Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Protein Conformational Changes in the Bacteriorhodopsin Photocycle: Comparison of Findings from Electron and X-Ray Crystallographic Analyses

Light-driven conformational changes in the membrane protein bacteriorhodopsin have been studied extensively using X-ray and electron crystallography, resulting in the deposition of >30 sets of coordinates describing structural changes at various stages of proton transport. Using projection difference Fourier maps, we show that coordinates reported by different groups for the same photocycle intermediates vary considerably in the extent and nature of conformational changes. The different structures reported for the same intermediate cannot be reconciled in terms of differing extents of change on a single conformational trajectory. New measurements of image phases obtained by cryo-electron microscopy of the D96G/F171C/F219L triple mutant provide independent validation for the description of the large protein conformational change derived at 3.2 Å resolution by electron crystallography of 2D crystals, but do not support atomic models for light-driven conformational changes derived using X-ray crystallography of 3D crystals. Our findings suggest that independent determination of phase information from 2D crystals can be an important tool for testing the accuracy of atomic models for membrane protein conformational changes

Correlates of overall and central obesity in adults from seven European countries: findings from the Food4Me Study

To identify predictors of obesity in adults and investigate to what extent these predictors are independent of other major confounding factors. Data collected at baseline from 1441 participants from the Food4Me study conducted in seven European countries were included in this study. A food frequency questionnaire was used to measure dietary intake. Accelerometers were used to assess physical activity levels (PA), whereas participants self-reported their body weight, height and waist circumference via the internet. The main factors associated (p < 0.05) with higher BMI per 1-SD increase in the exposure were age (β:1.11 kg/m2), intakes of processed meat (β:1.04 kg/m2), red meat (β:1.02 kg/m2), saturated fat (β:0.84 kg/m2), monounsaturated fat (β:0.80 kg/m2), protein (β:0.74 kg/m2), total energy intake (β:0.50 kg/m2), olive oil (β:0.36 kg/m2), sugar sweetened carbonated drinks (β:0.33 kg/m2) and sedentary time (β:0.73 kg/m2). In contrast, the main factors associated with lower BMI per 1-SD increase in the exposure were PA (β:-1.36 kg/m2), intakes of wholegrains (β:-1.05 kg/m2), fibre (β:-1.02 kg/m2), fruits and vegetables (β:-0.52 kg/m2), nuts (β:-0.52 kg/m2), polyunsaturated fat (β:-0.50 kg/m2), Healthy Eating Index (β:-0.42 kg/m2), Mediterranean diet score (β:-0.40 kg/m2), oily fish (β:-0.31 kg/m2), dairy (β:-0.31 kg/m2) and fruit juice (β:-0.25 kg/m2). These findings are important for public health and suggest that promotion of increased PA, reducing sedentary behaviours and improving the overall quality of dietary patterns are important strategies for addressing the existing obesity epidemic and associated disease burden

Geodemographic Patterns of Meat Expenditure in Great Britain

The future of the meat industry will require the management of important trade-offs between economic, environmental and health aspects of both humans and animals. Understanding the patterns and trends of meat expenditure and consumption is crucial for assessing the current resilience of the system and for economic, planning, health and environmental applications. Here, we show how the technique of geodemographic classification, combined with fine scale expenditure estimates can be used to explore temporal and spatial patterns of meat expenditure in Great Britain between 2008 and 2017. Whilst the expenditure patterns of some food categories such as sausages remained relatively consistent, others such as lamb show a trend towards a reduced proportion of expenditure and increased inequality of purchases. Short term changes in expenditure patterns also occurred, potentially due to product specific price variability, price elasticities or zoonotic disease scare. Environmental attitudes, financial constraints and the prominence of communities who do not eat meat for religious or cultural reasons are likely to be driving the differences between geodemographic groups. The methodology and results could be a valuable tool for policy makers in the meat industry and beyond

CMS Data Processing Workflows during an Extended Cosmic Ray Run

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Aligning the CMS Muon Chambers with the Muon Alignment System during an Extended Cosmic Ray Run

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Commissioning of the CMS high-level trigger with cosmic rays

This is the Pre-print version of the Article. The official published version of the paper can be accessed from the link below - Copyright @ 2010 IOPThe CMS High-Level Trigger (HLT) is responsible for ensuring that data samples with potentially interesting events are recorded with high efficiency and good quality. This paper gives an overview of the HLT and focuses on its commissioning using cosmic rays. The selection of triggers that were deployed is presented and the online grouping of triggered events into streams and primary datasets is discussed. Tools for online and offline data quality monitoring for the HLT are described, and the operational performance of the muon HLT algorithms is reviewed. The average time taken for the HLT selection and its dependence on detector and operating conditions are presented. The HLT performed reliably and helped provide a large dataset. This dataset has proven to be invaluable for understanding the performance of the trigger and the CMS experiment as a whole.This work is supported by FMSR (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); Academy of Sciences and NICPB (Estonia); Academy of Finland, ME, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); PAEC (Pakistan); SCSR (Poland); FCT (Portugal); JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MST and MAE (Russia); MSTDS (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF (USA)

Identification and Filtering of Uncharacteristic Noise in the CMS Hadron Calorimeter

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Performance of CMS Hadron Calorimeter Timing and Synchronization using Test Beam, Cosmic Ray, and LHC Beam Data

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