Exploration of a Co-Production Approach to Developing a Walking Group with People with Huntington's Disease.

Background: People with Huntington's disease (HD) struggle to maintain regular physical activity despite evidence of the benefits of exercise. This study aimed to evaluate the experiences of people who co-produced a walking group for people with HD.

Methods: Three people with HD, a specialist HD advisor (sHDA), two project officers from Let's Walk Cymru (LWC) and the research team co-produced and participated in a walking group for people with HD.

High-performance iterative electron tomography reconstruction with long-object compensation using graphics processing units (GPUs).

Iterative reconstruction algorithms pose tremendous computational challenges for 3D Electron Tomography (ET). Similar to X-ray Computed Tomography (CT), graphics processing units (GPUs) offer an affordable platform to meet these demands. In this paper, we outline a CT reconstruction approach for ET that is optimized for the special demands and application setting of ET.

On the efficiency of iterative ordered subset reconstruction algorithms for acceleration on GPUs.

Expectation Maximization (EM) and the Simultaneous Iterative Reconstruction Technique (SIRT) are two iterative computed tomography reconstruction algorithms often used when the data contain a high amount of statistical noise, have been acquired from a limited angular range, or have a limited number of views. A popular mechanism to increase the rate of convergence of these types of algorithms has been to perform the correctional updates within subsets of the projection data. This has given rise to the method of Ordered Subsets EM (OS-EM) and the Simultaneous Algebraic Reconstruction Technique (SART).