A novel iterative solution of the three dimensional electric field integral equation

A novel forward backward iterative scheme for solving the three-dimensional (3-D) electric field integral equation is presented. This communication details how a naive extension of a 2-D forward backward algorithm to 3-D problems results in convergence difficulties due to spurious edge effects. The method proposed in this communication postulates the use of local "buffer regions" to suppress these unwanted effects and ensure stability. Results are presented illustrating the convergence of the algorithm when applied to scattering by a 15λ square metallic plate with an aperture and a metallic right-angled wedge

Crowdsourcing Image Extraction and Annotation: Software Development and Case Study

We describe the development of web-based software that facilitates large-scale, crowdsourced image extraction and annotation within image-heavy corpora that are of interest to the digital humanities. An application of this software is then detailed and evaluated through a case study where it was deployed within Amazon Mechanical Turk to extract and annotate faces from the archives of Time magazine. Annotation labels included categories such as age, gender, and race that were subsequently used to train machine learning models. The systemization of our crowdsourced data collection and worker quality verification procedures are detailed within this case study. We outline a data verification methodology that used validation images and required only two annotations per image to produce high-fidelity data that has comparable results to methods using five annotations per image. Finally, we provide instructions for customizing our software to meet the needs for other studies, with the goal of offering this resource to researchers undertaking the analysis of objects within other image-heavy archives

A research and evaluation capacity building model in Western Australia

Evaluation of public health programs, services and policies is increasingly required to demonstrate effectiveness. Funding constraints necessitate that existing programs, services and policies be evaluated and their findings disseminated. Evidence-informed practice and policy is also desirable to maximise investments in public health. Partnerships between public health researchers, service providers and policymakers can help address evaluation knowledge and skills gaps. The Western Australian Sexual Health and Blood-borne Virus Applied Research and Evaluation Network (SiREN) aims to build research and evaluation capacity in the sexual health and blood-borne virus sector in Western Australia (WA). Partners’ perspectives of the SiREN model after 2 years were explored. Qualitative written responses from service providers, policymakers and researchers about the SiREN model were analysed thematically. Service providers reported that participation in SiREN prompted them to consider evaluation earlier in the planning process and increased their appreciation of the value of evaluation. Policymakers noted benefits of the model in generating local evidence and highlighting local issues of importance for consideration at a national level. Researchers identified challenges communicating the services available through SiREN and the time investment needed to develop effective collaborative partnerships. Stronger engagement between public health researchers, service providers and policymakers through collaborative partnerships has the potential to improve evidence generation and evidence translation. These outcomes require long-term funding and commitment from all partners to develop and maintain partnerships. Ongoing monitoring and evaluation can ensure the partnership remains responsive to the needs of key stakeholders. The findings are applicable to many sectors

Mix design considerations of foamed bitumen mixtures with reclaimed asphalt pavement material

In the present work, a mix design parametric study was carried out with the aim of proposing a practical and consistent mix design procedure for foamed bitumen mixtures (FBMs). The mix design parameters that were adopted in the study are mixing and compaction water content (MWC), compaction effort using a gyratory compactor and aggregate temperature. This parametric study was initially carried out on FBMs with virgin limestone aggregate without reclaimed asphalt pavement (RAP) material and a mix design procedure was proposed. This proposed methodology was also found to apply to FBMs with RAP. A detailed consideration was also given to characterising the RAP material so as to understand its contribution to the mechanical properties of FBMs. Optimum MWC was achieved by optimising mechanical properties such as indirect tensile stiffness modulus and indirect tensile strength (ITS-dry and ITS-wet). A rational range of 75–85% of optimum water content obtained by the modified Proctor test was found to be the optimum range of MWC that gives optimum mechanical properties for FBMs. It was also found that the presence of RAP influenced the design foamed bitumen content, which means that treating RAP as black rock in FBM mix design is not appropriate. To study the influence of bitumen and water during compaction, modified Proctor compaction and gyratory compaction were employed on mixes with varying amounts of water and bitumen. By this, the work also evaluated the validity of the total fluid (water + bitumen) concept that is widely used in bitumen–emulsion-treated mixes, and found it not to be applicable

A statistical model to describe longitudinal and correlated metabolic risk factors: the Whitehall II prospective study.

Background Novel epidemiology models are required to link correlated variables over time, especially haemoglobin A1c (HbA1c) and body mass index (BMI) for diabetes prevention policy analysis. This article develops an epidemiology model to correlate metabolic risk factor trajectories. Method BMI, fasting plasma glucose, 2-h glucose, HbA1c, systolic blood pressure, total cholesterol and high density lipoprotein (HDL) cholesterol were analysed over 16 years from 8150 participants of the Whitehall II prospective cohort study. Latent growth curve modelling was employed to simultaneously estimate trajectories for multiple metabolic risk factors allowing for variation between individuals. A simulation model compared simulated outcomes with the observed data. Results The model identified that the change in BMI was associated with changes in glycaemia, total cholesterol and systolic blood pressure. The statistical analysis quantified associations among the longitudinal risk factor trajectories. Growth in latent glycaemia was positively correlated with systolic blood pressure and negatively correlated with HDL cholesterol. The goodness-of-fit analysis indicates reasonable fit to the data. Conclusions This is the first statistical model that estimates trajectories of metabolic risk factors simultaneously for diabetes to predict joint correlated risk factor trajectories. This can inform comparisons of the effectiveness and cost-effectiveness of preventive interventions, which aim to modify metabolic risk factors

