Abstract: The invention concerns a process to convert di-rhamnolipid to mono-rhamnolipid, using an ?-L-rhamnosidase enzyme which has a sequence identity of at least 70% with either SEQ ID. 1 or SEQ. ID 2.

Abstract: Wax-based compositions for making barrier layers used in oral treatment devices are thermally stable when formed into a flat sheet or three-dimensional article to a temperature of at least 45° C. and are plastically deformable at room temperature (25° C.). The wax-based compositions include a wax fraction homogeneously blended with a polymer fraction. The wax fraction includes at least one wax and the polymer fraction includes at least one polymer selected such that, when the at least one wax and at least one polymer are homogeneously blended together, they yield a wax-based composition having the desired properties of thermal stability and plastic deformability. Barrier layers and oral treatment devices made from such wax-based compositions are dimensionally stable to a temperature of at least 40° C. without external support and can be plastically deformed in a user's mouth to become at least partially customized to the size and shape of user's unique dentition.

Abstract: The invention concerns a process to convert di-rhamnolipid to mono-rhamnolipid comprising the following process steps: —(a) contact of a starting di-rhamnolipid material with an ?-L-rhamnosidase enzyme which is immobilised on a support; (b) separation of the produced mono-rhamnolipid from the reaction medium and/or side products; wherein the ?-L-rhamnosidase enzyme does not have ?-D-glucosidase activity.

Abstract: Apparatus for providing breathing assistance, the apparatus including a body for positioning within an oral cavity of a user, the body defining at least one first opening for allowing airflow between lips of the user, two second openings provided in the oral cavity to allow air flow into and out of a posterior region of the oral cavity and two channels, each channel connecting a respective second opening to the at least one first opening and each channel passing at least one of at least partially along the buccal cavity and at least partially between the teeth to thereby provide an airway for the user, the airway at least partially bypassing the nasal passage and acting to replicate a healthy nasal passage and pharyngeal space.

Abstract: A computer-implemented method for determining whether a first image contains at least a portion of a second image includes: determining a first set of feature points associated with the first image; removing from said first set of feature points at least some feature points in the first set that correspond to one or more textures in the first image; and then attempting to match feature points in said first set of feature points with feature points in a second set of feature points associated with said second image to determine whether said first image contains at least a portion of said second image.

Abstract: Apparatus for providing breathing assistance, the apparatus including a body for positioning within an oral cavity of a user, the body defining at least one first opening for allowing airflow between lips of the user, two second openings provided in the oral cavity to allow air flow into and out of a posterior region of the oral cavity and two channels, each channel connecting a respective second opening to the at least one first opening and each channel passing at least one of at least partially along the buccal cavity and at least partially between the teeth to thereby provide an airway for the user, the airway at least partially bypassing the nasal passage and acting to replicate a healthy nasal passage and pharyngeal space.

Abstract: A computer-implemented method for determining whether a first image contains at least a portion of a second image includes: determining a first set of feature points associated with the first image; removing from said first set of feature points at least some feature points in the first set that correspond to one or more textures in the first image; and then attempting to match feature points in said first set of feature points with feature points in a second set of feature points associated with said second image to determine whether said first image contains at least a portion of said second image.

Abstract: A computer-implemented method for determining whether a first image contains at least a portion of a second image includes: determining a first set of feature points associated with the first image; removing from said first set of feature points at least some feature points in the first set that correspond to one or more textures in the first image; and then attempting to match feature points in said first set of feature points with feature points in a second set of feature points associated with said second image to determine whether said first image contains at least a portion of said second image.

Abstract: An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Feature points from the template image are then matched to the feature points in the test image. An additional matching technique boosts the number of points that match each other. The additional points improve the match quality and help discriminate true from false positive matches.

Abstract: An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Feature points from the template image are then matched to the feature points in the test image. An additional matching technique boosts the number of points that match each other. The additional points improve the match quality and help discriminate true from false positive matches.

Abstract: A computer-implemented method for determining whether a first image contains at least a portion of a second image includes: determining a first set of feature points associated with the first image; removing from said first set of feature points at least some feature points in the first set that correspond to one or more textures in the first image; and then attempting to match feature points in said first set of feature points with feature points in a second set of feature points associated with said second image to determine whether said first image contains at least a portion of said second image.

Abstract: A catheter assembly comprises a first elongate tubular member having a proximal end portion defining a proximal end, a distal end portion having an opening therein and defining a distal end, and at least one lumen defined between the proximal end and the distal end. A second elongate tubular member has a proximal end portion defining a proximal end, a distal end portion defining a distal end, and at least one lumen defined between the proximal end and the distal end. The second elongate tubular member is received within the at least one lumen of the first elongate tubular member, such that the distal end portion of the second elongate tubular member projects from the opening in the distal end portion of the first elongate tubular member. An elongate, shape-imparting element is receivable in the at least one lumen of at least one of the first elongate tubular member and the second elongate tubular member.

Abstract: An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Feature points of a template image are determined under various transformations and used to determine a set of composite feature points for each template image. The composite feature points are used to determine if the template image is present in a test image.

Abstract: An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Classifiers are trained for multiple template images and the classifiers are used to evaluate a match between a template image and a test image.

Abstract: A computer-implemented method for determining whether a first image contains at least a portion of a second image, includes: dividing set first image into multiple image regions; for a particular image region of the multiple image regions, determining a particular set of feature points associated with the particular image region; and attempting to match feature points in the particular set of feature points with second feature points associated with the second image to determine whether the particular image region of the first image contains at least a portion of the second image, wherein the first image is considered to contain at least a portion of a second image when the particular image region of the first image contains at least a portion of the second image.

Abstract: An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Feature points of a template image are determined under various transformations and used to determine a set of composite feature points for each template image. The composite feature points are used to determine if the template image is present in a test image. A covering set for a template image is used to optimize processing of test images.

Abstract: An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Feature points of a template image are determined under various transformations and used to determine a set of composite feature points for each template image. The composite feature points are used to determine if the template image is present in a test image.

Abstract: An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Classifiers are trained for multiple template images and the classifiers are used to evaluate a match between a template image and a test image.

Abstract: A computer-implemented method for determining whether a first image contains at least a portion of a second image includes: determining a first set of feature points associated with the first image; removing from said first set of feature points at least some feature points in the first set that correspond to one or more textures in the first image; and then attempting to match feature points in said first set of feature points with feature points in a second set of feature points associated with said second image to determine whether said first image contains at least a portion of said second image.

Abstract: An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Feature points of a template image are determined under various transformations and used to determine a set of composite feature points for each template image. The composite feature points are used to determine if the template image is present in a test image. A covering set for a template image is used to optimize processing of test images.