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Diagonalization‑Based Parallel‑in‑Time Preconditioners for Instationary Fluid Flow Control Problems
No full textWe derive a new parallel-in-time approach for solving large-scale optimization problems constrained by time-dependent partial differential equations arising from fluid dynamics. The solver involves the use of a block circulant approximation of the original matrices, enabling parallelization-in-time via the use of fast Fourier transforms, and we devise bespoke matrix approximations which may be applied within this framework. These make use of permutations, saddle-point approximations, commutator arguments, as well as inner solvers such as the Uzawa method, Chebyshev semi-iteration, and multigrid. Theoretical results underpin our strategy of applying a block circulant strategy, and numerical experiments demonstrate the effectiveness and robustness of our approach on Stokes and Oseen problems. Noteably, satisfying results for the strong and weak scaling of our methods are provided within a fully parallel architecture
ImpactLens: Using AI and Data to Communicate Research Impact Effectively
No full textAlthough the impact science has on society is a dimension that has been receiving increasing attention in recent years, surprisingly little work has been done on developing soft- ware tools that track it systematically by integrating information from different data sources and trying to capture all of its dimensions explicitly (e.g. impact on the economy, health and wellbeing, public understanding, the environment etc).In this paper, we present the prototypical ImpactLens system, which aims to leverage modern-day data-driven and AI technologies to extract ‘impact stories’ from rich, yet diverse data sources. We argue that the development of such tools can significantly enhance the ability of research communities to communicate the value of their work to society, while also pro- viding opportunities to benefit researcher development, strategic research planning, and better exploitation of research results
Assessment of hepatic steatosis and liver stiffness using transient elastography in late pregnancy: a cross-sectional study
No full textBackgroundSteatotic liver disease is increasingly affecting younger individuals and women of reproductive age. Pregnancy provides an opportunity to identify maternal disease predispositions and to apply preventive interventions. The aim of this study was to establish reference ranges for vibration controlled transient elastography (VCTE) measurements in pregnancy and to examine factors associated with the presence of steatotic liver disease.MethodsIn this cross-sectional study, pregnant women were prospectively recruited at Harris Birthright Research Centre (London, UK) between 35 weeks and 36 weeks and 6 days of gestation. Women with a history of chronic liver disease, alcohol consumption of more than 14 units per week before pregnancy, multifetal gestation, or major fetal abnormalities were excluded. Controlled attenuation parameters (CAPs) and liver stiffness measurements (LSMs) were recorded using a FibroScan. Cutoffs for non-pregnant populations were used to determine the prevalence of hepatic steatosis (CAP ≥248 dB/m) and increased liver stiffness (LSM ≥6 kPa). The 90th percentile of each parameter was used to establish gestational cutoffs, and these values were used to investigate determinants of disease through multiple linear and logistic regression analyses.FindingsBetween Oct 1, 2023, and Jan 31, 2025, 5088 pregnant women were included. 501 (9·8%) of 5088 women had steatosis and 768 (23·2%) had increased liver stiffness according to the cutoffs for non-pregnant populations. The 90th percentile for CAP was 247 dB/m and for LSM was 6·8 kPa. In multivariable analysis using the gestational cutoffs, the factors associated with steatosis were history of type 2 diabetes (odds ratio 3·93, 95% CI 1·09–14·01) and weight in early pregnancy (1·05, 1·05–1·06). Factors associated with increased liver stiffness were type 1 diabetes (8·20, 2·37–26·40), type 2 diabetes (4·28, 1·29–13·40), pre-eclampsia (1·86, 1·19–2·82), and weight in early pregnancy (1·07, 1·01–1·14).InterpretationOur results suggest that obesity, pregestational diabetes, and pre-eclampsia might be associated with hepatic steatosis or increased liver stiffness in pregnancies assessed with VCTE, although due to the single-centre nature of our study, these findings need replication in larger multicentre studies. Future longitudinal studies targeting these subgroups are also needed to better understand the natural course of hepatic changes throughout pregnancy, the prognostic value of VCTE, and to evaluate postnatal interventions that could improve long-term liver health
Ethical tensions:Problematising the duality of community-embedded researcher identity in the REALITIES project
