Abstract: Described herein is a system and method in a user equipment (UE) supporting registration using third generation partnership project (3GPP) access and using non-3GPP access, the method comprising storing, in a memory of the UE, first emergency information received using first registration procedures; receiving, by the UE, a REGISTRATION ACCEPT message using second registration procedures via non-3GPP access; and keeping, in the memory, the first emergency information after receiving the REGISTRATION ACCEPT message.

Abstract: A method for measuring autophagosome flux is provided. The autophagosome pool size in a single cell is quantified, where the pool size is the total number of autophagosomes in the cell. Fusion between the autophagosomes and lysosomes in the cell is then inhibited. The autophagosome pool size is quantified over one or more time points after fusion has been inhibited, and the autophagosome flux is calculated as the initial rate of change of the autophagosome pool size at the time point after fusion has been inhibited. The method can be used to determine basal autophagosome flux, whether a cell is diseased or dysfunctional, or to diagnose a subject with a disease, disorder or dysfunction. The transition time, the time required to clear an autophagosome pool, can also be derived from the autophagosome flux. A molecule can also be characterized according to its ability to modulate autophagosome flux in a cell.

Abstract: A computer-implemented method for adapting a pretrained machine learning system, which has been trained on a first training data set, to a second dataset, wherein the second dataset has different characteristics than the first data set. An input transformation module for partly undoing the distribution shift between the first and second training data set is provided.

Abstract: A method of calibrating a sensors in a system for obtaining animal data from animals is described. The sensors are configured to obtain measurements of an animal related parameter during arbitrary visits by the animal to the sensors. For at least one of the animals, a first measurement associated with a first sensor of the sensors is obtained, and calculating one or more relations between the first measurement and one or more second measurements associated with the respective animal. Each of the second measurements is obtained using a further sensor, so as to obtain at least one representative relation for each combination of the first sensor and each one of the further sensors. The system calculates, based on the at least one representative relation, a correction factor associated with at least one sensor of the plurality of sensors.

Abstract: A computer-implemented method for post-training a machine learning system. The machine learning system is configured to generate digital images under the specification of a spatial image structure. The method includes: receiving training data, which each contain specifications of a spatial image structure, by means of the machine learning system; adding further parameters to the machine learning system; generating an image for each training datum by means of the machine learning system; ascertaining the spatial image structure of an image generated by the machine learning system, by means of a second machine learning system; and adjusting the further parameters by using a loss function, which measures a similarity between the ascertained spatial image structure of a generated image and the spatial image structure specified by the associated training datum.

Abstract: The present invention relates to an insufflator with a novel pressure measuring device for minimally invasive surgery. The new device allows to reliably measure the pressure in the body cavity while at the same time ensuring that the gas supply lines are free of occlusions.

Abstract: Described herein is a system and method in a user equipment (UE) supporting registration using third generation partnership project (3GPP) access and using non-3GPP access, the method comprising storing, in a memory of the UE, first emergency information received using first registration procedures; receiving, by the UE, a REGISTRATION ACCEPT message using second registration procedures via non-3GPP access; and keeping, in the memory, the first emergency information after receiving the REGISTRATION ACCEPT message.

Abstract: A process for producing a carboxylic acid composition including 2,5-furandicarboxylic acid, including the steps: a) oxidizing an oxidizable compound including 5-alkoxymethylfurfural in an oxidation reactor in the presence of a saturated organic acid solvent having from 2 to 6 carbon atoms and a catalyst system comprising cobalt, manganese and bromine using an oxidizing gas at a temperature in the range of 160 to 210° C. to obtain a crude carboxylic acid composition including mono alkyl ester of 2,5-furandicarboxylic acid and solid 2,5-furandicarboxylic acid, b) isolating at least a portion of the solid 2,5-furandicarboxylic acid from the crude carboxylic acid composition in a solid-liquid separation zone to generate a solid cake and a mother liquor, c) determining the amount of manganese and/or cobalt in the cake, and d) increasing the amount of one or more controlling acids in the oxidation reactor.

Abstract: Subject matter of the invention is a method for determining the difference in height level between a medical fluid pump and the body cavity of a patient for the correction of the measurement of the fluid pressure existing at the outlet end.

Abstract: A computer-implemented method of classifying a sensor signal by a sensor signal encoder and a text encoder. The encoders are configured to encoder their inputs into a latent representation. The method includes: encoding the sensor signal to a first latent representation by the sensor signal encoder; generating a plurality of text prompts, wherein for each class several text prompts characterizing the corresponding class are instantiated; encoding the generated text prompts into second latent representations by the text encoder; determining a class query for each class by weighted averaging over the second representations corresponding to the same class; computing a similarity between the first latent representation and each of the class queries; assigning the sensor signal to the class with the highest similarity.

