The fast and the frame-dragging: efficient waveforms for asymmetric-mass eccentric equatorial inspirals into rapidly-spinning black holes

Observations of gravitational-wave signals emitted by compact binary inspirals provide unique insights into their properties, but their analysis requires accurate and efficient waveform models. Intermediate- and extreme-mass-ratio inspirals (I/EMRIs), with mass ratios q≳102, are promising sources for future detectors such as the Laser Interferometer Space Antenna (LISA). Modelling waveforms for these asymmetric-mass binaries is challenging, entailing the tracking of many harmonic modes over thousands to millions of cycles. The FastEMRIWaveforms (FEW) modelling framework addresses this need, leveraging precomputation of mode data and interpolation to rapidly compute adiabatic waveforms for eccentric inspirals into zero-spin black holes. In this work, we extend FEW to model eccentric equatorial inspirals into black holes with spin magnitudes |a|≤0.999. Our model supports eccentricities e<0.9 and semi-latus recta p<200, enabling the generation of long-duration IMRI waveforms, and produces waveforms in ∼100 ms with hardware acceleration. Characterising systematic errors, we estimate that our model attains mismatches of ∼10−5 (for LISA sensitivity) with respect to error-free adiabatic waveforms over most of parameter space. We find that kludge models introduce errors in signal-to-noise ratios (SNRs) as great as +60%−40% and induce marginal biases of up to ∼1σ in parameter estimation. We show LISA's horizon redshift for I/EMRI signals varies significantly with a, reaching a redshift of 3 (15) for EMRIs (IMRIs) with only minor (∼10%) dependence on e for an SNR threshold of 20. For signals with SNR ∼50, spin and eccentricity-at-plunge are measured with uncertainties of δa∼10−7 and δef∼10−5. This work advances the state-of-the-art in waveform generation for asymmetric-mass binaries

Multi-criteria decision making: sustainable water desalination

With an increasingly more urbanised global population, surface water and groundwater resources are being/have become outpaced by growing demand. The oceans could address this pertinent scarcity issue, once their high-salinity content is removed. Water desalination could thus be a crucial pathway towards addressing global water scarcity. However, conventional desalination is known to be highly energy-intensive, with limited scalability and potentially significant negative environmental impacts. Multi-criteria Decision Making (MCDM) presents a novel approach towards sustainable water desalination based on sustainability-related criteria. The Fuzzy Analytical Hierarchy Process (FAHP) was implemented to determine the most optimal small-scale, modularised, and remote reverse osmosis (RO) desalination plant configurations. Twelve configurations were assessed, based on four plant capacities (50, 100, 150, and 200 m3/day) and three diesel-to-solar photovoltaic energy configurations (100–0%, 75–25%, and 60–40%). The hybridised diesel-to-solar configurations were generally ranked higher, particularly when less reliant on diesel, and at small(er) capacities, in terms of the criteria: sustainability, overall efficiency, and standalone potential while maintaining competitive costs. This can likely be attributed to their relatively lower fuel and energy consumption and associated costs. Further research should aim to consider additional criteria, such as battery cost, as well as life cycle assessments that include transportation-related costs/emissions

Holistically green and sustainable pathway prioritisation for chemical process plant systems via a FAHP-TOPSIS framework

Multi-criteria Decision Making (MCDM) presents a novel approach towards truly holistic green sustainability, particularly within the context of chemical process plants (CPPs). ASPEN Plus v12.0 was utilised for two representative CPP cases: isopropanol (IPA) production via isopropyl acetate, and green ammonia (NH3) production. An integrated Fuzzy Analytic Hierarchy Process (FAHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was modelled in MATLAB v24.1 to prioritise the holistically green and sustainable pathways. Life cycle assessments (LCAs) were employed to select the pathways, and the most suitable sub-criteria per the four criteria are as follows: social, economic, environmental, and technical. In descending order of optimality, the pathways were ranked as follows for green NH3 and IPA, respectively: Hydropower (HPEA) > Wind Turbine (WGEA) > Biomass Gasification (BGEA)/Solar Photovoltaic (PVEA) > Nuclear High Temperature (NTEA), and Propylene Indirect Hydration (IAH) > Direct Propylene Hydration (PH) > Acetone Hydrogenation (AH). Sensitivity analysis evaluated the FAHP–TOPSIS framework to be overall robust. However, there are potential uncertainties within and/or among sub-criteria, particularly in the social dimension, due to software and data limitations. Future research would seek to integrate FAHP with VIKOR and the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE-II)

Can a portable flash visual evoked potential (VEP) device identify chiasmal decussation anomalies in albinism?

