Stokes flows in a 2D bifurcation

The flow network model is an established approach to approximate pressure-flow relationships in a network, which has been widely used in many contexts. However, little is known about the impact of bifurcation geometry on such approximations, so the existing models mostly rely on unidirectional flow assumption and Poiseuille's law, and thus neglect the flow details at each bifurcation. In this work, we address these limitations by computing Stokes flows in a 2D bifurcation using LARS (Lightning-AAA Rational Stokes), a novel mesh-free algorithm for solving 2D Stokes flow problems utilising an applied complex analysis approach based on rational approximation of the Goursat functions. Using our 2D bifurcation model, we show that the fluxes in two child branches depend on not only pressures and widths of inlet and outlet branches, as most previous studies have assumed, but also detailed bifurcation geometries (e.g. bifurcation angle), which were not considered in previous studies. The 2D Stokes flow simulations allow us to represent the relationship between pressures and fluxes of a bifurcation using an updated flow network, which considers the bifurcation geometry and can be easily incorporated into previous flow network approaches. The errors in the flow conductance of a channel in a bifurcation approximated using Poiseuille's law can be greater than 16%, when the centreline length is twice the inlet channel width and the bifurcation geometry is highly asymmetric. In addition, we present details of 2D Stokes flow features, such as flow separation in a bifurcation and flows around fixed objects at different locations, which previous flow network models cannot capture. These findings suggest the importance of incorporating detailed flow modelling techniques alongside existing flow network approaches when solving complex flow problems

Stokes flows in a 2D bifurcation

The flow network model is an established approach to approximate pressure-flow relationships in a network, which has been widely used in many contexts. However, little is known about the impact of bifurcation geometry on such approximations, so the existing models mostly rely on unidirectional flow assumption and Poiseuille's law, and thus neglect the flow details at each bifurcation. In this work, we address these limitations by computing Stokes flows in a 2D bifurcation using LARS (Lightning-AAA Rational Stokes), a novel mesh-free algorithm for solving 2D Stokes flow problems utilising an applied complex analysis approach based on rational approximation of the Goursat functions. Using our 2D bifurcation model, we show that the fluxes in two child branches depend on not only pressures and widths of inlet and outlet branches, as most previous studies have assumed, but also detailed bifurcation geometries (e.g. bifurcation angle), which were not considered in previous studies. The 2D Stokes flow simulations allow us to represent the relationship between pressures and fluxes of a bifurcation using an updated flow network, which considers the bifurcation geometry and can be easily incorporated into previous flow network approaches. The errors in the flow conductance of a channel in a bifurcation approximated using Poiseuille's law can be greater than 16%, when the centreline length is twice the inlet channel width and the bifurcation geometry is highly asymmetric. In addition, we present details of 2D Stokes flow features, such as flow separation in a bifurcation and flows around fixed objects at different locations, which previous flow network models cannot capture. These findings suggest the importance of incorporating detailed flow modelling techniques alongside existing flow network approaches when solving complex flow problems

The Stony Brook / SMARTS Atlas of mostly Southern Novae

We introduce the Stony Brook / SMARTS Atlas of (mostly) Southern Novae. This atlas contains both spectra and photometry obtained since 2003. The data archived in this atlas will facilitate systematic studies of the nova phenomenon and correlative studies with other comprehensive data sets. It will also enable detailed investigations of individual objects. In making the data public we hope to engender more interest on the part of the community in the physics of novae. The atlas is on-line at \url{http://www.astro.sunysb.edu/fwalter/SMARTS/NovaAtlas/} .Comment: 11 figures; 5 table

The association between antihypertensive treatment and serious adverse events by age and frailty: A cohort study

BACKGROUND: Antihypertensives are effective at reducing the risk of cardiovascular disease, but limited data exist quantifying their association with serious adverse events, particularly in older people with frailty. This study aimed to examine this association using nationally representative electronic health record data. METHODS AND FINDINGS: This was a retrospective cohort study utilising linked data from 1,256 general practices across England held within the Clinical Practice Research Datalink between 1998 and 2018. Included patients were aged 40+ years, with a systolic blood pressure reading between 130 and 179 mm Hg, and not previously prescribed antihypertensive treatment. The main exposure was defined as a first prescription of antihypertensive treatment. The primary outcome was hospitalisation or death within 10 years from falls. Secondary outcomes were hypotension, syncope, fractures, acute kidney injury, electrolyte abnormalities, and primary care attendance with gout. The association between treatment and these serious adverse events was examined by Cox regression adjusted for propensity score. This propensity score was generated from a multivariable logistic regression model with patient characteristics, medical history and medication prescriptions as covariates, and new antihypertensive treatment as the outcome. Subgroup analyses were undertaken by age and frailty. Of 3,834,056 patients followed for a median of 7.1 years, 484,187 (12.6%) were prescribed new antihypertensive treatment in the 12 months before the index date (baseline). Antihypertensives were associated with an increased risk of hospitalisation or death from falls (adjusted hazard ratio [aHR] 1.23, 95% confidence interval (CI) 1.21 to 1.26), hypotension (aHR 1.32, 95% CI 1.29 to 1.35), syncope (aHR 1.20, 95% CI 1.17 to 1.22), acute kidney injury (aHR 1.44, 95% CI 1.41 to 1.47), electrolyte abnormalities (aHR 1.45, 95% CI 1.43 to 1.48), and primary care attendance with gout (aHR 1.35, 95% CI 1.32 to 1.37). The absolute risk of serious adverse events with treatment was very low, with 6 fall events per 10,000 patients treated per year. In older patients (80 to 89 years) and those with severe frailty, this absolute risk was increased, with 61 and 84 fall events per 10,000 patients treated per year (respectively). Findings were consistent in sensitivity analyses using different approaches to address confounding and taking into account the competing risk of death. A strength of this analysis is that it provides evidence regarding the association between antihypertensive treatment and serious adverse events, in a population of patients more representative than those enrolled in previous randomised controlled trials. Although treatment effect estimates fell within the 95% CIs of those from such trials, these analyses were observational in nature and so bias from unmeasured confounding cannot be ruled out. CONCLUSIONS: Antihypertensive treatment was associated with serious adverse events. Overall, the absolute risk of this harm was low, with the exception of older patients and those with moderate to severe frailty, where the risks were similar to the likelihood of benefit from treatment. In these populations, physicians may want to consider alternative approaches to management of blood pressure and refrain from prescribing new treatment

