A scalable mass customisation design process for 3D-printed respirator mask to combat COVID-19

Purpose A three-dimensional (3D) printed custom-fit respirator mask has been proposed as a promising solution to alleviate mask-related injuries and supply shortages during COVID-19. However, creating a custom-fit computer-aided design (CAD) model for each mask is currently a manual process and thereby not scalable for a pandemic crisis. This paper aims to develop a novel design process to reduce overall design cost and time, thus enabling the mass customisation of 3D printed respirator masks. Design/methodology/approach Four data acquisition methods were used to collect 3D facial data from five volunteers. Geometric accuracy, equipment cost and acquisition time of each method were evaluated to identify the most suitable acquisition method for a pandemic crisis. Subsequently, a novel three-step design process was developed and scripted to generate respirator mask CAD models for each volunteer. Computational time was evaluated and geometric accuracy of the masks was evaluated via one-sided Hausdorff distance. Findings Respirator masks were successfully generated from all meshes, taking <2 min/mask for meshes of 50,000∼100,000 vertices and <4 min for meshes of ∼500,000 vertices. The average geometric accuracy of the mask ranged from 0.3 mm to 1.35 mm, depending on the acquisition method. The average geometric accuracy of mesh obtained from different acquisition methods ranged from 0.56 mm to 1.35 mm. A smartphone with a depth sensor was found to be the most appropriate acquisition method. Originality/value A novel and scalable mass customisation design process was presented, which can automatically generate CAD models of custom-fit respirator masks in a few minutes from a raw 3D facial mesh. Four acquisition methods, including the use of a statistical shape model, a smartphone with a depth sensor, a light stage and a structured light scanner were compared; one method was recommended for use in a pandemic crisis considering equipment cost, acquisition time and geometric accuracy

Biopolitics meets Terrapolitics: Political Ontologies and Governance in Settler-Colonial Australia

Crises persist in Australian Indigenous affairs because current policy approaches do not address the intersection of Indigenous and European political worlds. This paper responds to this challenge by providing a heuristic device for delineating Settler and Indigenous Australian political ontologies and considering their interaction. It first evokes Settler and Aboriginal ontologies as respectively biopolitical (focused through life) and terrapolitical (focused through land). These ideal types help to identify important differences that inform current governance challenges. The paper discusses the entwinement of these traditions as a story of biopolitical dominance wherein Aboriginal people are governed as an “included-exclusion” within the Australian political community. Despite the overall pattern of dominance, this same entwinement offers possibilities for exchange between biopolitics and terrapolitics, and hence for breaking the recurrent crises of Indigenous affairs

Variational prototype learning for deep face recognition

Deep face recognition has achieved remarkable improvements due to the introduction of margin-based softmax loss, in which the prototype stored in the last linear layer represents the center of each class. In these methods, training samples are enforced to be close to positive prototypes and far apart from negative prototypes by a clear margin. However, we argue that prototype learning only employs sample-to-prototype comparisons without considering sample-to-sample comparisons during training and the low loss value gives us an illusion of perfect feature embedding, impeding the further exploration of SGD. To this end, we propose Variational Prototype Learning (VPL), which represents every class as a distribution instead of a point in the latent space. By identifying the slow feature drift phenomenon, we directly inject memorized features into prototypes to approximate variational prototype sampling. The proposed VPL can simulate sample-to-sample comparisons within the classification framework, encouraging the SGD solver to be more exploratory, while boosting performance. Moreover, VPL is conceptually simple, easy to implement, computationally efficient and memory saving. We present extensive experimental results on popular benchmarks, which demonstrate the superiority of the proposed VPL method over the state-of-the-art competitors

Practical and scalable desktop-based high-quality facial capture

We present a novel desktop-based system for high-quality facial capture including geometry and facial appearance. The proposed acquisition system is highly practical and scalable, consisting purely of commodity components. The setup consists of a set of displays for con- trolled illumination for reflectance capture, in conjunction with multi- view acquisition of facial geometry. We additionally present a novel set of modulated binary illumination patterns for efficient acquisition of re- flectance and photometric normals using our setup, with diffuse-specular separation. We demonstrate high-quality results with two different vari- ants of the capture setup – one entirely consisting of portable mobile devices targeting static facial capture, and the other consisting of desk- top LCD displays targeting both static and dynamic facial capture

Gene expression of 5-, 12-, and 15-lipoxygenases and leukotriene receptors along the rat nephron

The arachidonate signaling pathways comprise prostanoids formed by cyclooxygenases, EETs, and HETEs formed by cytochrome P-450 (CYP) enzymes and HETEs and leukotrienes generated by lipoxygenases. Whereas the intrarenal localization of cyclooxygenases and of some CYP enzymes along the nephron has already been determined, the localization of lipoxygenases and leukotriene-forming enzymes together with leukotriene receptors in the kidney is less clear. This study therefore aimed to determine the expression of 5-, 12-, and 15-lipoxygenases as well as the leukotriene receptors along the rat nephron. The kidneys were dissected into cortex and outer and inner medulla, and the microdissected nephron segments were collected after a collagenase digestion. mRNA abundance was determined by RT-PCR and real-time PCR. 15-LOX mRNA showed a characteristic expression pattern along the distal nephron. 12-LOX mRNA was only found in the glomerulus. Similarly, 5-LOX mRNAs together with 5-LOX-activating protein mRNAs were expressed in the glomerulus and also in the vasa recta. The leukotriene A4 hydrolase was found in all nephron segments, whereas leukotriene C4 synthase mRNA could not be found in any nephron segment. The leukotriene receptor B4 and the cysteinyl leukotriene receptor type 1 were selectively expressed in the glomerulus, whereas cysteinyl receptor type 2 was not found in any nephron segment. Our data suggest that the glomerulus is a major source and target for 5- and 12-HETE and for leukotrienes. The collecting duct system, on the other hand, appears to be a major source of 15-HETE