922017 research outputs found
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Efficient Approximation of Expected Hypervolume Improvement using Gauss-Hermite Quadrature
No full textMany methods for performing multi-objective optimisation of computationally expensive problems have been proposed recently. Typically, a probabilistic surrogate for each objective is constructed from an initial dataset. The surrogates can then be used to produce predictive densities in the objective space for any solution. Using the predictive densities, we can compute the expected hypervolume improvement (EHVI) due to a solution. Maximising the EHVI, we can locate the most promising solution that may be expensively evaluated next. There are closed-form expressions for computing the EHVI, integrating over the multivariate predictive densities. However, they require partitioning the objective space, which can be prohibitively expensive for more than three objectives. Furthermore, there are no closed-form expressions for a problem where the predictive densities are dependent, capturing the correlationsbetween objectives. Monte Carlo approximation is used instead in such cases, which is not cheap. Hence, the need to develop new accurate but cheaper approximation methods remains. Here we investigate an alternative approach toward approximating the EHVI using Gauss-Hermite quadrature.We show that it can be an accurate alternative to Monte Carlo for both independent and correlated predictive densities with statistically signicant rank correlations for a range of popular test problems
Investigating the shared genetic architecture of uterine leiomyoma and breast cancer: a genome-wide cross-trait analysis
No full textLittle is known regarding the shared genetic architecture or causality underlying the phenotypic association observed for uterine leiomyoma (UL) and breast cancer (BC). Leveraging summary statistics from the hitherto largest genome-wide association study (GWAS) conducted in each trait, we investigated the genetic overlap and causal associations of UL with BC overall, as well as with its subtypes defined by the status of estrogen receptor (ER). We observed a positive genetic correlation between UL and BC overall (r_g = 0.09, P = 6.00×10-3), which was consistent in ER+ subtype (r_g = 0.06, P = 0.01) but not in ER subtype (r_g = 0.06, P = 0.08). Partitioning the whole genome into 1,703 independent regions, local genetic correlation was identified at 22q13.1 for UL with BC overall and with ER+ subtype. Significant genetic correlation was further discovered in 9 out of 14 functional categories, with the highest estimates observed in coding, H3K9ac, and repressed regions. Cross-trait meta-analysis identified 9 novel loci shared between UL and BC. Mendelian randomization demonstrated a significantly increased risk of BC overall (OR = 1.09, 95% CI = 1.01-1.18) and ER+ subtype (OR = 1.09, 95% CI = 1.01-1.17) for genetic liability to UL. No reverse causality was found. Our comprehensive genome-wide cross-trait analysis demonstrates a shared genetic basis, pleiotropic loci, as well as a putative causal relationship between UL and BC, highlighting an intrinsic link underlying these two complex female diseases
Control flow graph, formal verification and constraint programming techniques
No full textFormal program verification is a generally undecidable problem. Bounded Model Checking (BMC) is one method that can achieve decidability by searching for violations of properties of a program up to a bound k. BMC reduces the program verification problem to the classic NP-complete Boolean Satisfiability (SAT). However, it can still lead to an exponential state-space exploration due to the program’s large and possibly unbounded loops. In this case, there might be many execution paths to traverse through a program during its symbolic execution. Therefore, the control flow or computation during the program’s execution, mainly in symbolic execution, can be represented as a directed graph named Control Flow Graph (CFG). In this work, we present the properties of the CFG and discuss the application of constraint programming techniques to reduce variable domains as a preprocessing step or during the BMC process for verifying software systems. We also describe how constraint programming can be exploited to prove the (partial) correctness of the program via proof by induction built on top of BMC
Obstetric Outcomes in Women with Rheumatic Disease and COVID-19 in the Context of Vaccination Status
