Abstract: The invention relates to a paste for marking textile fabrics and/or other products incapable of x-ray contrast. The paste comprises the mineral materials barite (BaSO4) and halloysite. These substances have a ratio of four volume parts barite to one volume part halloysite. The invention also relates to a wound dressing. The wound dressing contains composite fibers and is provided with the paste described at the outset. The invention additionally relates to the use of this wound dressing for the care of wound lesions. The invention also relates to a method for applying the paste described at the outset to a textile fabric and/or other products. The paste is applied to a textile fabric and/or to a different product by means of a printing process.

Abstract: A wound dressing is which has haemostatic, coagulation-promoting and biocidal properties and can therefore be utilized particularly for acute wound care. Typical areas of application for acute wound care are, for example, the treatment of gunshot wounds. The wound dressing features selected halloysites which, for example, are applied to textile fibers or non-woven materials.

Abstract: The invention relates to adhesives for medical applications and methods of their preparation and use.

Abstract: The invention relates to adhesives for medical applications and methods of their preparation and use.

Abstract: The invention relates to a kit comprising the following individual components: (a) polymers comprising at least one free amino group, (b) bridge molecules selected from the group consisting of monocyclic ortho-dihydroxyaromates, mono-cyclic para-dihydroxyaromates, bicyclic monohydrxyaromates, polycyclic monohydroxyaromates, bicyclic dihydroxyaromates, polycyclic dihydroxyaromates, bicyclic trihydroxyaromates, polycyclic trihydroxyaromates, and mixtures thereof, and (c) polyphenoloxidases, in particular, lignolytic polyphenoloxidases, whereby the individual components b) and c) are not in contact.

Abstract: The invention relates to a kit comprising the following individual components: (a) polymers comprising at least one free amino group, (b) bridge molecules selected from the group consisting of monocyclic ortho-dihydroxyaromates, mono-cyclic para-dihydroxyaromates, bicyclic monohydrxyaromates, polycyclic monohydroxyaromates, bicyclic dihydroxyaromates, polycyclic dihydroxyaromates, bicyclic trihydroxyaromates, polycyclic trihydroxyaromates, and mixtures thereof, and (c) polyphenoloxidases, in particular, lignolytic polyphenoloxidases, whereby the individual components b) and c) are not in contact.

Abstract: An optical scanning device is provided. The optical scanning device an excitation light source that is operable to illuminate the object to be scanned. An image detector is operable to detect excited emission rays through illumination of the object to be scanned by the excitation light source and imaging optics that dictate a focal distance. The image detector detects a scan image of the emission radiation of the object to be scanned with the highest level of image sharpness if the focal distance is maintained. A control device includes a distance sensor through which a distance between an optical scanning device and the object to be scanned can be measured, wherein maintenance of the focal distance as the function of the measured distance can be checked by the control device.

Abstract: In a method of 3D object detection, a learning procedure is used for feature selection from a feature set based on an annotated image-volume database, generating a set of selected features. A classifier is built using a classification scheme to distinguish between an object location and a non-object location and using the set of selected features. The classifier is applied at a candidate volume to determine whether the candidate volume contains an object of interest.

Abstract: A method for segmenting a digitized image includes providing a digitized image comprising a plurality of intensities defined on a lattice of pixels, initializing a Bayesian prior probability and likelihood function for segmenting said image, decomposing said image into a union of a plurality of subspaces wherein each subspace is a product of k-partitions, and distributing a plurality Bayesian posterior probability functions over said subspaces, updating said Bayesian posterior probability functions via a data-driven Markov-chain, and selecting a subset of said Bayesian posterior probability functions that approximate a true Bayesian posterior probability function.