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A sparse hierarchical hp-finite element method on disks and annuli
No full textWe develop a sparse hierarchical hp-finite element method (hp-FEM) for the Helmholtz equation with variable coefficients posed on a two-dimensional disk or annulus. The mesh is an inner disk cell (omitted if on an annulus domain) and concentric annuli cells. The discretization preserves the Fourier mode decoupling of rotationally invariant operators, such as the Laplacian, which manifests as block diagonal mass and stiffness matrices. Moreover, the matrices have a sparsity pattern
independent of the order of the discretization and admit an optimal complexity factorization. The sparse hp-FEM can handle radial discontinuities in the right-hand side and in rotationally invariant Helmholtz coefficients. Rotationally anisotropic coefficients that are approximated by low-degree polynomials in Cartesian coordinates also result in sparse linear systems. We consider examples
such as a high-frequency Helmholtz equation with radial discontinuities and rotationally anisotropic coefficients, singular source terms, the time-dependent Schr¨odinger equation, and an extension to a three-dimensional cylinder domain, with a quasi-optimal solve, via the Alternating Direction Implicit (ADI) algorithm
Lung development genes, adult lung function and cardiovascular comorbidities
No full textBackground: The association between lower adult lung function and increased cardiovascular comorbidity has not been adequately explained. We investigated whether shared developmental signalling pathways, critical to lung development and repair, could partly explain it.
Methods: In UK Biobank (UKB), we performed pairwise colocalisation analysis of variants in 55 lung development genes associated with adult forced vital capacity (FVC) or forced expiratory volume in 1 s (FEV1)/FVC, to see if these are also associated with coronary heart disease (CHD), blood pressure (systolic, diastolic, hypertension), pulse pressure, Arterial Stiffness index and carotid intima-media thickness. For CHD, we meta-analysed data from UKB and the CARDIoGRAM consortium.
Results: We found that 12 of the 55 genes shared the same variant between one (or more) lung function trait and one (or more) cardiovascular trait (H4colocalisation). The direction of effects was always in keeping with our hypothesis (lower lung function–higher cardiovascular risk) for FVC, but not always for FEV1/FVC. The seven signals for hypertension and CHD all replicated nominally in the FinnGen study, while replication was poor in the China Kadoorie Biobank (CKB) study. In addition, we found a further 10 genes where genetic associations with lung function and cardiovascular traits were within the same gene but involved different variants (H3 colocalisation). Interestingly, six of all 22 genes (H4 and H3 colocalisation) were novel for cardiovascular traits; four replicated in FinnGen, three in CKB.
Conclusion: Lung function and cardiovascular traits have shared developmental pathways that may partly explain why lower lung function, especially FVC, is associated with increased cardiovascular risk
Statistical learning to identify and characterise neurodevelopmental outcomes at 2 years in babies born preterm: model development and validation using population-level data from England and Wales
No full textBackground Children born preterm face elevated risks of neurodevelopmental impairments across domains. Prior studies have relied on expert-imposed typologies within single domains. This study applies statistical learning to a national database to identify transdomain clusters and their maternal and neonatal predictors.
Methods Latent class analysis (LCA) was used to derive transdomain clusters from parent-reported visual, auditory, neuromotor, and communication impairments in preterm-born children at two years corrected age using the UK National Neonatal Research Database data (N=27,261). Replication was conducted in an independent sample from Wales (N=975). Clusters were clinically validated using cerebral palsy diagnosis, Bayley Scales of Infant and Toddler Development (3rd edition), and global neurodevelopmental delay. Random forest identified cluster-specific and shared predictors.
Findings Four homogeneous clusters were derived (silhouette score = 0.71) and replicated in Wales with high balanced accuracy (93%): (1) typically developing (84.8%), (2) communication impairments (8.4%), (3) neuro-motor impairments (4.1%), and (4) multiple neuro-morbidity (2.7%). Clusters had high clinical validity and were distinguishable by shared and cluster-specific predictors. Neonatal brain injuries were most predictive of neuro-motor and multiple neuro-morbidity clusters. Birthweight, gestational age, socio-economic deprivation, and sex were stronger predictors of the communication cluster than preterm co-morbidities.
Interpretation This study provides first evidence of the transdomain nature of neurodevelopmental impairments after preterm birth using LCA. The finding that socio-demographic and perinatal factors rather than co-morbidities increase the risk of communication impairment highlights the importance of environmental modification alongside clinical interventions. Applying data-driven approaches to routinely collected data may offer a cost-effective way to stratify at-risk children and inform targeted support strategies.
