Forensic facial professionals have been shown in previous studies to identify people from frontal face images more accurately than untrained participants when given 30 s per face pair. We tested whether this superiority holds in more challenging conditions. Two groups of forensic facial professionals (examiners, reviewers) and untrained participants were tested in three lab-based tasks: other-race face identification, disguised face identification, and face memory.
View Article and Find Full Text PDFDeep convolutional neural networks (DCNNs) are remarkably accurate models of human face recognition. However, less is known about whether these models generate face representations similar to those used by humans. Sensitivity to facial configuration has long been considered a marker of human perceptual expertise for faces.
View Article and Find Full Text PDFIn response to the escalating SARS-CoV-2 pandemic, in March 2020 the COVID-19 Genomics UK (COG-UK) consortium was established to enable national-scale genomic surveillance in the UK. By the end of 2020, 49% of all SARS-CoV-2 genome sequences globally had been generated as part of the COG-UK programme, and to date, this system has generated >3 million SARS-CoV-2 genomes. Rapidly and reliably analysing this unprecedented number of genomes was an enormous challenge.
View Article and Find Full Text PDFRecent reports raise concerns on the changing epidemiology of mpox in the Democratic Republic of the Congo (DRC). High-quality genomes were generated for 337 patients from 14/26 provinces to document whether the increase in number of cases is due to zoonotic spillover events or viral evolution, with enrichment of APOBEC3 mutations linked to human adaptation. Our study highlights two patterns of transmission contributing to the source of human cases.
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