225 research outputs found

    Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

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    Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization

    Vibrational spectra and structures of bare and Xe-tagged cationic Si<sub>n</sub>O<sub>m</sub><sup>+</sup> clusters

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    Vibrational spectra of Xe-tagged cationic silicon oxide clusters SinOm+ with n = 3–5 and m = n, n ± 1 in the gas phase are obtained by resonant infrared multiple photon dissociation (IRMPD) spectroscopy and density functional theory calculations. The SinOm+ clusters are produced in a laser vaporization ion source and Xe complexes are formed after thermalization to 100 K. The clusters are subsequently irradiated with tunable light from an IR free electron laser and changes in the mass distribution yield size-specific IR spectra. The measured IRMPD spectra are compared to calculated linear IR absorption spectra leading to structural assignments. For several clusters, Xe complexation alters the energetic order of the SinOm+ isomers. Common structural motifs include the Si2O2 rhombus, the Si3O2 pentagon, and the Si3O3 hexagon

    De detectie van een laag prevalente infectie in het kader van een surveillance systeem

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    Adviezen en opmerkingen voor het project: 'validatie van serologische testen met het doel om de surveillance op Trichinella in Nederlandse slachtvarkens te optimaliseren

    Microsecond Isomer at the N=20 Island of Shape Inversion Observed at FRIB

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    Excited-state spectroscopy from the first Facility for Rare Isotope Beams (FRIB) experiment is reported. A 24(2)-ÎŒ\mus isomer was observed with the FRIB Decay Station initiator (FDSi) through a cascade of 224- and 401-keV Îł\gamma rays in coincidence with 32Na^{32}\textrm{Na} nuclei. This is the only known microsecond isomer (1 Όs≀T1/2<1 ms1{\text{ }\mu\text{s}}\leq T_{1/2} < 1\text{ ms}) in the region. This nucleus is at the heart of the N=20N=20 island of shape inversion and is at the crossroads of spherical shell-model, deformed shell-model, and ab initio theories. It can be represented as the coupling of a proton hole and neutron particle to 32Mg^{32}\textrm{Mg}, 32Mg+π−1+Îœ+1^{32}\textrm{Mg}+\pi^{-1} + \nu^{+1}. This odd-odd coupling and isomer formation provides a sensitive measure of the underlying shape degrees of freedom of 32Mg^{32}\textrm{Mg}, where the onset of spherical-to-deformed shape inversion begins with a low-lying deformed 2+2^+ state at 885 keV and a low-lying shape-coexisting 02+0_2^+ state at 1058 keV. We suggest two possible explanations for the 625-keV isomer in 32^{32}Na: a 6−6^- spherical shape isomer that decays by E2E2 or a 0+0^+ deformed spin isomer that decays by M2M2. The present results and calculations are most consistent with the latter, indicating that the low-lying states are dominated by deformation.Comment: 7 pages, 5 figures, accepted by Physical Review Letter

    Prospect Theory and Hedging Risks

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    The prospect theory is one of the most popular decision-making theories. It is based on the S-shaped utility function, unlike the von Neumann and Morgenstern (NM) theory, which is based on the concave utility function. The S-shape brings in mathematical challenges: simple extensions and generalizations of NM theory into the prospect theory cannot be frequently achieved. For example, the nature of monotonicity of the indifference curve depends on the underlying mean. Price hedging decisions also become more complex within the prospect theory. We discuss these topics in detail and offer a general result concerning the sign of a covariance from which we then infer desired properties of the indifference curve and also justify hedging decisions within the prospect theory. We illustrate our general considerations with a thoroughly worked out example
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