Abstract: The present application relates to novel substituted indazoles, to processes for preparation thereof, to the use thereof alone or in combinations for treatment and/or prophylaxis of diseases, and to the use thereof for production of medicaments for treatment and/or prophylaxis of diseases, especially for treatment and/or prophylaxis of endometriosis and endometriosis-associated pain and other endometriosis-associated symptoms such as dysmenorrhoea, dyspareunia, dysuria and dyschezia, of lymphoma, rheumatoid arthritis, spondyloarthritis (especially psoriatic spondyloarthritis and Bekhterev's disease), lupus erythematosus, multiple sclerosis, macular degeneration, COPD, gout, fatty liver disorders, insulin resistance, neoplastic disorders and psoriasis.

Abstract: An axial piston motor having a cylinder housing, in which a plurality of cylinders are formed, and having pistons which are movably guided in the cylinders, wherein the pistons are attached to a swash plate and wherein a flow of a fluid that has entered via an inlet into the axial piston motor is controlled into and out of the cylinders by means of inlet and outlet valves, wherein the inlet and/or outlet valves comprise fluid change openings which are formed in a cylinder head plate and which can be temporarily released and covered by means of a rotary slide, for which purpose the rotary slide forms at least one passage opening.

Abstract: An axial piston motor having a cylinder housing, in which a plurality of cylinders are formed, and having pistons which are movably guided in the cylinders, wherein the pistons are attached to a swash plate and wherein a flow of a fluid that has entered via an inlet into the axial piston motor is controlled into and out of the cylinders by means of inlet and outlet valves, wherein the inlet and/or outlet valves comprise fluid change openings which are formed in a cylinder head plate and which can be temporarily released and covered by means of a rotary slide, for which purpose the rotary slide forms at least one passage opening.

Abstract: The disclosure concerns a method for assessing muscular dystrophy-linked protein expression in muscle fibers using digital image analysis of tissue. The method relates to assessing disease severity in individuals with muscular dystrophy. Muscle tissue samples are obtained from patients submitted for evaluation and processed to produce tissue sections mounted on glass slides which have been stained for a muscular dystrophy-linked protein. Digital images of the stained tissue sections are generated and analyzed by applying an algorithm process implemented by a computer to the images. The algorithm process extracts the morphometric and staining features of the muscular dystrophy-linked protein staining in the tissue, and parameters relating to these features are used to score the disease status for each patient submitted for evaluation.

Abstract: The disclosure concerns a method for extracting geographic distribution statistics from patient tissue samples assayed with a tissue-based test for the purpose of scoring the patient tissue samples and guiding treatment based on the score(s). The method described herein utilizes digital image analysis of an image of one or more tissue sections to extract object-based (e.g., cells) features to generate a data array representing said tissue numerically in image analysis feature space. The numerical representation of the image of the tissue section in image analysis feature space is further processed using one or more algorithm processes to extract sophisticated geographical distribution features of one or more object type or sub-type in the tissue. Statistics describing the geographic distribution features are summarized to generate a patient-specific diagnostic score, and this score can be evaluated to guide patient treatment decisions.

Abstract: The disclosure concerns a method for patient stratification and selection of patients who are candidates for a specific therapy is described which is based on quantifying one or more digital image analysis feature distributions from stained tissue. The method extends beyond the abilities of a manual observer and a microscope, and generally comprises: acquiring digital images of stained tissue sections from patients submitted for evaluation, applying an algorithm process to said images with a computer to extract the morphometric and staining features of image pixels and tissue objects, deriving one or more distribution function for one or more image analysis features, calculating a summary statistic of the one or more distribution functions, and using said summary statistic along with an associated predefined patient stratification paradigm to separate a patient cohort into distinct strata which correspond to a decision to include or exclude a patient for a specific therapy.

Abstract: The disclosure concerns a method for assessing muscular dystrophy-linked protein expression in muscle fibers using digital image analysis of tissue. The method relates to assessing disease severity in individuals with muscular dystrophy. Muscle tissue samples are obtained from patients submitted for evaluation and processed to produce tissue sections mounted on glass slides which have been stained for a muscular dystrophy-linked protein. Digital images of the stained tissue sections are generated and analyzed by applying an algorithm process implemented by a computer to the images. The algorithm process extracts the morphometric and staining features of the muscular dystrophy-linked protein staining in the tissue, and parameters relating to these features are used to score the disease status for each patient submitted for evaluation.

Abstract: The disclosure concerns a method for patient stratification and selection of patients who are candidates for a specific therapy is described which is based on quantifying one or more digital image analysis feature distributions from stained tissue. The method extends beyond the abilities of a manual observer and a microscope, and generally comprises: acquiring digital images of stained tissue sections from patients submitted for evaluation, applying an algorithm process to said images with a computer to extract the morphometric and staining features of image pixels and tissue objects, deriving one or more distribution function for one or more image analysis features, calculating a summary statistic of the one or more distribution functions, and using said summary statistic along with an associated predefined patient stratification paradigm to separate a patient cohort into distinct strata which correspond to a decision to include or exclude a patient for a specific therapy.