Funding
UKRI Medical Research Council
Cryo-EM structure of the conjugation H-pilus reveals the cyclic nature of the TrhA pilin
No full textConjugation, the major driver of the spread of antimicrobial resistance genes, relies on a conjugation pilus for DNA transfer. Conjugative pili, such as the F-pilus, are dynamic tubular structures, composed of a polymerized pilin, that mediate the initial donor–recipient interactions, a process known as mating pair formation (MPF). IncH are low-copy-number plasmids, traditionally considered broad host range, which are found in bacteria infecting both humans and animals. The reference IncHI1 plasmid R27, isolated from Salmonella enterica serovar Typhi, encodes the conjugative H-pilus subunit TrhA containing 74 residues after cleavage of the signal sequence. Here, we show that the H-pilus forms long filamentous structures that mediate MPF and describe its cryoelectron-microscopic (cryo-EM) structure at 2.2 Å resolution. Like the F pilus, the H-pilin subunits form helical assemblies with phospholipid molecules at a stoichiometric ratio of 1:1. While there were previous reports that the T-pilus from Agrobacterium tumefaciens was composed of cyclic subunits, three recent cryo-EM structures of the T-pilus found no such cyclization. Here, we report that the H-pilin is cyclic, with a covalent bond connecting the peptide backbone between the N and C termini. Both the cryo-EM map and mass spectrometry revealed cleavage of the last five residues of the pilin, followed by cyclization via condensation of the amine and carboxyl residues. Mutagenesis experiments revealed that loss of cyclization abolished pilus biogenesis and efficient plasmid transfer. The cyclic nature of the pilin could stabilize the pilus and may explain the high incidence of IncH plasmid dissemination
A novel machine learning-based approach to thermal integrity profiling of concrete pile foundations
No full textThermal Integrity Profiling (TIP) is a non-destructive testing technique which takes advantage of the concrete heat of hydration (HoH) to detect inclusions during the casting process. This method is becoming more popular due to its ease of application, as it can be used to predict defects in most concrete foundation structures requiring only the monitoring of temperatures. Despite its advantages, challenges remain with regard to data interpretation and analysis, as temperature is only known at discrete points within a given cross-section. This study introduces a novel method for the interpretation of TIP readings using neural networks. Training data is obtained through numerical FE simulation spanning an extensive range of soil, concrete and geometrical parameters. The developed algorithm first classifies concrete piles, establishing the presence or absence of defects. This is followed by a regression algorithm that predicts the defect size and its location within the cross-section. Additionally, the regression model provides reliable estimates for the reinforcement cage misalignment and concrete hydration parameters. To make these predictions, the proposed methodology only requires temperature data in the form standard in TIP, and so it can be seamlessly incorporated within the TIP workflows. This work demonstrates the applicability and robustness of machine learning algorithms in enhancing non-destructive TIP testing of concrete foundations, thereby improving the safety and efficiency of civil engineering projects
Diabetic ketoacidosis in pregnancy: a systematic review of the reported cases
No full textBackground:
Diabetic ketoacidosis (DKA) is a rare but serious complication that can develop during pregnancy, with up to 30% of patients presenting with euglycemia, making prompt recognition challenging. It is associated with increased perinatal mortality rates, although the exact risk of maternal mortality remains unclear. The purpose of this systematic review was to examine the available literature and provide an overview of reported cases of DKA during pregnancy.
Methods:
PubMed, Web of Science and Scopus library databases were screened from inception until January 2024. Included studies provided data on classic or euglycemic DKA during pregnancy. All study designs were considered eligible for inclusion.
Results:
We identified 66 eligible articles, which included 57 case reports and case series with individual patient data, and 9 studies without individual patient data. The mean age at diagnosis was 28.8 years, and the average gestational age at diagnosis was 29.5 weeks. The majority of women had type 1 diabetes mellitus (T1DM) (45.9%), followed by gestational diabetes (GDM) (40.5%). Most cases were classified as classic DKA (70.3%), with nearly one-third developing euglycemic DKA (29.7%). The most common trigger factors were infections (28%), followed by poor adherence to treatment (13.5%). The most frequent symptoms included nausea (32.4%), vomiting (32.4%), osmotic symptoms (21.6%), and abdominal pain (20.2%). All cases were treated with intravenous insulin and fluids. The vast majority (98.9%) of women eventually fully recovered, with only 1 reported death due to organ failure (1.3%). Intrauterine death or stillbirth occurred in one-third of cases (35.2%), including 1 instance of a twin pregnancy.
