78 research outputs found
Generalized averaged Gaussian quadrature and applications
A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal
MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications
Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described
Book of Abstracts 15th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering and 3rd Conference on Imaging and Visualization
In this edition, the two events will run together as a single conference, highlighting the strong connection with the Taylor & Francis journals: Computer Methods in Biomechanics and Biomedical Engineering (John Middleton and Christopher Jacobs, Eds.) and Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization (JoãoManuel R.S. Tavares, Ed.).
The conference has become a major international meeting on computational biomechanics, imaging andvisualization. In this edition, the main program includes 212 presentations. In addition, sixteen renowned researchers will give plenary keynotes, addressing current challenges in computational biomechanics and biomedical imaging.
In Lisbon, for the first time, a session dedicated to award the winner of the Best Paper in CMBBE Journal will take place.
We believe that CMBBE2018 will have a strong impact on the development of computational biomechanics and biomedical imaging and visualization, identifying emerging areas of research and promoting the collaboration and networking between participants. This impact is evidenced through the well-known research groups, commercial companies and scientific organizations, who continue to support and sponsor the CMBBE meeting
series. In fact, the conference is enriched with five workshops on specific scientific topics and commercial software.info:eu-repo/semantics/draf
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Mathematical approaches for the clinical translation of hyperpolarised 13C imaging in oncology
Dissolution dynamic nuclear polarisation is an emerging clinical technique which enables
the metabolism of hyperpolarised 13C-labelled molecules to be dynamically and non-
invasively imaged in tissue. The first molecule to gain clinical approval is [1-13C]pyruvate,
the conversion of which to [1-13C]lactate has been shown to detect early treatment re-
sponse in cancers and correlate with tumour grade. As the technique has recently been
translated into humans, accurate and reliable quantitative methods are required in order
to detect, analyse and compare regions of altered metabolism in patients. Furthermore,
there is a requirement to understand the biological processes which govern lactate pro-
duction in tumours in order to draw reliable conclusions from this data.
This work begins with a comprehensive analysis of the quantitative methods which
have previously been applied to hyperpolarised 13C data and compares these to some
novel approaches. The most appropriate kinetic model to apply to hyperpolarised data is
determined and some simple, robust quantitative metrics are identified which are suitable
for clinical use. A means of automatically segmenting 5D hyperpolarised imaging data
using a fuzzy Markov random field approach is presented in order to reliably identify
regions of abnormal metabolic activity. The utility of the algorithm is demonstrated
on both in silico and animal data. To gain insight into the processes driving lactate
metabolism, a mathematical model is developed which is capable of simulating tumour
growth and treatment response under a range of metabolic and tissue conditions, focusing
on the interaction between tumour and stroma. Finally, hyperpolarised 13C-pyruvate
imaging data from the first human subjects to be imaged in Cambridge is analysed. The
ability to detect and quantify lactate production in patients is demonstrated through
application of the methods derived in earlier chapters. The mathematical approaches
presented in this work have the potential to inform both the analysis and interpretation
of clinical hyperpolarised 13C imaging data and to aid in the clinical translation of this
technique.Joint funded by GlaxoSmithKline and the Cambridge Biomedical Research Centre
Proceedings of the Cardiff University Engineering Research Conference 2023
The conference was established for the first
time in 2023 as part of a programme to sustain the research
culture, environment, and dissemination activities of the
School of Engineering at Cardiff University in the United
Kingdom. The conference served as a platform to celebrate
advancements in various engineering domains researched
at our School, explore and discuss further advancements in
the diverse fields that define contemporary engineering
The research on mechanical properties and compressive behavior of graphene foam with multi-scale model?
Computational simulation is an effective method to study the deformation
mechanism and mechanical behaviour of graphene-based porous materials.
However, due to limitations in computational methods and costs, existing
research model deviate significantly from the real material in terms of the
scale of structure. Therefore, building a highly accurate computational model
and maintaining an appropriate cost is both necessary and challenging. This
paper proposed a multi-scale modelling approach for finite element (FE)
analysis based on the concept of structural hierarchy. The stochastic feature
of the microstructure of porous materials are also considered. The simulation
results of the regular structure model and the Voronoi tessellation model are
compared to investigate the effect of regularity on the material properties.
Despite some shortcomings, other microstructural features of porous
graphene materials can be gradually introduced to improve the material
model step by step. Thus the developed multiscale model has great potential
to simulate the properties of materials with mesoscopic size structure such as
graphene foam (GF)
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