Abstract: The disclosure relates to a motor vehicle having a data network via multiple control devices of the motor vehicle for exchanging message data (that are coupled together, wherein the data network is subdivided into different domains and via each of the domains respectively some of the control devices are coupled to the data network and in each domain respectively other of the control devices are included and the exchange of message data is blocked between the control devices of different domains or permitted only as a function of an authorization check of at least one domain transition is provided. The disclosure provides that the data network also includes an overall domain and each of the control devices is also coupled via the overall domain to the data network.

Abstract: The disclosure relates to a motor vehicle having a data network via multiple control devices of the motor vehicle for exchanging message data (that are coupled together, wherein the data network is subdivided into different domains and via each of the domains respectively some of the control devices are coupled to the data network and in each domain respectively other of the control devices are included and the exchange of message data is blocked between the control devices of different domains or permitted only as a function of an authorization check of at least one domain transition is provided. The disclosure provides that the data network also includes an overall domain and each of the control devices is also coupled via the overall domain to the data network.

Abstract: Apparatus and methods for calculating cardiac output (CO) of a living subject using applanation tonometry measurements. In one embodiment, the apparatus and methods build a nonlinear mathematical model to correlate physiologic source data vectors to target CO values. The source data vectors include one or more measurable or derivable parameters such as: systolic and diastolic pressure, pulse pressure, beat-to-beat interval, mean arterial pressure, maximal slope of the pressure rise during systole, the area under systolic part of the pulse pressure wave, gender (male or female), age, height and weight. The target CO values are acquired using various methods, across a plurality of individuals. Multidimensional nonlinear optimization is then used to find a mathematical model which transforms the source data to the target CO data. The model is then applied to an individual by acquiring physiologic data for the individual and applying the model to the collected data.

Abstract: The present invention relates to a method of producing an oligomer array. The invention comprises the steps of: providing a substrate with a multitude of recesses; introducing a first particle with a first molecule into a recess; releasing the first molecule from the first particle; binding the first molecule to a second molecule to form an oligomer while immobilizing the second molecule in the recess; optionally repeating the steps, wherein at least one of the first particles and/or the first molecules comprises a detectable marker.

Abstract: The present invention relates to a method of producing an oligomer array. The invention comprises the steps of: providing a substrate with a multitude of recesses; introducing a first particle with a first molecule into a recess; releasing the first molecule from the first particle; binding the first molecule to a second molecule to form an oligomer while immobilizing the second molecule in the recess; optionally repeating the steps, wherein at least one of the first particles and/or the first molecules comprises a detectable marker.

Abstract: Apparatus and methods for calculating cardiac output (CO) of a living subject using applanation tonometry measurements. In one embodiment, the apparatus and methods build a nonlinear mathematical model to correlate physiologic source data vectors to target CO values. The source data vectors include one or more measurable or derivable parameters such as: systolic and diastolic pressure, pulse pressure, beat-to-beat interval, mean arterial pressure, maximal slope of the pressure rise during systole, the area under systolic part of the pulse pressure wave, gender (male or female), age, height and weight. The target CO values are acquired using various methods, across a plurality of individuals. Multidimensional nonlinear optimization is then used to find a mathematical model which transforms the source data to the target CO data. The model is then applied to an individual by acquiring physiologic data for the individual and applying the model to the collected data.

Abstract: Apparatus and methods for calculating cardiac output (CO) of a living subject. In one embodiment, the apparatus and methods build a nonlinear mathematical model to correlate physiologic source data vectors to target CO values. The source data vectors include one or more measurable or derivable parameters such as: systolic and diastolic pressure, pulse pressure, beat-to-beat interval, mean arterial pressure, maximal slope of the pressure rise during systole, the area under systolic part of the pulse pressure wave, gender (male or female), age, height and weight. The target CO values are acquired using various methods, across a plurality of individuals. Multidimensional nonlinear optimization is then used to find a mathematical model which transforms the source data to the target CO data. The model is then applied to an individual by acquiring physiologic data for the individual and applying the model to the collected data.

Abstract: Apparatus and methods for calculating cardiac output (CO) of a living subject. In one embodiment, the apparatus and methods build a nonlinear mathematical model to correlate physiologic source data vectors to target CO values. The source data vectors include one or more measurable or derivable parameters such as: systolic and diastolic pressure, pulse pressure, beat-to-beat interval, mean arterial pressure, maximal slope of the pressure rise during systole, the area under systolic part of the pulse pressure wave, gender (male or female), age, height and weight. The target CO values are acquired using various methods, across a plurality of individuals. Multidimensional nonlinear optimization is then used to find a mathematical model which transforms the source data to the target CO data. The model is then applied to an individual by acquiring physiologic data for the individual and applying the model to the collected data.

Abstract: Apparatus and methods for calculating cardiac output (CO) of a living subject using applanation tonometry measurements. In one embodiment, the apparatus and methods build a nonlinear mathematical model to correlate physiologic source data vectors to target CO values. The source data vectors include one or more measurable or derivable parameters such as: systolic and diastolic pressure, pulse pressure, beat-to-beat interval, mean arterial pressure, maximal slope of the pressure rise during systole, the area under systolic part of the pulse pressure wave, gender (male or female), age, height and weight. The target CO values are acquired using various methods, across a plurality of individuals. Multidimensional nonlinear optimization is then used to find a mathematical model which transforms the source data to the target CO data. The model is then applied to an individual by acquiring physiologic data for the individual and applying the model to the collected data.