9 research outputs found
Depth resolved snapshot energy-dispersive X-ray diffraction using a conical shell beam
We demonstrate a novel imaging architecture to collect range encoded diffraction patterns from overlapping samples in a single conical shell projection. The patterns were measured in the dark area encompassed by the beam via a centrally positioned aperture optically coupled to a pixelated energy-resolving detector. We show that a single exposure measurement of 0.3 mAs enables d-spacing values to be calculated. The axial positions of the samples were not required and the resultant measurements were robust in the presence of crystallographic textures. Our results demonstrate rapid volumetric materials characterization and the potential for a direct imaging method, which is of great relevance to applications in medicine, non-destructive testing and security screening
The Vulnverability Cube: A Multi-Dimensional Framework for Assessing Relative Vulnerability
The diversity and abundance of information available for vulnerability assessments can present a challenge to decision-makers. Here we propose a framework to aggregate and present socioeconomic and environmental data in a visual vulnerability assessment that will help prioritize management options for communities vulnerable to environmental change. Socioeconomic and environmental data are aggregated into distinct categorical indices across three dimensions and arranged in a cube, so that individual communities can be plotted in a three-dimensional space to assess the type and relative magnitude of the communitiesâ vulnerabilities based on their position in the cube. We present an example assessment using a subset of the USEPA National Estuary Program (NEP) estuaries: coastal communities vulnerable to the effects of environmental change on ecosystem health and water quality. Using three categorical indices created from a pool of publicly available data (socioeconomic index, land use index, estuary condition index), the estuaries were ranked based on their normalized averaged scores and then plotted along the three axes to form a vulnerability cube. The position of each community within the three-dimensional space communicates both the types of vulnerability endemic to each estuary and allows for the clustering of estuaries with like-vulnerabilities to be classified into typologies. The typologies highlight specific vulnerability descriptions that may be helpful in creating specific management strategies. The data used to create the categorical indices are flexible depending on the goals of the decision makers, as different data should be chosen based on availability or importance to the system. Therefore, the analysis can be tailored to specific types of communities, allowing a data rich process to inform decision-making