The CMS Phase-1 pixel detector upgrade

The CMS detector at the CERN LHC features a silicon pixel detector as its innermost subdetector. The original CMS pixel detector has been replaced with an upgraded pixel system (CMS Phase-1 pixel detector) in the extended year-end technical stop of the LHC in 2016/2017. The upgraded CMS pixel detector is designed to cope with the higher instantaneous luminosities that have been achieved by the LHC after the upgrades to the accelerator during the first long shutdown in 2013–2014. Compared to the original pixel detector, the upgraded detector has a better tracking performance and lower mass with four barrel layers and three endcap disks on each side to provide hit coverage up to an absolute value of pseudorapidity of 2.5. This paper describes the design and construction of the CMS Phase-1 pixel detector as well as its performance from commissioning to early operation in collision data-taking.Peer reviewe

Development and validation of HERWIG 7 tunes from CMS underlying-event measurements

This paper presents new sets of parameters (“tunes”) for the underlying-event model of the HERWIG7 event generator. These parameters control the description of multiple-parton interactions (MPI) and colour reconnection in HERWIG7, and are obtained from a fit to minimum-bias data collected by the CMS experiment at s=0.9, 7, and 13Te. The tunes are based on the NNPDF 3.1 next-to-next-to-leading-order parton distribution function (PDF) set for the parton shower, and either a leading-order or next-to-next-to-leading-order PDF set for the simulation of MPI and the beam remnants. Predictions utilizing the tunes are produced for event shape observables in electron-positron collisions, and for minimum-bias, inclusive jet, top quark pair, and Z and W boson events in proton-proton collisions, and are compared with data. Each of the new tunes describes the data at a reasonable level, and the tunes using a leading-order PDF for the simulation of MPI provide the best description of the dat

Alignment of the CMS tracker with LHC and cosmic ray data

© CERN 2014 for the benefit of the CMS collaboration, published under the terms of the Creative Commons Attribution 3.0 License by IOP Publishing Ltd and Sissa Medialab srl. Any further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation and DOI.The central component of the CMS detector is the largest silicon tracker ever built. The precise alignment of this complex device is a formidable challenge, and only achievable with a significant extension of the technologies routinely used for tracking detectors in the past. This article describes the full-scale alignment procedure as it is used during LHC operations. Among the specific features of the method are the simultaneous determination of up to 200 000 alignment parameters with tracks, the measurement of individual sensor curvature parameters, the control of systematic misalignment effects, and the implementation of the whole procedure in a multi-processor environment for high execution speed. Overall, the achieved statistical accuracy on the module alignment is found to be significantly better than 10μm

Estimation of Alignment Parameters, using the Kalman Filter with annealing

Detector alignment is an essential step in the track reconstruction and analysis process. Alignment with tracks is one possible strategy to estimate positions and orientations of components of a track detector. We present a method for the estimation of alignment constants during track reconstruction, in parallel with the usual track parameters. The formalism is related to the standard Kalman Filter and uses annealing in order to avoid suboptimal solutions. The algorithm has been implemented in the Object oriented Reconstruction for Cms Analysis (ORCA) framework and has been tested with a simulated test-beam like setup for silicon detectors

Cardiorespiratory Interaction and Autonomic Sleep Quality Improve during Sleep in Beds Made from Pinus cembra (Stone Pine) Solid Wood

Cardiorespiratory interactions (CRIs) reflect the mutual tuning of two important organismic oscillators—the heartbeat and respiration. These interactions can be used as a powerful tool to characterize the self-organizational and recreational quality of sleep. In this randomized, blinded and cross-over design study, we investigated CRIs in 15 subjects over a total of 253 nights who slept in beds made from different materials. One type of bed, used as control, was made of melamine faced chipboard with a wood-like appearance, while the other type was made of solid wood from stone pine (Pinus cembra). We observed a significant increase of vagal activity (measured by respiratory sinus arrhythmia), a decrease in the heart rate (as an indicator of energy consumption during sleep) and an improvement in CRIs, especially during the first hours of sleep in the stone pine beds as compared to the chipboard beds. Subjective assessments of study participants’ well-being in the morning and sub-scalar assessments of their intrapsychic stability were significantly better after they slept in the stone pine bed than after they slept in the chipboard bed. Our observations suggest that CRIs are sensitive to detectable differences in indoor settings that are relevant to human health. Our results are in agreement with those of other studies that have reported that exposure to volatile phytochemical ingredients of stone pine (α-pinene, limonene, bornyl acetate) lead to an improvement in vagal activity and studies that show a reduction in stress parameters upon contact with solid wood surfaces

