Optimal crossover designs for logistic regression models in pharmacodynamics

Pharmacodynamics (PD) is the study of the biochemical and physiological effects of drugs. The construction of optimal designs for dose-ranging trials with multiple periods is considered in this paper, where the outcome of the trial (the effect of the drug) is considered to be a binary response: the success or failure of a drug to bring about a particular change in the subject after a given amount of time. The carryover effect of each dose from one period to the next is assumed to be proportional to the direct effect. It is shown for a logistic regression model that the efficiency of optimal parallel (single-period) or crossover (two-period) design is substantially greater than a balanced design. The optimal designs are also shown to be robust to misspecification of the value of the parameters. Finally, the parallel and crossover designs are combined to provide the experimenter with greater flexibility.

Effect of sample geometry on regression rate of the melting interface for carbon steel burned in oxygen

Promoted-ignition testing on carbon steel rods of varying cross-sectional area and shape was performed in high pressure oxygen to assess the effect of sample geometry on the regression rate of the melting interface. Cylindrical and rectangular geometries and three different cross sections were tested and the regression rates of the cylinders were compared to the regression rates of the rectangular samples at test pressures around 6.9 MPa. Tests were recorded and video analysis used to determine the regression rate of the melting interface by a new method based on a drop cycle which was found to provide a good basis for statistical analysis and provide excellent agreement to the standard averaging methods used. Both geometries tested showed the typical trend of decreasing regression rate of the melting interface with increasing cross-sectional area; however, it was shown that the effect of geometry is more significant as the sample's cross sections become larger. Discussion is provided regarding the use of 3.2-mm square rods rather than 3.2-mm cylindrical rods within the standard ASTM test and any effect this may have on the observed regression rate of the melting interface.

Use of regression equation of peripheral pulse timing characteristics to predict hypertension in children

Studies have shown that an increase in arterial stiffening can indicate the presence of cardiovascular diseases like hypertension. Current gold standard in clinical practice is by measuring the blood pressure of patients using a mercury sphygmomanometer. However, the nature of this technique is not suitable for prolonged monitoring. It has been established that pulse wave velocity is a direct measure of arterial stiffening. However, its usefulness is hampered by the absence of techniques to estimate it non-invasively. Pulse transit time (PTT) is a simple and non-intrusive method derived from pulse wave velocity. It has shown its capability in childhood respiratory sleep studies. Recently, regression equations that can predict PTT values for healthy Caucasian children were formulated. However, its usefulness to identify hypertensive children based on mean PTT values has not been investigated. This was a continual study where 3 more Caucasian male children with known clinical hypertension were recruited. Results indicated that the PTT predictive equations are able to identify hypertensive children from their normal counterparts in a significant manner (p < 0.05). Hence, PTT can be a useful diagnostic tool in identifying hypertension in children and shows potential to be a non-invasive continual monitor for arterial stiffening.

Growth mechanism of truncated triangular GaAs nanowires

During the growth of GaAs nanowires on the {111}B GaAs substrate, truncated triangular GaAs nanowires were commonly observed in the bottom region of nanowires. Through detailed structural analysis by electron microscopy, we have determined the growth mechanism of truncated triangular GaAs nanowires.