Constraining Gluon Shadowing Using Photoproduction in Ultraperipheral pA and AA Collisions

Photoproduction of heavy quarks and exclusive production of vector mesons in ultraperipheral proton-nucleus and nucleus-nucleus collisions depend significantly on nuclear gluon distributions. In the present study we investigate quantitatively the extent of the applicability of these processes at the Large Hadron Collider (LHC) in constraining the shadowing component of nuclear gluon modifications.Comment: 15 pages, 10 figures. arXiv admin note: substantial text overlap with arXiv:1104.428

Nuclear effects in photoproduction of heavy quarks and vector mesons in ultraperipheral PbPb and pPb collisions at the LHC

The comparison of photoproduction cross sections for $c\bar{c}$ and b-b(bar) in PbPb and pPb collisions can give sensitivity to nuclear shadowing effects. The photoproduction of vector mesons is even more sensitive to the underlying gluon distributions. In this study we present the cross sections and rapidity dependence of the photoproduction of heavy quarks and exclusive production of vector mesons in ultraperipheral pPb and PbPb collisions at the Large Hadron Collider at sqrt(s_NN)=5 TeV and sqrt(s_NN)=2.76$TeV, respectively. The potentials of using these processes for constraining nuclear gluon shadowing are explored. It is found that photoproduction of$J/\psi$and$\Upsilon$ in PbPb collisions in particular exhibit very good sensitivity to gluon shadowing.Comment: 4 pages, 4 figure

Mass dependence of nuclear shadowing at small Bjorken-x from diffractive scattering

We calculate the nuclear shadowing ratio for a wide range of nuclei at small Bjorken-x in the framework of Gribov theory. The coherent contribution to the (virtual) photon-nucleon cross section is obtained in terms of the diffractive dissociation cross section. Information on diffraction from FNAL and HERA is used. Our results are compared to available experimental data from the NMC and E665 experiments at x ~ 10^{-4}.Comment: To be published in Phys. Rev.

Quarkonium+γ\gamma production in coherent hadron - hadron interactions at LHC energies

In this paper we study the $H + \gamma$ ($H = J/\Psi$ and $\Upsilon$) production in coherent hadron - hadron interactions at LHC energies. Considering the ultrarelativistic protons as a source of photons, we estimate the $\gamma + p \rightarrow H + \gamma + X$ cross section using the non-relativistic QCD (NRQCD) factorization formalism and considering different sets of values for the matrix elements. Our results for the total $p + p \rightarrow p + H + \gamma + X$ cross sections and rapidity distributions at $\sqrt{s} = 7$ and 14 TeV demonstrate that the experimental analysis of the $J/\Psi + \gamma$ production at LHC is feasible.Comment: 6 pages, 3 figures, 1 table. Improved version with a new figure. Version to be published in European Physical Journal

Study of production and cold nuclear matter effects in pPb collisions at=5 TeV

Production of mesons in proton-lead collisions at a nucleon-nucleon centre-of-mass energy = 5 TeV is studied with the LHCb detector. The analysis is based on a data sample corresponding to an integrated luminosity of 1.6 nb(-1). The mesons of transverse momenta up to 15 GeV/c are reconstructed in the dimuon decay mode. The rapidity coverage in the centre-of-mass system is 1.5 < y < 4.0 (forward region) and -5.0 < y < -2.5 (backward region). The forward-backward production ratio and the nuclear modification factor for (1S) mesons are determined. The data are compatible with the predictions for a suppression of (1S) production with respect to proton-proton collisions in the forward region, and an enhancement in the backward region. The suppression is found to be smaller than in the case of prompt J/psi mesons

Medical Virtual Instrumentation for Personalized Health Monitoring: A Systematic Review

The rising cost of healthcare and the increased senior population are some reasons for the growing adoption of the Personalized Health Monitoring (PHM) systems. Medical Virtual Instruments (MVIs) provide portable, flexible, and low-cost options for these systems. Our systematic literature search covered the Cochrane Library, Web of Science, and MEDLINE databases, resulting in 915 articles, and 25 of which were selected for inclusion after a detailed screening process that involved five stages. The review sought to understand the key aspects regarding the use of MVIs for PHM, and we identified the main disease domains, sensors, platforms, algorithms, and communication protocols for such systems. We also identified the key challenges affecting the level of integration of MVIs into the global healthcare framework. The review shows that MVIs provide a good opportunity for the development of low cost personalized health systems that meet the unique instrumentation requirements for a given medical domain

A Computerized Bioinspired Methodology for Lightweight and Reliable Neural Telemetry

Personalized health monitoring of neural signals usually results in a very large dataset, the processing and transmission of which require considerable energy, storage, and processing time. We present bioinspired electroceptive compressive sensing (BeCoS) as an approach for minimizing these penalties. It is a lightweight and reliable approach for the compression and transmission of neural signals inspired by active electroceptive sensing used by weakly electric fish. It uses a signature signal and a sensed pseudo-sparse differential signal to transmit and reconstruct the signals remotely. We have used EEG datasets to compare BeCoS with the block sparse Bayesian learning-bound optimization (BSBL-BO) technique&mdash;A popular compressive sensing technique used for low-energy wireless telemonitoring of EEG signals. We achieved average coherence, latency, compression ratio, and estimated per-epoch power values that were 35.38%, 62.85%, 53.26%, and 13 mW better than BSBL-BO, respectively, while structural similarity was only 6.295% worse. However, the original and reconstructed signals remain visually similar. BeCoS senses the signals as a derivative of a predefined signature signal resulting in a pseudo-sparse signal that significantly improves the efficiency of the monitoring process. The results show that BeCoS is a promising approach for the health monitoring of neural signals