Correlating matched-filter model for analysis and optimisation of neural networks

A new formalism is described for modelling neural networks by means of which a clear physical understanding of the network behaviour can be gained. In essence, the neural net is represented by an equivalent network of matched filters which is then analysed by standard correlation techniques. The procedure is demonstrated on the synchronous Little-Hopfield network. It is shown how the ability of this network to discriminate between stored binary, bipolar codes is optimised if the stored codes are chosen to be orthogonal. However, such a choice will not often be possible and so a new neural network architecture is proposed which enables the same discrimination to be obtained for arbitrary stored codes. The most efficient convergence of the synchronous Little-Hopfield net is obtained when the neurons are connected to themselves with a weight equal to the number of stored codes. The processing gain is presented for this case. The paper goes on to show how this modelling technique can be extended to analyse the behaviour of both hard and soft neural threshold responses and a novel time-dependent threshold response is described

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Transverse bed slope experiments in an annular flume

Large scale morphology, in particular bar dimensions and bifurcation dynamics, are greatly affected by the deflection of sediment transport on transverse bed slopes due to gravity and by helical flows. However, existing transverse bed slope predictors are based on a small set of experiments with a minor range of flow conditions and sediment sizes, and do not account for the presence of bedforms. In morphological modelling the deflection angle is therefore often calibrated on measured morphology. Our objective is to experimentally quantify the transverse slope effect for a large range of near-bed flow conditions and sediment sizes (0.17 – 4 mm) to test existing predictors, in order to improve morphological modelling of rivers and estuaries. We have conducted about 400 experiments in an annular flume, which functions as an infinitely long bended flume and therefore avoids boundary effects. Flow is generated by rotating the lid of the flume, while the intensity of the helical flow can be decreased by counterrotating the bottom of the flume. The equilibrium transverse slope that develops during the experiments is a balance between the transverse bed slope effect and the bed shear stress caused by the helical flow. We obtained sediment mobilities from no motion to sheet flow, ranging across bedload and suspended load. Resulting equilibrium transverse slopes show a clear trend with varying sediment mobilities and helical flow intensities that deviate from typical power relations with Shields number. As an end member we found transversely horizontal beds by counterrotation that partially cancelled the helical flow near the bed, which allows us to quantify helical flow. The large range in sediment mobilities caused different bed states from ripples and dunes to sheet flow that affect near-bed flow, which cause novel nonlinear relations between transverse slope and Shields number. In conclusion, our results show for a wide range of conditions and sediments that transverse bed slope effects are not simple functions of sediment mobility but depend strongly on bed state. We are now focusing on isolating effects of helical flow intensity and near-bed flow patterns, working towards a new transverse bed slope predictor for use in morphodynamic models

Transverse bed slope effects in an annular flume

Large scale morphology, in particular bar dimensions and bifurcation dynamics, are greatly affected by the deflection of sediment transport on transverse bed slopes due to gravity and by helical flows. However, existing transverse bed slope predictors are based on a small set of experiments with a minor range of flow conditions and sediment sizes, and do not account for the presence of bedforms. In morphological modelling the deflection angle is therefore often calibrated on measured morphology. Our objective is to experimentally quantify the transverse slope effect for a large range of near-bed flow conditions and sediment sizes (0.17 - 4 mm) to test existing predictors, in order to improve morphological modelling of rivers and estuaries. We have conducted about 400 experiments in an annular flume, which functions as an infinitely long bended flume and therefore avoids boundary effects. Flow is generated by rotating the lid of the flume, while the intensity of the helical flow can be decreased by counterrotating the bottom of the flume. The equilibrium transverse slope that develops during the experiments is a balance between the transverse bed slope effect and the bed shear stress caused by the helical flow. We obtained sediment mobilities from no motion to sheet flow, ranging across bedload and suspended load. Resulting equilibrium transverse slopes show a clear trend with varying sediment mobilities and helical flow intensities that deviate from typical power relations with Shields number. As an end member we found transversely horizontal beds by counterrotation that partially cancelled the helical flow near the bed, which allows us to quantify helical flow. The large range in sediment mobilities caused different bed states from ripples and dunes to sheet flow that affect near-bed flow, which cause novel nonlinear relations between transverse slope and Shields number. In conclusion, our results show for a wide range of conditions and sediments that transverse bed slope effects are not simple functions of sediment mobility but depend strongly on bed state. We are now focusing on isolating effects of helical flow intensity and near-bed flow patterns, working towards a new transverse bed slope predictor for use in morphodynamic models