We present an ultrafast neural network (NN) model, QLKNN, which predicts core tokamak transport heat and particle fluxes. QLKNN is a surrogate model based on a database of 300 million flux calculations of the quasilinear gyrokinetic transport model QuaLiKiz. The database covers a wide range of realistic tokamak core parameters. Physical features such as the existence of a critical gradient for the onset of turbulent transport were integrated into the neural network training methodology. We have coupled QLKNN to the tokamak modelling framework JINTRAC and rapid control-oriented tokamak transport solver RAPTOR. The coupled frameworks are demonstrated and validated through application to three JET shots covering a representative spread of H-mode operating space, predicting turbulent transport of energy and particles in the plasma core. JINTRAC-QLKNN and RAPTOR-QLKNN are able to accurately reproduce JINTRAC-QuaLiKiz T i,e and n e profiles, but 3 to 5 orders of magnitude faster. Simulations which take hours are reduced down to only a few tens of seconds. The discrepancy in the final source-driven predicted profiles between QLKNN and QuaLiKiz is on the order 1%-15%. Also the dynamic behaviour was well captured by QLKNN, with differences of only 4%-10% compared to JINTRAC-QuaLiKiz observed at mid-radius, for a study of density buildup following the L-H transition. Deployment of neural network surrogate models in multi-physics integrated tokamak modelling is a promising route towards enabling accurate and fast tokamak scenario optimization, Uncertainty Quantification, and control applications.

BackgroundThe oxidation of carbohydrates from lignocellulose can facilitate the synthesis of new biopolymers and biochemicals, and also reduce sugar metabolism by lignocellulolytic microorganisms, reserving aldonates for fermentation to biofuels. Although oxidoreductases that oxidize cellulosic hydrolysates have been well characterized, none have been reported to oxidize substituted or branched xylo-oligosaccharides. Moreover, this is the first report that identifies amino acid substitutions leading to GOOX variants with reduced substrate inhibition.ResultsThe recombinant wild type gluco-oligosaccharide oxidase (GOOX) from the fungus Sarocladium strictum, along with variants that were generated by site-directed mutagenesis, retained the FAD cofactor, and showed high activity on cello-oligosaccharide and xylo-oligosaccharides, including substituted and branched xylo-oligosaccharides. Mass spectrometric analyses confirmed that GOOX introduces one oxygen atom to oxidized products, and 1H NMR and tandem mass spectrometry analysis confirmed that oxidation was restricted to the anomeric carbon. The A38V mutation, which is close to a predicted divalent ion-binding site in the FAD-binding domain of GOOX but 30 Å away from the active site, significantly increased the kcat and catalytic efficiency of the enzyme on all oligosaccharides. Eight amino acid substitutions were separately introduced to the substrate-binding domain of GOOX-VN (at positions Y72, E247, W351, Q353 and Q384). In all cases, the Km of the enzyme variant was higher than that of GOOX, supporting the role of corresponding residues in substrate binding. Most notably, W351A increased Km values by up to two orders of magnitude while also increasing kcat up to 3-fold on cello- and xylo-oligosaccharides and showing no substrate inhibition.ConclusionsThis study provides further evidence that S. strictum GOOX has broader substrate specificity than the enzyme name implies, and that substrate inhibition can be reduced by removing aromatic side chains in the -2 binding subsite. Of the enzyme variants, W351A might be particularly advantageous when oxidizing oligosaccharides present at high substrate concentrations often experienced in industrial processes.

The JET 2019-2020 scientific and technological programme exploited the results of years of concerted scientific and engineering work, including the ITER-like wall (ILW: Be wall and W divertor) installed in 2010, improved diagnostic capabilities now fully available, a major Neutral Beam Injection (NBI) upgrade providing record power in 2019-2020, and tested the technical & procedural preparation for safe operation with tritium. Research along three complementary axes yielded a wealth of new results. Firstly, the JET plasma programme delivered scenarios suitable for high fusion power and alpha particle physics in the coming D-T campaign (DTE2), with record sustained neutron rates, as well as plasmas for clarifying the impact of isotope mass on plasma core, edge and plasma-wall interactions, and for ITER pre-fusion power operation. The efficacy of the newly installed Shattered Pellet Injector for mitigating disruption forces and runaway electrons was demonstrated. Secondly, research on the consequences of long-term exposure to JET-ILW plasma was completed, with emphasis on wall damage and fuel retention, and with analyses of wall materials and dust particles that will help validate assumptions and codes for design & operation of ITER and DEMO. Thirdly, the nuclear technology programme aiming to deliver maximum technological return from operations in D, T and D-T benefited from the highest D-D neutron yield in years, securing results for validating radiation transport and activation codes, and nuclear data for ITER.

These studies indicate that the turnover of type III collagen is increased in patients with AAA.