3D Monte Carlo radiation transfer modelling of photodynamic therapy

We acknowledge the support of the UK Engineering and Physics Sciences Research Council (EPSRC) for funding through a studentship for C L Campbell as well as the Alfred Stewart Trust.The effects of ageing and skin type on Photodynamic Therapy (PDT) for different treatment methods have been theoretically investigated. A multilayered Monte Carlo Radiation Transfer model is presented where both daylight activated PDT and conventional PDT are compared. It was found that light penetrates deeper through older skin with a lighter complexion, which translates into a deeper effective treatment depth. The effect of ageing was found to be larger for darker skin types. The investigation further strengthens the usage of daylight as a potential light source for PDT where effective treatment depths of about 2 mm can be achieved.Publisher PD

Efficient meshing technique for textile composites unit cells of arbitrary complexity

Meso-scale unit cell models are often used to simulate mechanical behaviour of textile composites. Apart from reliable ways to create meso-scale geometries, such simulations require reliable meshing algorithms. While the former is made possible via dedicated textile pre-processors or high-fidelity weaving simulations, the meshing remains quite problematic for complex textiles and geometries. Even though, with a lot of user input, it is possible to create very complex meshes using meshing pre-processors, this approach remains infeasible for cases when a large number of models need to be analysed.This paper presents a meshing approach based on the combination of local octree-refinement with surface smoothing. This allows nearly conformal meshes to be generated for geometries of any complexity which achieve accuracy comparable to that of conformal meshes. A range of unit cells was analysed using the new approach and it was shown that the error in local stresses is within 10% of the reference solution and the average error is below 7%. It was found that the computational cost of the analysis using the new meshing technique is not considerably higher than for an analysis which uses a conventional conformal mesh yet the new approach allows analysis of any geometry

Advanced geometry modelling of 3D woven reinforcements in polymer composites: processing and performance analysis

Numerical methods have become increasingly effective tools for analysis and design of composite materials. This study investigates how the inclusion of geometrical variations in modelling 3D woven fabrics affects the accuracy of numerical predictions. Based on micro-Computed Tomography data of 3D orthogonal woven composites, unit cell models were generated in TexGen at different levels of geometrical detail. Two types of analysis were implemented: (a) computational fluid dynamics (CFD) simulates resin flow during fabric impregnation in composites processing to predict permeability; (b) implicit static finite element analysis predicts in-plane tensile strength of the composites. By comparison with experimental data, the numerical predictions indicate that local geometrical variations, particularly in yarn cross-section, surface crimp and binder yarn path, have significant influence on both permeability and material strength. It is important to model the precise geometry in certain locations while the overall geometry can be simplified in order to maintain the practicality of model generation

Modelling framework for optimum multiaxial 3D woven textile composites

The application of 3D weaves has advantages over conventional uni-directional or 2D woven lay-ups. There is potential to produce near net-shaped preforms and to increase damage resistance due to the presence of through thickness reinforcement. Conventional 3D weaves typically consist of orthogonal yarns interwoven with through thickness binder yarns. This paper describes a feasibility study to find optimum architectures for 3D woven fabrics where some of the normal manufacturing constraints are relaxed. This will provide the basis for development of novel manufacturing methods based on optimum textile architectures. A framework has been developed for the automatic generation and analysis of 3D textile geometries, utilising the open-source pre-processor TexGen. A genetic algorithm is used to select an optimum geometry by evaluating results from finite element simulations using the commercial solver Abaqus. This paper highlights the flexibility of TexGen software to create complex 3D models by means of its Python scripting application programming interface (API). A standard layer-to-layer geometry is used as a starting point to which off-axis yarn rotations, in-plane shift of entire layers and adjustments to binder yarns can be applied. Geometric variables are selected to represent the textile architecture enabling the automation of unit cell creation and finite element analysis. A Genetic Algorithm is used to determine the optimum through thickness binder path, the number and the width of the binders, and yarn angles using a weighted objective function of the material elastic properties. The case studies show that the algorithm is efficient to converge to the optimum fibre architecture

Mesoscale geometric modelling of bifurcation in 3D woven T-beam preforms

Manipulation of the through-thickness yarn path enables 3D woven reinforcement to separate locally in the form of a bifurcation, creating net-shaped preforms for T- and I-beams. Preforming introduces fibre architecture deformation at the 3D woven bifurcation area. We report a geometric modelling approach to represent the realistic fibre architecture, as a preprocessing tool for finite element analyses. The study started with x-ray micro-computed tomography (µCT) of two 3D woven T-beams varying only by their yarn path at the T-junction area. Supported by the µCT image analysis, a set of mathematical formula were proposed to describe the identified features in the 3D woven T-beams. We then moved on to implement the automated modelling procedure in the open-source software TexGen. Using the weave pattern as input data, TexGen first simulates as-woven flat T-piece. Next, TexGen applies geometric transformation and refinements to simulate the preforming process of T-beams. The paper highlights an efficient approach to model the complex woven bifurcation structure at mesoscale

