Abstract: Stevia varieties with high a content of RebD, a high content of RebM, and a high content of RebD and RebM containing various SNP markers and UGT isoforms, are disclosed. Methods of screening for the SNPs are also disclosed as well as for using the SNPs in marker assisted breeding. Further provided are methods for introgressing the disclosed SNPs associated with high RebD and high RebM into Stevia plants by selecting plants comprising for one or more SNPs and breeding with such plants to confer such desirable agronomic phenotypes to plant progeny.

Abstract: A neural network is trained for, and may be used in, the simulation of the fluid flow through a domain around an object geometry. A first training process for the neural network includes training (902) the network on a first set of encodings of pre-computed computational fluid dynamics (CFD) simulations for object geometries and associated boundary conditions. The first training process uses a first loss function that evaluates an error between the network output and the pre-computed CFD simulations. A second training process is then carried out which includes training (905) the network on a second set of encodings of object geometries and associated boundary conditions. The second training process uses a second loss function that evaluates an error between the network output and a set of fluid dynamics conditions.

Abstract: A flow feature detection method is described. The method includes storing a plurality of points at locations over a region in which vortex detection is to be performed. A value for each of a plurality of fluid flow parameters, such as velocity, pressure and density, is determined at each point. The points are grouped as being contained in either a flow feature portion or normal flow portion of the region according to one or more statistical distribution for the fluid flow parameters. A point is identified as being indicative of the flow feature by identifying multiple further points at least partially surrounding the point, and determining a plane in which the flow feature is identifiable based upon the relative values of the one or more fluid flow parameter for the further points. The method may be used to detect vortices and to identify a two-dimensional plane representative of a vortex.

Abstract: A vortex detection method is described. The method comprises storing a plurality of points at locations over a region (32) in which vortex detection is to be performed. A value for each of a plurality of fluid flow parameters, such as velocity, pressure and density, is determined at each point. The points are grouped as being contained in either a vortical flow portion or non-vortical flow portion of the region according to one or more statistical distribution for said fluid flow parameters. A point (p) in a vortex core is identified according to the direction of motion of an array of further points (46) relative to said point in the vortex core. The further points (46) may surround the vortex core point.

Abstract: A flow feature detection method is described. The method includes storing a plurality of points at locations over a region in which vortex detection is to be performed. A value for each of a plurality of fluid flow parameters, such as velocity, pressure and density, is determined at each point. The points are grouped as being contained in either a flow feature portion or normal flow portion of the region according to one or more statistical distribution for the fluid flow parameters. A point is identified as being indicative of the flow feature by identifying multiple further points at least partially surrounding the point, and determining a plane in which the flow feature is identifiable based upon the relative values of the one or more fluid flow parameter for the further points. The method may be used to detect vortices and to identify a two-dimensional plane representative of a vortex.

Abstract: A vortex detection method is described. The method comprises storing a plurality of points at locations over a region (32) in which vortex detection is to be performed. A value for each of a plurality of fluid flow parameters, such as velocity, pressure and density, is determined at each point. The points are grouped as being contained in either a vortical flow portion or non-vortical flow portion of the region according to one or more statistical distribution for said fluid flow parameters. A point (p) in a vortex core is identified according to the direction of motion of an array of further points (46) relative to said point in the vortex core. The further points (46) may surround the vortex core point.