The ALICE Transition Radiation Detector: Construction, operation, and performance

The Transition Radiation Detector (TRD) was designed and built to enhance the capabilities of the ALICE detector at the Large Hadron Collider (LHC). While aimed at providing electron identification and triggering, the TRD also contributes significantly to the track reconstruction and calibration in the central barrel of ALICE. In this paper the design, construction, operation, and performance of this detector are discussed. A pion rejection factor of up to 410 is achieved at a momentum of 1 GeV/c in p-Pb collisions and the resolution at high transverse momentum improves by about 40% when including the TRD information in track reconstruction. The triggering capability is demonstrated both for jet, light nuclei, and electron selection. (c) 2017 CERN for the benefit of the Authors. Published by Elsevier B.V

Rotating night shift work and risk of obesity and weight gain in Nurses' Health Study II.

<p>The figure shows the odds ratio (95% CI) of being obese in 2007 and excessive weight gain between 1989 and 2007 by categories of rotating night shift work in Nurses' Health Study II. Excessive weight gain was defined as weight gain between 1989 and 2007 of more than 5% of the baseline body weight in 1989. The model was adjusted for baseline age, BMI, alcohol consumption, physical activity level, smoking status, ethnicity, menopausal status and hormone use, oral contraceptive use, family history of diabetes, current aspirin use, quintiles of total calorie and dietary score in 1989.</p

Age and age-standardized baseline characteristics of the study population at baseline by category of years spent in rotating night shift work.

<p>Data were expressed as mean (SD) or percentage, unless otherwise specified. The number of missing data in NHS I: BMI (<i>n = </i>4,825); physical activity level (<i>n = </i>126); diet information (<i>n = </i>14,612); smoking status (<i>n = </i>145); menopausal status and hormone use (<i>n = </i>3,229); sleep duration (<i>n = </i>8,964); snoring frequency (<i>n = </i>9,031). The number of missing data in NHS II: BMI (<i>n = </i>252); physical activity level (<i>n = </i>393); diet information (<i>n = </i>19,496); smoking status (<i>n = </i>473); menopausal status and hormone use (<i>n = </i>649).</p>a<p>Because of small sample size in this category, the percentage might not be accurate. In 2001 for NHS II, the corresponding percentage was 95%.</p

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Not AvailableEnormous sequence information is available in public databases as a result of sequencing of diverse crop genomes. It is important to use this genomic information for the identification and isolation of novel and superior alleles of agronomically important genes from crop gene pools to suitably deploy for the development of improved cultivars. Allele mining is a promising approach to dissect naturally occurring allelic variation at candidate genes controlling key agronomic traits which has potential applications in crop improvement programs. It helps in tracing the evolution of alleles, identification of new haplotypes and development of allele-specific markers for use in marker-assisted selection. Realizing the immense potential of allele mining, concerted allele mining efforts are underway in many international crop research institutes. This review examines the concepts, approaches and applications of allele mining along with the challenges associated while emphasizing the need for more refined ‘mining’ strategies for accelerating the process of allele discovery and its utilization in molecular breeding.Not Availabl