This is a description of TPS, a theorem proving system for classical type theory (Church's typed λ-calculus). TPS has been designed to be a general research tool for manipulating wffs of first-and higher-order logic, and searching for proofs of such wffs interactively or automatically, or in a combination of these modes. An important feature of TPS is the ability to translate between expansion proofs and natural deduction proofs. Examples of theorems which TPS can prove completely automatically are given to illustrate certain aspects of TPS's behavior and problems of theorem proving in higher-order logic. 7

Acetone is one of the most abundant carbonyl compounds in the atmosphere, and it serves as an important source of HOx (OH + HO2) radicals in the upper troposphere and a precursor for peroxyacetyl nitrate. We present a global sensitivity analysis targeted at several major natural source and sink terms in the global acetone budget to find the input factor or factors to which the simulated acetone mixing ratio was most sensitive. The ranges of input factors were taken from literature. We calculated the influence of these factors in terms of their elementary effects on model output. Of the six factors tested here, the four factors with the highest contribution to total global annual model sensitivity are direct emissions of acetone from the terrestrial biosphere, acetone loss to photolysis, the concentration of acetone in the ocean mixed layer, and the dry deposition of acetone to ice‐free land. The direct emissions of acetone from the terrestrial biosphere are globally important in determining acetone mixing ratios, but their importance varies seasonally outside the tropics. Photolysis is most influential in the upper troposphere. Additionally, the influence of the oceanic mixed layer concentrations are relatively invariant between seasons, compared to the other factors tested. Monoterpene oxidation in the troposphere, despite the significant uncertainties in acetone yield in this process, is responsible for only a small amount of model uncertainty in the budget analysis.

No abstract

No abstract

Background Prospective studies harnessing late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) afford the potential to non-invasively characterise the phenotypic substrate for sudden cardiac death (SCD) and simultaneously interrogate its mechanistic drivers. Purpose To assess the utility of infarct characterisation by CMR, including scar microstructure analysis, to predict SCD in prospectively investigated patients with coronary heart disease (CHD). Methods Patients with stable CHD were prospectively recruited into a registry between August 2009 and January 2016. The primary outcome for this study was SCD or aborted SCD. Patients with a secondary prevention implantable cardioverter defibrillator (ICD) indication were excluded. All patients had CMR with LGE imaging. Infarct quantification (core scar and peri-infarct zone [PIZ]) was performed by an independent level 3 CMR reader. Outcome events were adjudicated by a panel of cardiologists blinded to the CMR data. To investigate fibrosis microstructure, bespoke computational image processing algorithms were applied to the LGE images in order to extract specific morphological and texture related features. Results Of 437 patients (mean age 64, mean left ventricular ejection fraction [LVEF] 47%, 91% with LGE) followed for a median of 6.3 years, 49 patients (11.2%) experienced the primary outcome. Patients with higher PIZ mass had an increased risk of the primary outcome (10-year risk 0.7%, 24.0% and 37.8% for patients with PIZ mass <5.66g, 5.66–12.28g and ≥12.29g respectively, P<0.001; figure 1a). On univariable analysis, an increase in PIZ mass and core infarct mass was associated with an increased risk of the primary outcome (per gram: HR 1.12, 95% CI 1.09–1.15, P<0.001 and HR 1.05, 95% CI 1.04–1.06, P<0.001 respectively). PIZ mass and core infarct mass remained independently associated with the primary outcome after adjustment for baseline predictors (per gram: HR 1.10, 95% CI 1.06–1.14, P<0.001 and HR 1.04, 95% CI 1.02–1.06, P<0.001 respectively) and together provided incremental value compared to conventional variables in predicting the endpoint (Harrell's C-statistic 0.76 to 0.82, figure 1b-c). Bespoke analysis of imaging data identified several shape-based scar metrics that associated with the primary outcome (figure 2). These included core infarct transmurality, radiality and interface length (the latter defining the core scar-PIZ boundary length), and the number of PIZ islets. Conclusions In this large prospective study of patients with stable CHD, both PIZ mass and core infarct mass independently predicted long-term SCD risk after adjusting for conventional predictors including LVEF. Reassuringly, minimal or absent LGE portended a comparatively low risk of SCD. Analysis of the scar microstructure identified several shape-based features that associated with SCD. These results highlight a potential avenue towards a more personalised approach to ICD implantation decisions. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Lung and Heart Institute, Imperial College London