Efficient parallel generation of partitioned, unstructured meshes

In this paper we introduce a method for generating unstructured meshes in parallel which are partitioned in a ‘good’ way. When solving a partial differential equation on a parallel distributed memory machine, the mesh should be decomposed so that the communication requirement of the numerical solver is minimised and also the amount of work to be performed on each processor is approximately equal. Most previous work in this area has concentrated on partitioning a mesh that has already been generated. We introduce a method which actually generates the partitioned mesh in parallel whilst producing a good quality decomposition and compare this method with other approaches

Tectaria gaudichaudii

Pteridophyte

‘I am not someone who gets skin cancer’: Risk, time and malignant melanoma

‘Delay’ is a term used in the cancer literature since the 1930s to describe the period between self-detection of a concerning sign of possible disease and presentation to a health professional. This linguistic choice carries an implication of blame for apparent failure to manage a risk appropriately, drawing attention away from the contemporaneous perspectives of those who respond to suspicious indicators more or less quickly. We present findings from a grounded theory study of accounts given by 45 patients about their slower or quicker journeys to a diagnosis of cutaneous malignant melanoma, a cancer which can ‘hide in plain sight’. There has been little research exploring in qualitative detail patients’ perspectives on their decision-making about what subsequently turn out to have been signs of this most risky of skin cancers. The findings frame referral time-lapses in terms of normalisation of symptoms, sometimes buttressed by reassurance derived from health promotion messages, disconfirmation of patients’ concerns by their general practitioners and prioritisation of other life concerns. We argue that a shared sense of urgency surrounding melanoma self-referral derives from a clinical representation of current knowledge which conceals numerous evidential uncertainties