An investigation into human response to unmanned aerial vehicle noise

It is predicted that urban air mobility, including the use of small to medium sized unmanned aerial vehicle (UAV) delivery systems, will be introduced into cities across the globe within the next 15 years. It is known, however, that noise is one of the main limiting factors for the wider adoption of these vehicles. Neither the metrics nor the methods used for conventional aircraft seem to be optimal for this novel source of noise. This research will aid in developing suitable psychoacoustic methodologies and metrics, specifically designed to quantify the community noise impact of these vehicles. This paper describes a psychoacoustic experiment used to gather participant responses to UAV sound recordings, performing a variety of different operations at differing distances. Results from this psychoacoustic experiment will be used to correlate perceptions of UAV noise with objective sound quality metrics, and build new regression relationships that could describe the impact of a given UAV on a community, as well as give insight into the key sound quality metrics that contribute to the perceived annoyance. Future extension to the research may include assessing the impact of introducing drone noise to a variety of soundscapes, evaluating the differences in psychoacoustic responses when introducing more accurate reproduction methods, such as virtual reality systems, and how these could be incorporated into a standardised human response measurement procedure

Investigation of metrics for assessing human response to drone noise

Novel electric air transportation is emerging as an industry that could help to improve the lives of people living in both metropolitan and rural areas through integration into infrastructure and services. However, as this new resource of accessibility increases in momentum, the need to investigate any potential adverse health impacts on the public becomes paramount. This paper details research investigating the effectiveness of available noise metrics and sound quality metrics (SQMs) for assessing perception of drone noise. A subjective experiment was undertaken to gather data on human response to a comprehensive set of drone sounds and to investigate the relationship between perceived annoyance, perceived loudness and perceived pitch and key psychoacoustic factors. Based on statistical analyses, subjective models were obtained for perceived annoyance, loudness and pitch of drone noise. These models provide understanding on key psychoacoustic features to consider in decision making in order to mitigate the impact of drone noise. For the drone sounds tested in this paper, the main contributors to perceived annoyance are perceived noise level (PNL) and sharpness; for perceived loudness are PNL and fluctuation strength; and for perceived pitch are sharpness, roughness and Aures tonality. Responses for the drone sounds tested were found to be highly sensitive to the distance between drone and receiver, measured in terms of height above ground level (HAGL). All these findings could inform the optimisation of drone operating conditions in order to mitigate community noise

Flight performance of actively foraging honey bees is reduced by a common pathogen

ArticleSudden and severe declines in honey bee (Apis mellifera) colony health in the US and Europe have been attributed, in part, to emergent microbial pathogens, however, the mechanisms behind the impact are unclear. Using roundabout flight mills, we measured the flight distance and duration of actively foraging, healthy-looking honey bees sampled from standard colonies, before quantifying the level of infection by Nosema ceranae and Deformed Wing Virus complex (DWV) for each bee. Neither the presence nor quantity of N. ceranae at low, natural levels of infection had any effect on flight distance or duration, but presence of DWV reduced flight distance by two thirds and duration by one half. Quantity of DWV was shown to have a significant, but weakly positive relation with flight distance and duration, however, the low amount of variation that was accounted for suggests further investigation by dose-response assays is required. We conclude that widespread, naturally occurring levels of infection by DWV weaken the flight ability of honey bees and high levels of within-colony prevalence are likely to reduce efficiency and increase the cost of resource acquisition. Predictions of implications of pathogens on colony health and function should take account of sub-lethal effects on flight performance.This work was funded by the Insect Pollinators Initiative (IPI) grants BB/I000100/1, BB/I000097/1 and BB/I000097/2, C.B. Dennis British Beekeepers' Research Trust and the High Wycombe Beekeepers’ Association. The IPI is funded jointly by the BBSRC, Defra, NERC, The Scottish Government and The Wellcome Trust, under the LWEC Partnership. Rothamsted Research is a national institute of bioscience strategically funded by the BBSRC

Hepatic Steatosis, Rather Than Underlying Obesity, Increases the Risk of Infection and Hospitalization for COVID-19.

OBJECTIVE: Obesity is a risk factor for SARS-COV2 infection and is often associated with hepatic steatosis. The aim of this study was to determine if pre-existing hepatic steatosis affects the risk of infection and severity for COVID-19. DESIGN: Prospective cohort study (UK Biobank). Univariate and stepwise multivariate logistic regression analyses were performed on liver phenotypic biomarkers to determine if these variables increased risk of testing positive and being hospitalized for COVID-19; then compared to previously described risk factors associated with COVID-19, including age, ethnicity, gender, obesity, socio-economic status. SETTING: UK biobank study. PARTICIPANTS: 502,506 participants (healthy at baseline) in the UK Biobank, of whom 41,791 underwent MRI (aged 50–83) for assessment of liver fat, liver fibro-inflammatory disease, and liver iron. Positive COVID-19 test was determined from UK testing data, starting in March 2020 and censored in January 2021. PRIMARY AND SECONDARY OUTCOME MEASURES: Liver fat measured as proton density fat fraction (PDFF%) MRI and body mass index (BMI, Kg/m2) to assess prior to February 2020 using MRI of the liver to assess hepatic steatosis. RESULTS: Within the imaged cohort (n = 41, 791), 4,458 had been tested and 1,043 (2.49% of the imaged population) tested positive for COVID-19. Individuals with fatty liver (≥10%) were at increased risk of testing positive (OR: 1.35, p = 0.007) and those participants with obesity and fatty liver, were at increased risk of hospitalization with a positive test result by 5.14 times (p = 0.0006). CONCLUSIONS: UK Biobank data revealed obese individuals with fatty liver disease were at increased risk of infection and hospitalization for COVID-19. Public policy measures and personalized medicine should be considered in order to protect these high-risk individuals

