CMS physics technical design report : Addendum on high density QCD with heavy ions

Peer reviewe

Assessing the readability of ClinicalTrials.gov

Objective ClinicalTrials.gov serves critical functions of disseminating trial information to the public and helping the trials recruit participants. This study assessed the readability of trial descriptions at ClinicalTrials.gov using multiple quantitative measures. Materials and Methods The analysis included all 165 988 trials registered at ClinicalTrials.gov as of April 30, 2014. To obtain benchmarks, the authors also analyzed 2 other medical corpora: (1) all 955 Health Topics articles from MedlinePlus and (2) a random sample of 100 000 clinician notes retrieved from an electronic health records system intended for conveying internal communication among medical professionals. The authors characterized each of the corpora using 4 surface metrics, and then applied 5 different scoring algorithms to assess their readability. The authors hypothesized that clinician notes would be most difficult to read, followed by trial descriptions and MedlinePlus Health Topics articles. Results Trial descriptions have the longest average sentence length (26.1 words) across all corpora; 65% of their words used are not covered by a basic medical English dictionary. In comparison, average sentence length of MedlinePlus Health Topics articles is 61% shorter, vocabulary size is 95% smaller, and dictionary coverage is 46% higher. All 5 scoring algorithms consistently rated CliniclTrials.gov trial descriptions the most difficult corpus to read, even harder than clinician notes. On average, it requires 18 years of education to properly understand these trial descriptions according to the results generated by the readability assessment algorithms. Discussion and Conclusion Trial descriptions at CliniclTrials.gov are extremely difficult to read. Significant work is warranted to improve their readability in order to achieve CliniclTrials.gov’s goal of facilitating information dissemination and subject recruitment

New and updated convex shape models of asteroids based on optical data from a large collaboration network

International audienc

New and updated convex shape models of asteroids based on optical data from a large collaboration network

status: publishe

The effect of highly ionising particles on the CMS silicon strip tracker

Inelastic nuclear collisions of hadrons incident on silicon sensors can generate secondary highly ionising particles (HIPs) and deposit as much energy within the sensor bulk as several hundred minimum ionising particles. The large signals generated by these \u27HIP events\u27 can momentarily saturate the APV25 front-end readout chip for the silicon strip tracker (SST) sub-detector of the compact muon solenoid (CMS) experiment, resulting in deadtime in the detector readout system. This paper presents studies of this phenomenon through simulation, laboratory measurements and dedicated beam tests. A proposed change to a front-end component to reduce the APV25 sensitivity to HIP events is also examined. The results are used to infer the expected effect on the performance of the CMS SST at the future large hadron collider. The induced inefficiencies are at the percent level and will have a negligible effect on the physics performance of the SST. (c) 2005 Elsevier B.V. All rights reserved