Understanding sit-to-stand through experimentation and constraint-based modelling

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Normative values of muscle strength across ages in a ‘real world’ population: results from the longevity check-up 7+ project

Background: Low muscle strength is a powerful predictor of negative health-related events and a key component of sarcopenia. The lack of normative values for muscle strength across ages hampers the practical appraisal of this parameter. The aim of the present study was to produce normative values for upper and lower extremity muscle strength across a wide spectrum of ages, in a large sample of community-dwellers recruited in the Longevity check-up (Lookup) 7+ project. Methods: Lookup 7+ is an ongoing project that started in June 2015 and conducted in unconventional settings (i.e. exhibitions, malls, and health promotion campaigns) across Italy with the aim of fostering the adoption of healthy lifestyles in the general population. Candidate participants are eligible for enrolment if they are 18+ years and provide written informed consent. Upper and lower extremity muscle strength is assessed by handgrip strength and five-repetition chair-stand [5 × sit-to-stand (STS)] tests, respectively. Cross-sectional centile and normative values for handgrip strength and 5 × STS tests from age 18 to 80+ years were generated for the two genders. Smoothed normative curves for the two tests were constructed for men and women using the lambda-mu-sigma method. Results: From 1 June 2015 to 30 May 2019, 11 448 participants were enrolled. The mean age of participants was 55.6 years (standard deviation: 11.5 years; range: 18–98 years), and 6382 (56%) were women. Normative values for handgrip strength and the 5 × STS test, both absolute and normalized by body mass index, were obtained for men and women, stratified by age groups. Values of upper and lower extremity muscle strength across ages identified three periods in life: an increase to peak in young age and early adulthood (18–24 years), preservation through midlife (25–44 years), and a decline from midlife onwards (45+ years). Conclusions: Our study established age-specific and gender-specific percentile reference values for handgrip strength and the 5 × STS test. The normative curves generated can be used to interpret the assessment of muscle strength in everyday practice for the early detection of individuals with or at risk of sarcopenia

Structured grid generation for gas turbine combustion systems

Commercial pressures to reduce time-scales encourage innovation in the design and analysis cycle of gas turbine combustion systems. The migration of Computational Fluid Dynamics (CFD) from the purview of the specialist into a routine analysis tool is crucial to achieve these reductions and forms the focus of this research. Two significant challenges were identified: reducing the time-scale for creating and solving a CFD prediction and reducing the level of expertise required to perform a prediction. The commercial pressure for the rapid production of CFD predictions, coupled with the desire to reduce the risk associated with adopting a new technology led, following a review of available techniques, to the identification of structured grids as the current optimum methodology. It was decided that the task of geometry definition would be entirely performed within commercial Computer Aided Design (CAD) systems. A critical success factor for this research was the adoption of solid models for the geometry representation. Solids ensure consistency, and accuracy, whilst eliminating the need for the designer to undertake difficult, and time consuming, geometry repair operations. The versatility of parametric CAD systems were investigated on the complex geometry of a combustion system and found to be useful in reducing the overhead in altering the geometry for a CFD prediction. Accurate and robust transfer between CAD and CFD systems was achieved by the use of direct translators. Restricting the geometry definition to solid models allowed a novel two stage grid generator to be developed. In stage one an initial algebraic grid is created. This reduces user interaction to a minimum, by the employment of a series of logical rules based on the solid model to fill in any missing grid boundary condition data. In stage two the quality of the grid is improved by redistributing nodes using elliptical partial differential equations. A unique approach of improving grid quality by simultaneously smoothing both internal and surface grids was implemented. The smoothing operation was responsible for quality, and therefore reduced the level of grid generation expertise required. The successful validation of this research was demonstrated using several test cases including a CFD prediction of a complete combustion system

Representation, Recognition and Collaboration with Digital Ink

Pen input for computing devices is now widespread, providing a promising interaction mechanism for many purposes. Nevertheless, the diverse nature of digital ink and varied application domains still present many challenges. First, the sampling rate and resolution of pen-based devices keep improving, making input data more costly to process and store. At the same time, existing applications typically record digital ink either in proprietary formats, which are restricted to single platforms and consequently lack portability, or simply as images, which lose important information. Moreover, in certain domains such as mathematics, current systems are now achieving good recognition rates on individual symbols, in general recognition of complete expressions remains a problem due to the absence of an effective method that can reliably identify the spatial relationships among symbols. Last, but not least, existing digital ink collaboration tools are platform-dependent and typically allow only one input method to be used at a time. Together with the absence of recognition, this has placed significant limitations on what can be done. In this thesis, we investigate these issues and make contributions to each. We first present an algorithm that can accurately approximate a digital ink curve by selecting a certain subset of points from the original trace. This allows a compact representation of digital ink for efficient processing and storage. We then describe an algorithm that can automatically identify certain important features in handwritten symbols. Identifying the features can help us solve a number of problems such as improving two-dimensional mathematical recognition. Last, we present a framework for multi-user online collaboration in a pen-based and graphical environment. This framework is portable across multiple platforms and allows multimodal interactions in collaborative sessions. To demonstrate our ideas, we present InkChat, a whiteboard application, which can be used to conduct collaborative sessions on a shared canvas. It allows participants to use voice and digital ink independently and simultaneously, which has been found useful in remote collaboration