=,2.2). Whereas the larger elution range can be attributed to the 25% reduction in EOF due to the interaction of unaggregated CTAB cations and the negatively charged capillary wall, the higher methylene selectivity is likely due to the lower concentration of water expected in the CTAB/SOS vesicle bilayer compared to the Palisades layer of SDS micelles. For a given phase ratio, CTAB/SOS vesicles are somewhat less retentive than SDS micelles, although retention factors comparable to those observed in 1.0,1.5% SDS can be obtained with 1.5,1.8% CTAB/SOS. A linear relationship was observed between phase ratio and retention factor, confirming the validity of the phase ratio model for these vesicles. Unique polar group selectivities and positional isomer shape selectivities were obtained with CTAB/SOS vesicles, with both types of selectivities being nearly independent of the phase ratio. For four sets of positional isomers, the elution order was always para < ortho < meta. Finally, the thermodynamics of solute retention was qualitatively similar to that reported for other surfactant aggregates (micelles and microemulsions); the enthalpic contribution to retention was consistently favorable for all compounds, whereas the entropic contribution was favorable only to hydrophobic solutes. [source]

Modelling of air drying of Hac,haliloglu-type apricots

JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE, Issue 2 2006
Hakan Okyay Menges
Abstract In this study a laboratory dryer was used for the thin layer drying of sulfured and non-sulfured apricots. The moisture ratio values throughout the drying process were calculated by 14 different mathematical models, namely Newton, Page, modified Page, modified Page-II, Henderson and Pabis, logarithmic, two-term, two-term exponential, Wang and Singh, Thompson, diffusion approximation, modified Henderson and Papis, Verma et al. and Midilli et al. models. Root mean square error, reduced chi-square, mean bias error, adjusted R -square and modelling efficiency were used as statistical parameters to determine the most suitable model among them. According to the results, the Page model was chosen to explain the thin layer drying behaviour of sulfured and non-sulfured apricots. The effects of drying air temperature (T) and velocity (V) on the constants and coefficients of the best moisture ratio model were determined by multiple regression analysis. The moisture ratio (MR) could be predicted by the Page model equation MR = exp(,ktn) with constants and coefficients k = 0.470893 + 0.078775V and n = 0.017786 exp(0.051935T) for sulfured apricots and k = 4.578252 + 1.144643T and n = 0.888040 + 0.145559V for non-sulfured apricots. It is possible to predict the moisture content of the product with the generalised Page model incorporating the effects of drying air temperature and velocity on the model constants and coefficients in the ranges T = 70,80 °C and V = 1,3 m s,1. This developed model showed acceptable agreement with the experimental results, explained the drying behaviour of the product and could also be used for engineering applications. Copyright © 2005 Society of Chemical Industry [source]

Bitumen content estimation of Athabasca oil sand from broad band infrared reflectance spectra

THE CANADIAN JOURNAL OF CHEMICAL ENGINEERING, Issue 5 2010
B. Rivard
Abstract Oil sand is a mixture of quartz grains, clay minerals, bitumen, water, and minor accessory minerals. There is a need in oil sands mining operations for a robust method to estimate total bitumen content in real time; and so modelling of the total bitumen content (TBC) in Athabasca oil sands of Western Canada was undertaken on the basis of hyperspectral reflectance spectra. A selection of different bitumen, water, and clay mineral spectral features (3.0,30.0,µm) was used to develop broad-band TBC predictive models that have good accuracy, with less than 1.5% error with respect to laboratory methods of bitumen assay. These models are also robust, in that they are independent of mine location. Simple broad band models, based upon previously identified Gaussian features or wavelet features, provide an incremental improvement over the currently deployed industry two-band ratio model. An improved two-band model was also developed, which makes use of a combination of the same two bands but normalised to their mean. A wavelet-based, broad-band model comprised of indices and five bands, where the bands are normalised to the mean of the bands, adequately addresses the influence of water, clay, and textural variation on selected bitumen features. This five-band model appears to produce the most robust estimator of TBC, with a dispersion of ,1.1,1.5%, which can be applied to different sites within a mine and to different mines without additional tuning or calibration, as evidenced by regression slopes of 0.99,1.0 for modelling, validation, and blind data sets. [source]

Order-Restricted Semiparametric Inference for the Power Bias Model

BIOMETRICS, Issue 2 2010
Ori Davidov
Summary The power bias model, a generalization of length-biased sampling, is introduced and investigated in detail. In particular, attention is focused on order-restricted inference. We show that the power bias model is an example of the density ratio model, or in other words, it is a semiparametric model that is specified by assuming that the ratio of several unknown probability density functions has a parametric form. Estimation and testing procedures under constraints are developed in detail. It is shown that the power bias model can be used for testing for, or against, the likelihood ratio ordering among multiple populations without resorting to any parametric assumptions. Examples and real data analysis demonstrate the usefulness of this approach. [source]