Abstract: A method for scheduling a set of jobs for a plurality of machines. Each job is defined by at least one feature which characterizes a processing time of the job. If any of the machines is free, a job from of the set of jobs is selected to be carrying out by said machine and scheduled for said machine. The job is selected as follows: a Graph Neural Network receives as input the set of jobs and a current state of at least the machine which is free, the Graph Neural Network outputs a reward for the set of jobs if launched on the machines, which states are inputted into the Graph Neuronal Network, and the job for the free machine is selected depending on the Graph Neural Network output.

Abstract: Provided herein is a curable fluoroelastomer composition including at least one fluoroelastomer comprising copolymerized units of a nitrile group-containing cure site monomer; a cure system comprising at least two different dihydrazides; and optionally at least one additive. Further provided are pre-forms comprising the curable composition, methods of curing the fluoroelastomer composition, compositions that are the product of curing the curable fluoroelastomer composition, and articles comprising the cured fluoroelastomer composition.

Abstract: Methods for ascertaining a control strategy for a technical system using a Bayesian optimization method. The control strategy is created based on model parameters of a control model and is executable. The method includes providing a quality function whose shape corresponds to a regression function and that evaluates a quality of a controlling of the technical system based on model parameters; carrying out a Bayesian optimization method based on the quality function in order to iteratively ascertain a model parameter set having model parameters within a model parameter domain that indicates the permissible value ranges for the model parameters; and determining the model parameter domain for at least one of the model parameters as a function of an associated maximum a posteriori estimated value of the quality function.

Abstract: An aircraft has a first antenna arrangement, a payload and a processing unit. The first antenna arrangement is designed to wirelessly receive electromagnetic signals. The processing unit is coupled to the first antenna arrangement, on the one hand, and to the payload, on the other hand. The processing unit is designed to modulate an electromagnetic signal received by the first antenna arrangement and thereby to generate a first modulated signal and to forward it to the payload. The payload is designed to use the first modulated signal as working signal. A radiofrequency power signal on an uplink is thus remodulated into a payload working signal, such that the payload working signal is able to be used directly by the payload without rectification into a DC voltage.

Abstract: A computational method for training a meta-learned, evolution strategy black box optimization classifier. The method includes receiving one or more training functions and one or more initial meta-learning parameters of the optimization classifier. The method further includes sampling a sampled objective function from the one or more training functions and an initial mean of the sampled function. The method also includes computing a set of T number of means by running the meta learned, evolution strategy classifier on the sampled objective function using the initial mean for T number of steps in t=1, . . . , T. The method also includes computing a loss function from the set of T number of means. The method further includes updating the one or more initial meta-learning parameters of the optimization classifier in response to a characteristic of the loss function.

Abstract: An aircraft has a first antenna arrangement, a payload and a processing unit. The first antenna arrangement is designed to wirelessly receive electromagnetic signals. The processing unit is coupled to the first antenna arrangement, on the one hand, and to the payload, on the other hand. The processing unit is designed to modulate an electromagnetic signal received by the first antenna arrangement and thereby to generate a first modulated signal and to forward it to the payload. The payload is designed to use the first modulated signal as working signal. A radiofrequency power signal on an uplink is thus remodulated into a payload working signal, such that the payload working signal is able to be used directly by the payload without rectification into a DC voltage.

Abstract: The invention relates to a method for connecting a first component, in particular a lancing means, to a second component, in particular a syringe body, in order to produce a product for medical or cosmetic purposes, by means of adhesion, having the following steps: (a) providing the first and the second component; (b) tempering at least one first contact surface of the first component and/or at least one second contact surface of the second component to a temperature T1; and (c) applying an adhesive to at least one portion of the first contact surface and/or to at least one portion of the second contact surface, wherein the adhesive is at a temperature T2, wherein temperatures T1 and T2 differ only by a tolerance deviation, wherein the tolerance deviation is at most 10° C.

Abstract: Method for coating a glass syringe body for a hypodermic pre-filled glass syringe, wherein at least one emulsion and/or one solution containing at least one layer-forming substance is applied to at least one inner surface of the hypodermic pre-filled glass syringe, which defines an axial direction, wherein at least a partial surface of the inner surface in a syringe cone of the pre-filled glass syringe is subsequently exposed to a plasma, wherein a negative pressure source is arranged in relation to the syringe cone in the axial direction opposite the atmospheric-pressure plasma source, wherein a negative pressure of less than atmospheric pressure is provided by means of the negative pressure source.

Abstract: Provided herein is a curable fluoroelastomer composition including at least one fluoroelastomer comprising copolymerized units of a nitrile group-containing cure site monomer; a cure system comprising at least two different dihydrazides; and optionally at least one additive. Further provided are pre-forms comprising the curable composition, methods of curing the fluoroelastomer composition, compositions that are the product of curing the curable fluoroelastomer composition, and articles comprising the cured fluoroelastomer composition.

Abstract: A system is described for configuring another system, e.g., a robotics system. The other system interacts with an environment according to a deterministic policy by repeatedly obtaining, from a sensor, sensor data indicative of a state of the environment, determining a current action, and providing, to an actuator, actuator data causing the actuator to effect the current action in the environment. To configure the other system, the system optimizes a loss function based on an accumulated reward distribution with respect to a set of parameters of the policy. The accumulated reward distribution includes an action probability of an action of a previous interaction log being performed according to the current set of parameters. The action probability is approximated using a probability distribution defined by an action selected by the deterministic policy according to the current set of parameters.