AI in my life: AI, ethics & privacy workshops for 15-16-year-olds

‘AI in My Life’ project will engage 500 Dublin teenagers from disadvantaged backgrounds in a 15-week (20- hour) co-created, interactive workshop series encouraging them to reflect on their experiences in a world shaped by Artificial Intelligence (AI), personal data processing and digital transformation. Students will be empowered to evaluate the ethical and privacy implications of AI in their lives, to protect their digital privacy and to activate STEM careers and university awareness. It extends the ‘DCU TY’ programme for innovative educational opportunities for Transition Year students from underrepresented communities in higher education. Privacy and cybersecurity researchers and public engagement professionals from the SFI Centres ADAPT1 and Lero2 will join experts from the Future of Privacy Forum3 and the INTEGRITY H20204 project to deliver the programme to the DCU Access5 22-school network. DCU Access has a mission of creating equality of access to third-level education for students from groups currently underrepresented in higher education. Each partner brings proven training activities in AI, ethics and privacy. A novel blending of material into a youthdriven narrative will be the subject of initial co-creation workshops and supported by pilot material delivery by undergraduate DCU Student Ambassadors. Train-the-trainer workshops and a toolkit for teachers will enable delivery. The material will use a blended approach (in person and online) for delivery during COVID- 19. It will also enable wider use of the material developed. An external study of programme effectiveness will report on participants’: enhanced understanding of AI and its impact, improved data literacy skills in terms of their understanding of data privacy and security, empowerment to protect privacy, growth in confidence in participating in public discourse about STEM, increased propensity to consider STEM subjects at all levels, and greater capacity of teachers to facilitate STEM interventions. This paper introduces the project, presents more details about co-creation workshops that is a particular step in the proposed methodology and reports some preliminary results

Perforin proteostasis is regulated through its C2 domain: supra-physiological cell death mediated by T431D-perforin

The pore forming, Ca2+-dependent protein, perforin, is essential for the function of cytotoxic lymphocytes, which are at the frontline of immune defence against pathogens and cancer. Perforin is a glycoprotein stored in the secretory granules prior to release into the immune synapse. Congenital perforin deficiency causes fatal immune dysregulation, and is associated with various haematological malignancies. At least 50% of pathological missense mutations in perforin result in protein misfolding and retention in the endoplasmic reticulum. However, the regulation of perforin proteostasis remains unexplored. Using a variety of biochemical assays that assess protein stability and acquisition of complex glycosylation, we demonstrated that the binding of Ca2+ to the C2 domain stabilises perforin and regulates its export from the endoplasmic reticulum to the secretory granules. As perforin is a thermo-labile protein, we hypothesised that by altering its C2 domain it may be possible to improve protein stability. On the basis of the X-ray crystal structure of the perforin C2 domain, we designed a mutation (T431D) in the Ca2+ binding loop. Mutant perforin displayed markedly enhanced thermal stability and lytic function, despite its trafficking from the endoplasmic reticulum remaining unchanged. Furthermore, by introducing the T431D mutation into A90V perforin, a pathogenic mutation, which results in protein misfolding, we corrected the A90V folding defect and completely restored perforin’s cytotoxic function. These results revealed an unexpected role for the Ca2+-dependent C2 domain in maintaining perforin proteostasis and demonstrated the possibility of designing perforin with supra-physiological cytotoxic function through stabilisation of the C2 domain

Computer modeling of diabetes and Its transparency: a report on the Eighth Mount Hood Challenge

Objectives The Eighth Mount Hood Challenge (held in St. Gallen, Switzerland, in September 2016) evaluated the transparency of model input documentation from two published health economics studies and developed guidelines for improving transparency in the reporting of input data underlying model-based economic analyses in diabetes. Methods Participating modeling groups were asked to reproduce the results of two published studies using the input data described in those articles. Gaps in input data were filled with assumptions reported by the modeling groups. Goodness of fit between the results reported in the target studies and the groups’ replicated outputs was evaluated using the slope of linear regression line and the coefficient of determination (R2). After a general discussion of the results, a diabetes-specific checklist for the transparency of model input was developed. Results Seven groups participated in the transparency challenge. The reporting of key model input parameters in the two studies, including the baseline characteristics of simulated patients, treatment effect and treatment intensification threshold assumptions, treatment effect evolution, prediction of complications and costs data, was inadequately transparent (and often missing altogether). Not surprisingly, goodness of fit was better for the study that reported its input data with more transparency. To improve the transparency in diabetes modeling, the Diabetes Modeling Input Checklist listing the minimal input data required for reproducibility in most diabetes modeling applications was developed. Conclusions Transparency of diabetes model inputs is important to the reproducibility and credibility of simulation results. In the Eighth Mount Hood Challenge, the Diabetes Modeling Input Checklist was developed with the goal of improving the transparency of input data reporting and reproducibility of diabetes simulation model results