Animals under human care are exposed to a potentially large range of both familiar and unfamiliar humans. Human-animal interactions vary across settings, and individuals, with the nature of the interaction being affected by a suite of different intrinsic and extrinsic factors. These interactions can be described as positive, negative or neutral. Across some industries, there has been a move towards the development of technologies to support or replace human interactions with animals. Whilst this has many benefits, there can also be challenges associated with increased technology use. A day-long Animal Welfare Research Network workshop was hosted at Harper Adams University, UK, with the aim of bringing together stakeholders and researchers (n = 38) from the companion, farm and zoo animal fields, to discuss benefits, challenges and limitations of human-animal interactions and machine-animal interactions for animals under human care and create a list of future research priorities. The workshop consisted of four talks from experts within these areas, followed by break-out room discussions. This work is the outcome of that workshop. The key recommendations are that approaches to advancing the scientific discipline of machine-animal interactions in animals under human care should focus on: (1) interdisciplinary collaboration; (2) development of validated methods; (3) incorporation of an animal-centred perspective; (4) a focus on promotion of positive animal welfare states (not just avoidance of negative states); and (5) an exploration of ways that machines can support a reduction in the exposure of animals to negative human-animal interactions to reduce negative, and increase positive, experiences for animals.

As part of a laboratory study of the hydrothermal alteration of kimberlite, a mass balance procedure has been developed for estimating the relative proportions of synthetic phyllosilicate phases— chlorite, vermiculite, smectite, kaolinite and serpentine—present in reaction products. The procedure is based on a combination of X-ray powder diffraction (XRD) measurements (for phase identification), atomic absorption determinations (for total Si, Al, Fe, and Mg) and published analyses of clay minerals (for stoichiometric deductions). It centers on the computer inversion of a 4 × 4 matrix form of four simultaneous equations representing the mass balance of Si, Al, Fe, and Mg in four chosen minerals and incorporates a systematic routine for selecting from all possible permutations of high and low estimates of the mineral chemical analyses acceptable sets of product stoichiometries and phase proportions consistent with the total metal analyses. To minimize uncertainties and computing time, the program takes account of elemental relationships and water mass balances associated with phyllosilicates. It also accommodates data relevant to poorly crystalline phases for which a range of theoretical type-analyses modeled on aluminum oxyhydroxides and 9–11-Å, 2:1 layered aluminosilicates are employed.

The procedure produces reliable trends in phase proportions consistent with the intensities of characteristic XRD peaks of clay minerals present in the analyzed mixture; for example, increases in estimated kaolinite proportions correspond with larger 7-Å (and other) peaks in analyzed samples. A precision of 7–25% has been routinely achievable.

This paper describes structural models of four pyrophyllite edge faces: {010}, {110}, {100}, and {130}. Water molecules chemisorbed to Lewis acid sites stabilize edge faces both crystallochemically and electrostatically. The detailed assignment of protons to surface oxygens and the orientation of OH bond-vectors both influence the surface Coulomb energy.

The geometry chosen for the electrostatic calculations was infinite pyrophyllite ribbon the thickness of a single phyllosilicate layer and the width of 50 to 70 unit cells. Such a phyllosilicate ribbon has only two edges, a top and bottom, which were simulated using the edge-face models mentioned above. About 94% of the surface Coulomb energy is confined to the edge-face repeat unit. The surface Coulomb energies of the four edge faces are on the order of 2–3 nJ/m, varying ± 1 nJ/m with proton assignment. The Coulomb potential, measured either within the layer or parallel to the layer, has a distinct negative trend near the edge face that can be traced to chemisorbed water molecules. Finally, the correlation between proton Coulomb potentials at the edge face and the coordination environment of the protons is poor, obscured by long-range interactions.

Aviation passenger screening has been used worldwide to mitigate the translocation risk of SARS-CoV-2. We present a model that evaluates factors in screening strategies used in air travel and assess their relative sensitivity and importance in identifying infectious passengers. We use adapted Monte Carlo simulations to produce hypothetical disease timelines for the Omicron variant of SARS-CoV-2 for travelling passengers. Screening strategy factors assessed include having one or two RT-PCR and/or antigen tests prior to departure and/or post-arrival, and quarantine length and compliance upon arrival. One or more post-arrival tests and high quarantine compliance were the most important factors in reducing pathogen translocation. Screening that combines quarantine and post-arrival testing can shorten the length of quarantine for travelers, and variability and mean testing sensitivity in post-arrival RT-PCR and antigen tests decrease and increase with the greater time between the first and second post-arrival test, respectively. This study provides insight into the role various screening strategy factors have in preventing the translocation of infectious diseases and a flexible framework adaptable to other existing or emerging diseases. Such findings may help in public health policy and decision-making in present and future evidence-based practices for passenger screening and pandemic preparedness.

Wastewater-based epidemiology (WBE) has proven to be a powerful tool for the population-level monitoring of pathogens, particularly severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). For assessment, several wastewater sampling regimes and methods of viral concentration have been investigated, mainly targeting SARS-CoV-2. However, the use of passive samplers in near-source environments for a range of viruses in wastewater is still under-investigated. To address this, near-source passive samples were taken at four locations targeting student hall of residence. These were chosen as an exemplar due to their high population density and perceived risk of disease transmission. Viruses investigated were SARS-CoV-2 and its variants of concern (VOCs), influenza viruses, and enteroviruses. Sampling was conducted either in the morning, where passive samplers were in place overnight (17 h) and during the day, with exposure of 7 h. We demonstrated the usefulness of near-source passive sampling for the detection of VOCs using quantitative polymerase chain reaction (qPCR) and next-generation sequencing (NGS). Furthermore, several outbreaks of influenza A and sporadic outbreaks of enteroviruses (some associated with enterovirus D68 and coxsackieviruses) were identified among the resident student population, providing evidence of the usefulness of near-source, in-sewer sampling for monitoring the health of high population density communities.