Abstract: A system includes a sensor element arranged to detect a spectrum of noise or vibrations of a medical device to be supervisedthe, a supervising element, whereby the sensor element and the supervising element may communicate with each other and thereby allow for provisioning of data corresponding to the acoustic signals, whereby the system further comprises a localized or distributed detection engine, the detection engine analyzing the data corresponding to the acoustic signals such that typical failures of each of a plurality of individual components of the medical device are distinguished, whereby the system further comprises a notification engine, the notification engine providing indications on the maintenance state of the medical device and/or one or more of the plurality of individual components of the medical device. The disclosure also pertains to a computer-implemented method for determining a maintenance state of a medical device.

Abstract: A cargo floor, in particular a trunk or storage floor, for a motor vehicle. The cargo floor includes a layer-shaped construction with a core layer, a first reinforcement layer and a second reinforcement layer. The core layer is arranged between the first reinforcement layer and the second reinforcement layer and includes a honeycomb structure produced in particular from polypropylene (PP). It is conceivable that the first reinforcement layer and/or the second reinforcement layer each include a meshwork made of a plurality of thermoplastic continuous fiber tapes (UD tapes).

Abstract: The described technology may include processes to model a modality status in patients and/or patient populations. In one embodiment, a method may include a modality analysis. The method may include, via a processor of a computing device: determining a modality analysis model configured to determine a modality status of a patient, the modality status configured to indicate a probability of a transition from a first modality to a second modality, and generating the modality status via the modality analysis model using patient information associated with the patient. Other embodiments are described.