Search

The resistive plate chambers (RPCs) muon trigger electronics of the Compact Muon Solenoid (CMS) detector performs a number of tasks: synchronization of detector signals, optical data transmission from the detector to the trigger electronics, pattern recognition, muons momentum measurement, selection of track candidates. For the diagnostic purposes, as well as for the calibration and real-time monitoring of the RPC detectors and electronic hardware, a set of flexible diagnostic modules was designed and implemented into the field programmable gate arrays on which the trigger electronics is based. These include: multichannel counters, timing histograms, test pulses generators, diagnostic readout and data spying ('snap-shots' of the data stream). Test results presented in this paper, including tests with Large Hadron Collider-like muon beam, illustrate the performance and the usefulness of these diagnostic modules. Index Terms--Electronic equipment testing, field programmable gate arrays, synchronization.

Kohonen self-organizing maps ( SOMs) are unsupervised Artificial Neural Networks ( ANNs) that are good for low-density data visualization. They easily deal with complex and nonlinear relationships between variables. We evaluated molecular events that characterize high- and low-grade BC pathways in the tumors from 104 patients. We compared the ability of statistical clustering with a SOM to stratify tumors according to the risk of progression to more advanced disease. In univariable analysis, tumor stage (log rank P = 0.006) and grade ( P < 0.001), HPV DNA ( P < 0.004), Chromosome 9 loss ( P = 0.04) and the A148T polymorphism (rs 3731249) in CDKN2A ( P = 0.02) were associated with progression. Multivariable analysis of these parameters identified that tumor grade (Cox regression, P = 0.001, OR.2.9 (95% CI 1.6-5.2)) and the presence of HPV DNA ( P = 0.017, OR 3.8 (95% CI 1.3-11.4)) were the only independent predictors of progression. Unsupervised hierarchical clustering grouped the tumors into discreet branches but did not stratify according to progression free survival (log rank P = 0.39). These genetic variables were presented to SOM input neurons. SOMs are suitable for complex data integration, allow easy visualization of outcomes, and may stratify BC progression more robustly than hierarchical clustering. [ABSTRACT FROM AUTHOR]