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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.

Primary challenges for current and future precision neutrino experiments using liquid argon time projection chambers (LArTPCs) include understanding detector effects and quantifying the associated systematic uncertainties. This paper presents a novel technique for assessing and propagating LArTPC detector-related systematic uncertainties. The technique makes modifications to simulation waveforms based on a parameterization of observed differences in ionization signals from the TPC between data and simulation, while remaining insensitive to the details of the detector model. The modifications are then used to quantify the systematic differences in low- and high-level reconstructed quantities. This approach could be applied to future LArTPC detectors, such as those used in SBN and DUNE.

A bstract The MicroBooNE liquid argon time projection chamber located at Fermilab is a neutrino experiment dedicated to the study of short-baseline oscillations, the measurements of neutrino cross sections in liquid argon, and to the research and development of this novel detector technology. Accurate and precise measurements of calorimetry are essential to the event reconstruction and are achieved by leveraging the TPC to measure deposited energy per unit length along the particle trajectory, with mm resolution. We describe the non-uniform calorimetric reconstruction performance in the detector, showing dependence on the angle of the particle trajectory. Such non-uniform reconstruction directly affects the performance of the particle identification algorithms which infer particle type from calorimetric measurements. This work presents a new particle identification method which accounts for and effectively addresses such non-uniformity. The newly developed method shows improved performance compared to previous algorithms, illustrated by a 93.7% proton selection efficiency and a 10% muon mis-identification rate, with a fairly loose selection of tracks performed on beam data. The performance is further demonstrated by identifying exclusive final states in ν μ CC interactions. While developed using MicroBooNE data and simulation, this method is easily applicable to future LArTPC experiments, such as SBND, ICARUS, and DUNE.

A significant challenge in measurements of neutrino oscillations is reconstructing the incoming neutrino energies. While modern fully-active tracking calorimeters such as liquid argon time projection chambers in principle allow the measurement of all final state particles above some detection threshold, undetected neutrons remain a considerable source of missing energy with little to no data constraining their production rates and kinematics. We present the first demonstration of tagging neutrino-induced neutrons in liquid argon time projection chambers using secondary protons emitted from neutron-argon interactions in the MicroBooNE detector. We describe the method developed to identify neutrino-induced neutrons and demonstrate its performance using neutrons produced in muon-neutrino charged current interactions. The method is validated using a small subset of MicroBooNE’s total dataset. The selection yields a sample with 60 % of selected tracks corresponding to neutron-induced secondary protons. At this purity, the integrated efficiency is 8.4% for neutrons that produce a detectable proton.

Background:Hyperbilirubinaemia is a common complication of sepsis. Elevated bilirubin may induce inflammation and apoptosis. It was hypothesised that increased serum bilirubin on Intensive Care Unit (ICU) admission contributes to sepsis-related acute respiratory distress syndrome (ARDS).Methods:Serum bilirubin on ICU admission was measured in 1006 patients with sepsis. Serial serum bilirubin was analysed prospectively in patients with sepsis who had ARDS for a period of 28 days. The effects of clinical factors and variants of the UGT1A1 gene on serum bilirubin levels were determined. Outcomes were ARDS risk and mortality.Results:During 60-day follow-up, 326 patients with sepsis developed ARDS, of whom 144 died from ARDS. The hyperbilirubinaemia (⩾2.0 mg/dl) rate in patients with ARDS (22.4%) was higher than in those without ARDS (14.1%, p = 0.002). For each 1.0 mg/dl increase in admission bilirubin, ARDS risk and 28- and 60-day ARDS mortalities were increased by 7% (OR = 1.07; p = 0.003), 20% (OR = 1.20; p = 0.002) and 18% (OR = 1.18; p = 0.004), respectively. Compared with subjects with bilirubin levels <2.0 mg/dl, patients with hyperbilirubinaemia had higher risks of ARDS (OR = 2.12; p = 0.0007) and 28-day (OR = 2.24; p = 0.020) and 60-day ARDS mortalities (OR = 2.09; p = 0.020). In sepsis-related ARDS, serial bilirubin levels in non-survivors were consistently higher than in survivors (p<0.0001). Clinical variables explained 29.5% of the interindividual variation in bilirubin levels, whereas genetic variants of UGT1A1 contributed 7.5%.Conclusion:In sepsis, a higher serum bilirubin level on ICU admission is associated with subsequent ARDS development and mortality.

