User-centred design criteria in next generation vehicle consoles

The purpose of this work is to gauge user opinions on vehicle dashboard design to ascertain the criteria important to consumers for the next generation of automobile dashboards. The results provide insight into the aspects of dashboard design that users feel are not beneficial and thereby lead to better informed dashboard designs in the future. Participants reviewed the physical ergonomics of their vehicles very positively. However, in dashboard design and instrument panel layout they were unsure of what an ideal dashboard would look like, often showing contradictory views. Controls on the steering wheel were also well reviewed but controls near the gear stick were not. In terms of vehicle technology Satnavs received good scoring for effectiveness but were reported as distracting. IVISs were negatively reviewed. Finally, automation was reviewed as potentially improving the daily lives of individuals but trust in automation is still a problem. Overall, this study showed that whilst dashboards are relatively well reviewed there are still issues to be addressed regarding in-vehicle technology and distraction, as well as improving public opinion on automated vehicles. Results represent the first stage in research studying current dashboards and distraction of in-vehicle technology and the design of automated dashboards of the future using virtual reality environments to create optimal console designs for drivers

Contrasting Regional Carbon Cycle Responses to Seasonal Climate Anomalies Across the East‐West Divide of Temperate North America

Across temperate North America, interannual variability (IAV) in gross primary production (GPP) and net ecosystem exchange (NEE) and their relationship with environmental drivers are poorly understood. Here, we examine IAV in GPP and NEE and their relationship to environmental drivers using two state‐of‐the‐science flux products: NEE constrained by surface and space‐based atmospheric CO2 measurements over 2010–2015 and satellite up‐scaled GPP from FluxSat over 2001–2017. We show that the arid western half of temperate North America provides a larger contribution to IAV in GPP (104% of east) and NEE (127% of east) than the eastern half, in spite of smaller magnitude of annual mean GPP and NEE. This occurs because anomalies in western ecosystems are temporally coherent across the growing season leading to an amplification of GPP and NEE. In contrast, IAV in GPP and NEE in eastern ecosystems is dominated by seasonal compensation effects, associated with opposite responses to temperature anomalies in spring and summer. Terrestrial biosphere models in the MsTMIP ensemble generally capture these differences between eastern and western temperate North America, although there is considerable spread between models

(Quantum) Space-Time as a Statistical Geometry of Fuzzy Lumps and the Connection with Random Metric Spaces

We develop a kind of pregeometry consisting of a web of overlapping fuzzy lumps which interact with each other. The individual lumps are understood as certain closely entangled subgraphs (cliques) in a dynamically evolving network which, in a certain approximation, can be visualized as a time-dependent random graph. This strand of ideas is merged with another one, deriving from ideas, developed some time ago by Menger et al, that is, the concept of probabilistic- or random metric spaces, representing a natural extension of the metrical continuum into a more microscopic regime. It is our general goal to find a better adapted geometric environment for the description of microphysics. In this sense one may it also view as a dynamical randomisation of the causal-set framework developed by e.g. Sorkin et al. In doing this we incorporate, as a perhaps new aspect, various concepts from fuzzy set theory.Comment: 25 pages, Latex, no figures, some references added, some minor changes added relating to previous wor

Prediction of leak flow rate in plastic water distribution pipes using vibro-acoustic measurements

Leakage from water distribution systems is a worldwide issue with consequences including loss of revenue, health and environmental concerns. Leaks have typically been found through leak noise correlation by placing sensors either side of the leak and recording and analysing its vibro-acoustic emission. While this method is widely used to identify the location of the leak, the sensors also record data that could be related to the leak’s flow rate, yet no reliable method exists to predict leak flow rate in water distribution pipes using vibro-acoustic emission. The aim of this research is to predict leak flow rate in medium-density polyethylene pipe using vibro-acoustic emission signals. A novel experimental methodology is presented whereby circular holes of four sizes are tested at several leak flow rates. Following the derivation of a number of features, least squares support vector machines are used in order to predict leak flow rate. The results show a strong correlation highlighting the potential of this technique as a rapid and practical tool for water companies to assess and prioritise leak repair

Dual-energy X-ray absorptiometry measures of lean body mass as a biomarker for progression in boys with Duchenne muscular dystrophy

We evaluated whether whole-body dual-energy X-ray absorptiometry (DXA) measures of lean body mass can be used as biomarkers for disease progression and treatment effects in patients with Duchenne muscular dystrophy. This post hoc analysis utilized data from a randomized, 2-period study of domagrozumab versus placebo in 120 ambulatory boys with DMD. DXA measures of lean body mass were obtained from the whole body (excluding head), arms, legs and appendicular skeleton at baseline and every 16 weeks. Treatment effects on DXA measures for domagrozumab versus placebo were assessed at Week 49. At Week 49, domagrozumab statistically significantly increased lean body mass versus placebo in the appendicular skeleton (p = 0.050) and arms (p < 0.001). The relationship between lean body mass at Week 49 and functional endpoints at Week 97 was evaluated. Changes in lean body mass at Week 49 in all regions except arms were significantly correlated with percent change from baseline in 4-stair climb (4SC) at Week 97. DXA-derived percent lean mass at Week 49 also correlated with 4SC and North Star Ambulatory Assessment at Week 97. These data indicate that whole-body DXA measures can be used as biomarkers for treatment effects and disease progression in patients with DMD, and warrant further investigation.Trial registration: ClinicalTrials.gov, NCT02310763; registered 8 December 2014

