Top Quark Mass Measurement in the lepton plus jets Channel Using a Matrix Element Method and in situ Jet Energy Calibration

A precision measurement of the top quark mass m(t) is obtained using a sample of t (t) over bar events from p (p) over bar collisions at the Fermilab Tevatron with the CDF II detector. Selected events require an electron or muon, large missing transverse energy, and exactly four high-energy jets, at least one of which is tagged as coming from a b quark. A likelihood is calculated using a matrix element method with quasi-Monte Carlo integration taking into account finite detector resolution and jet mass effects. The event likelihood is a function of mt and a parameter Delta(JES) used to calibrate the jet energy scale in situ. Using a total of 1087 events in 5.6 fb(-1) of integrated luminosity, a value of m(t) 173.0 +/- 1.2 GeV/c(2) is measured

Automated Cell Identification and Tracking Using Nanoparticle Moving-Light-Displays

An automated technique for the identification, tracking and analysis of biological cells is presented. It is based on the use of nanoparticles, enclosed within intra-cellular vesicles, to produce clusters of discrete, point-like fluorescent, light sources within the cells. Computational analysis of these light ensembles in successive time frames of a movie sequence, using k-means clustering and particle tracking algorithms, provides robust and automated discrimination of live cells and their motion and a quantitative measure of their proliferation. This approach is a cytometric version of the moving light display technique which is widely used for analyzing the biological motion of humans and animals. We use the endocytosis of CdTe/ZnS, core-shell quantum dots to produce the light displays within an A549, epithelial, lung cancer cell line, using time-lapse imaging with frame acquisition every 5 minutes over a 40 hour time period. The nanoparticle moving light displays provide simultaneous collection of cell motility data, resolution of mitotic traversal dynamics and identification of familial relationships allowing construction of multi-parameter lineage trees