Series expansions of the percolation probability for directed square and honeycomb lattices

We have derived long series expansions of the percolation probability for site and bond percolation on directed square and honeycomb lattices. For the square bond problem we have extended the series from 41 terms to 54, for the square site problem from 16 terms to 37, and for the honeycomb bond problem from 13 terms to 36. Analysis of the series clearly shows that the critical exponent $\beta$ is the same for all the problems confirming expectations of universality. For the critical probability and exponent we find in the square bond case, $q_c = 0.3552994\pm 0.0000010$, $\beta = 0.27643\pm 0.00010$, in the square site case $q_c = 0.294515 \pm 0.000005$, $\beta = 0.2763 \pm 0.0003$, and in the honeycomb bond case $q_c = 0.177143 \pm 0.000002$, $\beta = 0.2763 \pm 0.0002$. In addition we have obtained accurate estimates for the critical amplitudes. In all cases we find that the leading correction to scaling term is analytic, i.e., the confluent exponent $\Delta = 1$.Comment: LaTex with epsf, 26 pages, 2 figures and 2 tables in Postscript format included (uufiled). LaTeX version of tables also included for the benefit of those without access to PS printers (note that the tables should be printed in landscape mode). Accepted by J. Phys.

MULTI-SCALE MODELING OF HIGH-SHEAR GRANULATION

High shear wet granulation is a particle design process used to increase the size of a primary powder material through the addition of liquid binder. This thesis focuses on the multi-scale nature of high-shear granulation in order to understand behavior changes due to coupled consolidation and coalescence as well as operational changes that occur during the scale up of horizontal ploughshare mixer granulators. The methodology relied on a micro-scale model for coalescence, a meso-scale model to describe flow within the granulator and a macro-scale population balance to describe the whole system

Procedural error monitoring and smart checklists

Human beings make and usually detect errors routinely. The same mental processes that allow humans to cope with novel problems can also lead to error. Bill Rouse has argued that errors are not inherently bad but their consequences may be. He proposes the development of error-tolerant systems that detect errors and take steps to prevent the consequences of the error from occurring. Research should be done on self and automatic detection of random and unanticipated errors. For self detection, displays should be developed that make the consequences of errors immediately apparent. For example, electronic map displays graphically show the consequences of horizontal flight plan entry errors. Vertical profile displays should be developed to make apparent vertical flight planning errors. Other concepts such as energy circles could also help the crew detect gross flight planning errors. For automatic detection, systems should be developed that can track pilot activity, infer pilot intent and inform the crew of potential errors before their consequences are realized. Systems that perform a reasonableness check on flight plan modifications by checking route length and magnitude of course changes are simple examples. Another example would be a system that checked the aircraft's planned altitude against a data base of world terrain elevations. Information is given in viewgraph form

Hydrogen Bond Dynamics Near A Micellar Surface: Origin of the Universal Slow Relaxation at Complex Aqueous Interfaces

The dynamics of hydrogen bonds among water molecules themselves and with the polar head groups (PHG) at a micellar surface have been investigated by long molecular dynamics simulations. The lifetime of the hydrogen bond between a PHG and a water molecule is found to be much longer than that between any two water molecules, and is likely to be a general feature of hydrophilic surfaces of organized assemblies. Analyses of individual water trajectories suggest that water molecules can remain bound to the micellar surface for more than a hundred picosecond. The activation energy for such a transition from the bound to a free state for the water molecules is estimated to be about 3.5kcal/mole.Comment: 12 pages. Phys. Rev. Lett. (Accepted) (2002

Capital Stocks and Their User Costs for West German Agriculture: A Documentation

Agricultural Finance,

The development of violence subscales from the LSI-OR

Current literature suggests that the Level of Service Inventory (LSI) and its derivatives (LSI-R, LS/CMI, LSI-OR) are capable of predicting violent recidivism, even though they were not initially designed for this function (Girard & Wormith, 2004; Mills & Kroner, 2006). The purpose of this study was to generate violence prediction scales, based on items or subscales from the LSI-OR, using five different statistical techniques. These analyses were completed on the full construction sample, then the males and the females separately to determine how the scales differ from each other and what, if any, benefits would accrue from utilizing a gender-specific scale. A cohort of 27,027 offenders who were released from custody or entered into community supervision over a one year period was included in the study. There was an average followup time of 4.4 years. In this sample there was a general recidivism rate of 36.0% and a violent recidivism rate of 11.3%. Fifteen violence prediction scales were generated that ranged in predictive validity from r = .139 to r = .214. The scale with the highest predictive validity was the 11 item scale created from the full sample using the item linear regression technique. The scale contained items indicating that history of assault, lack of education and anger management issues were related to violent recidivism. Risk levels were developed for this new scale to classify offenders from very low to very high risk. Although there was little difference in the predictive validity of the generated scales, the stepwise multiple linear regression technique was identified as the most successful method of creating a tool for predicting violent recidivism. There was no increase in predictive validity when using the scale that was developed for just the females in the sample, although fewer items were consistently generated for females than males. Therefore the full sample item linear regression scale is recommended for the prediction of violent recidivism of both male and female offenders in the jurisdiction from which the data were collected. Future research directions may replicate this study in other populations and further analyze the gender differences in violent recidivism