Background: visual evoked potentials (VEPs) are used to detect chiasmal misrouting associated with albinism. However, VEPs are only performed in specialist centres and typically have long waiting lists. The portable electrophysiology device RETeval® shows promise as a clinical screening tool across a range of ophthalmic conditions. Here, we explore its utility in detecting chiasmal abnormalities associated with albinism. Methods: flash VEPs were recorded on the RETeval® and by standard ISCEV techniques for 27 patients with suspected albinism and 40 control patients as part of routine appointments. We retrospectively investigated the agreeability between the two methods. The amplitude/latency of the main component was measured for standard VEPs whilst a correlation value of interhemispheric difference was calculated for the RETeval® data.Results: we demonstrate a significant difference between albinism patients and controls (p < 0.001) with respect to the interhemispheric difference identified by the RETeval®. By applying a threshold of 0.001865 to the correlation value, the RETeval® detected chiasmal misrouting in all 27 patients with albinism and had 97% agreeability to standard testing. Conclusions: this study shows the potential of using the RETeval® as a clinical tool for the diagnosis of chiasmal anomalies in albinism. The RETeval® has significant time/cost savings which could hasten diagnoses

Uncertainty modelling in under-represented languages with Bayesian deep Gaussian processes

NLP models often face challenges with underrepresented languages due to a lack of sufficient training data and language complexities. This can result in inaccurate predictions and a failure to capture the inherent uncertainties within these languages. This paper introduces a new method for modelling uncertainty in under-represented languages by employing deep Bayesian Gaussian Processes. We develop a novel framework that integrates prior knowledge and leverages kernel functions. This helps enable the quantification of uncertainty in predictions to overcome the data limitations in under-represented languages. The efficacy of our approach is validated through various experiments, and the results are benchmarked against existing methods to highlight the enhancements in prediction accuracy and measurement of uncertainty.</p

Robust iterative learning control for unstable MIMO systems

Iterative learning control (ILC) is a well-established technique to successively improve tracking accuracy for systems that repeatedly perform the same task. Most current literature imposes constraints on the nature of the system, such as requiring it to be full-rank, or inherently stable. This paper presents a generalised ILC framework that can handle non-linear, unstable, MIMO systems with rank deficiency. This involves the minimisation of a cost function that balances tracking performance and input effort, extending previous approaches to include a 'robustness filter' within the optimisation. Gap metric analysis is then applied to examine the robustness of the resulting system, with performance bounds derived for both serial and parallel ILC architectures. A design procedure is presented that allows the designer to transparently trade-off robustness and convergence properties. The design framework is illustrated via application to the inverted pendulum problem, a classic example of a highly nonlinear, unstable, and under-actuated system

Gene-environment interaction affects risk of atopic eczema: population and in vitro studies

Background: multiple environmental and genetic factors play a role in the pathogenesis of atopic eczema (AE). We aimed to investigate gene–environment interactions (G × E) to improve understanding of the pathophysiology. Methods: we analysed data from 16 European studies to test for interaction between the 24 most significant AE-associated loci identified from genome-wide association studies and 18 early-life environmental factors. We tested for replication using a further 10 studies and in vitro modeling to independently assess findings. Results: the discovery analysis (including 25,339 individuals) showed suggestive evidence for interaction (p &lt; 0.05) between seven environmental factors (antibiotic use, cat ownership, dog ownership, breastfeeding, elder sibling, smoking and washing practices) and at least one established variant for AE, 14 interactions in total. In the replication analysis (254,532 individuals) dog exposure × rs10214237 (on chromosome 5p13.2 near IL7R) was nominally significant (OR interaction = 0.91 [0.83–0.99] p = 0.025), with a risk effect of the T allele observed only in those not exposed to dogs. A similar interaction with rs10214237 was observed for siblings in the discovery analysis (OR interaction = 0.84 [0.75–0.94] p = 0.003), but replication analysis was under-powered (OR interaction = 1.09 [0.82–1.46]). rs10214237 homozygous risk genotype is associated with lower IL-7R expression in human keratinocytes, and dog exposure modelled in vitro showed a differential response according to rs10214237 genotype. Conclusion: interaction analysis and functional assessment provide preliminary evidence that early-life dog exposure may modify the genetic effect of rs10214237 on AE via IL7R, supporting observational epidemiology showing a protective effect for dog ownership. The lack of evidence for other G × E studied here implies only weak effects are likely to occur.</p