Get PDFCommunity-based research (CBR) is increasingly used when investigating experiences of those whose voices are historically marginalised. REALITIES (Researching Evidence-based Alternatives in Living, Imaginative, Traumatised, Integrated, Embodied Systems in health disparities) takes a CBR approach to understand and re-imagine systems of health and social care so that they might better meet the needs of those under-served groups who most need them. Focused on five place-based community ‘hubs’ across Scotland, Community-Embedded Researchers (CERs) gather data arising through everyday practices of the organisations in which they are situated. These CERs occupy a dual role of organisational worker and researcher. This paper draws on reflections of CERs focused on challenges of navigating issues of autonomy, vulnerability and power arising from this dual identity as they undertake the research. We argue that the positionality of the CER as organisational worker who then takes forward an additional researcher identity, creates complexity that is beyond such concepts as of participant-observer. CERs draw on their relational skills and values to navigate these situations, each of which is contextually situated. We conclude that alongside existing toolkits it is necessary to encourage those engaging with similar research to focus on a range of questions to surface and enable discussion of potential relational challenges. The centrality of relational skills and judgement highlights the need for researcher support through training and ongoing reflective discussion of challenges experienced
Adaptive Vessel Navigation for Purse Seine Fishing Net Deployment
Get PDFThis paper presents an innovative framework for adaptive navigation of purse-seine vessels during the deployment of fishing nets. Firstly, the framework leverages geometry based real-time fish net shape estimation using sparse acoustic and GPS positioning sensors embedded within the net. This shape estimation is then utilized to predict the optimal path for vessel navigation, ensuring efficient and precise net deployment. By integrating real-time observations and graphical optimization techniques, the proposed method addresses practical challenges in uncertain marine environments such as adapting the navigation path plan to the inherent variability in fish school behaviour and ocean currents. The approach is validated through simulated fishing net deformation scenarios with Blender software, demonstrating its capability to maintain the operational efficiency and adaptation to environmental uncertainties
Pallas:A Data-Plane-Only Approach to Accurate Persistent Flow Detection on Programmable Switches in High-Speed Networks
Get PDFIn high-speed data center networks, persistent flows are repeatedly observed over extended periods, potentially signaling threats such as stealthy DDoS or botnet attacks. Monitoring every flow in production-grade hardware switches that feature limited memory, however, is challenging under typical high flow rates and data volumes. To tackle this, approximate data structures, like sketches, are often employed. Yet many existing methods rely on per-time-window flag resets, which require frequent control-plane interventions that make them unsuitable for high-speed traffic. This paper introduces Pallas, a fully data-plane-implementable sketch for detecting persistent flows in high-speed networks with high accuracy, obviating the need for time-window-based resets. We further propose Opt-Pallas, an enhanced variant of Pallas that improves detection accuracy by incorporating flow arrival patterns. We present a rigorous error bound analysis for both Pallas and Opt-Pallas, along with extensive performance evaluations using a P4-based prototype on an Intel Tofino switch. Pallas scales persistent flow detection to line-rate capacity, while state-of-the-art solutions fail to operate beyond a few Mbps. Our results show that Pallas and Opt-Pallas can accurately detect persistent flows in traffic volumes over 60× higher than those handled by the best existing approach. Additionally, even under low-speed traffic, Pallas and Opt-Pallas achieve 4.21% and 7.85% higher lookup accuracy while consuming only 8.5% and 9.7% of switch resources, respectively. Extensive trace-driven results on a CPU platform further validate the high detection accuracy of Opt-Pallas compared to existing methods
Mifepristone alone and in combination with scAAV9-SMN1 gene therapy improves disease phenotypes in Smn2B/- spinal muscular atrophy mice
