The next-generation radio astronomy instruments are providing a massive increase in sensitivity and coverage, largely through increasing the number of stations in the array and the frequency span sampled. The two primary problems encountered when processing the resultant avalanche of data are the need for abundant storage and the constraints imposed by I/O, as I/O bandwidths drop significantly on cold storage. An example of this is the data deluge expected from the SKA Telescopes of more than 60 PB per day, all to be stored on the buffer filesystem. While compressing the data is an obvious solution, the impacts on the final data products are hard to predict. In this paper, we chose an error-controlled compressor – MGARD – and applied it to simulated SKA-Mid and real pathfinder visibility data, in noise-free and noise-dominated regimes. As the data have an implicit error level in the system temperature, using an error bound in compression provides a natural metric for compression. MGARD ensures the compression incurred errors adhere to the user-prescribed tolerance. To measure the degradation of images reconstructed using the lossy compressed data, we proposed a list of diagnostic measures, exploring the trade-off between these error bounds and the corresponding compression ratios, as well as the impact on science quality derived from the lossy compressed data products through a series of experiments. We studied the global and local impacts on the output images for continuum and spectral line examples. We found relative error bounds of as much as 10%, which provide compression ratios of about 20, have a limited impact on the continuum imaging as the increased noise is less than the image RMS, whereas a 1% error bound (compression ratio of 8) introduces an increase in noise of about an order of magnitude less than the image RMS. For extremely sensitive observations and for very precious data, we would recommend a $0.1\%$ error bound with compression ratios of about 4. These have noise impacts two orders of magnitude less than the image RMS levels. At these levels, the limits are due to instabilities in the deconvolution methods. We compared the results to the alternative compression tool DYSCO, in both the impacts on the images and in the relative flexibility. MGARD provides better compression for similar error bounds and has a host of potentially powerful additional features.

Current evidence underscores a need to transform how we do clinical research, shifting from academic-driven priorities to co-led community partnership focused programs, accessible and relevant career pathway programs that expand opportunities for career development, and design of trainings and practices to develop cultural competence among research teams. Failures of equitable research translation contribute to health disparities. Drivers of this failed translation include lack of diversity in both researchers and participants, lack of alignment between research institutions and the communities they serve, and lack of attention to structural sources of inequity and drivers of mistrust for science and research. The Duke University Research Equity and Diversity Initiative (READI) is a program designed to better align clinical research programs with community health priorities through community engagement. Organized around three specific aims, READI-supported programs targeting increased workforce diversity, workforce training in community engagement and cultural competence, inclusive research engagement principles, and development of trustworthy partnerships.

This study investigates two clayey facies from the Bomkoul area in the littoral region of Cameroon for their suitability as fired clay building products. The field study consisted of a geological survey and a geotechnical mission (G0). Assessment of the raw clayey materials included their mineralogy, particle size, determination of Atterberg limits, density and shear stress. Firing properties (shrinkage, water absorption and flexural strength) at 900−1100°C were also determined. The two main facies observed in the field are the mottled red/yellow grey clays from surface ‘A’ with a thickness of 2.0–2.5 m and the deep blackish fossiliferous schisteous grey clays ‘B’ with a thickness of 8−10 m. Estimation based on boreholes revealed a minimum of 1,400,000 tons of clayey materials. These reserves will supply a small brick-manufacturing unit for a minimum period of 25 years at an extraction rate of 50,000 tons per year. The main clay minerals of both samples are kaolinite (35% and 49%) and illite (1–11%). Both samples contain quartz (47% and 49%) as non-clay minerals, associated with a small amount of anatase (0.5–2.6%) and trace hematite (<1%). The major oxides are SiO2 (71–76%) and Al2O3 (14%). The raw clayey material ‘A’ was finer and more plastic than the ‘B’ facies. The technological properties of the fired bricks obtained from the ‘A’ facies showed greater potential than the ‘B’ facies in terms of sonority and flexural strength. A mixture made of 40% ‘A’ and 60% ‘B’ yielded satisfactory brick properties at 1050°C.

Paternity leave may promote greater gender equality in domestic labour. Though numerous studies show that paternity leave promotes greater fathers’ involvement in childcare, less is known about whether paternity leave-taking may facilitate fathers’ involvement in other forms of domestic labour such as housework. Using repeated cross-sectional data on different-gender partnered US parents from the Study on Parents’ Divisions of Labor During COVID-19 (SPDLC), this study examines the extent to which paternity leave-taking and length of paternity leave are associated with US fathers’ shares of, and time spent on, housework. Findings suggest that paternity leave-taking is positively associated with fathers’ shares of, and time spent on, housework tasks. Longer paternity leaves are also associated with fathers performing greater shares of housework. Overall, this study indicates that the benefits of paternity leave likely extend to fathers’ greater participation in housework, providing additional support for the belief that increased use of paternity leave may help to promote gender equality in domestic labour.

Actuaries must model mortality to understand, manage and price risk. Continuous-time methods offer considerable practical benefits to actuaries analysing portfolio mortality experience. This paper discusses six categories of advantage: (i) reflecting the reality of data produced by everyday business practices, (ii) modelling rapid changes in risk, (iii) modelling time- and duration-varying risk, (iv) competing risks, (v) data-quality checking and (vi) management information. Specific examples are given where continuous-time models are more useful in practice than discrete-time models.

We reprise some common statistical models for actuarial mortality analysis using grouped counts. We then discuss the benefits of building mortality models from the most elementary items. This has two facets. First, models are better based on the mortality of individuals, rather than groups. Second, models are better defined in continuous time, rather than over fixed intervals like a year. We show how Poisson-like likelihoods at the “macro” level are built up by product integration of sequences of infinitesimal Bernoulli trials at the “micro” level. Observed data is represented through a stochastic mortality hazard rate, and counting processes provide the natural notation for left-truncated and right-censored actuarial data, individual or age-grouped. Together these explain the “pseudo-Poisson” behaviour of survival model likelihoods.

Recent changes to US research funding are having far-reaching consequences that imperil the integrity of science and the provision of care to vulnerable populations. Resisting these changes, the BJPsych Portfolio reaffirms its commitment to publishing mental science and advancing psychiatric knowledge that improves the mental health of one and all.