The role of parental achievement goals in predicting autonomy-supportive and controlling parenting

Although autonomy-supportive and controlling parenting are linked to numerous positive and negative child outcomes respectively, fewer studies have focused on their determinants. Drawing on achievement goal theory and self-determination theory, we propose that parental achievement goals (i.e., achievement goals that parents have for their children) can be mastery, performance-approach or performance-avoidance oriented and that types of goals predict mothers' tendency to adopt autonomy-supportive and controlling behaviors. A total of 67 mothers (aged 30-53 years) reported their goals for their adolescent (aged 13-16 years; 19.4 % girls), while their adolescent evaluated their mothers' behaviors. Hierarchical regression analyses showed that parental performance-approach goals predict more controlling parenting and prevent acknowledgement of feelings, one autonomy-supportive behavior. In addition, mothers who have mastery goals and who endorse performance-avoidance goals are less likely to use guilt-inducing criticisms. These findings were observed while controlling for the effect of maternal anxiety

Automated mineralogical profiling of soils as an indicator of local bedrock lithology: a tool for predictive forensic geolocation

This is the author accepted manuscript. The final version is available from Geological Society of London via the DOI in this record The use of soil evidence to identify an unknown location is a powerful tool to determine the provenance of an item in an investigation. We are particularly interested in the use of these indicators in nuclear forensic cases, whereby identification of locations associated with, for example, a smuggled nuclear material, may be used to indicate the provenance of a find. The use of soil evidence to identify an unknown location relies on understanding and predicting how soils vary in composition depending on their geological/geographical setting. In this study, compositional links between the mineralogy of 40 soils and the underlying bedrock geology, as documented in local-scale geological maps, were established. The soil samples were collected from locations with broadly similar climate and land use across a range of geological settings in a ‘test bed’ 3500 km2 area of SW England. In this region, the soils formed through chemical weathering of the bedrock, representing a worst case scenario for this type of forensic geolocation owing to the high degree of alteration of the parent rock during soil formation. The mineralogy was quantified using automated scanning electron microscopy–energy dispersive X-ray spectrometry analysis based on QEMSCAN technology. Soil mineralogy and texture as measured using this technique are consistent with the underlying geology as indicated by regional-scale geological mapping. Furthermore, differences between individual units of the same bedrock lithology, such as different granites, were identified by examining trace mineralogical signatures. From an investigative viewpoint, this demonstrated that rapid automated mineral profiling of soil samples could be used, in conjunction with readily available geological mapping or similar datasets, to provide indication of the areas from which a soil sample of unknown origin could, or could not, have been sourced

Feasibility and Validity of Computed Tomography-Derived Fractional Flow Reserve in Patients With Severe Aortic Stenosis: The CAST-FFR Study

BACKGROUND: Coronary artery disease is common in patients with severe aortic stenosis. Computed tomography-derived fractional flow reserve (CT-FFR) is a clinically used modality for assessing coronary artery disease, however, its use has not been validated in patients with severe aortic stenosis. This study assesses the safety, feasibility, and validity of CT-FFR in patients with severe aortic stenosis. METHODS: Prospectively recruited patients underwent standard-protocol invasive FFR and coronary CT angiography (CTA). CTA images were analyzed by central core laboratory (HeartFlow, Inc) for independent evaluation of CT-FFR. CT-FFR data were compared with FFR (ischemia defined as FFR ≤0.80). RESULTS: Forty-two patients (68 vessels) underwent FFR and CTA; 39 patients (92.3%) and 60 vessels (88.2%) had interpretable CTA enabling CT-FFR computation. Mean age was 76.2±6.7 years (71.8% male). No patients incurred complications relating to premedication, CTA, or FFR protocol. Mean FFR and CT-FFR were 0.83±0.10 and 0.77±0.14, respectively. CT calcium score was 1373.3±1392.9 Agatston units. On per vessel analysis, there was positive correlation between FFR and CT-FFR (Pearson correlation coefficient, R=0.64, P<0.0001). Sensitivity, specificity, positive predictive value, and negative predictive values were 73.9%, 78.4%, 68.0%, and 82.9%, respectively, with 76.7% diagnostic accuracy. The area under the receiver-operating characteristic curve for CT-FFR was 0.83 (0.72-0.93, P<0.0001), which was higher than that of CTA and quantitative coronary angiography (P=0.01 and P<0.001, respectively). Bland-Altman plot showed mean bias between FFR and CT-FFR as 0.059±0.110. On per patient analysis, the sensitivity, specificity, positive predictive, and negative predictive values were 76.5%, 77.3%, 72.2%, and 81.0% with 76.9% diagnostic accuracy. The per patient area under the receiver-operating characteristic curve analysis was 0.81 (0.67-0.95, P<0.0001). CONCLUSIONS: CT-FFR is safe and feasible in patients with severe aortic stenosis. Our data suggests that the diagnostic accuracy of CT-FFR in this cohort potentially enables its use in clinical practice and provides the foundation for future research into the use of CT-FFR for coronary evaluation pre-aortic valve replacement