Liquid-gas phase transition in nuclear multifragmentation

The equation of state of nuclear matter suggests that at suitable beam energies the disassembling hot system formed in heavy ion collisions will pass through a liquid-gas coexistence region. Searching for the signatures of the phase transition has been a very important focal point of experimental endeavours in heavy ion collisions, in the last fifteen years. Simultaneously theoretical models have been developed to provide information about the equation of state and reaction mechanisms consistent with the experimental observables. This article is a review of this endeavour.Comment: 63 pages, 27 figures, submitted to Adv. Nucl. Phys. Some typos corrected, minor text change

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Ligand Mobility Modulates Immunological Synapse Formation and T Cell Activation

T cell receptor (TCR) engagement induces clustering and recruitment to the plasma membrane of many signaling molecules, including the protein tyrosine kinase zeta-chain associated protein of 70 kDa (ZAP70) and the adaptor SH2 domain-containing leukocyte protein of 76 kDa (SLP76). This molecular rearrangement results in formation of the immunological synapse (IS), a dynamic protein array that modulates T cell activation. The current study investigates the effects of apparent long-range ligand mobility on T cell signaling activity and IS formation. We formed stimulatory lipid bilayers on glass surfaces from binary lipid mixtures with varied composition, and characterized these surfaces with respect to diffusion coefficient and fluid connectivity. Stimulatory ligands coupled to these surfaces with similar density and orientation showed differences in their ability to activate T cells. On less mobile membranes, central supramolecular activation cluster (cSMAC) formation was delayed and the overall accumulation of CD3ζ at the IS was reduced. Analysis of signaling microcluster (MC) dynamics showed that ZAP70 MCs exhibited faster track velocity and longer trajectories as a function of increased ligand mobility, whereas movement of SLP76 MCs was relatively insensitive to this parameter. Actin retrograde flow was observed on all surfaces, but cell spreading and subsequent cytoskeletal contraction were more pronounced on mobile membranes. Finally, increased tyrosine phosphorylation and persistent elevation of intracellular Ca2+ were observed in cells stimulated on fluid membranes. These results point to ligand mobility as an important parameter in modulating T cell responses

CMS Data Processing Workflows during an Extended Cosmic Ray Run

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Aligning the CMS Muon Chambers with the Muon Alignment System during an Extended Cosmic Ray Run

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Commissioning of the CMS high-level trigger with cosmic rays

This is the Pre-print version of the Article. The official published version of the paper can be accessed from the link below - Copyright @ 2010 IOPThe CMS High-Level Trigger (HLT) is responsible for ensuring that data samples with potentially interesting events are recorded with high efficiency and good quality. This paper gives an overview of the HLT and focuses on its commissioning using cosmic rays. The selection of triggers that were deployed is presented and the online grouping of triggered events into streams and primary datasets is discussed. Tools for online and offline data quality monitoring for the HLT are described, and the operational performance of the muon HLT algorithms is reviewed. The average time taken for the HLT selection and its dependence on detector and operating conditions are presented. The HLT performed reliably and helped provide a large dataset. This dataset has proven to be invaluable for understanding the performance of the trigger and the CMS experiment as a whole.This work is supported by FMSR (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); Academy of Sciences and NICPB (Estonia); Academy of Finland, ME, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); PAEC (Pakistan); SCSR (Poland); FCT (Portugal); JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MST and MAE (Russia); MSTDS (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF (USA)

The decision rule approach to optimization under uncertainty: methodology and applications

Dynamic decision-making under uncertainty has a long and distinguished history in operations research. Due to the curse of dimensionality, solution schemes that naïvely partition or discretize the support of the random problem parameters are limited to small and medium-sized problems, or they require restrictive modeling assumptions (e.g., absence of recourse actions). In the last few decades, several solution techniques have been proposed that aim to alleviate the curse of dimensionality. Amongst these is the decision rule approach, which faithfully models the random process and instead approximates the feasible region of the decision problem. In this paper, we survey the major theoretical findings relating to this approach, and we investigate its potential in two applications areas

Identification and Filtering of Uncharacteristic Noise in the CMS Hadron Calorimeter

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Performance of CMS Hadron Calorimeter Timing and Synchronization using Test Beam, Cosmic Ray, and LHC Beam Data

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