Energetic deposition using filtered cathodic arc plasma is known to lead to well adherent and dense films. Interface mixing, subplantation depth, texture, and stress of the growing film are often studied as a function of the kinetic energy of condensing ions. Ions have also potential energy contributing to atomic scale heating, secondary electron emission and potential sputtering, thereby affecting all film properties. A table is presented showing kinetic and potential energies of ions in cathodic arc plasmas. These energies are greater than the binding energy, surface binding energy, and activation energy of surface diffusion. The role of potential energy on film growth is not limited to the cathodic arc plasma deposition process.

Recent work in classification indicates that significant improvements in accuracy can be obtained by growing an ensemble of classifiers and having them vote for the most popular class. Implicit in many of these techniques is the concept of randomization that generates different classifiers. In this paper, they focus on ensembles of decision trees that are created using a randomized procedure based on histograms. Techniques, such as histograms, that discretize continuous variables, have long been used in classification to convert the data into a form suitable for processing and to reduce the compute time. The approach combines the ideas behind discretization through histograms and randomization in ensembles to create decision trees by randomly selecting a split point in an interval around the best bin boundary in the histogram. The experimental results with public domain data show that ensembles generated using this approach are competitive in accuracy and superior in computational cost to other ensembles techniques such as boosting and bagging.

The preparation of the title compound, [{sup 3}H{sub 3}]CNS-5161, was accomplished in three steps starting with the production of [{sup 3}H{sub 3}]iodomethane (CT{sub 3}I). The intermediate N-[{sup 3}H{sub 3}]methyl-3-(thiomethylphenyl)cyanamide was prepared in 77% yield by the addition of CT{sub 3}I to 3-(thiomethylphenyl)cyanamide, previously treated with sodium hydride. Reaction of this tritiated intermediate with 2-chloro-5-thiomethylaniline hydrochloride formed the guanidine compound [{sup 3}H{sub 3}]CNS-5161. Purification by HPLC gave the desired labeled product in an overall yield of 9% with greater than 96% radiochemical purity and a final specific activity of 66 Ci mmol{sup -1}.

Current ideas for designing neutrino factories [ 1,2] and muon colliders [3] require unique configurations of fields and materials to prepare the muon beam for acceleration. This so-called front end system must accomplish the goals of phase rotation, bunching and cooling. We have continued the development of a 3-D tracking code, ICOOL [4], for examining possible muon collider front end configurations. A system is described in terms of a series of longitudinal regions with associated material and field properties. The tracking takes place in a coordinate system that follows a reference orbit through the system. The code takes into account decays and interactions of {approx}50-500 MeV/c muons in matter. Material geometry regions include cylinders and wedges. A number of analytic models are provided for describing the field configurations. Simple diagnostics are built into the code, including calculation of emittances and correlations, longitudinal traces, histograms and scatter plots. A number of auxiliary codes can be used for pre-processing, post-processing and optimization.