Abstract: Methods for ascertaining a control strategy for a technical system using a Bayesian optimization method. The control strategy is created based on model parameters of a control model and is executable. The method includes providing a quality function whose shape corresponds to a regression function and that evaluates a quality of a controlling of the technical system based on model parameters; carrying out a Bayesian optimization method based on the quality function in order to iteratively ascertain a model parameter set having model parameters within a model parameter domain that indicates the permissible value ranges for the model parameters; and determining the model parameter domain for at least one of the model parameters as a function of an associated maximum a posteriori estimated value of the quality function.

Abstract: A method is provided for ascertaining a NOx concentration and an NH3 slip downstream from an SCR catalytic converter of an internal combustion engine of a vehicle. State variables of an internal combustion engine as first input variables and an updated NH3 fill level of the SCR catalytic converter as a second input variable cooperate with at least one machine learning algorithm or at least one stochastic model. The at least one machine learning algorithm or at least one stochastic model calculates the NOx concentration and the NH3 slip downstream from the SCR catalytic converter as a function of the first input variables and the second input variables and output the same as output variables.

Abstract: A computational method for training a meta-learned, evolution strategy black box optimization classifier. The method includes receiving one or more training functions and one or more initial meta-learning parameters of the meta-learned, evolution strategy black box optimization classifier. The method further includes sampling a sampled objective function from the one or more training functions and an initial mean of the sampled function. The method also includes computing a set of T number of means by running the meta-learned, evolution strategy black box optimization classifier on the sampled objective function using the initial mean for T number of steps in t=1, . . . ,T. The method also includes computing a loss function from the set of T number of means. The method further includes updating the one or more initial meta-learning parameters of the meta-learned, evolution strategy black box optimization classifier in response to a characteristic of the loss function.

Abstract: A method for scheduling a set of jobs for a plurality of machines. Each job is defined by at least one feature which characterizes a processing time of the job. If any of the machines is free, a job from of the set of jobs is selected to be carrying out by said machine and scheduled for said machine. The job is selected as follows: a Graph Neural Network receives as input the set of jobs and a current state of at least the machine which is free, the Graph Neural Network outputs a reward for the set of jobs if launched on the machines, which states are inputted into the Graph Neuronal Network, and the job for the free machine is selected depending on the Graph Neural Network output.

Abstract: A method for ascertaining a time characteristic of a measured variable adjustable by an actuator, wherein a time characteristic of a control variable is applied to the actuator, wherein the ascertaining is effected by means of a Gaussian process state model of the behavior of the actuator, wherein the time characteristic of the measured variable of the actuator is ascertained on the basis of a parameterizable family of functions, wherein in the parameterizable family of functions a time dependency of a later latent state, in particular ascertained using a transfer function, of the actuator on an earlier latent state of the actuator and an earlier control variable of the actuator is the same as the applicable dependency of the Gaussian process state model.

Abstract: A method for ascertaining a time characteristic of a measured variable adjustable by an actuator, wherein a time characteristic of a control variable is applied to the actuator, wherein the ascertaining is effected by means of a Gaussian process state model of the behavior of the actuator, wherein the time characteristic of the measured variable of the actuator is ascertained on the basis of a parameterizable family of functions, wherein in the parameterizable family of functions a time dependency of a later latent state, in particular ascertained using a transfer function, of the actuator on an earlier latent state of the actuator and an earlier control variable of the actuator is the same as the applicable dependency of the Gaussian process state model.

Abstract: A system is described for configuring another system, e.g., a robotics system. The other system interacts with an environment according to a deterministic policy by repeatedly obtaining, from a sensor, sensor data indicative of a state of the environment, determining a current action, and providing, to an actuator, actuator data causing the actuator to effect the current action in the environment. To configure the other system, the system optimizes a loss function based on an accumulated reward distribution with respect to a set of parameters of the policy. The accumulated reward distribution includes an action probability of an action of a previous interaction log being performed according to the current set of parameters. The action probability is approximated using a probability distribution defined by an action selected by the deterministic policy according to the current set of parameters.

Abstract: The invention relates to a method for connecting a first component, in particular a lancing means, to a second component, in particular a syringe body, in order to produce a product for medical or cosmetic purposes, by means of adhesion, having the following steps: (a) providing the first and the second component; (b) tempering at least one first contact surface of the first component and/or at least one second contact surface of the second component to a temperature T1; and (c) applying an adhesive to at least one portion of the first contact surface and/or to at least one portion of the second contact surface, wherein the adhesive is at a temperature T2, wherein temperatures T1 and T2 differ only by a tolerance deviation, wherein the tolerance deviation is at most 10° C.

Abstract: A method is provided for ascertaining a NOx concentration and an NH3 slip downstream from an SCR catalytic converter of an internal combustion engine of a vehicle. State variables of an internal combustion engine as first input variables and an updated NH3 fill level of the SCR catalytic converter as a second input variable cooperate with at least one machine learning algorithm or at least one stochastic model. The at least one machine learning algorithm or at least one stochastic model calculates the NOx concentration and the NH3 slip downstream from the SCR catalytic converter as a function of the first input variables and the second input variables and output the same as output variables.

Abstract: Method for coating a glass syringe body for a hypodermic pre-filled glass syringe, wherein at least one emulsion and/or one solution containing at least one layer-forming substance is applied to at least one inner surface of the hypodermic pre-filled glass syringe, which defines an axial direction, wherein at least a partial surface of the inner surface in a syringe cone of the pre-filled glass syringe is subsequently exposed to a plasma, wherein a negative pressure source is arranged in relation to the syringe cone in the axial direction opposite the atmospheric-pressure plasma source, wherein a negative pressure of less than atmospheric pressure is provided by means of the negative pressure source.