Abstract: The present application relates to methods for the isolation of EVs from a sample containing EVs, the method comprising: (i) contacting the sample with one or more polyethylenimines to form an EV-polyethylenimine complex; and (ii) separating the EV-polyethylenimine complex from the sample. Also included in the application are kits for performing the methods for isolating EVs and methods of diagnosis and therapy using the EVs isolated using the described methods.

Abstract: A dynamic video communications system provides real time provisioning of a video communication session in a domain video network between a set of user devices. The real time provisioning is implemented by receiving an identifier of a video communication session from a user device, where the identifier includes a domain and a name, determining an authentication principle associated with the user device, where the authentication principle includes a domain of the user, checking whether the domain of the user matches a domain of the video communication session, and joining the user device with the video communication session.

Abstract: Described herein is a method and system for marker-less three-dimensional modelling, fitting and tracking of a skeletal representation of an object in a three-dimensional point cloud. In particular, it concerns the tracking of a human user skeletal representation with respect to time. The method comprises inputting a three-dimensional point cloud derived from a depth map; predetermining a set of control points representing the skeleton of the user, determining a start-up skeleton pose, obtaining an orthographic representation of the user 3D point cloud projected onto a grid by sampling the 3D point cloud with a predetermined static size, determining a set of curvature centers points approximating central axes of main parts of the user, determining the torso plane, and refining and/or defining the principal direction of the body.

Abstract: The present invention relates to a volume recognition method comprising the steps of: a) capturing three-dimensional image data using a 3D imaging system 3, wherein said image data represent a plurality of points 5, each point 5 having at least a set of coordinates in a three-dimensional space; b) grouping at least some of the points 5 in a set of clusters 6; c) selecting, according to a first set of parameters such as position and size, a cluster 6 corresponding to an object of interest 1 located in range of said imaging system 3; d) grouping at least some of the points 5 of the selected cluster 6 in a set of sub-clusters according to a second set of parameters comprising their positions in the three-dimensional space, wherein each sub-cluster has a centroid 11 in the three-dimensional space; and e) associating a volume 12 to each of at least some of said sub-clusters, wherein said volume 12 is fixed to the centroid 11 of said sub-cluster.

Abstract: The present invention relates to a volume recognition method comprising the steps of: a) capturing three-dimensional image data using a 3D imaging system 3, wherein said image data represent a plurality of points 5, each point 5 having at least a set of coordinates in a three-dimensional space; b) grouping at least some of the points 5 in a set of clusters 6; c) selecting, according to a first set of parameters such as position and size, a cluster 6 corresponding to an object of interest 1 located in range of said imaging system 3; d) grouping at least some of the points 5 of the selected cluster 6 in a set of sub-clusters according to a second set of parameters comprising their positions in the three-dimensional space, wherein each sub-cluster has a centroid 11 in the three-dimensional space; and e) associating a volume 12 to each of at least some of said sub-clusters, wherein said volume 12 is fixed to the centroid 11 of said sub-cluster.

Abstract: A system is provided which enables the computer- and web-assisted assimilation of fixed income securities data. The system uses this data to identify potential trading opportunities. Semi-structured and unstructured data describing fixed income holdings, indications of interest and axes are automatically interpreted and assimilated into the system. Instances of similar data across different sets of data are automatically identified and subsequently notify individuals uniquely. Bids and offers are routed to the correct individuals after comparison with assimilated data.