Energy dependent forward B →\rightarrow J/ψJ/\psi measurements in p+p collisions at PHENIX

The heavy flavor studies at RHIC help improve the knowledge of the bottom/charm quark production and can test Quantum Chromodynamics (QCD). Compared to the LHC/Tevatron, the RHIC heavy flavor production originates from different partonic sub-processes and has a complementary kinematic coverage. The PHENIX forward rapidity silicon vertex detector (FVTX) provides precise determination of the event vertex, tracking and the Distance of Closest Approach (DCA) of charged tracks. This detector allows direct access to the $B$ meson production via measurements of non-prompt $J/\psi \to \mu^{+} + \mu^{-}$ within $1.2<|y|<2.2$ rapidity in $p$+$p$ collisions at $\sqrt{s} =$ 510 and 200 GeV. Comparison among PHENIX measurements of the $B \rightarrow J/\psi$ fraction with integrated $J/\psi$ $p_{T}$ up to 5 GeV$/c$ and higher energy results at the Tevatron and the LHC presents a smooth center of mass energy dependence from 0.2 to 13 TeV in $p$+$p$ ($p$+$\bar{p}$) collisions. The Next-To-Leading order Perturbative QCD (NLO pQCD) calculations are in reasonable agreement with the extracted total $b\bar{b}$ cross section based on the $B \rightarrow J/\psi$ fraction measurements at PHENIX.Comment: 6 pages, 4 figures, the XXV International Workshop on Deep-Inelastic Scattering and Related Subjects proceeding

The Impact of Higher Standards in Patent Protection for Pharmaceutical Industries under the TRIPS Agreement: A Comparative Study of China and India

A comparative study is undertaken that explores Chinese and Indian pharmaceutical industries under different patent regimes. It is found that relative to India, which had implemented process patent until 2005, China with a product patent regime since 1993 suffers from both lower drug accessibility and availability (the latter is a missing parameter in the literature). Also, China lags behind in both lower R&D investment and patents filed by Chinese nationals. Based on these findings and associated legal interpretation, we conclude that higher patent protection in China generates negative impacts on the pharmaceutical industries. Thus, governments should utilize TRIPS flexibilities and other regimes like price control to offset the anticompetitive effect in designing patent policies.product patent, process patent, TRIPS, pharmaceutical industries, China, India

Lazy stochastic principal component analysis

Stochastic principal component analysis (SPCA) has become a popular dimensionality reduction strategy for large, high-dimensional datasets. We derive a simplified algorithm, called Lazy SPCA, which has reduced computational complexity and is better suited for large-scale distributed computation. We prove that SPCA and Lazy SPCA find the same approximations to the principal subspace, and that the pairwise distances between samples in the lower-dimensional space is invariant to whether SPCA is executed lazily or not. Empirical studies find downstream predictive performance to be identical for both methods, and superior to random projections, across a range of predictive models (linear regression, logistic lasso, and random forests). In our largest experiment with 4.6 million samples, Lazy SPCA reduced 43.7 hours of computation to 9.9 hours. Overall, Lazy SPCA relies exclusively on matrix multiplications, besides an operation on a small square matrix whose size depends only on the target dimensionality.Comment: To be published in: 2017 IEEE International Conference on Data Mining Workshops (ICDMW