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Airborne ultrasonic ranging is used in a variety of different engineering applications for which other positional metrology techniques cannot be used, for example in closed-cell locations, when optical line of sight is limited, and when multipath effects preclude electromagnetic-based wireless systems. Although subject to fundamental physical limitations, e.g., because of the temperature dependence of acoustic velocity in air, these acoustic techniques often provide a cost-effective solution for applications in mobile robotics, structural inspection, and biomedical imaging. In this article, the different techniques and limitations of a range of airborne ultrasonic ranging approaches are reviewed, with an emphasis on the accuracy and repeatability of the measurements. Simple time-domain approaches are compared with their frequency-domain equivalents, and the use of hybrid models and biologically inspired approaches are discussed.

Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

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