Investigation of a Micro-test for Circulatory Autonomic Nervous System Responses

Aims and Objectives: The autonomic nervous system plays an important role in homeostasis and organismic recreation, control of immune function, inflammation, and bone growth. It also regulates blood pressure and orthostasis via vagal and sympathetic pathways. Besides recording of heart rate variability (HRV), which characterizes medium (1–5 min) and long term (circadian) autonomic tone or modulation, no gentle tests of short-term autonomic reactivity and control are available. In 1976 Nogier described a short time cardiovascular response (“Réflexe Auriculo Cardiaque”, RAC) which could be used to investigate short term autonomic reactions without changing system characteristics and thus being repeatable in short intervals. In this paper, we investigated the possible application of the Nogier reaction as a micro-test for the identification of a disturbed sensitivity or reactivity of the autonomic nervous system.Methods: We statistically analyzed cardiovascular signals derived during the application of small repeated stimuli utilizing methods of signal averaging to characterize the physiological background. Specifically, the Nogier reaction was investigated using simultaneous recordings of ECG, pulse waves, and respiration.Results: Significant fast (delay 1–5 s) and slower (delay 6–12 s) cardio-autonomic responses to different stimuli which characterize short term were observed. From time characteristics and type of signals where they occur we deduce that fast changes observed in heart rate are vagal reactions to the small stimuli whereas slower changes observed in pulse waves stem from sympathetic nervous system responses.Conclusions: The investigated autonomic micro-test opens the possibility to differentially investigate both limbs of the autonomic nervous system with minimal stimuli. It can be performed within seconds and does not change the set point of the system in opposition to less subtle tests such as Valsalva maneuver. Therefore, it is well-suited for quick, repeated measurements of autonomic nervous system reactivity

The microbe-heart-brain dialogue: Vagal activity is associated with gut-microbiome patterns in women

Introduction: A functional reciprocity between the gut microbiome and vagal nerve activity has been suggested, however, human studies addressing this phenomenon are limited. Methods: 24- hour cardiac vagal activity (CVA) was assessed from 73 female participants (aged 24.5±4.3 years). Additionally, stool samples were subjected to 16SrRNA gene analysis (V1–V2). Quantitative Insights Into Microbial Ecology (QIIME) was used to analyze microbiome data. Additionally, inflammatory parameters (such as CRP and IL-6) were derived from serum samples. Results: Daytime CVA correlated significantly with gut microbiota diversity (r=0.254, p=0.030), CRP (r=-0.348, p= 0.003), and IL-6 (r=-0.320, p=0.006). When the group was divided at the median of 24 hour CVA (Mdn=1.322), the following features were more abundant in the high CVA group: Clostridia (Linear discriminant analysis effect size (LDA)= 4.195, p= 0.029), Clostridiales (LDA=4.195, p= 0.029), Lachnospira (LDA=3.489, p=0.004), Ruminococcaceae (LDA=4.073, p=0.010), Faecalibacterium (LDA=3.982, p= 0.042), Lactobacillales (LDA=3.317, p=0.029), Bacilli (LDA=3.294, p=0.0350), Streptococcaceae (LDA=3.353, p= 0.006), Streptococcus (LDA=3.332, p=0.011). Based on Dirichlet multinomial mixtures two enterotypes could be detected, which differed significantly in CVA, age, BMI, CRP, IL-6 and diversity. Conclusions: As an indicator of gut-brain communication, gut microbiome analysis could be extended by measurements of CVA to enhance our understanding of signalling via microbiota-gut-brain-axis and its alterations through psychobiotics