Friedrich-Alexander-Universität Erlangen-Nürnberg

A, preferably computer-implemented, method of automatic data format adaptation, the method comprising the steps of: determining machine data generated by one or more machines controlling a production process, the machine data being incompatible with a data parser, prompting a computational model for language processing, LLM, with the incompatible machine data and a desired output data format, e.g., with machine data in the desired output data format, for the LLM to generate a program code capable of converting the incompatible machine data into the desired output data format, updating the data parser to comprise the program code capable of converting the incompatible machine data into the desired output data format.

For material characterization, first and second measured MRI data (20, 23, 26) representing an object (6) and corresponding first and second sequence descriptions (21, 24, 27) are received. For each iteration, first and second simulated MRI data (22, 25, 28) is generated according to the sequence descriptions (21, 24, 27) based on a model (29) comprising model values for at least one material parameter. An error (31) is determined, which depends on a deviation of the simulated MRI data (22, 25, 28) from the measured MRI data (20, 23, 26). The model (29) is adapted depending on the error (31). For an initial iteration, the model (29) corresponds to an initial model (29) and otherwise it corresponds to the adapted model (29) of the preceding iteration. The quantitative material characterization is determined depending on the adapted model (29) of a final iteration of the two or more iterations.

The invention relates to systems comprising a device, in particular a digital subtraction angiography (DSA) device, and a method of temporal interpolation based on data measured by the device. The method comprises generating training data for a neural network; training the neural network using the generated training data; measuring a series of data frames on a sample; interpolating one or more data frames using the trained neural network based on a plurality of data frames of the measured series of data frames to increase a temporal resolution of the measured series of data frames and/or to extrapolate the measured series of data frames. In DSA, the systems and methods enable increased accuracy of estimations of, for instance, a bolus arrival time (BAT) enabling, for instance, improved use of contrast agents (CAs) and/or improved diagnosis of circulatory issues while reducing the risk of unnecessary exposure to radiation. More generally, a time required for performing measurements may be reduced, thereby reducing costs and/or increasing the lifetime of the measurement device.

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Zusammenfassung wird geladen …

The invention describes a method for automatic motion detection in medical image-series, comprising the steps: - providing a dataset (D) of a series of images (I1, I2, I3), wherein images (I1, I2, I3) of a similar region of interest are recorded at consecutive points of time, - calculating localization data (LD) of a target (T) by localizing the target (T) in the images (I1, I2, I3) of the dataset (D) and calculating the position of this target (T) in these images (I1, I2, I3), - calculating movement data (MD) of the movement of the target (T) on the basis of temporal adjacent images (I1, I2, I3) based on the localization data (LD). The invention further describes a related system, a related control device and a related medical imaging system.

Ein Messsystem (1) zur primären und instrumentierten Härtemessung eines Gegenstands (2) mit direkter Rückführung über die primäre Kraft- und Wegmessung umfasst ein Stativ (3) mit einer Grundplatte (4) und einer daran befestigten Vertikalsäule (5), einem entlang der Vertikalsäule (5) verfahrbaren Stativschlitten (17) und mit einem Gegenlager (6) zum Auflegen des Gegenstands (2), einen am Stativschlitten (17) befestigten und relativ dazu geführt verlagerbaren Läufer (19) mit einem Indenter (20) zum Eindringen in den Gegenstand (2), mit mindestens einem Krafterzeugungs-Aktor (23, 24), mindestens einem Bewegungserzeugungs-Aktor (23, 24), wobei der Indenter (20) über die Aktoren (23, 24) mit dem Stativschlitten (17) gekoppelt ist, wobei der Indenter (20), der mindestens eine Krafterzeugungs-Aktor (23, 24) der Stativschlitten (17), die Grundplatte (4), die Vertikalsäule (5), das Gegenlager (6) und der Gegenstand (2) einen Kraftmesskreis (48) definieren. Das Messsystem (1) umfasst ferner einen Metrologierahmen (12), der an dem Gegenlager (6) befestigt ist und sich seitlich an der Vertikalsäule (5) abstützt, eine Wegmesseinheit (33) zur Messung eines Weges des Stativschlittens (17) und/oder des Läufers (19) mit dem Indenter (20), wobei der Metrologierahmen (12), die Wegmesseinheit (33), der Läufer (19), der Indenter (20), der Gegenstand (2) und das Gegenlager (6) einen Wegmesskreis (47) definieren, wobei der Kraftkreis (48) und der Wegmesskreis (47) großteils getrennt voneinander ausgeführt sind.

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An electrode assembly is provided, comprising (a) a first electrode (1), (b) a monolayer of particles (2), (c) an electron transport material (ETM) layer (3), (d) a light-absorbing layer (4), (e) a hole transport material (HTM) layer (5), and (f) a second electrode (6), wherein at least one of the first and the second electrode (1, 6) is transparent; wherein said monolayer of particles (2) is a non-close packed monolayer; wherein the monolayer of particles (2) is obtained by depositing a non-close packed monolayer of core-shell particles and subsequently removing the shell from said as-deposited non-close packed monolayer of core-shell particles; and wherein a minimum interparticle distance in the monolayer of particles (2) is equal to or greater than two times the thickness of the shell of said core-shell particles. Furthermore, a process for manufacturing the electrode assembly as well as photovoltaic device, comprising the electrode assembly and the use of a non-close packed monolayer of transparent particles in an electrode assembly are provided.