School of Mathematics and Statistics - Research Publications

Permanent URI for this collection

Search Results

Now showing 1 - 3 of 3
  • Item
    No Preview Available
    The effect of object-scene associations upon representational similarity dissociates structured from image-based representations
    Bracci, S ; Mraz, J ; Zeman, A ; Leys, G ; Op de Beeck, H (Association for Research in Vision and Ophthalmology (ARVO), 2021-09-27)
  • Item
    Thumbnail Image
    Dynamics of undeforming regions in the lead up to failure: jumping scales from lab to field
    Tordesillas, A ; Zhou, S ; Campbell, L ; Bellett, P ; Aguirre, MA ; Luding, S ; Pugnaloni, LA ; Soto, R (EDP Sciences, 2021)
    Knowledge transfer from micromechanics of granular media failure to geohazard forecasting and mitigation has been slow. But in the face of a rapidly expanding data infrastructure on the motion of individual grains for laboratory samples – and ground motion data at the field scale – opportunities to accelerate this knowledge transfer are emerging. In particular, such data assets coupled with data-driven approaches enable ‘new eyes’ to re-examine granular failure. To this end, effective strategies that can jump scales from bench to field are urgently needed. Here we demonstrate one strategy that focusses on the study of deformation patterns in the precursory failure regime using kinematic data. Unlike previous studies which focus on regions of high strains, here we probe the development and evolution of near-undeforming regions through the lens of explosive percolation. We find a common dynamical signature in which undeforming regions, which are initially transient in the precursory failure regime, become persistent from the time of imminent failure. We demonstrate the robustness of these findings for data on individual grain motions in a classical laboratory test and ground motion in two real landslides at vastly different scales.
  • Item
    Thumbnail Image
    A TOOLKIT FOR THE QUANTITATIVE ANALYSIS OF THE SPATIAL DISTRIBUTION OF CELLS OF THE TUMOR IMMUNE MICROENVIRONMENT
    Trigos, A ; Yang, T ; Feng, Y ; Ozcoban, V ; Doyle, M ; Pasam, A ; Kocovski, N ; Pizzolla, A ; Huang, Y-K ; Bass, G ; Keam, S ; Speed, T ; Neeson, P ; Sandhu, S ; Goode, D (BMJ PUBLISHING GROUP, 2020-11-01)