4,088 research outputs found

    Stability, mechanisms and kinetics of emergence of Au surface reconstructions using Bayesian force fields

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    Metal surfaces have long been known to reconstruct, significantly influencing their structural and catalytic properties. Many key mechanistic aspects of these subtle transformations remain poorly understood due to limitations of previous simulation approaches. Using active learning of Bayesian machine-learned force fields trained from ab initio calculations, we enable large-scale molecular dynamics simulations to describe the thermodynamics and time evolution of the low-index mesoscopic surface reconstructions of Au (e.g., the Au(111)-`Herringbone,' Au(110)-(1×\times2)-`Missing-Row,' and Au(100)-`Quasi-Hexagonal' reconstructions). This capability yields direct atomistic understanding of the dynamic emergence of these surface states from their initial facets, providing previously inaccessible information such as nucleation kinetics and a complete mechanistic interpretation of reconstruction under the effects of strain and local deviations from the original stoichiometry. We successfully reproduce previous experimental observations of reconstructions on pristine surfaces and provide quantitative predictions of the emergence of spinodal decomposition and localized reconstruction in response to strain at non-ideal stoichiometries. A unified mechanistic explanation is presented of the kinetic and thermodynamic factors driving surface reconstruction. Furthermore, we study surface reconstructions on Au nanoparticles, where characteristic (111) and (100) reconstructions spontaneously appear on a variety of high-symmetry particle morphologies.Comment: Main: 17 pages, 7 figures, 1 table. SI: 9 pages, 15 figures, 1 tabl

    Applications of Blockchain Within Healthcare.

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    There are several areas of healthcare and well-being that could be enhanced using blockchain technologies. These include device tracking, clinical trials, pharmaceutical tracing, and health insurance. Within device tracking, hospitals can trace their asset within a blockchain infrastructure, including through the complete lifecycle of a device. The information gathered can then be used to improve patient safety and provide after-market analysis to improve efficiency savings. This paper outlines recent work within the areas of pharmaceutical traceability, data sharing, clinical trials, and device tracking

    Applications of Blockchain Within Healthcare.

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    There are several areas of healthcare and well-being that could be enhanced using blockchain technologies. These include device tracking, clinical trials, pharmaceutical tracing, and health insurance. Within device tracking, hospitals can trace their asset within a blockchain infrastructure, including through the complete lifecycle of a device. The information gathered can then be used to improve patient safety and provide after-market analysis to improve efficiency savings. This paper outlines recent work within the areas of pharmaceutical traceability, data sharing, clinical trials, and device tracking

    Complexity of Many-Body Interactions in Transition Metals via Machine-Learned Force Fields from the TM23 Data Set

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    This work examines challenges associated with the accuracy of machine-learned force fields (MLFFs) for bulk solid and liquid phases of d-block elements. In exhaustive detail, we contrast the performance of force, energy, and stress predictions across the transition metals for two leading MLFF models: a kernel-based atomic cluster expansion method implemented using sparse Gaussian processes (FLARE), and an equivariant message-passing neural network (NequIP). Early transition metals present higher relative errors and are more difficult to learn relative to late platinum- and coinage-group elements, and this trend persists across model architectures. Trends in complexity of interatomic interactions for different metals are revealed via comparison of the performance of representations with different many-body order and angular resolution. Using arguments based on perturbation theory on the occupied and unoccupied d states near the Fermi level, we determine that the large, sharp d density of states both above and below the Fermi level in early transition metals leads to a more complex, harder-to-learn potential energy surface for these metals. Increasing the fictitious electronic temperature (smearing) modifies the angular sensitivity of forces and makes the early transition metal forces easier to learn. This work illustrates challenges in capturing intricate properties of metallic bonding with current leading MLFFs and provides a reference data set for transition metals, aimed at benchmarking the accuracy and improving the development of emerging machine-learned approximations.Comment: main text: 21 pages, 9 figures, 2 tables. supplementary information: 57 pages, 83 figures, 20 table

    Nuclear Disks of Gas and Dust in Early Type Galaxies and the Hunt for Massive Black Holes: Hubble Space Telescope Observations of NGC 6251

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    We discuss Hubble Space Telescope optical images and spectra of NGC 6251, a giant E2 galaxy and powerful radio source at a distance of 106 Mpc (for H_0 = 70 km/s/Mpc). The galaxy is known to host a very well defined dust disk (O'Neil et al. 1994); the exceptional resolution of our V and I images allows a detailed study of the disk structure. Furthermore, narrow band images centered on the Halpha+[NII] emission lines, reveal the presence of ionized gas in the inner 0.3 arcsec of the disk. We used the HST/Faint Object Spectrograph with the 0.09 arcsec aperture to study the velocity structure of the disk. Dynamical models were constructed for two extreme (in terms of central concentration) analytical representations of the stellar surface brightness profile, from which the mass density and corresponding rotational velocity are derived assuming a constant mass-to-light ratio (M/L)_V ~ 8.5 M_solar/L_solar. For both representations of the stellar component, the models show that the gas is in Keplerian motion around a central mass ~ 4 - 8 X 10^8 solar masses, and that the contribution of radial flows to the velocity field is negligible.Comment: 45 pages, submitted to Ap

