7,002 research outputs found

    The 1979 Southeastern Virginia Urban Plume Study (SEV-UPS): Surface and airborne studies

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    The operation of two surface monitoring stations (one in downtown Norfolk, Virginia, one south of the city near the Great Dismal Swamp) and the collection of 40 hours of airborne measurements is described. Surface site measurements of ozone, oxides of nitrogen, sulfur dioxide, temperature, dew point, b sub seat, and condensation nuclei were made. Instrument calibrations, quality assurance audits, and preliminary data analysis in support of the Urban Plume Study were also made. The air pollution problems that were addressed are discussed. Data handling procedures followed for the surface stations are presented. The operation of the aircraft sampling platform is described. Aircraft sampling procedures are discussed. A preliminary descriptive analysis of the aircraft data is given along with data or plots for surface sites, airborne studies, hydrocarbon species, and instrument performance audits. Several of the aircraft flights clearly show the presence of an urban ozone plume downwind of Norfolk in the direction of the mean wind flow

    In situ sensors for measurements in the global trosposphere

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    Current techniques available for the in situ measurement of ambient trace gas species, particulate composition, and particulate size distribution are reviewed. The operational specifications of the various techniques are described. Most of the techniques described are those that have been used in airborne applications or show promise of being adaptable to airborne applications. Some of the instruments described are specialty items that are not commercially-available. In situ measurement techniques for several meteorological parameters important in the study of the distribution and transport of ambient air pollutants are discussed. Some remote measurement techniques for meteorological parameters are also discussed. State-of-the-art measurement capabilities are compared with a list of capabilities and specifications desired by NASA for ambient measurements in the global troposphere

    Determinants of anemia and hemoglobin concentration in haitian school-aged children

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    Anemia diminishes oxygen transport in the body, resulting in potentially irreversible growth and developmental consequences for children. Limited evidence for determinants of anemia exists for school-aged children. We conducted a cluster randomized controlled trial in Haiti from 2012 to 2013 to test the efficacy of a fortified school snack. Children (N = 1,047) aged 3–13 years were followed longitudinally at three time points for hemoglobin (Hb) concentrations, anthropometry, and bioelectrical impedance measures. Dietary intakes, infectious disease morbidities, and socioeconomic and demographic factors were collected at baseline and endline. Longitudinal regression modeling with generalized least squares and logit models with random effects identified anemia risk factors beyond the intervention effect. At baseline, 70.6% of children were anemic and 2.6% were severely anemic. Stunting increased the odds of developing anemia (adjusted odds ratio [OR]: 1.48, 95% confidence interval [CI]: 1.05–2.08) and severe anemia (adjusted OR: 2.47, 95% CI: 1.30–4.71). Parent-reported vitamin A supplementation and deworming were positively associated with Hb concentrations, whereas fever and poultry ownership showed a negative relationship with Hb concentration and increased odds of severe anemia, respectively. Further research should explore the full spectrum of anemia etiologies in school children, including genetic causes

    HIV Treatment as Prevention: Considerations in the Design, Conduct, and Analysis of Cluster Randomized Controlled Trials of Combination HIV Prevention

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    The rigorous evaluation of the impact of combination HIV prevention packages at the population level will be critical for the future of HIV prevention. In this review, we discuss important considerations for the design and interpretation of cluster randomized controlled trials (C-RCTs) of combination prevention interventions. We focus on three large C-RCTs that will start soon and are designed to test the hypothesis that combination prevention packages, including expanded access to antiretroviral therapy, can substantially reduce HIV incidence. Using a general framework to integrate mathematical modelling analysis into the design, conduct, and analysis of C-RCTs will complement traditional statistical analyses and strengthen the evaluation of the interventions. Importantly, even with combination interventions, it may be challenging to substantially reduce HIV incidence over the 2- to 3-y duration of a C-RCT, unless interventions are scaled up rapidly and key populations are reached. Thus, we propose the innovative use of mathematical modelling to conduct interim analyses, when interim HIV incidence data are not available, to allow the ongoing trials to be modified or adapted to reduce the likelihood of inconclusive outcomes. The preplanned, interactive use of mathematical models during C-RCTs will also provide a valuable opportunity to validate and refine model projections

    An Optical Study of BG Geminorum: An Ellipsoidal Binary with an Unseen Primar Star

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    We describe optical photometric and spectroscopic observations of the bright variable BG Geminorum. Optical photometry shows a pronounced ellipsoidal variation of the K0 I secondary, with amplitudes of ~0.5 mag at VRI and a period of 91.645 days. A deep primary eclipse is visible for wavelengths < 4400A; a shallower secondary eclipse is present at longer wavelengths. Eclipse timings and the radial velocity curve of the K0 secondary star indicate an interacting binary where a lobe-filling secondary, M_2 ~ 0.5 Msun, transfers material into a extended disk around a massive primary, M_1 ~ 4.5 Msun. The primary star is either an early B-type star or a black hole. If it did contain a black hole, BG Gem would be the longest period black hole binary known by a factor of 10, as well as the only eclipsing black hole binary system.Comment: 27 pages, includes 8 figures and 5 tables, accepted to A

    Sovereign debt restructuring : the judge, the vultures and creditor rights

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    What role did the US courts play in the Argentine debt swap of 2005? What implications does this have for the future of creditor rights in sovereign bond markets? The judge in the Argentine case has, it appears, deftly exploited creditor heterogeneity – between holdouts seeking capital gains and institutional investors wanting a settlement – to promote a swap with a supermajority of creditors. Our analysis of Argentine debt litigation reveals a ‘judge-mediated’ sovereign debt restructuring, which resolves the key issues of Transition and Aggregation - two of the tasks envisaged for the IMF’s still-born Sovereign Debt Restructuring Mechanism. For the future, we discuss how judge-mediated sovereign debt restructuring (together with creditor committees) could complement the alternative promoted by the US Treasury, namely collective action clauses in sovereign bond contracts

    Integrated waveguides and deterministically positioned nitrogen vacancy centers in diamond created by femtosecond laser writing

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    Diamond's nitrogen vacancy (NV) center is an optically active defect with long spin coherence times, showing great potential for both efficient nanoscale magnetometry and quantum information processing schemes. Recently, both the formation of buried 3D optical waveguides and high quality single NVs in diamond were demonstrated using the versatile femtosecond laser-writing technique. However, until now, combining these technologies has been an outstanding challenge. In this work, we fabricate laser written photonic waveguides in quantum grade diamond which are aligned to within micron resolution to single laser-written NVs, enabling an integrated platform providing deterministically positioned waveguide-coupled NVs. This fabrication technology opens the way towards on-chip optical routing of single photons between NVs and optically integrated spin-based sensing

    Expert-Augmented Machine Learning

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    Machine Learning is proving invaluable across disciplines. However, its success is often limited by the quality and quantity of available data, while its adoption by the level of trust that models afford users. Human vs. machine performance is commonly compared empirically to decide whether a certain task should be performed by a computer or an expert. In reality, the optimal learning strategy may involve combining the complementary strengths of man and machine. Here we present Expert-Augmented Machine Learning (EAML), an automated method that guides the extraction of expert knowledge and its integration into machine-learned models. We use a large dataset of intensive care patient data to predict mortality and show that we can extract expert knowledge using an online platform, help reveal hidden confounders, improve generalizability on a different population and learn using less data. EAML presents a novel framework for high performance and dependable machine learning in critical applications
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