Exile Vol. XXXVII No. 1

And It Was Sunday by Julie Gruen 1-6 Like a Lady by Grace Mulvihill 7 The Final You by Eric Franzon 8 Joseph\u27s Children by Seneca Murley 9 Ain\u27t the 1950s Anymore by Ellen Stader 10-12 Bonding Women by Shannon salser 13 Ice Man (for mami 1905-1975) by Anne Mulligan 14 The Car Salesman by Tom Ream 15 Cancelling the Bunny by Stewart Engesser 16-17 Richard Brautigan\u27s Body by Michael Payne 18-19 Dinner in Barcelona by Holly Kurtz 20 Untitled by Margaret Strachen 21 Candles by Eric Franzon 22 Summer Rules by Jim Cox 23-31 My Boat by Holly Kurtz 32 Untitled by Michael Payne 33 Half the Birds in the City by Tiffany Richardson 34-35 Down Queen Anne Hill by Julie Gruen 36-37 Your Music by Tim Emrick 38 Zephyrs by Steve Corinth 39-41 Mother by Anne Mulligan 42 As I Look to the Sky, Maize by Shannon Salser 43-45 Close Book before Striking by Sarah Verdon 46-47 Smoked by Tom Ream 48 Driving through Rain by Stewart Engesser 49-50 Contributors 51 Editorial decision is shared equally among the Editorial Board. -i 35th Yea

Machine learning-enabled maternal risk assessment for women with pre-eclampsia (the PIERS-ML model): a modelling study.

Affecting 2-4% of pregnancies, pre-eclampsia is a leading cause of maternal death and morbidity worldwide. Using routinely available data, we aimed to develop and validate a novel machine learning-based and clinical setting-responsive time-of-disease model to rule out and rule in adverse maternal outcomes in women presenting with pre-eclampsia. We used health system, demographic, and clinical data from the day of first assessment with pre-eclampsia to predict a Delphi-derived composite outcome of maternal mortality or severe morbidity within 2 days. Machine learning methods, multiple imputation, and ten-fold cross-validation were used to fit models on a development dataset (75% of combined published data of 8843 patients from 11 low-income, middle-income, and high-income countries). Validation was undertaken on the unseen 25%, and an additional external validation was performed in 2901 inpatient women admitted with pre-eclampsia to two hospitals in south-east England. Predictive risk accuracy was determined by area-under-the-receiver-operator characteristic (AUROC), and risk categories were data-driven and defined by negative (-LR) and positive (+LR) likelihood ratios. Of 8843 participants, 590 (6·7%) developed the composite adverse maternal outcome within 2 days, 813 (9·2%) within 7 days, and 1083 (12·2%) at any time. An 18-variable random forest-based prediction model, PIERS-ML, was accurate (AUROC 0·80 [95% CI 0·76-0·84] vs the currently used logistic regression model, fullPIERS: AUROC 0·68 [0·63-0·74]) and categorised women into very low risk (-LR 0·2 and +LR 10·0; 11 [1·0%] women). Adverse maternal event rates were 0% for very low risk, 2% for low risk, 5% for moderate risk, 26% for high risk, and 91% for very high risk within 48 h. The 2901 women in the external validation dataset were accurately classified as being at very low risk (0% with outcomes), low risk (1%), moderate risk (4%), high risk (33%), or very high risk (67%). The PIERS-ML model improves identification of women with pre-eclampsia who are at lowest and greatest risk of severe adverse maternal outcomes within 2 days of assessment, and can support provision of accurate guidance to women, their families, and their maternity care providers. University of Strathclyde Diversity in Data Linkage Centre for Doctoral Training, the Fetal Medicine Foundation, The Canadian Institutes of Health Research, and the Bill & Melinda Gates Foundation. [Abstract copyright: Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license