Abstract: Disclosed is a medical imaging system (100, 400) component comprising: an optical image generator (122) configured for generating a two-dimensional image (200); an optical imaging system (126) configured for acquiring optical image data (166); and an optical waveguide bundle (124) comprising a subject end (132) and an equipment end (130). The subject end comprises at least one lens (136, 136). The optical image generator is configured for optically coupling to the equipment end to form an image projection pathway. The optical waveguide bundle is configured for projecting the two-dimensional image through the image projection pathway. The optical imaging system is configured for optically coupling to the equipment end to form an optical image data acquisition pathway. The optical imaging system is configured for acquiring the optical image data through the lens via the optical image data acquisition pathway.

Abstract: A method for forming an electrical contact is provided. The method includes grinding a silicon carbide surface using a grinding disk which includes a grinding face containing nickel or a nickel compound, such that particles of the nickel or nickel compound from the grinding disk are embedded in the ground silicon carbide surface, and hardening the ground silicon carbide surface with the aid of a laser, such that at least some of the embedded nickel particles form a nickel silicide with silicon from the silicon carbide.

Abstract: Provided herein is an arc-shaped meniscus prosthesis with a first end having a first fastening part for securing the first end to a bone surface and a second end having a second fastening part for securing the second end to a bone surface. A curved intermediate section connects the first end and the second end. The curved intermediate section is made of a single first biocompatible, non-resorbable material that has a tensile modulus of at most 160 MPa. The first material is isotropic with regard to the tensile modulus and the intermediate section is a monolithic piece of the first material.

Abstract: The present invention relates to a packaging unit (2) for a moulded pulp material and a manufacturing process therefore. The packaging unit according to the invention comprises a product receiving or carrying compartment having a product contact surface, wherein the product contact surface comprises a peelable laminate layer (10). In a presently preferred embodiment the moulded pulp material comprises an amount of a bio-degradable aliphatic polyester.

Abstract: A computer-implemented method for determining an output signal characterizing a semantic segmentation and/or an instance segmentation of an image. The method includes: determining a first intermediate output signal from a machine learning system, wherein the first intermediate output signal characterizes a semantic segmentation and/or an instance segmentation of the image; adapting parameters of the machine learning system based on a loss function, wherein the loss function characterizes an entropy or a cross-entropy of the first intermediate output signal; determining the output signal from the machine learning system based on the image and the adapted parameters.

Abstract: A method comprising transmitting, by a user equipment (UE) to a network node, a registration message comprising at least one of a first indicator configured to indicate emergency call information display capability, a second indicator configured to indicate language information, or a third indicator configured to indicate a status of previously received emergency information, and receiving, by the user equipment from the network node, a registration accept message.

Abstract: A trench transistor. The transistor including: a semiconductor region, a trench structure formed in the semiconductor region; a gate insulation layer and an electrically conductive gate layer formed on the gate insulation layer in the trench structure, and a gate contact, which is electrically conductively connected to the gate layer in an edge area of the trench transistor. A thickness of the gate insulation layer in the edge area of the trench transistor is greater than in an active area of the trench transistor.

Abstract: A method for processing measurement data in a neural network including a plurality of layers of neurons. In the method: inputs supplied to each neuron are processed according to parameters associated with the neuron to produce a work result; a group of neurons is selected; a target distribution for the work results of the neurons of the group is defined; an inverse cumulative density function of the target distribution is provided; the work results are mapped with a predetermined unit function onto unit values in an interval, so that the unit value associated with each work result occupies the same rank on the list of all unit values as the corresponding work result occupies on the list of all work results; normalized work results are calculated from the unit values using the inverse cumulative density function; the normalized work results are further processed to produce outputs of the neural network.

Abstract: The present invention relates to a double-face adhesive tape that can be removed by twisting, prying or peeling off from, e.g., a wall without leaving residues. The present invention also relates to a method for the concealed mounting on and residue-free and non-destructive removal of objects from a sensitive substrate, wherein the object is affixed to the sensitive substrate by means of the double-face adhesive tape and, as and when necessary, is removed by twisting or prying or peeling.

Abstract: A method for gradient-based retraining of a machine learning system with non-public training data with regard to a target task. The method includes: adding further parameters to the pre-trained machine learning system, and adjusting the added further parameters with the non-public training data using a differentially private backpropagation method, wherein the added parameters are adjusted with regard to the target task.