Consistent Point Data Assimilation in Firedrake and Icepack

We present methods and tools that significantly improve the ability to estimate quantities and fields which are difficult to directly measure, such as the fluidity of ice, using point data sources, such as satellite altimetry. These work with both sparse and dense point data with estimated quantities and fields becoming more accurate as the number of measurements are increased. Such quantities and fields are often used as inputs to mathematical models that are used to make predictions so improving their accuracy is of vital importance. We demonstrate how our methods and tools can increase the accuracy of results, ensure posterior consistency, and aid discourse between modellers and experimenters. To do this, we bring point data into the finite element method ecosystem as discontinuous fields on meshes of disconnected vertices. Point evaluation can then be formulated as a finite element interpolation operation (dual-evaluation). Our new abstractions are well-suited to automation. We demonstrate this by implementing them in Firedrake, which generates highly optimised code for solving PDEs with the finite element method. Our solution integrates with dolfin-adjoint/pyadjoint which allows PDE-constrained optimisation problems, such as data assimilation, to be solved through forward and adjoint mode automatic differentiation. We demonstrate our new functionality through examples in the fields of groundwater hydrology and glaciology

Evaluating a new generation of wearable high-density diffuse optical tomography (HD-DOT) technology via retinotopic mapping in the adult brain

We investigated the performance of a novel HD-DOT system by replicating a series of classic visual stimulation paradigms. Haemodynamic response functions and cortical activation maps replicated the results obtained with larger fibre-based systems

ANIMATE: Wearable, flexible, and ultra-lightweight high-density diffuse optical tomography technologies for functional neuroimaging of newborns

We have developed a series of wearable high-density diffuse optical tomography (HD-DOT) technologies specifically for neonatal applications. These systems provide an ultra-lightweight form factor, a low profile and high mechanical flexibility. This new technology is validated using a novel, anatomically accurate dynamic phantom

Number of teeth, C‐reactive protein, fibrinogen and cardiovascular mortality: a 15‐year follow‐up study in a Finnish cohort

Aim To test whether the number of teeth, an inverse proxy for composite oral infection scores is associated with better survival. Materials and Methods The Kuopio Oral Health and Heart study initiated a case–control study in 1995–1996 consisting of 256 consecutive coronary artery disease patients and 250 age and gender‐matched controls. We appended the mortality data and formulated a longitudinal study. By May 31st, 2011, 124 mortalities had occurred and 80 of which were of cardiovascular origin. Using Cox proportional hazards models, we assessed the association of the teeth group (Teethgrp) – consisting of 10 teeth – with cardiovascular and all‐cause mortality after 15.8 years of median follow‐up. Results In multivariate models, with the edentulous state as reference, one level increase in Teethgrp was associated with significantly increased survival from cardiovascular disease (CVD) mortality with a Hazard Ratio (HR) 0.73, p ‐value = 0.02 but not with all‐cause mortality (HR = 0.87, p  = 0.13). The findings were not mediated by C‐reactive protein (CRP) levels ≥3 mg/L or by median fibrinogen levels, but were mediated by CRP levels >5 mg/L. Conclusion Each increment of 10 teeth from the edentulous state was associated with a 27% improved CVD survival, independent of low‐grade systemic inflammation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/102655/1/jcpe12192.pd