We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton-proton collisions at an energy of s = 13 TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 fb - 1 . A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to b b ¯ .
Searches for pair-produced multijet signatures using data corresponding to an integrated luminosity of 128 fb^{-1} of proton-proton collisions at sqrt[s]=13 TeV are presented. A data scouting technique is employed to record events with low jet scalar transverse momentum sum values. The electroweak production of particles predicted in R-parity violating supersymmetric models is probed for the first time with fully hadronic final states. This is the first search for prompt hadronically decaying mass-degenerate higgsinos, and extends current exclusions on R-parity violating top squarks and gluinos.
Using proton-proton collision data corresponding to an integrated luminosity of 140 fb - 1 collected by the CMS experiment at s = 13 Te V , the Λ b 0 → J / ψ Ξ - K + decay is observed for the first time, with a statistical significance exceeding 5 standard deviations. The relative branching fraction, with respect to the Λ b 0 → ψ ( 2 S ) Λ decay, is measured to be B ( Λ b 0 → J / ψ Ξ - K + ) / B ( Λ b 0 → ψ ( 2 S ) Λ ) = [ 3.38 ± 1.02 ± 0.61 ± 0.03 ] % , where the first uncertainty is statistical, the second is systematic, and the third is related to the uncertainties in B ( ψ ( 2 S ) → J / ψ π + π - ) and B ( Ξ - → Λ π - ) .
In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.