4 resultados para coleman
em Duke University
Indication of electron neutrino appearance from an accelerator-produced off-axis muon neutrino beam.
Resumo:
The T2K experiment observes indications of ν(μ) → ν(e) appearance in data accumulated with 1.43×10(20) protons on target. Six events pass all selection criteria at the far detector. In a three-flavor neutrino oscillation scenario with |Δm(23)(2)| = 2.4×10(-3) eV(2), sin(2)2θ(23) = 1 and sin(2)2θ(13) = 0, the expected number of such events is 1.5±0.3(syst). Under this hypothesis, the probability to observe six or more candidate events is 7×10(-3), equivalent to 2.5σ significance. At 90% C.L., the data are consistent with 0.03(0.04) < sin(2)2θ(13) < 0.28(0.34) for δ(CP) = 0 and a normal (inverted) hierarchy.
Resumo:
The goal of this paper is to improve our understanding of the role of institutional arrangements and ecological factors that facilitate the emergence and sustainability of successful collective action in small-scale fishing social-ecological systems. Using a modified logistic growth function, we simulate how ecological factors (i.e. carrying capacity) affect small-scale fishing communities with varying degrees of institutional development (i.e. timeliness to adopt new institutions and the degree to which harvesting effort is reduced), in their ability to avoid overexploitation. Our results show that strong and timely institutions are necessary but not sufficient to maintain sustainable harvests over time. The sooner communities adopt institutions, and the stronger the institutions they adopt, the more likely they are to sustain the resource stock. Exactly how timely the institutions must be adopted, and by what amount harvesting effort must be diminished, depends on the ecological carrying capacity of the species at the particular location. Small differences in the carrying capacity between fishing sites, even under scenarios of similar institutional development, greatly affects the likelihood of effective collective action. © 2009 Elsevier B.V. All rights reserved.
Resumo:
We propose a novel method to harmonize diffusion MRI data acquired from multiple sites and scanners, which is imperative for joint analysis of the data to significantly increase sample size and statistical power of neuroimaging studies. Our method incorporates the following main novelties: i) we take into account the scanner-dependent spatial variability of the diffusion signal in different parts of the brain; ii) our method is independent of compartmental modeling of diffusion (e.g., tensor, and intra/extra cellular compartments) and the acquired signal itself is corrected for scanner related differences; and iii) inter-subject variability as measured by the coefficient of variation is maintained at each site. We represent the signal in a basis of spherical harmonics and compute several rotation invariant spherical harmonic features to estimate a region and tissue specific linear mapping between the signal from different sites (and scanners). We validate our method on diffusion data acquired from seven different sites (including two GE, three Philips, and two Siemens scanners) on a group of age-matched healthy subjects. Since the extracted rotation invariant spherical harmonic features depend on the accuracy of the brain parcellation provided by Freesurfer, we propose a feature based refinement of the original parcellation such that it better characterizes the anatomy and provides robust linear mappings to harmonize the dMRI data. We demonstrate the efficacy of our method by statistically comparing diffusion measures such as fractional anisotropy, mean diffusivity and generalized fractional anisotropy across multiple sites before and after data harmonization. We also show results using tract-based spatial statistics before and after harmonization for independent validation of the proposed methodology. Our experimental results demonstrate that, for nearly identical acquisition protocol across sites, scanner-specific differences can be accurately removed using the proposed method.