Technical University of Dortmund

About: Technical University of Dortmund is a education organization based out in Dortmund, Nordrhein-Westfalen, Germany. It is known for research contribution in the topics: Context (language use) & Large Hadron Collider. The organization has 13028 authors who have published 27666 publications receiving 615557 citations. The organization is also known as: Dortmund University & University of Dortmund.

Incremental learning with support vector machines

Abstract: Support vector machines (SVMs) have become a popular tool for machine learning with large amounts of high dimensional data. In this paper an approach for incremental learning with support vector machines is presented, that improves the existing approach of Syed et al. (1999). An insight into the interpretability of support vectors is also given.

Test of lepton universality with B 0 → K *0 ℓ + ℓ − decays

Abstract: A test of lepton universality, performed by measuring the ratio of the branching fractions of the B$^{0}$ → K$^{*0}$ μ$^{+}$ μ$^{−}$ and B$^{0}$ → K$^{*0}$ e$^{+}$ e$^{−}$ decays, $ {R}_{K^{*0}} $ , is presented. The K$^{*0}$ meson is reconstructed in the final state K$^{+}$ π$^{−}$, which is required to have an invariant mass within 100 MeV/c$^{2}$ of the known K$^{*}$(892)$^{0}$ mass. The analysis is performed using proton-proton collision data, corresponding to an integrated luminosity of about 3 fb$^{−1}$, collected by the LHCb experiment at centre-of-mass energies of 7 and 8 TeV. The ratio is measured in two regions of the dilepton invariant mass squared, q$^{2}$, to be $ {R}_{K^{*0}}=\left\{\begin{array}{l}{0.66_{-}^{+}}_{0.07}^{0.11}\left(\mathrm{stat}\right)\pm 0.03\left(\mathrm{syst}\right)\kern1em \mathrm{f}\mathrm{o}\mathrm{r}\kern1em 0.045<{q}^2<1.1\kern0.5em {\mathrm{GeV}}^2/{c}^4,\hfill \\ {}{0.69_{-}^{+}}_{0.07}^{0.11}\left(\mathrm{stat}\right)\pm 0.05\left(\mathrm{syst}\right)\kern1em \mathrm{f}\mathrm{o}\mathrm{r}\kern1em 1.1<{q}^2<6.0\kern0.5em {\mathrm{GeV}}^2/{c}^4.\hfill \end{array}\right. $

Chemical Strategies for Generating Protein Biochips

Abstract: Protein biochips are at the heart of many medical and bioanalytical applications. Increasing interest has been focused on surface activation and subsequent functionalization strategies for immobilizing these biomolecules. Different approaches using covalent and noncovalent chemistry are reviewed; particular emphasis is placed on the chemical specificity of protein attachment and on retention of protein function. Strategies for creating protein patterns (as opposed to protein arrays) are also outlined. An outlook on promising and challenging future directions for protein biochip research and applications is also offered.