76 research outputs found
On the isoperimetric problem for the Laplacian with Robin and Wentzell boundary conditions
Doctor of PhilosophyWe consider the problem of minimising the eigenvalues of the Laplacian with Robin boundary conditions and generalised Wentzell boundary conditions with respect to the domain on which the problem is defined. For the Robin problem, when we extend the Faber-Krahn inequality of Daners [Math. Ann. 335 (2006), 767--785], which states that the ball minimises the first eigenvalue, to prove that the minimiser is unique amongst domains of class . The method of proof uses a functional of the level sets to estimate the first eigenvalue from below, together with a rearrangement of the ball's eigenfunction onto the domain and the usual isoperimetric inequality.
We then prove that the second eigenvalue attains its minimum only on the disjoint union of two equal balls, and set the proof up so it works for the Robin -Laplacian. For the higher eigenvalues, we show that it is in general impossible for a minimiser to exist independently of . When , we prove that every eigenvalue behaves like as , provided only that is bounded with boundary. This generalises a result of Lou and Zhu [Pacific J. Math. 214 (2004), 323--334] for the first eigenvalue.
For the Wentzell problem, we (re-)prove general operator properties, including for the less-studied case establish a type of equivalence property between the Wentzell and Robin minimisers for all eigenvalues. This yields a minimiser of the second Wentzell eigenvalue. We also prove a Cheeger-type inequality for the first eigenvalue in this case
Identification of common genetic risk variants for autism spectrum disorder
Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.Peer reviewe
Broadband multi-wavelength properties of M87 during the 2017 Event Horizon Telescope campaign
In 2017, the Event Horizon Telescope (EHT) Collaboration succeeded in capturing the first direct image of the
center of the M87 galaxy. The asymmetric ring morphology and size are consistent with theoretical expectations
for a weakly accreting supermassive black hole of mass ∼6.5 × 109Me. The EHTC also partnered with several
international facilities in space and on the ground, to arrange an extensive, quasi-simultaneous multi-wavelength
campaign. This Letter presents the results and analysis of this campaign, as well as the multi-wavelength data as a
legacy data repository. We captured M87 in a historically low state, and the core flux dominates over HST-1 at
high energies, making it possible to combine core flux constraints with the more spatially precise very long
baseline interferometry data. We present the most complete simultaneous multi-wavelength spectrum of the active
nucleus to date, and discuss the complexity and caveats of combining data from different spatial scales into one
broadband spectrum. We apply two heuristic, isotropic leptonic single-zone models to provide insight into the
basic source properties, but conclude that a structured jet is necessary to explain M87’s spectrum. We can exclude
that the simultaneous γ-ray emission is produced via inverse Compton emission in the same region producing the
EHT mm-band emission, and further conclude that the γ-rays can only be produced in the inner jets (inward of
HST-1) if there are strongly particle-dominated regions. Direct synchrotron emission from accelerated protons and
secondaries cannot yet be excluded.http://iopscience.iop.org/2041-8205am2022Physic
Factors Associated with Revision Surgery after Internal Fixation of Hip Fractures
Background: Femoral neck fractures are associated with high rates of revision surgery after management with internal fixation. Using data from the Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trial evaluating methods of internal fixation in patients with femoral neck fractures, we investigated associations between baseline and surgical factors and the need for revision surgery to promote healing, relieve pain, treat infection or improve function over 24 months postsurgery. Additionally, we investigated factors associated with (1) hardware removal and (2) implant exchange from cancellous screws (CS) or sliding hip screw (SHS) to total hip arthroplasty, hemiarthroplasty, or another internal fixation device. Methods: We identified 15 potential factors a priori that may be associated with revision surgery, 7 with hardware removal, and 14 with implant exchange. We used multivariable Cox proportional hazards analyses in our investigation. Results: Factors associated with increased risk of revision surgery included: female sex, [hazard ratio (HR) 1.79, 95% confidence interval (CI) 1.25-2.50; P = 0.001], higher body mass index (fo
Whole-genome sequencing reveals host factors underlying critical COVID-19
Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease
The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance
INTRODUCTION
Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic.
RATIONALE
We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs).
RESULTS
Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants.
CONCLUSION
Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century
The work hardening and fracture behaviour of linepipe steels
Available from British Library Document Supply Centre- DSC:D061795 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo
Bearing fault diagnosis using multi-layer neural networks
This paper presents an investigation into bearing fault diagnosis on centrifugal pumps which can be applied to the waste water industry. After the establishment of a vibration monitoring system in a pumping station, signals were recorded regularly to build up a vibration database for future monitoring. Conventional methods were used to analyse the vibration signals and some bearing defects were successfully detected.However, the major challenge for this project was to use a vibration monitoring system to predict pump bearing faults automatically instead of by analysing the data off-line. This paper proposes a solution based on artificial neural networks (ANNs), which is a powerful technique for pattern recognition and can be applied to the classification of pump faults. Due to the long period of time required to obtain essential information from the pumping station for neural network training, a test-rig pump was established in the laboratory to simulate the common pump faults, including typical bearing defects. Bearing faults were simulated by generating pit marks on the bearings using electrical discharge machining (EDM.). Vibration signals in the time-domain were collected and pre-processed to act as the inputs to neural networks. The neural networks were then trained and their classification accuracy rates evaluated. In this study neural network models were designed using the Matlab Neural Network Toolbox and the models which successfully classified the vibration signals were chosen for pump fault diagnosis
A systematic procedure for the application of artificial neural networks to pump fault diagnosis
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