Conclusions:
DKA is a condition that clinicians may encounter during pregnancy. Although rare, increased awareness and early recognition are crucial for optimal management and improved maternal and neonatal outcomes
Isotropy testing in spatial point patterns: nonparametric versus parametric replication under misspecification
No full textSeveral hypothesis testing methods have been proposed to validate the assumption of isotropy in spatial point patterns. A majority of these methods are characterised by an unknown distribution of the test statistic under the null hypothesis of isotropy. Parametric approaches to approximating the distribution involve simulation of patterns from a user-specified isotropic model. Alternatively, nonparametric replicates of the test statistic under isotropy can be used to waive the need for specifying a model. In this paper, we first present a general framework which allows for the integration of a selected nonparametric replication method into isotropy testing. We then conduct a large simulation study comprising application-like scenarios to assess the performance of tests with different parametric and nonparametric replication methods. In particular, we explore distortions in test size and power caused by model misspecification, and demonstrate the advantages of nonparametric replication in such scenarios
Practical rules for defining initial geometric imperfections for in-plane stability design of steel frames
No full textThe appropriate modelling of initial imperfections, in terms of both amplitude and shape/direction, is a key challenge in the design of structures by geometrically and materially nonlinear analysis with imperfections (GMNIA). While recent research has addressed the amplitude aspect of imperfection modelling, there remains a lack of clear guidance for determining the appropriate imperfection shape. This is tackled herein through the establishment of comprehensive rules for introducing global sway and member bow imperfections in the in-plane stability design of steel frames. The proposed rules cover the two most commonly used imperfection definition approaches – the direct definition (DD) method and the elastic buckling mode (EBM) method. In the DD method recommended herein, the directions of global sway and member bow imperfections are introduced following a set of prescribed rules. Two EBM methods are recommended. In the first EBM method, the ultimate capacity is taken as the lowest among n values obtained by considering the first n buckling modes as imperfection shapes individually, with n = 6 recommended. In the second EBM method, the bow and sway components of the imperfection shape are determined separately from different LBA in which loads are applied on the key load paths. The bow components are established by combining the first buckling mode for each key vertical and horizontal load path, while the sway component is based on the first mode – provided it is a sway mode – obtained from an LBA considering the maximum gravity load case. The consequences of using no imperfections are also explored. The accuracy of the proposed methods is verified based on a series of moment frames and braced frames considering both regular and irregular configurations
Graph expansions of neural networks: theory and applications for time-series analysis
No full textThe study of scaling limits in neural networks, particularly as the number of parameters grows large, provides crucial insights into their generalization properties, training stability, and information processing efficiency, making it an area of significant empirical interest.
However, existing approaches often lack mathematical rigor and are specific to certain architectures and hyper-parameters.
Our research introduces a novel mathematical framework for analyzing the scaling limits of arbitrary architectures.
By utilizing genus expansion techniques from random matrix theory, we represent neural networks as Taylor-like series of operator graphs, separating the effects of activation functions from the network’s random weights.
We then leverage these expansions to study the statistical properties of Feed Forward Neural Networks, State Space Models, and Neural Controlled Differential Equations, discovering new expressive kernels on path spaces.Open Acces
Considerations on the process of target selection for the Comet Interceptor mission
No full textComet Interceptor is an ESA science mission with payload contributions from ESA Member States and with an international participation by JAXA. It is the first mission that is being designed, built, and potentially launched before its target is known. This approach will enable the spacecraft to perform the first mission to a Long Period Comet from the Oort Cloud, as these comets have fleeting visits to the inner Solar System lasting only months to years from first discovery, too short for the usual process of mission development to be followed. In this paper we describe a number of factors that need to be considered in selecting a target for the mission, including scientific, orbital, spacecraft and instrument constraints, and discussion of different prioritisation strategies. We find that, in the case where we have a choice of targets, our decisions will mostly be driven by orbital information, which we will have relatively early on, with information on the activity level of the comet an important but secondary consideration. As cometary activity levels are notoriously hard to predict based on early observations alone, this prioritisation / decision approach based more on orbits gives us confidence that a good comet that is compatible with the spacecraft constraints will be selectable with sufficient warning time to allow the mission to intercept it