Mycotic aneurysm of the posterior tibial artery – a rare complication of bacterial endocarditis: a case report

<p>Abstract</p> <p>Introduction</p> <p>Distal arterial embolisation and subsequent aneurysm formation are rare occurrences and most are secondary to trauma. We have found no case reports that describe posterior tibial aneurysm formation secondary to bacterial endocarditis.</p> <p>Case presentation</p> <p>We report the case of a 47-year-old Caucasian man who, 2 years after an episode of subacute bacterial endocarditis, presented with signs and symptoms consistent with posterior tibial aneurysm formation.</p> <p>Conclusion</p> <p>Posterior tibial aneurysm formation is a rare occurrence, most commonly occurring after trauma and, although other causes have been described, to our knowledge, endocarditis has not been implicated before, and as such should therefore be borne in mind when dealing with cases where no obvious aetiology is evident.</p

The promotion of local wellbeing: A primer for policymakers

There is growing interest among policymakers in the promotion of wellbeing as an objective of public policy. In particular, local authorities have been given powers to undertake action to promote wellbeing in their area. Recent advances in the academic literature on wellbeing are giving rise to an increasingly detailed picture of the factors that determine people’s subjective wellbeing (how they think and feel about their lives). However, the concept of subjective wellbeing is poorly understood within local government and much of the evidence base is extremely recent. I therefore review the literature on the definition, measurement, and determinants of wellbeing, and discuss some of its implications for local public policy

Experiment Simulation Configurations Used in DUNE CDR

The LBNF/DUNE CDR describes the proposed physics program and experimental design at the conceptual design phase. Volume 2, entitled The Physics Program for DUNE at LBNF, outlines the scientific objectives and describes the physics studies that the DUNE collaboration will perform to address these objectives. The long-baseline physics sensitivity calculations presented in the DUNE CDR rely upon simulation of the neutrino beam line, simulation of neutrino interactions in the far detector, and a parameterized analysis of detector performance and systematic uncertainty. The purpose of this posting is to provide the results of these simulations to the community to facilitate phenomenological studies of long-baseline oscillation at LBNF/DUNE. Additionally, this posting includes GDML of the DUNE single-phase far detector for use in simulations. DUNE welcomes those interested in performing this work as members of the collaboration, but also recognizes the benefit of making these configurations readily available to the wider community.Comment: 9 pages, 4 figures, configurations in ancillary file

Analysing Port Community System Network Evolution

Ports have played an important role in facilitating exchanges among countries since the day when inland transportation was poor. As ports become hubs for global supply chain, they have to maintain their competitiveness not only by reassuring their efficiency, reliability, accessibility to hinterland, and sustainability. In addition, there is a constant challenge from all operational parties of the port to acquire needed information or to trust information received, due to multiple legacy systems and platforms that do not integrate with each other, and to the lack of real time updates. There are differing agendas between parties and, sometimes, distrust within the multi-stakeholder ecosystem leads to working in silos. This jeopardises seamless data exchange and cooperation across the port value chain, resulting in significant inefficiencies. Port community system (PCS) can enhance communication and simplify administrative process resulting economic and environmental benefit for actors in the supply chain. The invisibility of the benefit, actors’ heterogeneity and significant investment to develop the system resulting a reluctance in implementing PCS. This chapter aims to study the evolution mechanism behind the process of PCS network development using lessons learned from industrial symbiosis network development and network trajectories theory. The PCS network development follows a serendipitous and goal-oriented process that can be categorised into three stages: pre-PCS network, PCS network emergence, and PCS network expansion. This chapter contributes to the exploration of network evolution and documents lesson learned to foster PCS implementation.© 2020 Springer. This is a post-peer-review, pre-copyedit version of an article published in European Port Cities in Transition: Moving Towards More Sustainable Sea Transport Hubs. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-36464-9_10fi=vertaisarvioitu|en=peerReviewed

Observation of seasonal variation of atmospheric multiple-muon events in the NOvA Near Detector

Using two years of data from the NOvA Near Detector at Fermilab, we report a seasonal variation of cosmic ray induced multiple-muon (Nμ≥2) event rates which has an opposite phase to the seasonal variation in the atmospheric temperature. The strength of the seasonal multiple-muon variation is shown to increase as a function of the muon multiplicity. However, no significant dependence of the strength of the seasonal variation of the multiple-muon variation is seen as a function of the muon zenith angle, or the spatial or angular separation between the correlated muons

First measurement of neutrino oscillation parameters using neutrinos and antineutrinos by NOvA.

The NOvA experiment has seen a 4.4σ signal of ν[over ¯]_{e} appearance in a 2&nbsp;GeV ν[over ¯]_{μ} beam at a distance of 810&nbsp;km. Using 12.33×10^{20} protons on target delivered to the Fermilab NuMI neutrino beamline, the experiment recorded 27 ν[over ¯]_{μ}→ν[over ¯]_{e} candidates with a background of 10.3 and 102 ν[over ¯]_{μ}→ν[over ¯]_{μ} candidates. This new antineutrino data are combined with neutrino data to measure the parameters |Δm_{32}^{2}|=2.48_{-0.06}^{+0.11}×10^{-3}  eV^{2}/c^{4} and sin^{2}θ_{23} in the ranges from (0.53-0.60) and (0.45-0.48) in the normal neutrino mass hierarchy. The data exclude most values near δ_{CP}=π/2 for the inverted mass hierarchy by more than 3σ and favor the normal neutrino mass hierarchy by 1.9σ and θ_{23} values in the upper octant by 1.6σ

Design and construction of the MicroBooNE Cosmic Ray Tagger system

The MicroBooNE detector utilizes a liquid argon time projection chamber (LArTPC) with an 85 t active mass to study neutrino interactions along the Booster Neutrino Beam (BNB) at Fermilab. With a deployment location near ground level, the detector records many cosmic muon tracks in each beam-related detector trigger that can be misidentified as signals of interest. To reduce these cosmogenic backgrounds, we have designed and constructed a TPC-external Cosmic Ray Tagger (CRT). This sub-system was developed by the Laboratory for High Energy Physics (LHEP), Albert Einstein center for fundamental physics, University of Bern. The system utilizes plastic scintillation modules to provide precise time and position information for TPC-traversing particles. Successful matching of TPC tracks and CRT data will allow us to reduce cosmogenic background and better characterize the light collection system and LArTPC data using cosmic muons. In this paper we describe the design and installation of the MicroBooNE CRT system and provide an overview of a series of tests done to verify the proper operation of the system and its components during installation, commissioning, and physics data-taking

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

A Deep Neural Network for Pixel-Level Electromagnetic Particle Identification in the MicroBooNE Liquid Argon Time Projection Chamber

We have developed a convolutional neural network (CNN) that can make a pixel-level prediction of objects in image data recorded by a liquid argon time projection chamber (LArTPC) for the first time. We describe the network design, training techniques, and software tools developed to train this network. The goal of this work is to develop a complete deep neural network based data reconstruction chain for the MicroBooNE detector. We show the first demonstration of a network's validity on real LArTPC data using MicroBooNE collection plane images. The demonstration is performed for stopping muon and a $\nu_\mu$ charged current neutral pion data samples