CP Violation in Top Physics at the NLC

Top quark is extremely sensitive to non-standard CP violating phases. General strategies for exposing different types of phases at the NLC are outlined. SUSY phase(s) cause PRA in $t\to Wb$. The transverse polarization of the $\tau$ in the reaction $t\to b\tau\nu$ is extremely sensitive to a phase from the charged Higgs sector. Phase(s) from the neutral Higgs sector cause appreciable dipole moment effects and lead to sizable asymmetries in $e^+e^-\to t\bar tH^0$ and $e^+e^-\to t\bar t\nu_e\bar\nu_e$.}]Comment: 4 pages, Latex, 2 figures. For the Proceedings of the 28th Int. Conf. on HEP, Warsaw(July 1996

Pure Leptonic Radiative Decays B±,Ds→ℓνγB^\pm, D_s\to\ell\nu\gamma and the Annihilation Graph

Pure leptonic radiative decays of heavy-light mesons are calculated using a very simple non-relativistic model. Dominant contribution originates from photon emission from light initial quark. We find $BR(B^\pm\to\ell\nu\gamma)\sim3.5\times10^{-6}$ and $BR(D_s\to \ell\nu\gamma)\sim1.7 \times10^{-4}$. The importance of these reactions to clarify the dynamics of the annihilation graph is emphasized.Comment: 7 pages, LaTeX, 3 figure

Identifying Parkinson’s Patients: A Functional Gradient Boosting Approach

Parkinson’s, a progressive neural disorder, is difficult to identify due to the hidden nature of the symptoms associated. We present a machine learning approach that uses a definite set of features obtained from the Parkinson’s Progression Markers Initiative (PPMI) study as input and classifies them into one of two classes: PD (Parkinson’s disease) and HC (Healthy Control). As far as we know this is the first work in applying machine learning algorithms for classifying patients with Parkinson’s disease with the involvement of domain expert during the feature selection process. We evaluate our approach on 1194 patients acquired from Parkinson’s Progression Markers Initiative and show that it achieves a state-of-the-art performance with minimal feature engineering