2,362 research outputs found

    Mind the gap: Patterns of red blood cell product usage in South Africa, 2014 - 2019

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    Background. A key component of any successful healthcare system is the availability of sufficient, safe blood products delivered in an equitable manner. South Africa (SA) has a two-tiered healthcare system with public and privately funded sectors. Blood utilisation data for both sectors are lacking. Evaluation of blood utilisation patterns in each healthcare sector will enable implementation of systems to bring about more equality.Objectives. To conduct a critical evaluation of red blood cell (RBC) product utilisation patterns at the South African National Blood Service (SANBS).Methods. Operationally collected data from RBC requests submitted to SANBS blood banks for the period 1 January 2014 - 31 March 2019 were used to determine temporal RBC product utilisation patterns by healthcare sector. Demographic patterns were determined, and per capita RBC utilisation trends calculated.Results. Of the 2 356 441 transfusion events, 65.9% occurred in the public and 34.1% in the private sector. Public sector patients were younger (median (interquartile range (IQR)) 33 (22 - 49) years) than in the private sector (median (IQR) 54 (37 - 68) years), and mainly female in both sectors (66.2% in the public sector and 53.4% in the private sector). Between 2014 and 2018, per capita RBC utilisation decreased from 11.9 to 11.0/1 000 population in the public sector, but increased from 34.8 to 38.2/1 000 population in the private sector.Conclusions. We confirmed distinctly different RBC utilisation patterns between the healthcare sectors in SA. Possible drivers for these differences may be healthcare access, differing patient populations and prescriber habits. Better understanding of these drivers may help inform equitable public health policy

    Boundary Condition Study for the Juncture Flow Experiment in the NASA Langley 14x22-Foot Subsonic Wind Tunnel

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    Because future wind tunnel tests associated with the NASA Juncture Flow project are being designed for the purpose of CFD validation, considerable effort is going into the characterization of the wind tunnel boundary conditions, particularly at inflow. This is important not only because wind tunnel flowfield nonuniformities can play a role in integrated testing uncertainties, but also because the better the boundary conditions are known, the better CFD can accurately represent the experiment. This paper describes recent investigative wind tunnel tests involving two methods to measure and characterize the oncoming flow in the NASA Langley 14- by 22-Foot Subsonic Tunnel. The features of each method, as well as some of their pros and cons, are highlighted. Boundary conditions and modeling tactics currently used by CFD for empty-tunnel simulations are also described, and some results using three different CFD codes are shown. Preliminary CFD parametric studies associated with the Juncture Flow model are summarized, to determine sensitivities of the flow near the wing-body juncture region of the model to a variety of modeling decisions

    Automated Grid Refinement Using Feature Detection

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    Ecological equivalence: a realistic assumption for niche theory as a testable alternative to neutral theory

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    Hubbell's 2001 neutral theory unifies biodiversity and biogeography by modelling steady-state distributions of species richness and abundances across spatio-temporal scales. Accurate predictions have issued from its core premise that all species have identical vital rates. Yet no ecologist believes that species are identical in reality. Here I explain this paradox in terms of the ecological equivalence that species must achieve at their coexistence equilibrium, defined by zero net fitness for all regardless of intrinsic differences between them. I show that the distinction of realised from intrinsic vital rates is crucial to evaluating community resilience. An analysis of competitive interactions reveals how zero-sum patterns of abundance emerge for species with contrasting life-history traits as for identical species. I develop a stochastic model to simulate community assembly from a random drift of invasions sustaining the dynamics of recruitment following deaths and extinctions. Species are allocated identical intrinsic vital rates for neutral dynamics, or random intrinsic vital rates and competitive abilities for niche dynamics either on a continuous scale or between dominant-fugitive extremes. Resulting communities have steady-state distributions of the same type for more or less extremely differentiated species as for identical species. All produce negatively skewed log-normal distributions of species abundance, zero-sum relationships of total abundance to area, and Arrhenius relationships of species to area. Intrinsically identical species nevertheless support fewer total individuals, because their densities impact as strongly on each other as on themselves. Truly neutral communities have measurably lower abundance/area and higher species/abundance ratios. Neutral scenarios can be parameterized as null hypotheses for testing competitive release, which is a sure signal of niche dynamics. Ignoring the true strength of interactions between and within species risks a substantial misrepresentation of community resilience to habitat los

    Gregariousness Does Not Vary with Geography, Developmental Stage, or Group Relatedness in Feeding Redheaded Pine Sawfly Larvae

