High temperature, low neutron cross-section highentropy alloys in the Nb-Ti-V-Zr system

High-entropy alloys (HEAs) with high melting points and low thermal neutron cross-section are promising new cladding materials for generation III+ and IV power reactors. In this study a recently developed high throughput computational screening tool Alloy Search and Predict (ASAP) has been used to identify the most likely candidate single-phase HEAs with low thermal neutron cross-section, from over a million four-element equimolar combinations. The selected NbTiVZr HEA was further studied by density functional theory (DFT) for moduli and lattice parameter, and by CALPHAD to predict phase formation with temperature. HEAs of NbTiVZrx (x = 0.5, 1, 2) were produced experimentally, with Zr varied as the dominant cross-section modifier. Contrary to previous experimental work, these HEAs were demonstrated to constitute a single-phase HEA system; a result obtained using a faster cooling rate following annealing at 1200 °C. However, the beta (BCC) matrix decomposed following aging at 700 °C, into a combination of nano-scale beta, alpha (HCP) and C15 Laves phases

Smart Publics: Public Perceptions of Smart Street Furniture in London and Glasgow: Insights for Policy and Practice

No abstract available

A modelling framework for the prediction of the herd-level probability of infection from longitudinal data

International audienceThe collective control programmes (CPs) that exist for many infectious diseases of farm animals rely on the application of diagnostic testing at regular time intervals for the identification of infected animals or herds. The diversity of these CPs complicates the trade of animals between regions or countries because the definition of freedom from infection differs from one CP to another. In this paper, we describe a statistical model for the prediction of herd-level probabilities of infection from longitudinal data collected as part of CPs against infectious diseases of cattle. The model was applied to data collected as part of a CP against bovine viral diarrhoea virus (BVDV) infection in Loire-Atlantique, France. The model represents infection as a herd latent status with a monthly dynamics. This latent status determines test results through test sensitivity and test specificity. The probability of becoming status positive between consecutive months is modelled as a function of risk factors (when available) using logistic regression. Modelling is performed in a Bayesian framework, using either Stan or JAGS. Prior distributions need to be provided for the sensitivities and specificities of the different tests used, for the probability of remaining status positive between months as well as for the probability of becoming positive between months. When risk factors are available, prior distributions need to be provided for the coefficients of the logistic regression, replacing the prior for the probability of becoming positive. From these prior distributions and from the longitudinal data, the model returns posterior probability distributions for being status positive for all herds on the current month. Data from the previous months are used for parameter estimation. The impact of using different prior distributions and model implementations on parameter estimation was evaluated. The main advantage of this model is its ability to predict a probability of being status positive in a month from inputs that can vary in terms of nature of test, frequency of testing and risk factor availability/presence. The main challenge in applying the model to the BVDV CP data was in identifying prior distributions, especially for test characteristics, that corresponded to the latent status of interest, i.e. herds with at least one persistently infected (PI) animal. The model is available on Github as an R package (https://github.com/AurMad/STOCfree) and can be used to carry out output-based evaluation of disease CPs

New insights into the correlation structure of DSM-IV depression symptoms in the general population v. subsamples of depressed individuals

Additional results and R-code for our paper "New insights into the correlation structure of DSM-IV depression symptoms in the general population versus subsamples of depressed individuals

Discovering smart: Early encounters and negotiations with smart street furniture in London and Glasgow

In the late 2010s, publics in the UK encountered new kinds of street furniture: Strawberry Energy Smart benches in London and InLinkUK kiosks in Glasgow, with smart features such as phone charging, free Wi-Fi, free phone calls, information screens and environmental data. This article analyses how smart street furniture is socially constructed by relevant social groups, each with different interests, forms of power and meanings. Smartness became associated not only with advanced technologies, but with a neoliberal agenda of private-public partnerships promising urban transformations, such as free devices for councils and citizens in exchange for access to advertising or sponsorship space in public places. The research examined the design, use and governance of new types of smart street furniture using mixed methods, including document analysis of promotional and regulatory texts, site observations of these devices, and interviews. We found that the uses and meanings of these devices were discovered at different moments by technology companies, local councils, and the public. Few members of the public knew about the devices, and showed little interest in them, even if they were the assumed users. An exception was gig workers and people experiencing homelessness who found uses for the smart features and a community activist who campaigned against these as surveillant and intrusive. Businesses and councils embraced smart city visions but took multiple approaches to agreements for the implementation and governance of smart street furniture. Notably, these more powerful groups discovered and negotiated the meanings of smart street furniture well before these were publicly encountered. This article reveals how a social construction of technology (SCOT) approach is strongest when it accounts for the relative power of social groups in struggles over meanings and resources. It provides empirical information on everyday sociotechnical encounters that provide nuanced evidence for wider critiques of smart city agendas

Situated, yet silent: data relations in smart street furniture

This article provides new evidence of the ways that smart cities materialize within specific sites and contexts through smart street furniture (SSF). Drawing on empirical data generated through mixed-method field research, the article examines the situated data relations that emerge in the context of the adoption of InLinkUK smart kiosks in Glasgow and Strawberry Energy smart benches in London. The concept of “silences” is proposed to analyze insufficiently articulated data relations resulting from gaps or absences in the use, design, and governance of this new type of urban furniture. The argument made is that data silences lead to failures to account for decisions and the deferral of responsibilities regarding the data aspects of these objects. It is suggested that an approach that focuses on “listening” to and “speaking” about data relations can enable dialogical forms of accountability, and realize the potential of SSF for citizens in local contexts

The design and public imaginaries of smart street furniture

No abstract available

Predictors of Hip Dysplasia at 4 Years in Children with Perinatal Risk Factors

Background:. While perinatal risk factors are widely used to help identify those at risk for developmental dysplasia of the hip (DDH) within the first 6 to 8 weeks of life, limited data exist about their association with radiographic evidence of dysplasia in childhood. The purpose of this study was to determine which perinatal risk factors are associated with acetabular dysplasia in children who are ≥2 years of age. Methods:. Pelvic radiographs were made in 1,053 children (mean age, 4.4 years [range, 2 to 7 years]) who had been assessed prospectively as having at least 1 of 9 widely accepted perinatal risk factors for DDH. Two radiologists who were blinded to patient risk factors, history, and age determined the acetabular index (AI). The primary outcome was defined as an AI >2 standard deviations from the Tönnis reference values (“severe” dysplasia). The secondary outcome was an AI of >20° at >2 years of age. The association between risk factors and outcomes was assessed using logistic regression. The effect of treatment in infancy was adjusted for in 37 hips. Results:. Twenty-seven participants (3%) showed “severe” hip dysplasia; 3 of these had received treatment for DDH in infancy. Girls were more likely to experience this outcome (odds ratio [OR] = 2.59; 95% confidence interval [CI] = 1.04 to 6.46; p = 0.04); no other examined risk factors were significant. The secondary outcome appeared in 146 participants (14%), 12 of whom had received treatment in infancy. We observed the following predictors for this outcome: female sex (OR = 1.77; 95% CI = 1.21 to 2.59; p = 0.003), breech presentation (OR = 1.74; 95% CI = 1.08 to 2.79; p = 0.02), and being a firstborn child, which had a protective effect (OR = 0.67; 95% CI = 0.46 to 0.96; p = 0.03). Conclusions:. We identified a substantial number of cases that will require at least radiographic surveillance for mild and severe hip dysplasia; 92% had no prior diagnosis of DDH. Those who had been born breech were affected by this outcome even if ultrasonography of the hip had been normal at 6 to 8 weeks, suggesting a benefit from additional radiographic testing. Level of Evidence:. Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence