Measurement of Z0 decays to hadrons, and a precise determination of the number of neutrino species

We have made a precise measurement of the cross section for e+e--->Z0-->hadrons with the L3 detector at LEP, covering the range from 88.28 to 95.04 GeV. From a fit to the Z0 mass, total width, and the hadronic cross section to be MZ0=91.160 +/- 0.024 (experiment) +/-0.030(LEP) GeV, [Gamma]Z0=2.539+/-0.054 GeV, and [sigma]h(MZ0)=29.5+/-0.7 nb. We also used the fit to the Z0 peak cross section and the width todetermine [Gamma]invisible=0.548+/-0.029 GeV, which corresponds to 3.29+/-0.17 species of light neutrinos. The possibility of four or more neutrino flavors is thus ruled out at the 4[sigma] confidence level.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/28683/3/0000500.pd

A measurement of the Z0 leptonic partial widths and the vector and axial vector coupling constants

We have measured the partial widths of the Z0 into lepton pairs, and the forward-backward charge asymmetry for the process e+e--->[mu]+[mu]- using the L3 detector at LEP. We obtain an average [Gamma]ll of 83.0+/-2.1+/-1.1 MeV.From this result and the asymmetry measurement, we extract the values of the vector and axial vector couplings of the Z0 to leptons: grmv=-0.066-0.027+0.046 and grmA= -0.495-0.007+0.007.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/28666/3/0000483.pd

Ontology-based geographic data set integration

In order to develop a system to propagate updates we investigate the semantic and spatial relationships between independently produced geographic data sets of the same region (data set integration). The goal of this system is to reduce operator intervention in update operations between corresponding (semantically similar) geographic object instances. Crucial for this reduction is certainty about the semantic similarity of different object representations. In this paper we explore a framework for ontology-based geographic data set integration, an ontology being a collection of shared concepts. Components of this formal approach are an ontology for topographic mapping (a domain ontology), an ontology for every geographic data set involved (the application ontologies), and abstraction rules (or capture criteria). Abstraction rules define at the class level the relationships between domain ontology and application ontology. Using these relationships, it is possible to locate semantic similarity at the object instance level with methods from computational geometry (like overlay operations). The components of the framework are formalized in the Prolog language, illustrated with a fictitious example, and tested on a practical example

Test of QED in e+e- -->gammagamma at LEP

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