Mesoscale geometric modelling of bifurcation in 3D woven T-beam preforms

Manipulation of the through-thickness yarn path enables 3D woven reinforcement to separate locally in the form of a bifurcation, creating net-shaped preforms for T- and I-beams. Preforming introduces fibre architecture deformation at the 3D woven bifurcation area. We report a geometric modelling approach to represent the realistic fibre architecture, as a preprocessing tool for finite element analyses. The study started with x-ray micro-computed tomography (µCT) of two 3D woven T-beams varying only by their yarn path at the T-junction area. Supported by the µCT image analysis, a set of mathematical formula were proposed to describe the identified features in the 3D woven T-beams. We then moved on to implement the automated modelling procedure in the open-source software TexGen. Using the weave pattern as input data, TexGen first simulates as-woven flat T-piece. Next, TexGen applies geometric transformation and refinements to simulate the preforming process of T-beams. The paper highlights an efficient approach to model the complex woven bifurcation structure at mesoscale

The relationships between body composition and cardiovascular risk factors in young Australian men

IntroductionCardiovascular (CV) disease is a leading cause of global mortality. Despite clear evidence of the coexistence of several risk factors in young people as children and an understanding of the importance of the health behaviors in controlling CV disease, there are limited data on the relationships between risk factors and CV disease in young people. Therefore further study is required. ObjectiveThis study aimed to investigate associations among body composition, health behaviors and CV risk factors in young Australian men. MethodsThirty five healthy men aged 18–25 years had their blood pressure (BP), blood lipids, body composition, resting metabolic rate (RMR), physical activity, dietary intake and cardiorespiratory fitness assessed. ResultsParticipants were categorised according to the percentage of body fat into two groups: lean and overweight men. There were no between-group differences in the biochemical indicators except that overweight men had lower HDL-C compared to lean men. Both groups had similar mean energy, protein, fat, carbohydrate and alcohol intake, RMR, physical activity level (PAL) and energy expenditure (EE). Most of the participants (65.7%) had LDL≥2.5 mmol/L. Other common individual risk factors were body fat≥20% (42.9%), waist circumference≥88 cm (28.6%), PAL<1.8 (22.9%) and systolic BP≥130 mmHg (20%). The mean number of CV risk factors was lower among men having a high intake of monounsaturated fatty acids (MUFA, >12% of the energy intake) regardless of whether they were overweight or lean and did not seem to differ according to the source of MUFA consumed. ConclusionsIt is a serious concern to observe such a high percentage of CV risk factors in a group of apparently healthy young men. The likelihood of multiple CV risk factors is greater among those with high body fatness and low MUFA intake. Intake of MUFA favorably affects CV risk factors regardless of the source

Comparing non-invasive surveying techniques for elusive, nocturnal mammals: a case study of the West European hedgehog (Erinaceus europaeus)

Monitoring changes in populations is fundamental for effective management. The West European hedgehog (Erinaceus europeaus) is of conservation concern in the UK because of recent substantial declines. Surveying hedgehogs is, however, problematic because of their nocturnal, cryptic behaviour. We compared the effectiveness of three methods (infra-red thermal camera, specialist search dog, spotlight) for detecting hedgehogs in three different habitats. Significantly more hedgehogs were detected, and at greater distance, using the camera and dog than the spotlight in amenity grassland and pasture; no hedgehogs were detected in woodland. Increasing ground cover reduced detection distances, with most detections (59.6%) associated with bare soil or mown grass; the dog was the only method that detected hedgehogs in vegetation taller than the target species’ height. The additional value of surveying with a detection dog is most likely to be realised in areas where badgers (Meles meles), an intra-guild predator, are and/or where sufficient ground cover is present; both would allow hedgehogs to forage further from refuge habitats such as hedgerows. Further consideration of the effectiveness of detection dogs for finding hedgehogs in nests, as well as developing techniques for monitoring this species in woodland, is warranted

Statistical consideration when adding new arms to ongoing clinical trials: the potentials and the caveats.

BACKGROUND: Platform trials improve the efficiency of the drug development process through flexible features such as adding and dropping arms as evidence emerges. The benefits and practical challenges of implementing novel trial designs have been discussed widely in the literature, yet less consideration has been given to the statistical implications of adding arms. MAIN: We explain different statistical considerations that arise from allowing new research interventions to be added in for ongoing studies. We present recent methodology development on addressing these issues and illustrate design and analysis approaches that might be enhanced to provide robust inference from platform trials. We also discuss the implication of changing the control arm, how patient eligibility for different arms may complicate the trial design and analysis, and how operational bias may arise when revealing some results of the trials. Lastly, we comment on the appropriateness and the application of platform trials in phase II and phase III settings, as well as publicly versus industry-funded trials. CONCLUSION: Platform trials provide great opportunities for improving the efficiency of evaluating interventions. Although several statistical issues are present, there are a range of methods available that allow robust and efficient design and analysis of these trials

Geometrical modelling of 3D woven reinforcements for polymer composites: prediction of fabric permeability and composite mechanical properties

For a 3D orthogonal carbon fibre weave, geometrical parameters characterising the unit cell were quantified using micro-Computed Tomography and image analysis. Novel procedures for generation of unit cell models, reflecting systematic local variations in yarn paths and yarn cross-sections, and discretisation into voxels for numerical analysis were implemented in TexGen. Resin flow during reinforcement impregnation was simulated using Computational Fluid Dynamics to predict the in-plane permeability. With increasing degree of local refinement of the geometrical models, agreement of the predicted permeabilities with experimental data improved significantly. A significant effect of the binder configuration at the fabric surfaces on the permeability was observed. In-plane tensile properties of composites predicted using mechanical finite element analysis showed good quantitative agreement with experimental results. Accurate modelling of the fabric surface layers predicted a reduction of the composite strength, particularly in the direction of yarns with crimp caused by compression at binder cross-over points