Abstract: Data processing systems and methods are provided that improve the perceived efficiency of image analysis tools in a digital pathology workflow when challenged by analyzing large size microscopic images. Various embodiments utilize a separation of the image analysis programs into a first automatically executed segment that requires no user interactions for identification and quantification of object data of processed images, and a second interactive segment for accepting user input. User interactions are only applied to the already calculated object data resulting in an improved system response time. A tile-based processing scheme with concurrent processing and generation of object data in a tile-based data format provides further performance improvements of the system.

Abstract: Methods for cell-based tissue analysis utilize modern trends in digital microscopy to obtain, process, calibrate, and analyze digital images of tissue sections to quantify cell-based data for improved histological analysis. Using data from multiple images of a common tissue section, or data from images of multiple tissue sections, additional degrees of freedom are realized and the resulting analysis provides added depth to histological analysis of tissue samples. With computerized analytical methods, speed and accuracy of histological analysis is greatly improved.

Abstract: Systems and methods relating to a cell-based pattern recognition tool for microscopy images from tissue sections are described, wherein cell features are extracted and a classifier is built in accordance with a particular application using an interactive training tied to a computerized platform, the result is an application-specific classifier that further processes images in accordance with the specific application, thereby tuning an automated process for cell based pattern recognition.

Abstract: A method for a continuous scoring scheme used for the assessment of biomarker expressions in the analysis of tissue sections, and digital images thereof, is based on cell classifications.

Abstract: This disclosure concerns methods for evaluating inflammatory cells and modulators of the inflammatory response in tumor tissue and other relevant tissue types. The methods entail: obtaining a tissue sample and processing said tissue sample to produce histologic slides of tissue sections; staining of the tissue sections to identify inflammatory cells and modulators of the inflammatory response; digitizing slides to produce an image of the stained tissue sections; digitally stratifying the tissue sample into tumor and other relevant tissue compartments; and using digital image analysis to quantify cell-based and cell population-based features. The quantification of cell-based and cell population-based features within a tissue compartment of interest is used to develop a summary score of the immune system-tissue compartment of interest interaction. Patient stratification and selection as candidates for a therapeutic approach is ultimately based on the summary score value.

Abstract: Methods for cell-based tissue analysis utilize modern trends in digital microscopy to obtain, process, calibrate, and analyze digital images of tissue sections to quantify cell-based data for improved histological analysis. Using data from multiple images of a common tissue section, or data from images of multiple tissue sections, additional degrees of freedom are realized and the resulting analysis provides added depth to histological analysis of tissue samples. With computerized analytical methods, speed and accuracy of histological analysis is greatly improved.

Abstract: A hybrid vehicle has an internal combustion engine and an electric engine. A drive arrangement for the vehicle has a crankshaft-side clutch part rigidly connected to a crankshaft of the internal combustion engine, and the crankshaft-side clutch part may be coupled to a drive train shaft-side clutch part via a clutch. The clutch part on the drive train shaft side is mechanically connected to a drive train shaft via at least one element for torsional vibration isolation. The drive train shaft is configured at least partially as a rotor of the electric engine. The crankshaft-side clutch part, the clutch and the drive train shaft-side clutch part form at least one part of the primary mass of a dual-mass flywheel. The drive train shaft forms at least one part of the secondary mass of the dual-mass flywheel.

Abstract: A method of automated image calibration that corrects for non-uniform illumination and calibrates color that is simple, fast, automated, accurate and reliable. A gray balance algorithm is applied to correct for non-uniform illumination and a color calibration algorithm is then applied to calibrate the human subject data. The system has been applied in multiple clinical sites with different instruments.

Abstract: Uterine cervical cancer Computer-Aided-Diagnosis (CAD) according to this invention consists of a core processing system that automatically analyses data acquired from the uterine cervix and provides tissue and patient diagnosis, as well as adequacy of the examination. The data can include, but is not limited to, color still images or video, reflectance and fluorescence multi-spectral or hyper-spectral imagery, coherent optical tomography imagery, and impedance measurements, taken with and without the use of contrast agents like 3-5% acetic acid, Lugol's iodine, or 5-aminolevulinic acid. The core processing system is based on an open, modular, and feature-based architecture, designed for multi-data, multi-sensor, and multi-feature fusion. The core processing system can be embedded in different CAD system realizations.

Abstract: Uterine cervical cancer Computer-Aided-Diagnosis (CAD) according to this invention consists of a core processing system that automatically analyses data acquired from the uterine cervix and provides tissue and patient diagnosis, as well as adequacy of the examination. The data can include, but is not limited to, color still images or video, reflectance and fluorescence multi-spectral or hyper-spectral imagery, coherent optical tomography imagery, and impedance measurements, taken with and without the use of contrast agents like 3-5% acetic acid, Lugol's iodine, or 5-aminolevulinic acid. The core processing system is based on an open, modular, and feature-based architecture, designed for multi-data, multi-sensor, and multi-feature fusion. The core processing system can be embedded in different CAD system realizations.

Abstract: A method of automated image calibration that corrects for non-uniform illumination and calibrates color that is simple, fast, automated, accurate and reliable. A gray balance algorithm is applied to correct for non-uniform illumination and a color calibration algorithm is then applied to calibrate the human subject data. The system has been applied in multiple clinical sites with different instruments.

Abstract: A control unit having an oscillator for a processor is described, the control unit storing a temporary absence of oscillation of the oscillator in a first error memory, if oscillation begins again after the absence.