Abstract: A trimmer line spool has first and second spool chambers for a trimmer line. First and second holder pairs are provided. The first holder pair has first and second trimmer line holders associated with the first spool chamber and the second spool chamber, respectively. The second holder pair has first and second trimmer line holders associated with the first spool chamber and the second spool chamber, respectively. The trimmer line holders of the first holder pair each have a first opening for the trimmer line. The trimmer line holders of the second holder pair each have a second opening for the trimmer line. A diameter of the first openings is larger than a diameter of the second openings. The first openings are positioned at an angle of 150° to 210° to each other. The second openings are positioned at an angle of 150° to 210° to each other.

Abstract: The present invention relates to plate elements for the construction of a reactor module for carrying out endothermic reactions at high temperatures, the plate elements being designed in such a way that all reactant gases are heated by flowing around heating elements and the reaction zone is heated at the same time. The present invention also relates to reactor modules and reactor systems using the plate elements according to the invention pressed against each other, as well as the corresponding methods for efficiently carrying out endothermic chemical reactions, in particular the rWGS reaction.

Abstract: The present invention relates to a reactor having a multilayer structure, wherein the different layers are structured in a particular manner, in preferred embodiments comprising square openings to enable an improved heat transport during catalytic reactions. Furthermore, the present invention relates to multi-reactor structures, methods for providing the reactors and multi-reactor structures, as well as uses and applications.

Abstract: A method is for teaching a machine learning system to predict failure probabilities of chips on a wafer. The method is based on a prediction of final test yields depending on wafer-level test measurements by the machine learning system. The machine learning system predicts the failure probabilities of the chips depending on the wafer-level test measurements, and the predicted failure probabilities are aggregated to the predicted final test yields. The machine learning system is trained, such that a math difference between predicted final test yields and final test yields from a training data set is minimized. Differences between the predicted final test yields and final test yields from a training data set are minimized.

Abstract: A method for producing a cover for a sensor module and in particular for a vehicle sensor module, wherein in the order indicated a) a base body having larger dimensions as at least one cover is provided, b) a coating is arranged by a flood coating method on at least one surface of the base body, c) the cover is cut out of an inner region of the base body.

Abstract: A method for generating a fused automotive sensor data graph as well as an automotive control unit configured to perform the method are disclosed. A plurality of automotive sensor data graphs is obtained, which are each based on sensor data captured by a corresponding automotive sensor of the vehicle. At least one calibration matrix is obtained, which defines a transformation between sensor data nodes of at least two automotive sensor data graphs. Based on the plurality of automotive sensor data graphs and the at least one calibration matrix, the fused automotive sensor data graph is generated, which includes the plurality of automotive sensor data graphs as well as a plurality of fusion edges. The fused automotive sensor data graph is provided to an automotive perception function, which is implemented by a graph neural network.

Abstract: A method for estimating an uncertainty of an assignment rule that assigns first variables from a first set of first variables to second variables from a second set of second variables. The method includes: ascertaining inaccuracies of a machine learning system trained with the assignment rule, wherein the inaccuracies are ascertained by means of a difference between the second variables predicted by the machine learning system depending on the first variables and the second variables assigned to the first variables according to the assignment rule; ascertaining a covariance matrix depending on the ascertained inaccuracies; ascertaining a likelihood matrix and normalizing the likelihood matrix by dividing the value of the likelihood matrix by the corresponding column sum.

Abstract: A computer-implemented method of adjudicating an imaged lesion, comprising: receiving a diagnostic image showing a lesion; processing the diagnostic image in a machine learning algorithm previously trained to classify the lesion and to propose, based on a lesion class for the lesion, a blood test panel suited to adjudicate the lesion; and outputting the proposed blood test panel to a user.

Abstract: In a device and method for determining a contact between a tool and a workpiece, which are displaceable relative to each other, the tool or workpiece being rotationally fixedly connected to a shaft, the device includes a measuring arrangement including a measuring scale rotationally fixedly disposed on the shaft and at least one position encoder disposed in a stationary manner relative to the shaft, and a processing device. The position encoder is adapted to scan the measuring scale and to generate position values indicating a position of the shaft. The position values are fed to the processing device, which determines contact between the tool and the workpiece by evaluating a progression of the position values and signals the result of the evaluation by the status of a displacement signal.

