67 research outputs found
Twin identification over viewpoint change: A deep convolutional neural network surpasses humans
Deep convolutional neural networks (DCNNs) have achieved human-level accuracy
in face identification (Phillips et al., 2018), though it is unclear how
accurately they discriminate highly-similar faces. Here, humans and a DCNN
performed a challenging face-identity matching task that included identical
twins. Participants (N=87) viewed pairs of face images of three types:
same-identity, general imposter pairs (different identities from similar
demographic groups), and twin imposter pairs (identical twin siblings). The
task was to determine whether the pairs showed the same person or different
people. Identity comparisons were tested in three viewpoint-disparity
conditions: frontal to frontal, frontal to 45-degree profile, and frontal to
90-degree profile. Accuracy for discriminating matched-identity pairs from
twin-imposters and general imposters was assessed in each viewpoint-disparity
condition. Humans were more accurate for general-imposter pairs than
twin-imposter pairs, and accuracy declined with increased viewpoint disparity
between the images in a pair. A DCNN trained for face identification (Ranjan et
al., 2018) was tested on the same image pairs presented to humans. Machine
performance mirrored the pattern of human accuracy, but with performance at or
above all humans in all but one condition. Human and machine similarity scores
were compared across all image-pair types. This item-level analysis showed that
human and machine similarity ratings correlated significantly in six of nine
image-pair types [range r=0.38 to r=0.63], suggesting general accord between
the perception of face similarity by humans and the DCNN. These findings also
contribute to our understanding of DCNN performance for discriminating
high-resemblance faces, demonstrate that the DCNN performs at a level at or
above humans, and suggest a degree of parity between the features used by
humans and the DCNN
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Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.
Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant
Evaluating the effects of SARS-CoV-2 Spike mutation D614G on transmissibility and pathogenicity
SummaryGlobal dispersal and increasing frequency of the SARS-CoV-2 Spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of Spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large data set, well represented by both Spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the Spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant.</jats:p
A Search for Technosignatures Around 31 Sun-like Stars with the Green Bank Telescope at 1.15-1.73 GHz
We conducted a search for technosignatures in April of 2018 and 2019 with the
L-band receiver (1.15-1.73 GHz) of the 100 m diameter Green Bank Telescope.
These observations focused on regions surrounding 31 Sun-like stars near the
plane of the Galaxy. We present the results of our search for narrowband
signals in this data set as well as improvements to our data processing
pipeline. Specifically, we applied an improved candidate signal detection
procedure that relies on the topographic prominence of the signal power, which
nearly doubles the signal detection count of some previously analyzed data
sets. We also improved the direction-of-origin filters that remove most radio
frequency interference (RFI) to ensure that they uniquely link signals observed
in separate scans. We performed a preliminary signal injection and recovery
analysis to test the performance of our pipeline. We found that our pipeline
recovers 93% of the injected signals over the usable frequency range of the
receiver and 98% if we exclude regions with dense RFI. In this analysis, 99.73%
of the recovered signals were correctly classified as technosignature
candidates. Our improved data processing pipeline classified over 99.84% of the
~26 million signals detected in our data as RFI. Of the remaining candidates,
4539 were detected outside of known RFI frequency regions. The remaining
candidates were visually inspected and verified to be of anthropogenic nature.
Our search compares favorably to other recent searches in terms of end-to-end
sensitivity, frequency drift rate coverage, and signal detection count per unit
bandwidth per unit integration time.Comment: 20 pages, 8 figures, in press at the Astronomical Journal (submitted
on Sept. 9, 2020; reviews received Nov. 6; re-submitted Nov. 6; accepted Nov.
17
Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial
Background
Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy
Evaluating the effects of SARS-CoV-2 Spike mutation D614G on transmissibility and pathogenicity
Global dispersal and increasing frequency of the SARS-CoV-2 Spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of Spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large data set, well represented by both Spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the Spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant
Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.
Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant
Genomic assessment of invasion dynamics of SARS-CoV-2 Omicron BA.1
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) now arise in the context of heterogeneous human connectivity and population immunity. Through a large-scale phylodynamic analysis of 115,622 Omicron BA.1 genomes, we identified >6,000 introductions of the antigenically distinct VOC into England and analyzed their local transmission and dispersal history. We find that six of the eight largest English Omicron lineages were already transmitting when Omicron was first reported in southern Africa (22 November 2021). Multiple datasets show that importation of Omicron continued despite subsequent restrictions on travel from southern Africa as a result of export from well-connected secondary locations. Initiation and dispersal of Omicron transmission lineages in England was a two-stage process that can be explained by models of the country’s human geography and hierarchical travel network. Our results enable a comparison of the processes that drive the invasion of Omicron and other VOCs across multiple spatial scales
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