Estimation of fatty acid composition in mammary adipose tissue using deep neural network with unsupervised training.

Purpose: To develop a deep learning-based method for robust and rapid estimation of the fatty acid composition (FAC) in mammary adipose tissue.

Methods: A physics-based unsupervised deep learning network for estimation of fatty acid composition-network (FAC-Net) is proposed to estimate the number of double bonds and number of methylene-interrupted double bonds from multi-echo bipolar gradient-echo data, which are subsequently converted to saturated, mono-unsaturated, and poly-unsaturated fatty acids. The loss function was based on a 10 fat peak signal model.

Observation of the decay.

Using proton-proton collision data corresponding to an integrated luminosity of collected by the CMS experiment at , the decay is observed for the first time, with a statistical significance exceeding 5 standard deviations. The relative branching fraction, with respect to the decay, is measured to be , where the first uncertainty is statistical, the second is systematic, and the third is related to the uncertainties in and .

Observation of the ϒ(3S) Meson and Suppression of ϒ States in Pb-Pb Collisions at sqrt[s_{NN}]=5.02 TeV.

The production of ϒ(2S) and ϒ(3S) mesons in lead-lead (Pb-Pb) and proton-proton (pp) collisions is studied in their dimuon decay channel using the CMS detector at the LHC. The ϒ(3S) meson is observed for the first time in Pb-Pb collisions, with a significance above 5 standard deviations. The ratios of yields measured in Pb-Pb and pp collisions are reported for both the ϒ(2S) and ϒ(3S) mesons, as functions of transverse momentum and Pb-Pb collision centrality.

Search for Narrow Trijet Resonances in Proton-Proton Collisions at sqrt[s]=13 TeV.

The first search for singly produced narrow resonances decaying to three well-separated hadronic jets is presented. The search uses proton-proton collision data corresponding to an integrated luminosity of 138  fb^{-1} at sqrt[s]=13  TeV, collected at the CERN LHC. No significant deviations from the background predictions are observed between 1.