Airborne measurements of western U.S. wildfire emissions: Comparison with prescribed burning and air quality implications

Wildfires emit significant amounts of pollutants that degrade air quality. Plumes from three wildfires in the western U.S. were measured from aircraft during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and the Biomass Burning Observation Project (BBOP), both in summer 2013. This study reports an extensive set of emission factors (EFs) for over 80 gases and 5 components of submicron particulate matter (PM1) from these temperate wildfires. These include rarely, or never before, measured oxygenated volatile organic compounds and multifunctional organic nitrates. The observed EFs are compared with previous measurements of temperate wildfires, boreal forest fires, and temperate prescribed fires. The wildfires emitted high amounts of PM1 (with organic aerosol (OA) dominating the mass) with an average EF that is more than 2 times the EFs for prescribed fires. The measured EFs were used to estimate the annual wildfire emissions of carbon monoxide, nitrogen oxides, total nonmethane organic compounds, and PM1 from 11 western U.S. states. The estimated gas emissions are generally comparable with the 2011 National Emissions Inventory (NEI). However, our PM1 emission estimate (1530 ± 570 Gg yr-1) is over 3 times that of the NEI PM2.5 estimate and is also higher thanthe PM2.5 emitted from all other sources in these states in the NEI. This study indicates that the source of OA from biomass burning in the western states is significantly underestimated. In addition, our results indicate that prescribed burning may be an effective method to reduce fine particle emissions

Needs Assessment of Cybercrime and Digital Evidence in a UK Police Force

Cybercrime has recently surpassed, in terms of volume, all other forms of crime in the United Kingdom, and has been acknowledged as a national priority. The purpose of this research is to analyse the police cyber-investigation lifecycle: from the experience of the public when reporting cybercrime to call takers, through to the attending officers, officer(s) in charge, and the many units and roles involved in supporting cybercrime investigations. A large scale needs assessment was conducted within one of the largest police forces in England and Wales, involving focus groups and interviews with police staff and strategic leads across key units and roles. The results of the needs assessment document the state of policing cybercrime in a UK police force, along with the improvements and needs that exist across the force and in specific units and roles. In total, 125 needs were identified and further coded based on a thematic analysis. Common themes identified include: knowledge/training, communication, recording, software, roles, governance, procedures, resources, consistency, staffing, national input, face-to-face, interactions with the public, new capabilities, and triage. The most common needs were related to training and knowledge, communications, quality of recording, software, governance, procedures, resourcing, and national input. Due to the nature of the findings, it is likely that some of these identified areas may parallel other police organisations’ experiences at national and international levels

Quantitative magnetic resonance imaging measures as biomarkers of disease progression in boys with Duchenne muscular dystrophy: a phase 2 trial of domagrozumab

Duchenne muscular dystrophy (DMD) is a progressive, neuromuscular disorder caused by mutations in the DMD gene that results in a lack of functional dystrophin protein. Herein, we report the use of quantitative magnetic resonance imaging (MRI) measures as biomarkers in the context of a multicenter phase 2, randomized, placebo-controlled clinical trial evaluating the myostatin inhibitor domagrozumab in ambulatory boys with DMD (n = 120 aged 6 to < 16 years). MRI scans of the thigh to measure muscle volume, muscle volume index (MVI), fat fraction, and T2 relaxation time were obtained at baseline and at weeks 17, 33, 49, and 97 as per protocol. These quantitative MRI measurements appeared to be sensitive and objective biomarkers for evaluating disease progression, with significant changes observed in muscle volume, MVI, and T2 mapping measures over time. To further explore the utility of quantitative MRI measures as biomarkers to inform longer term functional changes in this cohort, a regression analysis was performed and demonstrated that muscle volume, MVI, T2 mapping measures, and fat fraction assessment were significantly correlated with longer term changes in four-stair climb times and North Star Ambulatory Assessment functional scores. Finally, less favorable baseline measures of MVI, fat fraction of the muscle bundle, and fat fraction of lean muscle were significant risk factors for loss of ambulation over a 2-year monitoring period. These analyses suggest that MRI can be a valuable tool for use in clinical trials and may help inform future functional changes in DMD.Trial registration: ClinicalTrials.gov identifier, NCT02310763; registered December 2014