Search for periodicities in the 8B solar neutrino flux measured by the Sudbury Neutrino Observatory -: art. no. 052010
PHYSICAL REVIEW D 72:5 (2005) ARTN 052010
Search for supersymmetric Higgs bosons in the di-tau decay mode in p(p)over-barcollisions at √s=1.8 TeV -: art. no. 072004
PHYSICAL REVIEW D 72:7 (2005) ARTN 072004
Heavy Quarkonium Physics
ArXiv hep-ph/0412158 (2004)
Abstract:
This report is the result of the collaboration and research effort of the Quarkonium Working Group over the last three years. It provides a comprehensive overview of the state of the art in heavy-quarkonium theory and experiment, covering quarkonium spectroscopy, decay, and production, the determination of QCD parameters from quarkonium observables, quarkonia in media, and the effects on quarkonia of physics beyond the Standard Model. An introduction to common theoretical and experimental tools is included. Future opportunities for research in quarkonium physics are also discussed.Measurement of IWTO-19 ash content by Near Infrared Reflectance (NIR) Analysis
Wool Technology and Sheep Breeding 52:3 (2004) 245-259
Abstract:
The prediction of ash content of laboratory-scoured core samples utilising Near Infrared Reflectance Analysis (NIRA) has been investigated. Modified Partial Least Squares (MPLS) Regression was found to underestimate ash content when the sample being tested contained significant quantities of dag. The underestimation was not a consequence of saturation of the NIRA detector but rather appeared to be due to an inability of the MPLS technique to adequately account for dag which was present in the sample but masked by wool. Application of Artificial Neu ral Networks (ANN) Regression to the calibration data set produced improved results. The underestimation at higher ash levels was not as evident, indicating that ANN is better able to utilise the spectral information to predict total ash content. High levels of dag were found to adversely affect the repeatability of the IWTO-19 method for determining ash content. Uneven distribution of dag within samples was believed to be responsible. This finding has implications for NIRA, as any method of prediction can only be as good as the reference method to which it is calibrated.Recent results from SNO
Nuclear Physics B Proceedings Supplements 137:1-3 SPEC. ISS. (2004) 15-20