6 research outputs found
Polyakov Lines in Yang-Mills Matrix Models
We study the Polyakov line in Yang-Mills matrix models, which include the
IKKT model of IIB string theory. For the gauge group SU(2) we give the exact
formulae in the form of integral representations which are convenient for
finding the asymptotic behaviour. For the SU(N) bosonic models we prove upper
bounds which decay as a power law at large momentum p. We argue that these
capture the full asymptotic behaviour. We also indicate how to extend the
results to some correlation functions of Polyakov lines.Comment: 19 pages, v2 typos corrected, v3 ref adde
Development of an E-learning System for the Endoscopic Diagnosis of Early Gastric Cancer: An International Multicenter Randomized Controlled Trial
Background: In many countries, gastric cancer is not diagnosed until an advanced stage. An Internet-based e-learning system to improve the ability of endoscopists to diagnose gastric cancer at an early stage was developed and was evaluated for its effectiveness.
Methods: The study was designed as a randomized controlled trial. After receiving a pre-test, participants were randomly allocated to either an e-learning or non-e-learning group. Only those in the e-learning group gained access to the e-learning system. Two months after the pre-test, both groups received a post-test. The primary endpoint was the difference between the two groups regarding the rate of improvement of their test results.
Findings: 515 endoscopists from 35 countries were assessed for eligibility, and 332 were enrolled in the study, with 166 allocated to each group. Of these, 151 participants in the e-learning group and 144 in the non-e-learning group were included in the analysis. The mean improvement rate (standard deviation) in the e-learning and non-e-learning groups was 1·24 (0·26) and 1·00 (0·16), respectively (P < 0·001).
Interpretation: This global study clearly demonstrated the efficacy of an e-learning system to expand knowledge and provide invaluable experience regarding the endoscopic detection of early gastric cancer (R000012039)