A Visual Modeling Method for Spatiotemporal and Multidimensional Features in Epidemiological Analysis: Applied COVID-19 Aggregated Datasets

The visual modeling method enables flexible interactions with rich graphical depictions of data and supports the exploration of the complexities of epidemiological analysis. However, most epidemiology visualizations do not support the combined analysis of objective factors that might influence the transmission situation, resulting in a lack of quantitative and qualitative evidence. To address this issue, we have developed a portrait-based visual modeling method called +msRNAer. This method considers the spatiotemporal features of virus transmission patterns and the multidimensional features of objective risk factors in communities, enabling portrait-based exploration and comparison in epidemiological analysis. We applied +msRNAer to aggregate COVID-19-related datasets in New South Wales, Australia, which combined COVID-19 case number trends, geo-information, intervention events, and expert-supervised risk factors extracted from LGA-based censuses. We perfected the +msRNAer workflow with collaborative views and evaluated its feasibility, effectiveness, and usefulness through one user study and three subject-driven case studies. Positive feedback from experts indicates that +msRNAer provides a general understanding of analyzing comprehension that not only compares relationships between cases in time-varying and risk factors through portraits but also supports navigation in fundamental geographical, timeline, and other factor comparisons. By adopting interactions, experts discovered functional and practical implications for potential patterns of long-standing community factors against the vulnerability faced by the pandemic. Experts confirmed that +msRNAer is expected to deliver visual modeling benefits with spatiotemporal and multidimensional features in other epidemiological analysis scenarios

Giant mesoscopic spin Hall effect on surface of topological insulator

We study mesoscopic spin Hall effect on the surface of topological insulator with a step-function potential. The giant spin polarization induced by a transverse electric current is derived analytically by using McMillan method in the ballistic transport limit, which oscillates across the potential boundary with no confinement from the potential barrier due to the Klein paradox, and should be observable in spin resolved scanning tunneling microscope.Comment: 5 pages, 3 figure

Investigation of Boundary Effects on the Natural Cavitating Flow around a 2D Wedge in Shallow Water

When a cavitated body moves in shallow water, both flexible free surface and rigid bottom wall will produce great influence on the cavity pattern and hydrodynamics to change the motion attitude and stability of the body. In this paper, a single-fluid multiphase flow method coupled with a natural cavitation model was employed to study the effects of two kinds of boundaries on the natural cavitating flow around a two-dimensional symmetry wedge in shallow water. Within the range of the cavitation number for computation (0.05 ~ 2.04), the cavity pattern would be divided into three types, namely, stable type, transition type and wake-vortex type. The shape of the free surface is fairly similar to that of the cavity's upper surface with well right-and-left symmetry. However, when the immersion depth and the cavitation number are decreasing, the symmetry of the cavity shape is destroyed due to the influence of bottom wall effects. When the cavitation number is less than about 0.1, with the immersion depth going down, free surface effects exerts a stronger influence on the drag coefficient of this 2D wedge, whereas wall effects bring a stronger influence on the lift coefficient