Rubin-LSST

Abstract:

The first measurement of jet shapes, defined as the fractional transverse momentum radial distribution, for inclusive jets produced in heavy-ion collisions is presented. Data samples of PbPb and pp collisions, corresponding to integrated luminosities of 150 μb-1 and 5.3 pb-1 respectively, were collected at a nucleon-nucleon centre-of-mass energy of sNN=2.76TeV with the CMS detector at the LHC. The jets are reconstructed with the anti-kT algorithm with a distance parameter R = 0.3, and the jet shapes are measured for charged particles with transverse momentum pT > 1GeV/c. The jet shapes measured in PbPb collisions in different collision centralities are compared to reference distributions based on the pp data. A centrality-dependent modification of the jet shapes is observed in the more central PbPb collisions, indicating a redistribution of the energy inside the jet cone. This measurement provides information about the parton shower mechanism in the hot and dense medium produced in heavy-ion collisions. © 2014 The Authors.

Abstract:

This Letter presents a search for quantum black-hole production using 20.3 fb-1 of data collected with the ATLAS detector in pp collisions at the LHC at √s = 8 TeV. The quantum black holes are assumed to decay into a final state characterized by a lepton (electron or muon) and a jet. In either channel, no event with a lepton-jet invariant mass of 3.5 TeV or more is observed, consistent with the expected background. Limits are set on the product of cross sections and branching fractions for the lepton+jet final states of quantum black holes produced in a search region for invariant masses above 1 TeV. The combined 95% confidence level upper limit on this product for quantum black holes with threshold mass above 3.5 TeV is 0.18 fb. This limit constrains the threshold quantum black-hole mass to be above 5.3 TeV in the model considered.

Abstract:

Background Validated methods of objective assessments of surgical skills are resource intensive. We sought to test a web-based grading tool using crowdsourcing called Crowd-Sourced Assessment of Technical Skill. Materials and methods Institutional Review Board approval was granted to test the accuracy of Amazon.com's Mechanical Turk and Facebook crowdworkers compared with experienced surgical faculty grading a recorded dry-laboratory robotic surgical suturing performance using three performance domains from a validated assessment tool. Assessor free-text comments describing their rating rationale were used to explore a relationship between the language used by the crowd and grading accuracy. Results Of a total possible global performance score of 3-15, 10 experienced surgeons graded the suturing video at a mean score of 12.11 (95% confidence interval [CI], 11.11-13.11). Mechanical Turk and Facebook graders rated the video at mean scores of 12.21 (95% CI, 11.98-12.43) and 12.06 (95% CI, 11.57-12.55), respectively. It took 24 h to obtain responses from 501 Mechanical Turk subjects, whereas it took 24 d for 10 faculty surgeons to complete the 3-min survey. Facebook subjects (110) responded within 25 d. Language analysis indicated that crowdworkers who used negation words (i.e., "but," "although," and so forth) scored the performance more equivalently to experienced surgeons than crowdworkers who did not (P < 0.00001). Conclusions For a robotic suturing performance, we have shown that surgery-naive crowdworkers can rapidly assess skill equivalent to experienced faculty surgeons using Crowd-Sourced Assessment of Technical Skill. It remains to be seen whether crowds can discriminate different levels of skill and can accurately assess human surgery performances. © 2014 Elsevier Inc. All rights reserved.