Predicting personality traits from social networking site profiles can help to assess individual differences in verbal reasoning without using long questionnaires. Inspired by earlier studies, which investigated whether abstract-thinking ability are predictable by social networking sites data, we used supervised machine learning to predict verbal-reasoning ability based on a proposed set of features extracted from virtual community membership. A large sample (N = 3,646) of Russian young adults aged 18-22 years approved access to the data from their social networking accounts and completed an online test on verbal reasoning.
View Article and Find Full Text PDFWe report the results of a search for a new vector boson ( ) decaying into two dark matter particles of different mass. The heavier particle subsequently decays to and an off-shell Dark Photon . For a sufficiently large mass splitting, this model can explain in terms of new physics the recently confirmed discrepancy observed in the muon anomalous magnetic moment at Fermilab.
View Article and Find Full Text PDFWe performed a search for a new generic X boson, which could be a scalar (S), pseudoscalar (P), vector (V), or an axial vector (A) particle produced in the 100 GeV electron scattering off nuclei, e^{-}Z→e^{-}ZX, followed by its invisible decay in the NA64 experiment at CERN. No evidence for such a process was found in the full NA64 dataset of 2.84×10^{11} electrons on target.
View Article and Find Full Text PDFRecently, the ATOMKI experiment has reported new evidence for the excess of events with a mass 17 MeV in the nuclear transitions of He, that they previously observed in measurements with Be. These observations could be explained by the existence of a new vector boson. So far, the search for the decay with the NA64 experiment at the CERN SPS gave negative results.
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