No full textObjective:To describe obstetric outcomes based on COVID-19 vaccination status, in women with rheumatic and musculoskeletal diseases (RMDs) who developed COVID-19 during pregnancy. Methods:Data regarding pregnant women entered into the COVID-19 Global Rheumatology Alliance registry from 24 March 2020 to 25 February 2022 were analysed. Obstetric outcomes were stratified by number of COVID-19 vaccine doses received prior to COVID-19 infection in pregnancy. Descriptive differences between groups were tested using the chi -square or Fisher’s exact test. Results: There were 73 pregnancies in 73 women with RMD and COVID-19. Overall, 24.7% (18) of pregnancies were ongoing, while of the 55 completed pregnancies 90.9% (50) of pregnancies resulted in livebirths. At the time of COVID-19 diagnosis, 60.3% (n=44) of women were unvaccinated, 4.1% (n=3) had received one vaccine dose while 35.6% (n=26) had two or more doses. Although 83.6% (n=61) of women required no treatment for COVID-19, 20.5% (n=15) required hospital admission. COVID-19 resulted in delivery in 6.8% (n=3) of unvaccinated women and 3.8% (n=1) of fully vaccinated women. There was a greater number of preterm births (PTB) in unvaccinated women compared to fully vaccinated 29.5% (n=13) vs 18.2%(n=2). Conclusion:In this descriptive study, unvaccinated pregnant women with RMD and COVID-19 had a greater number of PTB compared with those fully vaccinated against COVID-19. Additionally, the need for COVID-19 pharmacological treatment was uncommon in pregnant women with RMD regardless of vaccination status. These results support active promotion of COVID-19 vaccination in women with RMD who are pregnant or planning a pregnancy.<br/
Combining sparse approximate factorizations with mixed precision iterative refinement
No full textThe standard LU factorization-based solution process for linear systems can be enhanced in speed or accuracy by employing mixed precision iterative refinement. Most recent work has focused on dense systems. We investigate the potential of mixed precision iterative refinement to enhance methods for sparse systems based on approximate sparse factorizations. In doing so we first develop a new error analysis for LU- and GMRES-based iterative refinement under a general model of LU factorization that accounts for the approximation methods typically used by modern sparse solvers, such as low-rank approximations or relaxed pivoting strategies. We then provide a detailed performance analysis of both the execution time and memory consumption of different algorithms, based on a selected set of iterative refinement variants and approximate sparse factorizations. Our performance study uses the multifrontal solver MUMPS, which can exploit block low-rank (BLR) factorization and static pivoting. We evaluate the performance of the algorithms on large, sparse problems coming from a variety of real-life and industrial applications showing that the proposed approach can lead to considerable reductions of both the time and memory consumption
The Skilled Teacher: A Heideggerian Perspective on Teacher Practical Knowledge
No full textThe concept of teacher Practical Knowledge, with its emphasis on the intuitive and situated nature of teaching practice, has provided a compelling approach to understanding what underlies teaching practice. However, much of the literature around Practical Knowledge focuses on teacher reflections on their practice and leaves unexplored the question of how the situation elicits particular practices from teachers. Moreover, there is a tendency to focus on individual Practical Knowledge, and this means that the social dimension, and particularly the socially normative element, of teaching practice is perhaps underappreciated. This article develops what I call the Skilled Teacher Approach to teaching practice, which shifts the focus from teachers’ individual cognitions about practice, to what teachers directly perceive as possible in their fundamentally social teaching environment. The Skilled Teacher Approach is rooted in Heidegger’s phenomenology but also draws substantially on Enactivist literature and argues that what teachers do in practice is largely a product of the affordances they directly perceive in their practice environment. It also argues that much of the landscape of affordances that a teacher perceives is socially constructed. Consequently, a significant part of Practical Knowledge relates to a sensitivity to the socially given affordances and knowing intuitively ‘what one does’ as a teacher. This perspective offers a new understanding of teaching practice and suggests new ways of engendering positive change in practice
Heart rate variability biofeedback in Long COVID (HEARTLOC)
