Azimuthal correlations of D-mesons in pp+pp and pp+Pb collisions at LHC energies

We study the correlations of D mesons produced in $p$+$p$ and $p$+Pb collisions. These are found to be sensitive to the effects of the cold nuclear medium and the transverse momentum ($p_T$) regions we are looking into. In order to put this on a quantitative footing, as a first step we analyse the azimuthal correlations of D meson-charged hadron(Dh), and then predict the same for D meson -anti D meson ($D\overline{D}$) pairs in $p$+$p$ and $p$+Pb collisions with strong coupling at leading order $\cal{O}$($\alpha_{s}^{2}$) and next to leading order $\cal{O}$($\alpha_{s}^{3}$) which includes space-time evolution (in both systems), as well cold nuclear matter effects (in $p$+Pb). This also sets the stage and baseline for the identification and study of medium modification of azimuthal correlations in relativistic collision of heavy nuclei at the Large Hadron Collider.Comment: 12 pages, 4 figure

Evaluating the Utility of Fly Ash for Waste Containment Application

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Macrocyclic cyanocobalamin (vitamin B12) as a homogeneous electrocatalyst for water oxidation under neutral conditions

Highly water-soluble cyanocobalamin (also known as vitamin B-12) is the most structurally macrocyclic complex comprising cobalt in the center of a corrin ring. Interestingly, it acts as a robust electrocatalyst in water oxidation at similar to 0.58 V overpotential with a faradaic efficiency of 97.50% under neutral buffered conditions. The catalyst is impressively stable even after long-term bulk electrolysis, and homogeneous in nature, as established by a series of experiments and characterization techniques

Subjectivity Detection through Socio-Linguistic Features

Social media platforms have opened new dimensions within the information retrieval domain leading to a novel concept known as Social Information Retrieval. We argue that the concept of Social Information Retrieval can be extended by augmenting the huge amount of content on the traditional Web with the ever-growing rich Social Web content to increase the information richness of today’s search engines. This paper proposes a subjectivity detection framework which can lead towards a proposed emotion-aware search engine interface. Our proposed method differs from previous subjectivity analysis approaches in that it is the first method that takes into account social features of social media platforms for the subjectivity classification task. Through experimental evaluations, we observe the accuracy of the proposed method to be 86.21% which demonstrates a promising outcome for large-scale application of our proposed subjectivity analysis technique