Publications by authors named "L I Levchuk"
Article Synopsis
- The study focuses on detecting multijet signatures from proton-proton collisions at a high energy of 13 TeV, analyzing a dataset totaling 128 fb^{-1}.
- A special data scouting method is utilized to pick out events with low combined momentum in jets.
- This research is pioneering in its investigation of electroweak particle production in R-parity violating supersymmetric models, particularly examining hadronically decaying mass-degenerate higgsinos, and it broadens the limits on the existence of R-parity violating top squarks and gluinos.
The first search for soft unclustered energy patterns (SUEPs) is performed using an integrated luminosity of 138 fb^{-1} of proton-proton collision data at sqrt[s]=13 TeV, collected in 2016-2018 by the CMS detector at the LHC. Such SUEPs are predicted by hidden valley models with a new, confining force with a large 't Hooft coupling. In events with boosted topologies, selected by high-threshold hadronic triggers, the multiplicity and sphericity of clustered tracks are used to reject the background from standard model quantum chromodynamics.
View Article and Find Full Text PDF[A pilot study of associations of markers of glial and neuronal degeneration with executive functions in alcohol use disorders].
Zh Nevrol Psikhiatr Im S S Korsakova
November 2024
Article Synopsis
- A study analyzed the link between serum markers of brain degeneration and cognitive functions in 74 men, comparing 44 patients with alcohol use disorders (AUDs) to 30 healthy volunteers.
- Patients with AUDs showed significantly higher levels of S100B and MBP, and performed worse on executive function tests compared to the control group.
- The research suggests that S100B and MBP levels correlate with impaired cognitive functions in AUD patients, indicating potential for these biomarkers to track cognitive decline.
The first search for the Z boson decay to ττμμ at the CERN LHC is presented, based on data collected by the CMS experiment at the LHC in proton-proton collisions at a center-of-mass energy of 13 TeV and corresponding to an integrated luminosity of 138 fb^{-1}. The data are compatible with the predicted background. For the first time, an upper limit at the 95% confidence level of 6.
View Article and Find Full Text PDF[Growth factors PDGF-AA, PDGF-BB and BDNF as potential differentiating biomarkers of unipolar and bipolar depression].
Zh Nevrol Psikhiatr Im S S Korsakova
October 2024
Article Synopsis
- The study aimed to differentiate between unipolar and bipolar depression by analyzing biological markers PDGF-AA, PDGF-BB, and BDNF using machine learning.
- It included 79 patients and utilized clinical assessments along with blood serum analysis to measure growth factor concentrations.
- Findings indicated significant differences in growth factor levels between the two types of depression, suggesting the potential use of these markers as prognostic tools for diagnosis.