The Layer 0 Inner Silicon Detector of the D0 Experiment

This paper describes the design, fabrication, installation and performance of the new inner layer called Layer 0 (L0) that was inserted in the existing Run IIa Silicon Micro-Strip Tracker (SMT) of the D0 experiment at the Fermilab Tevatron collider. L0 provides tracking information from two layers of sensors, which are mounted with center lines at a radial distance of 16.1 mm and 17.6 mm respectively from the beam axis. The sensors and readout electronics are mounted on a specially designed and fabricated carbon fiber structure that includes cooling for sensor and readout electronics. The structure has a thin polyimide circuit bonded to it so that the circuit couples electrically to the carbon fiber allowing the support structure to be used both for detector grounding and a low impedance connection between the remotely mounted hybrids and the sensors.Comment: 28 pages, 9 figure

Search for associated Higgs boson production using like charge dilepton events in p(p)over-bar collisions at root s=1.96 TeV

We present a search for associated Higgs boson production in the process p (p) over bar -> W/ZH -> l(+/-)l'(+/-) + X in ee, e mu, and mu mu final states. The search is based on data collected by the D0 experiment at the Fermilab Tevatron Collider at root s = 1.96 TeV corresponding to 5.3 fb(-1) of integrated luminosity. We require two isolated leptons (electrons or muons) with the same electric charge and additional kinematic requirements. No significant excess above background is observed, and we set 95% C. L. observed (expected) upper limits on ratio of the production cross section to the standard model prediction of 6.4 (7.3) for a Higgs boson mass of 165 GeV and 13.5 (19.8) for a mass of 115 GeV

The length dependence of the series elasticity of pig bladder smooth muscle

Strips of urinary bladder smooth muscle were subjected to a series of quick release measurements. Each measurement consisted of several releases and resets to the original length, made during one contraction. The complete length-force characteristic of series elasticity was quantified by estimating H, the amplitude of quick release necessary to reduce the active force to exactly zero, and Db, a measure for the deviation of the characteristic from a straight line. By measuring a series of contractions at increasing stretched strip lengths, the length dependence of these parameters was studied. It was found that H depends linearly on stretched strip length. On average H/length amounted to 0.04. Db decreased when strips were stretched, i.e. a straight line was more closely approximated. Both parameter dependencies support the concept of two separate elastic mechanisms, a linear true passive elasticity in series with a non-linear elasticity in the cross-bridges. For the latter, H amounts to 3.8% of the initial strip length

The MINERν\nuA Data Acquisition System and Infrastructure

MINER$\nu$A (Main INjector ExpeRiment $\nu$-A) is a new few-GeV neutrino cross section experiment that began taking data in the FNAL NuMI (Fermi National Accelerator Laboratory Neutrinos at the Main Injector) beam-line in March of 2010. MINER$\nu$A employs a fine-grained scintillator detector capable of complete kinematic characterization of neutrino interactions. This paper describes the MINER$\nu$A data acquisition system (DAQ) including the read-out electronics, software, and computing architecture.Comment: 34 pages, 16 figure

Towards comprehensive understanding of bacterial genetic diversity:large-scale amplifications in Bordetella pertussis and Mycobacterium tuberculosis

Bacterial genetic diversity is often described solely using base-pair changes despite a wide variety of other mutation types likely being major contributors. Tandem duplication/amplifications are thought to be widespread among bacteria but due to their often-intractable size and instability, comprehensive studies of these mutations are rare. We define a methodology to investigate amplifications in bacterial genomes based on read depth of genome sequence data as a proxy for copy number. We demonstrate the approach with Bordetella pertussis , whose insertion sequence element-rich genome provides extensive scope for amplifications to occur. Analysis of data for 2430 B. pertussis isolates identified 272 putative amplifications, of which 94 % were located at 11 hotspot loci. We demonstrate limited phylogenetic connection for the occurrence of amplifications, suggesting unstable and sporadic characteristics. Genome instability was further described in vitro using long-read sequencing via the Nanopore platform, which revealed that clonally derived laboratory cultures produced heterogenous populations rapidly. We extended this research to analyse a population of 1000 isolates of another important pathogen, Mycobacterium tuberculosis . We found 590 amplifications in M. tuberculosis , and like B. pertussis , these occurred primarily at hotspots. Genes amplified in B. pertussis include those involved in motility and respiration, whilst in M. tuberuclosis, functions included intracellular growth and regulation of virulence. Using publicly available short-read data we predicted previously unrecognized, large amplifications in B. pertussis and M. tuberculosis . This reveals the unrecognized and dynamic genetic diversity of B. pertussis and M. tuberculosis , highlighting the need for a more holistic understanding of bacterial genetics

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector.

The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies

Immune-related pan-cancer gene expression signatures of patient survival revealed by NanoString-based analyses

The immune system plays a central role in the onset and progression of cancer. A better understanding of transcriptional changes in immune cell-related genes associated with cancer progression, and their significance in disease prognosis, is therefore needed. NanoString-based targeted gene expression profiling has advantages for deployment in a clinical setting over RNA-seq technologies. We analysed NanoString PanCancer Immune Profiling panel gene expression data encompassing 770 genes, and overall survival data, from multiple previous studies covering 10 different cancer types, including solid and blood malignancies, across 515 patients. This analysis revealed an immune gene signature comprising 39 genes that were upregulated in those patients with shorter overall survival; of these 39 genes, three (MAGEC2, SSX1 and ULBP2) were common to both solid and blood malignancies. Most of the genes identified have previously been reported as relevant in one or more cancer types. Using Cibersort, we investigated immune cell levels within individual cancer types and across groups of cancers, as well as in shorter and longer overall survival groups. Patients with shorter survival had a higher proportion of M2 macrophages and γδ T cells. Patients with longer overall survival had a higher proportion of CD8+ T cells, CD4+ T memory cells, NK cells and, unexpectedly, T regulatory cells. Using a transcriptomics platform with certain advantages for deployment in a clinical setting, our multi-cancer meta-analysis of immune gene expression and overall survival data has identified a specific transcriptional profile associated with poor overall survival