High-pt Particle Production at PHENIX

It has been established that "hard probes", observables involving high-momentum transfer, provide useful tools for studying the hot, dense medium created in nucleus-nucleus collisions at RHIC. The nuclear modification factor, azimuthal correlations, direct photon production, as well as the dependence of the nuclear modificaton factor on centrality and angle with respect to the reaction plane are critical for understanding the early dynamics of such heavy-ion collisions. We will review recent results from PHENIX for particle production at high-pT and discuss their implications.Comment: Proceedings from the Conference on the Intersections of Particle and Nuclear Physics, 30 May - 3 June 200

Quantum Theory of Probability and Decisions

The probabilistic predictions of quantum theory are conventionally obtained from a special probabilistic axiom. But that is unnecessary because all the practical consequences of such predictions follow from the remaining, non-probabilistic, axioms of quantum theory, together with the non-probabilistic part of classical decision theory

The floriculture industry in Malta

The floriculture industry in Malta is relatively small when compared to that of other European countries. However, despite several constraints, a number of growers deal exclusively with the production of floriculture products for local use. In the early 1970s, a locally based company was much involved in the export of floricultural products to the United Kingdom. This year (2002), four local growers initiated the growing and export of gladioli flowers to Italy.peer-reviewe

Item Response Modeling of Multivariate Count Data With Zero Inflation, Maximum Inflation, and Heaping

Questionnaires that include items eliciting count responses are becoming increasingly common in psychology. This study proposes methodological techniques to overcome some of the challenges associated with analyzing multivariate item response data that exhibit zero inflation, maximum inflation, and heaping at preferred digits. The modeling framework combines approaches from three literatures: item response theory (IRT) models for multivariate count data, latent variable models for heaping and extreme responding, and mixture IRT models. Data from the Behavioral Risk Factor Surveillance System are used as a motivating example. Practical implications are discussed, and recommendations are provided for researchers who may wish to use count items on questionnaires