    The propensity of non-concussive and concussive head contacts during elite-level women's rugby league matches : A prospective analysis of over 14,000 tackle events

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    Objectives Identify the frequency, propensity, and factors related to tackle events which result in contact with the head in elite-level women's rugby league. Design Prospective video analysis study. Methods Video footage from 59 Women's Super League matches were analysed (n = 14,378 tackle events). All tackle events were coded as no head contact or head contact. Other independent variables included: area contacting head, impacted player, concussion outcome, penalty outcome, round of competition, time in match and team standard. Results There were 83.0 ± 20.0 (propensity 304.0/1000 tackle events) head contacts per match. The propensity of head contact was significantly greater for the tackler than ball-carrier (178.5 vs. 125.7/1000 tackle events; incident rate ratio 1.42, 95 % confidence interval 1.34 to 1.50). Head contacts occurring from an arm, shoulder, and head occurred significantly more than any other contact type. The propensity of concussions was 2.7/1000 head contacts. There was no significant influence of team standard or time in match on the propensity of head contacts. Conclusions The observed head contacts can inform interventions, primarily focusing on the tackler not contacting the ball-carrier's head. The tackler's head should also be appropriately positioned to avoid contact with the ball-carrier's knee (highest propensity for concussion). The findings are consistent with other research in men's rugby. Law modifications and/or enforcement (reducing the number of un-penalised head contacts), concurrent with coaching interventions (optimising head placement or reducing the head being contacted) may help minimise head contact risk factors for women's rugby league

    Health and mortality consequences of abdominal obesity : evidence from the AusDiab study

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    Objective: To provide an estimate of the morbidity and mortality resulting from abdominal overweight and obesity in the Australian population.Design and setting: Prospective, national, population-based study (the Australian Diabetes, Obesity and Lifestyle [AusDiab] study).Participants: 6072 men and women aged ≥ 25 years at study entry between May 1999 and December 2000, and aged ≤ 75 years, not pregnant and for whom there were waist circumference data at the follow-up survey between June 2004 and December 2005.Main outcome measures: Incident health outcomes (type 2 diabetes, hypertension, dyslipidaemia, the metabolic syndrome and cardiovascular diseases) at 5 years and mortality at 8 years. Comparison of outcome measures between those classified as abdominally overweight or obese and those with a normal waist circumference at baseline, and across quintiles of waist circumference, and (for mortality only) waist-to-hip ratio.Results: Abdominal obesity was associated with odds ratios of between 2 and 5 for incident type 2 diabetes, dyslipidaemia, hypertension and the metabolic syndrome. The risk of myocardial infarction among obese participants was similarly increased in men (hazard ratio [HR], 2.75; 95% CI, 1.08–7.03), but not women (HR, 1.43; 95% CI, 0.37–5.50). Abdominal obesity-related population attributable fractions for these outcomes ranged from 13% to 47%, and were highest for type 2 diabetes. No significant associations were observed between all-cause mortality and increasing quintiles of abdominal obesity.Conclusions: Our findings confirm that abdominal obesity confers a considerably heightened risk for type 2 diabetes, the metabolic syndrome (as well as its components) and cardiovascular disease, and they provide important information that enables a more precise estimate of the burden of disease attributable to obesity in Australia

    Wet scavenging of soluble gases in DC3 deep convective storms using WRF-Chem simulations and aircraft observations

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    We examine wet scavenging of soluble trace gases in storms observed during the Deep Convective Clouds and Chemistry (DC3) field campaign. We conduct high-resolution simulations with the Weather Research and Forecasting model with Chemistry (WRF-Chem) of a severe storm in Oklahoma. The model represents well the storm location, size, and structure as compared with Next Generation Weather Radar reflectivity, and simulated CO transport is consistent with aircraft observations. Scavenging efficiencies (SEs) between inflow and outflow of soluble species are calculated from aircraft measurements and model simulations. Using a simple wet scavenging scheme, we simulate the SE of each soluble species within the error bars of the observations. The simulated SEs of all species except nitric acid (HNO_3) are highly sensitive to the values specified for the fractions retained in ice when cloud water freezes. To reproduce the observations, we must assume zero ice retention for formaldehyde (CH_2O) and hydrogen peroxide (H_2O_2) and complete retention for methyl hydrogen peroxide (CH_3OOH) and sulfur dioxide (SO_2), likely to compensate for the lack of aqueous chemistry in the model. We then compare scavenging efficiencies among storms that formed in Alabama and northeast Colorado and the Oklahoma storm. Significant differences in SEs are seen among storms and species. More scavenging of HNO_3 and less removal of CH_3OOH are seen in storms with higher maximum flash rates, an indication of more graupel mass. Graupel is associated with mixed-phase scavenging and lightning production of nitrogen oxides (NO_x), processes that may explain the observed differences in HNO_3 and CH_3OOH scavenging
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