No full textIntroduction: Long COVID (LC) refers to symptoms persisting 12 weeks after SARS-COV-2 infection. It affects over 50 million people worldwide, causing varied symptoms including fatigue, breathlessness and palpitations Many of these symptoms can be linked to autonomic nervous system dysregulation (dysautonomia). This proof-of-concept study tests feasibility, and estimates efficacy, of a heart rate variability biofeedback (HRV-B) intervention using a standardised diaphragmatic breathing technique in LC patients.Methods and Analysis: 30 adult LC patients with symptoms of palpitations or dizziness and abnormal NASA Lean Test (NLT) are recruited from a UK COVID-19 rehabilitation service. They undertake an active 4-week HRV-B intervention using a chest strap linked to a HRV phone application while undertaking the breathing technique for 10-min twice daily. Quantitative data including HRV are gathered during the study period using Fitbit, the modified COVID-19 Yorkshire Rehabilitation Scale (C19-YRSm), Composite Autonomic Symptom Score (COMPASS 31), World Health Organisation Disability Assessment Schedule (WHODAS 2.0) and EQ-5D-5L health related quality of life measure. Quantitative data will be analysed using standard statistical tests.Results: This study is ongoing; we have preliminary data for 3 completed participants. They demonstrated mean improvement of 3.7 points (from 16.7 pre-intervention to 13 post-intervention) on C19-YRS symptom severity scale, 1.3 (from 5.3 to 4.0) on C19-YRS functional scale, and 0.6 (from 4.7 to 5.3) on C19-YRS overall health score. Average autonomic score improved by 9.6 (from 47.0 to 37.4). Mean WHODAS score improvement was 4.3 (from 28.5 to 24.2) There was improvement in HRV score and reduction in resting heart rate. Further data will be presented at conference.Conclusion: These preliminary data demonstrate that HRV-B can improve LC symptoms, autonomic symptoms, reduce disability and improve HRV
Measuring the structural complexity of music: fromstructural segmentations to the automatic evaluation of models for music generation
No full textNickel encapsulated in silicalite-1 zeolite catalysts for steam reforming of glycerol (SRG) towards renewable hydrogen production
No full textValorisation of crude glycerol via steam reforming, i.e., SRG, is a promising method to produce sustainable hydrogen. However, catalyst deactivation under harsh SRG conditions is still a main challenge which hinders the further development of practical SRG. In this work, the encapsulated Ni catalyst in siliceous silicalite-1 zeolite (Ni@Si-1) were developed to show the improved performance and enhanced anti-deactivation potentials in catalytic SRG as compared with the conventional impregnated Ni catalysts (i.e., Ni/Si-1). Importantly, the post-synthetic treatment of Ni@Si-1 using TPAOH solution formed the encapsulated Ni catalyst with the mesoporous hollow structure (i.e., Ni@HolSi-1), which demonstrate even better performance in SRG with glycerol conversion of >95%, H2 yield of ~70%, H2/CO2 molar ratio of > 2.33 and CO/CO2 molar ratio of <1 at 750 °C. Specifically, highly dispersed ultrasmall encapsulated Ni particles were retained within the hollow crystals of siliceous silicalite-1, as confirmed by XPS and HRTEM characterisation. The activation energy for glycerol conversion over Ni@HolSi-1 (i.e., Ea = ~ 19 kJ mol−1) was much lower than that of Ni/Si-1 and Ni@Si-1. 100-h longevity tests over the three catalysts were investigated at 750 °C, and the Ni@HolSi-1 catalyst exhibited an excellent stability and activity, as well as insignificant coke deposition, which could be due to the enhancement of highly dispersed yet accessible Ni NPs within the hollow Si-1 crystals. The findings of the work show the promise of the encapsulation strategy and mesoporous zeolites for developing the future reforming catalysts. <br/
Conversion of glucose to fructose over Sn and Ga-doped zeolite Y in methanol and water media
No full textIn this study, we use zeolite Y as a support for the synthesis of Sn and Ga doped zeolites aimed at the isomerization of glucose to fructose. Though these materials are inactive in water, they are active in methanol and we could ascertain a reaction pathway involving a hydride shift for the interconversion of glucose to fructose and mannose, and a Brønsted acid pathway with the formation of a methyl fructoside intermediate and its hydrolysis to fructose if water was added afterwards. By using characterizations comprising: chemisorption, XPS, XRD, HAADF-STEM and EXAFS; it was possible to demonstrate that a straightforward impregnation protocol for the preparation of our catalysts, led to Sn/Y mainly consisting of small SnO2 clusters on the external surface of the zeolite, whereas Ga/Y consisting of highly dispersed Ga species mostly inside the zeolite pores; and a catalytic activity that appears to be dominated by Brønsted acid sites