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    Aggregations are widespread across the animal kingdom, yet the underlying proximate and ultimate causes are still largely unknown. An ideal system to investigate this simple, social behavior is the pine sawfly genus Neodiprion, which is experimentally tractable and exhibits interspecific variation in larval gregariousness. To assess intraspecific variation in this trait, we characterized aggregative tendency within a single widespread species, the redheaded pine sawfly (N. lecontei). To do so, we developed a quantitative assay in which we measured interindividual distances over a 90-min video. This assay revealed minimal behavioral differences: (1) between early-feeding and late-feeding larval instars, (2) among larvae derived from different latitudes, and (3) between groups composed of kin and those composed of nonkin. Together, these results suggest that, during the larval feeding period, the benefits individuals derive from aggregating outweigh the costs and that this cost-to-benefit ratio does not vary dramatically across space (geography) or ontogeny (developmental stage). In contrast to the feeding larvae, our assay revealed a striking reduction in gregariousness following the final larval molt in N. lecontei. We also found some intriguing interspecific variation: While N. lecontei and N. maurus feeding larvae exhibit significant aggregative tendencies, feeding N. compar larvae do not aggregate at all. These results set the stage for future work investigating the proximate and ultimate mechanisms underlying developmental and interspecific variation in larval gregariousness across Neodiprion

    Determination of muon momentum in the MicroBooNE LArTPC using an improved model of multiple Coulomb scattering

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    We discuss a technique for measuring a charged particle's momentum by means of multiple Coulomb scattering (MCS) in the MicroBooNE liquid argon time projection chamber (LArTPC). This method does not require the full particle ionization track to be contained inside of the detector volume as other track momentum reconstruction methods do (range-based momentum reconstruction and calorimetric momentum reconstruction). We motivate use of this technique, describe a tuning of the underlying phenomenological formula, quantify its performance on fully contained beam-neutrino-induced muon tracks both in simulation and in data, and quantify its performance on exiting muon tracks in simulation. Using simulation, we have shown that the standard Highland formula should be re-tuned specifically for scattering in liquid argon, which significantly improves the bias and resolution of the momentum measurement. With the tuned formula, we find agreement between data and simulation for contained tracks, with a small bias in the momentum reconstruction and with resolutions that vary as a function of track length, improving from about 10% for the shortest (one meter long) tracks to 5% for longer (several meter) tracks. For simulated exiting muons with at least one meter of track contained, we find a similarly small bias, and a resolution which is less than 15% for muons with momentum below 2 GeV/c. Above 2 GeV/c, results are given as a first estimate of the MCS momentum measurement capabilities of MicroBooNE for high momentum exiting tracks

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

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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.Comment: Preprint to be submitted to The European Physical Journal

    Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

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    We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level

    How to make epidemiological training infectious

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    CITATION: Bellan, S. E. et al. 2012. How to make epidemiological training infectious. PLoS Biology, 10(4): e1001295, doi:10.1371/journal.pbio.1001295.The original publication is available at http://journals.plos.org/plosbiologyModern infectious disease epidemiology builds on two independently developed fields: classical epidemiology and dynamical epidemiology. Over the past decade, integration of the two fields has increased in research practice, but training options within the fields remain distinct with few opportunities for integration in the classroom. The annual Clinic on the Meaningful Modeling of Epidemiological Data (MMED) at the African Institute for Mathematical Sciences has begun to address this gap. MMED offers participants exposure to a broad range of concepts and techniques from both epidemiological traditions. During MMED 2010 we developed a pedagogical approach that bridges the traditional distinction between classical and dynamical epidemiology and can be used at multiple educational levels, from high school to graduate level courses. The approach is hands-on, consisting of a real-time simulation of a stochastic outbreak in course participants, including realistic data reporting, followed by a variety of mathematical and statistical analyses, stemming from both epidemiological traditions. During the exercise, dynamical epidemiologists developed empirical skills such as study design and learned concepts of bias while classical epidemiologists were trained in systems thinking and began to understand epidemics as dynamic nonlinear processes. We believe this type of integrated educational tool will prove extremely valuable in the training of future infectious disease epidemiologists. We also believe that such interdisciplinary training will be critical for local capacity building in analytical epidemiology as Africa continues to produce new cohorts of well-trained mathematicians, statisticians, and scientists. And because the lessons draw on skills and concepts from many fields in biology—from pathogen biology, evolutionary dynamics of host–pathogen interactions, and the ecology of infectious disease to bioinformatics, computational biology, and statistics—this exercise can be incorporated into a broad array of life sciences courses.http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001295Publisher's versio
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