Statistical methods for polyhedral shape classification with incomplete data - application to cryo-electron tomographic images

A certain type of bacterial inclusion, known as a bacterial microcompartment, was recently identified and imaged through cryo-electron tomography. A reconstructed 3D object from single-axis limited angle tilt-series cryo-electron tomography contains missing regions and this problem is known as the missing wedge problem. Due to missing regions on the reconstructed images, analyzing their 3D structures is a challenging problem. The existing methods overcome this problem by aligning and averaging several similar shaped objects. These schemes work well if the objects are symmetric and several objects with almost similar shapes and sizes are available. Since the bacterial inclusions studied here are not symmetric, are deformed, and show a wide range of shapes and sizes, the existing approaches are not appropriate. This research develops new statistical methods for analyzing geometric properties, such as volume, symmetry, aspect ratio, polyhedral structures etc., of these bacterial inclusions in presence of missing data. These methods work with deformed and non-symmetric varied shaped objects and do not necessitate multiple objects for handling the missing wedge problem. The developed methods and contributions include: (a) an improved method for manual image segmentation, (b) a new approach to 'complete' the segmented and reconstructed incomplete 3D images, (c) a polyhedral structural distance model to predict the polyhedral shapes of these microstructures, (d) a new shape descriptor for polyhedral shapes, named as polyhedron profile statistic, and (e) the Bayes classifier, linear discriminant analysis and support vector machine based classifiers for supervised incomplete polyhedral shape classification. Finally, the predicted 3D shapes for these bacterial microstructures belong to the Johnson solids family, and these shapes along with their other geometric properties are important for better understanding of their chemical and biological characteristics.

The transition movement and food sovereignty: from local resilience to global engagement in food system transformation

The emergence of grassroots social movements variously preoccupied with a range of external threats, such as diminishing supplies of fossil energy or climate change, has led to increased interest in the production of local food. Drawing upon the notion of cognitive praxis, this article utilises transition as a trajectory guided by an overarching cosmology that brings together a broad social movement seeking a more resilient future. This ‘grand narrative’ is reinforced by ‘transition movement intellectuals’ who serve to shape an agenda of local preparedness in the face of uncertainty, rather than structural analysis of the global system. In this context, growing and producing food offers important multi-functional synergies by reconnecting people to place and its ecological endowments and serves to provide a vital element in civic mobilisation. Yet, local food could also become a means to build international solidarity in defence of food sovereignty and establish a global coalition opposed to the corporate agri-food agenda of biotechnologies, land grabbing and nutritional impoverishment.