Emergency and routine presentation of neuroendocrine neoplasia in England: determinants of late presentation and survival outcomes

Objective: the time from onset of symptoms of neuroendocrine neoplasia (NEN) to diagnosis ranges between 5-7 years. Risk factors associated with this and the difference in overall survival (OS) between routine and emergency presentation (RP and EP) are not known.Design: a retrospective, population-based study.Methods: a retrospective, population-based study of gastroenteropancreatic and lung NEN registered on England’s national cancer between 2012 and 2021. Factors associated with worse OS, or emergency or late presentation (EP or LP), were evaluated using the Kaplan–Meier estimator, Cox and logistic regressions, and machine learning (ML) in two models.Results: a total of 21,345 NEN were included. 20.3% were EP. EP showed worse OS compared to RP. Factors associated with EP were male sex, advanced stage, worse deprivation, and NEC. The ML model showed EP related to advanced stage, small intestinal NEN, NEC, advanced age, deprivation, and male sex in decreasing order of importance. Factors associated with LP includedEP, male sex, and NEC. The ML model showed NEC, small intestinal NEN, advanced age, EP, and male sex are associated with LP in decreasing order of importance.Conclusion: EP is associated with poor survival. Addressing the associated factors may aid in timely diagnosis and improved surviva

State responsiveness, collective efficacy and threat perception: Catalyst and complacency effects in opposition to crime across eight countries.

Collective action can be a crucial tool for enabling individuals to combat crime in their communities. In this research, we investigated individuals' intentions to mobilize against organized crime, a particularly impactful form of crime characterized by its exercises of power over territories and communities. We focused on individuals' views and perceptions of state authorities, examining how these views may be linked to intentions for collective mobilization. Using a large dataset with participants from eight countries (NTotal = 2088), we tested two distinct and opposing indirect paths through which perceived state responsiveness may be associated with collective mobilization intentions against organized crime, namely increased collective community efficacy (a CatalystIndirect Effect) and diminished perceived threat from criminal groups (a Complacency Indirect Effects). Results showed that state responsiveness was associated with stronger collective action intentions through increased collective community efficacy. There was also some evidence of reduced collective action intentions through diminished perceived threat. These findings highlight the complex role of state responsiveness in predicting people's intentions to mobilize against collective problems in their communities. Implications of the findings, limitations and future directions are discussed

Lost in turbulence? Healthcare workers’ conceptualisations and experiences with navigating time in personalised care

Purpose: The study aims to explore how healthcare workers (HCWs) navigate and experience time when caring for older cancer patients living with other illnesses. Design/methodology/approach: This paper presents findings from a qualitative study of how HCWs conceptualise and navigate the temporal aspects of delivering personalised care to older people living with multimorbidity. Building on research from organisation studies and the sociology of time, we interviewed 19 UK HCWs about their experiences of delivering care to this patient group. Findings: Our findings illustrate how the delivery of personalised care contradicts contemporary models for healthcare delivery defined by efficiency and standardisation. We found that HCWs engage with time as both a valuable commodity to be rationed and prioritised within a constrained context and as a malleable resource for managing workload and overcoming “turbulence” in the system. However, participants in this study also shared how the simultaneous multiplicity and lack of time had a profoundly personal impact on them through the emotional toll associated with “time debt” and “lost” time. Originality/value: This research presents a unique analysis of how time is conceptualised and navigated in contemporary healthcare, offering valuable insights for policy improvement. We conclude that personalised models of healthcare are incompatible with many current temporal structures of treatment trajectories and work-practices, by nature of being centred around the person and not the system of delivery.</p