Quark and gluon distribution functions in a viscous quark-gluon plasma medium and dilepton production via q(q)over-bar annihilation

Viscous modifications to the thermal distributions of quark-antiquarks and gluons have been studied in a quasiparticle description of the quark-gluon-plasma medium created in relativistic heavy-ion collision experiments. The model is described in terms of quasipartons that encode the hot QCD medium effects in their respective effective fugacities. Both shear and bulk viscosities have been taken in to account in the analysis, and the modifications to thermal distributions have been obtained by modifying the energy-momentum tensor in view of the nontrivial dispersion relations for the gluons and quarks. The interactions encoded in the equation of state induce significant modifications to the thermal distributions. As an implication, the dilepton production rate in the q (q) over bar annihilation process has been investigated. The equation of state is found to have a significant impact on the dilepton production rate along with the viscosities.

Investigations into enhanced wax production with combustion synthesized Fischer-Tropsch catalysts

Combustion synthesized (CS) cobalt catalysts deposited over two supports, alumina and silica doped alumina (SDA), were characterized and tested for its Fischer-Tropsch (FT) activity. The properties of CS catalysts were compared to catalysts synthesized by conventional impregnation method (IWI). The CS catalysts resulted in 40-70% increase in the yield of C6+ hydrocarbons compared to MI catalysts. The FT activity for CS catalysts showed formation of long chain hydrocarbon waxes (C24+) compared to the formation of middle distillates (C-10-C-20) for IWI synthesized catalysts, indicating higher hydrocarbon chain growth probability for CS catalysts. This is ascribed to the smaller crystallite sizes, increased degree of cobalt reduction and consequentially, a higher number of active metal sites, exposed over the catalyst surface. Additionally, 12-13% increase in the overall C6+ hydrocarbon yield is realized for SDA-CS catalysts, compared to Al2O3-CS catalysts. The improved performance of CS-SDA catalysts is attributed to 48% increase in cobalt dispersion compared to Al2O3 supported CS catalysts, which is again caused by the decrease in the cobalt -support interaction for SDA supports. The metal support interactions were analyzed using XPS and H-2 TPR-TPD experiments. Combustion method produced catalysts with smaller crystallite size (17-18 nm), higher degree of reduction (similar to 92%) and higher metal dispersion (16.1%) compared to the IWI method. Despite its enhanced properties, the CS catalysts require prominently higher reduction temperatures (similar to 1100-1200 K). The hydrocarbon product analysis for Al2O3 supported catalyst showed higher paraffin wax concentrations compared to SDA supported catalysts, due to the lower surface basicity of Al2O3. This work reveals the impact of the CS catalysts and the nature of support on FT activity and hydrocarbon product spectrum. (C) 2016 Elsevier Ltd. All rights reserved.

Low Resolution Face Recognition Across Variations in Pose and Illumination

We propose a completely automatic approach for recognizing low resolution face images captured in uncontrolled environment. The approach uses multidimensional scaling to learn a common transformation matrix for the entire face which simultaneously transforms the facial features of the low resolution and the high resolution training images such that the distance between them approximates the distance had both the images been captured under the same controlled imaging conditions. Stereo matching cost is used to obtain the similarity of two images in the transformed space. Though this gives very good recognition performance, the time taken for computing the stereo matching cost is significant. To overcome this limitation, we propose a reference-based approach in which each face image is represented by its stereo matching cost from a few reference images. Experimental evaluation on the real world challenging databases and comparison with the state-of-the-art super-resolution, classifier based and cross modal synthesis techniques show the effectiveness of the proposed algorithm.