Potential for virus transfer between the honey bees Apis mellifera and A. cerana

Viruses seem to play a key role in European honey bee, Apis mellifera health, and have a much broader host spectrum than previously thought. Few studies have investigated interspecific virus transfer within the genus Apis. The introduction of A. mellifera into Asia exposed endemic Apis species to the risk of obtaining new viruses or viral strains and vice versa. To investigate the potential for host shifts, virus prevalence and sequences were monitored over three years in single and mixed-species apiaries hosting introduced A. mellifera and endemic Apis cerana. Deformed wing virus (DWV), Israeli acute paralysis virus (IAPV), black queen cell virus (BQCV), and sacbrood virus (SBV) were found, but not KBV, VDV-1, ABPV, or CBPV. Virus infections and prevalence were generally lower in A. cerana compared to A. mellifera, and varied over the years. The sequence data provided evidence for interspecific transfer of IAPV, BQCV, and DWV, but SBV strains seem to be species specific. Prevalence and sequence results taken together indicate that interspecific transfers of viruses are rare, even if honey bees are kept in close proximity. We discuss the pattern observed in the context host specificity and resistance. Our understanding of the extent of these exchanges is limited by a lack of knowledge on the mechanisms of adaptation of viruses to different hosts.

Building the View Graph of a Category by Exploiting Image Realism

We propose a weakly supervised method to arrange images of a given category based on the relative pose between the camera and the object in the scene. Relative poses are points on a sphere centered at the object in a given canonical pose, which we call object viewpoints. Our method builds a graph on this sphere by assigning images with similar viewpoint to the same node and by connecting nodes if they are related by a small rotation. The key idea is to exploit a large unlabeled dataset to validate the likelihood of dominant 3D planes of the object geometry. A number of 3D plane hypotheses are evaluated by applying small 3D rotations to each hypothesis and by measuring how well the deformed images match other images in the dataset. Correct hypotheses will result in deformed images that correspond to plausible views of the object, and thus will likely match well other images in the same category. The identified 3D planes are then used to compute affinities between images related by a change of viewpoint. We then use the affinities to build a view graph via a greedy method and the maximum spanning tree.