Abstract: The present invention pertains to reactive (moisture curing) plasticizers; adhesives and sealants containing the plasticizers and methods of bonding and sealing substrates with adhesives and sealants containing the plasticizers.

Abstract: A computer-implemented method for optimizing a detection threshold of a prediction model used to determine an anomaly of a component is disclosed. The detection threshold indicates the criterion above which the prediction model classifies a component as anomalous.

Abstract: A method is for supporting medical personnel. The method includes taking account of patient data of the patient in an electronic health record stored in a first database; determining at least one prevalence value, each relating to a diagnosis to be made for a group of people including the patient, to which the patient has been classified as belonging in dependence on at least one part of the patient data; generating, from the at least one prevalence value, at least one item of evaluation information based on at least one future examination procedure performable with respect to the diagnosis to be made, taking into account prediction information present in a second database describing at least one of sensitivity and specificity for the at least one future examination procedure with respect to the diagnosis to be made; and outputting the at least one item of evaluation information to the medical personnel.

Abstract: A method for determining an operating condition of at least one plain bearing includes measuring, by a sensor, structure-borne noise arising from a toothed engagement of a first gear and a second gear, wherein the first gear is rotatably mounted via the plain bearing and meshes with the second gear. The method further includes assigning, to a signal of the sensor, a variable that correlates with the operating condition of the plain bearing.

Abstract: The present invention relates to a reactor having a multilayer structure, wherein the different layers are structured in a particular manner, in preferred embodiments comprising square openings to enable an improved heat transport during catalytic reactions. Furthermore, the present invention relates to multi-reactor structures, methods for providing the reactors and multi-reactor structures, as well as uses and applications.

Abstract: A sensor for measuring a species in a process medium includes a reinforced membrane, a sensor shaft, and an electrolyte provided between the reinforced membrane and the sensor shaft. The sensor shaft includes electrodes. A device for such a sensor also includes a pre-disposed gel electrolyte. Systems and methods related to the same are also disclosed.

Abstract: A system and method for identifying abnormal medical images. The system can be configured to receive a medical image, segment an anatomical structure from the medical image to define a segmented dataset, register the segmented dataset to a baseline dataset defining a normal anatomical structure, classify, by an abnormality classifier, whether the anatomical structure within the medical image as either abnormal or normal, wherein the abnormality classifier comprises a machine learning algorithm trained to distinguish between normal and abnormal versions of the anatomical structure in medical images, and based on whether the anatomical structure can be segmented from the medical image, whether the segmented dataset can be registered to the baseline dataset, or a classification associated with the medical image output by the abnormality classifier, flagging the medical image as either normal or abnormal.

Abstract: One or more example embodiments of the present invention relates to a computer-implemented method for providing radiological visualization data. The method includes receiving radiological imaging data which relates to an examination region, calculating confidence data based on the radiological imaging data, the confidence data relating to a confidence score with which an abnormality of the examination region can be automatically excluded, calculating the radiological visualization data which relates to the examination region, wherein a data reduction of the radiological visualization data relative to the radiological imaging data is effected as a function of the confidence data, and providing the radiological visualization data.

Abstract: An analysis method is for automatically determining radiological result data from radiology data sets. In an embodiment, the method includes provisioning a first radiology data set at least based on X-ray data of a first X-ray energy spectrum; provisioning at least one second radiology data set at least based on X-ray data of a second X-ray energy spectrum; provisioning an analysis unit including a neural network, to analyze radiology data sets including an input layer with a plurality of cells, a number of intermediate layers and an output layer representing a radiological result; analyzing the first radiology data set and the at least one second radiology data set, at least subsets of the first radiology data set and the at least one second radiology data set being assigned to different cells of the input layer for joint processing in the neural network; and acquiring result data on the output layer.