Cosmic ray (CR) interactions can be a challenging source of background for neutrino oscillation and cross-section measurements in surface detectors. We present methods for CR rejection in measurements of charged-current quasielastic-like (CCQE-like) neutrino interactions, with a muon and a proton in the final state, measured using liquid argon time projection chambers (LArTPCs). Using a sample of cosmic data collected with the MicroBooNE detector, mixed with simulated neutrino scattering events, a set of event selection criteria is developed that produces an event sample with minimal contribution from CR background. Depending on the selection criteria used a purity between 50 and 80% can be achieved with a signal selection efficiency between 50 and 25%, with higher purity coming at the expense of lower efficiency. While using a specific dataset and selection criteria values optimized for the MicroBooNE detector, the concepts presented here are generic and can be adapted for various studies of exclusive \\[\\nu _{\\mu }\\] CCQE interactions in LArTPCs.

Purpose>This case study highlights state-logic influence on hybrid organizations and institutionally complex environments through acts of regulation (and deregulation).Design/methodology/approach>This study presents a 30-year narrative case focused on the significant social achievements of the Bonneville Power Administration within the Northwest United States. It combines the analysis of historical documentation, annual reports issued by the organization and interviews with firm management to observe the wax and wane of regulatory influence through time.Findings>The presented case suggests two ways regulation projects state-logic influence onto hybrid organizations. First, it imposes a “floor” level of baseline social activity that must be met despite pressure from market logic stakeholders. Second, it imposes formal administrative procedures that require interaction with, and often approval from, key social stakeholders. Administrative procedures provide a series of public forums used to promote additional social resource allocation in excess of baseline regulatory mandates.Research limitations/implications>A narrative case covering a 30-year period will by necessity have to prioritize breadth of analysis over depth. This is a limitation of the analysis presented, but it also provides an opportunity to observe the oscillating impact of state and market-logic influence through time.Originality/value>The study findings have several implications for the growing accounting literature on institutional complexity and hybrid organization. First, the authors highlight the ways regulation shapes institutionally complex spaces and, as a result, the hybrid organizations formed within those environments. Second, the exogenous nature of regulatory mandates indicate hybrid firms could emerge as both a voluntary and an involuntary adaptation to institutionally complex environments. Finally, this study highlights opportunities to further one’s understanding how state logics influence hybrid organizations through the study of state-owned enterprises (SOEs).

The ProtoDUNE-SP is a single-phase liquid argon time projection chamber (LArTPC) prototype for the Deep Underground Neutrino Experiment (DUNE). Signals from 15,360 electronic channels are received by 60 Reconfigurable Cluster Elements (RCEs), which are processing elements designed at SLAC for a wide range of applications and are based upon the “system-onchip” Xilinx Zynq family of FPGAs. The RCEs are housed in industry-standard ATCA shelves on a custom blade, called the Cluster on Board (COB). The RCE platform and its processing functions for the ProtoDUNE-SP will be presented.

The sensitivity of the Deep Underground Neutrino Experiment (DUNE) to neutrino oscillation is determined, based on a full simulation, reconstruction, and event selection of the far detector and a full simulation and parameterized analysis of the near detector. Detailed uncertainties due to the flux prediction, neutrino interaction model, and detector effects are included. DUNE will resolve the neutrino mass ordering to a precision of 5 σ , for all δ CP values, after 2 years of running with the nominal detector design and beam configuration. It has the potential to observe charge-parity violation in the neutrino sector to a precision of 3 σ (5 σ ) after an exposure of 5 (10) years, for 50% of all δ CP values. It will also make precise measurements of other parameters governing long-baseline neutrino oscillation, and after an exposure of 15 years will achieve a similar sensitivity to sin 2 2 θ 13 to current reactor experiments.

We have solved the crystal structure of the Holliday junction resolving enzyme T7 endonuclease I at 2.1 Å resolution using the multiwavelength anomalous dispersion (MAD) technique. Endonuclease I exhibits strong structural specificity for four-way DNA junctions. The structure shows that it forms a symmetric homodimer arranged in two well-separated domains. Each domain, however, is composed of elements from both subunits, and amino acid side chains from both protomers contribute to the active site. While no significant structural similarity could be detected with any other junction resolving enzyme, the active site is similar to that found in several restriction endonucleases. T7 endonuclease I therefore represents the first crystal structure of a junction resolving enzyme that is a member of the nuclease superfamily of enzymes.