Predictor-corrector methods of Runge-Kutta type for stochastic differential equations

In this paper we construct predictor-corrector (PC) methods based on the trivial predictor and stochastic implicit Runge-Kutta (RK) correctors for solving stochastic differential equations. Using the colored rooted tree theory and stochastic B-series, the order condition theorem is derived for constructing stochastic RK methods based on PC implementations. We also present detailed order conditions of the PC methods using stochastic implicit RK correctors with strong global order 1.0 and 1.5. A two-stage implicit RK method with strong global order 1.0 and a four-stage implicit RK method with strong global order 1.5 used as the correctors are constructed in this paper. The mean-square stability properties and numerical results of the PC methods based on these two implicit RK correctors are reported.

Exposure to automotive pollution increases plasma susceptibility to oxidation

Low-density lipoprotein oxidation is implicated in the development of atherosclerosis. Plasma susceptibility to oxidation may be used as a marker of low-density lipoprotein oxidation and thus predict atherosclerotic risk. In this study the authors investigated the relationship between plasma susceptibility to oxidation and exposure to automotive pollution in a group of automobile mechanics (n = 16) exposed to high levels of automotive pollution, vs. matched controls (n = 13). The authors induced plasma oxidation by a free radical initiator and they determined susceptibility to oxidation by (1) change in absorbance at 234 nm, (2) lag time to conjugated diene formation, and (3) linear slope of the oxidation curve. Mechanics had significantly higher values (mean standard error) for change in absorbance (1.60 +/- 0.05 vs. 1.36 +/- 0.05; p < .002), and slope (1.6 x 10(-3) +/- 0.1 x 10(-3) vs. 1.3 x 10(-3) +/- 0.1 x 10(-3); p < .001), compared with controls. These results indicate that regular exposure to automotive pollutants increases plasma susceptibility to oxidation and may, in the long term, increase the risk of developing atherosclerosis.

EMG activity normalization for trunk muscles in subjects with and without back pain

Purpose: The aims of the present study were to examine electromyographic (EMG) activity of six bilateral trunk muscles during maximal contraction in three cardinal planes, and to determine the direction of contraction that gives maximal activation for each muscle. both for healthy subjects and back-pain patients. Methods: Twenty-eight healthy subjects and 15 back-pain patients performed maximum voluntary contractions in three cardinal planes, Surface EMG signals were recorded from rectus abdominis, external oblique, internal oblique, latissimus dorsi, iliocostalis lumborum, and multifidus bilaterally. Root mean square values of the EMG data were calculated to quantify I the amplitude of EMG signals. Results: For both healthy subjects and back-pain patients. one single direction of contraction was found to give the maximum EMG signals for most muscles. Rectus abdominis demonstrated maximal activity in trunk flexion, external oblique in lateral flexion. internal oblique in axial rotation, and multifidus in extension. For the latissimus dorsi and iliocostalis lumborum. maximal activity was demonstrated in more than one cardinal plane. Conclusion: This study has implications for future research involving normalization of muscle activity to maximal levels required in many trunk EMG studies. As the latissimus dorsi and iliocostalis lumborum demonstrate individual differences in the plane that gives maximal activity, these muscles may require testing in more than one plane.