Get PDFSpinal muscular atrophy (SMA) is a neuromuscular disease caused by deletions or mutations in the survival motor neuron 1 (SMN1) gene. SMA is characterised by alpha motor neuron loss in the spinal cord and subsequent muscle atrophy. There are currently three approved SMN-directed therapies for SMA patients. While these therapies have transformed what was once a life-limiting condition into one that can be managed and even improved, they are unfortunately not cures, highlighting the need for additional supporting second-generation therapies. These should not only target the neuromuscular system but also peripheral and metabolic perturbations that are present in both SMA models and patients. Krüppel-like factor 15 (Klf15) is a transcription factor that maintains metabolic homeostasis, is involved in the glucocorticoid-glucocorticoid receptor (GR) signalling pathway and is dysregultated in several peripheral and metabolic tissues in SMA mice. Here, we used murine and human cellular models as well as SMA mice and Caenorhabditis Elegans (C. elegans) to assess the therapeutic potential of reducing Klf15 activity with mifepristone, a glucocorticoid antagonist, combined with a SMN-targeted gene therapy. We report that mifepristone reduces Klf15 expression across several in vitro models, ameliorates neuromuscular pathology in SMA smn-1(ok355) C. elegans and improves survival of SMA Smn2B/- mice. Furthermore, we show that combining mifepristone with an approved SMN-directed gene therapy (scAAV9-SMN1) results in improved tissue- and sex-specific responses to treatment. Our study demonstrates that a multi-tissue targeting SMN-independent drug, alone and in combination with an approved SMN-dependent therapy, has the potential to improve SMA disease pathology
Addressing biases in sliding window analysis gives new insight into the response of parturition date to weather in a wild mammal
Get PDFAnimal breeding phenology in temperate and high latitude regions is often predicted by weather variables, such as temperature. Much work on this topic has focused on taxonomic groups that employ adaptive plastic responses to annual variation in an environmental cue, with analytical approaches developed to determine when weather has an effect and the magnitude of response. However, adaptive responses are not always likely, so it is important to consider the assumptions and limitations of an approach when analysing similar questions in distinct taxonomic groups. The prolonged period between conception and birth means parturition date in seasonally breeding ungulates, such as red deer, is unlikely to show adaptive plastic responses to variation in weather. Prior studies of red deer on the Isle of Rum, Scotland, have documented that parturition date is sensitive to summer temperature and getting earlier over time, while birth weight is sensitive to spring temperature but shows no temporal trend. Here, we reinvestigate this topic with updated statistical methods to establish confidence in previous results by deploying two approaches: permutations, combatting anti-conservative aspects of sliding window analyses, and detrending, a valuable tool for weather attribution studies containing temporal trends. Incorporating detrending within the sliding window analyses of parturition date identified a different window as best fitting with a shallower temperature slope estimate compared to sliding windows that did not detrend. Permutations then showed all our parturition date results could be achieved by chance. In contrast, and consistent with earlier work, birth weight was predicted by spring temperature. Our novel results regarding the environmental sensitivity of parturition date in red deer suggest a lack of plasticity in response to weather and highlight the distinction between the phenology of mammals with long gestations and many more commonly studied taxa. We encourage the use of permutations and detrending within sliding window analyses when a trait shows temporal trends, to prevent inaccurate windows and effect sizes being identified
Political leaders’ role in Latin American foreign policy:A systematic review
Get PDFThis article systematically reviews the current state of Foreign Policy Analysis (FPA) in Latin America, focusing on political leaders, especially presidents, highlighting the region’s significant but often overlooked contributions to the field. It analyses scholarly articles from both Western and Latin American journals to explore who is involved in the decision-making process, the elements that shape decision-making, and the types of decisions analysed in the region. Additionally, the review sheds light on where the knowledge originates and where it is published, underscoring the underrepresentation of Latin American perspectives in International Relations literature. It concludes by stressing the advancements in regional FPA research and the importance of integrating these diverse Latin American viewpoints to enhance the field, as the region offers rich empirical data that supports theory-building and comparative analysis
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