Abstract: An electric machine has a stator and a rotor which is rotatably mounted relative to the stator. The rotor has a rotor shaft and a rotor body which is rotationally fixed to the rotor shaft. The rotor shaft has a hydraulic channel which extends in the axial direction, can be filled with a hydraulic fluid, and from which a first radial fluid channel extends outwards in the radial direction. At least one ring disc-shaped cover element is rotationally fixed to the rotor body on an axial end face of the rotor body, and the cover element together with the axial end face of the rotor body forms at least one first cooling channel which is open on both sides and which can be hydraulically coupled to the first radial fluid channel such that a hydraulic fluid can be conveyed out of the hydraulic channel of the rotor shaft and through the radial fluid channel and the first cooling channel in the radial direction in a centrifugal force-supported manner.

Abstract: A system (100), method and computer program product for optimization of crop protection. A generator module (120) accesses one or more configuration data structures (220) wherein the one or more configuration data structures include data fields to store crop data (221), advice data (222) related to respective crop data, and crop protection product data (223) related to respective advice. Further, it accesses a plurality of code snippets (230) wherein each code snippet (231, 232, 233) has a condition which relates either to at least one property field of the one or more data structures (220) or to a result of another code snippet, and further includes generic program logic associated with the condition, and wherein each property field is used in the condition of at least one code snippet. The plurality of code snippets is applied to the one or more configuration data structures to generate an advice logic program.

Abstract: A computer-implemented method, computer program product and computer system (100) for detecting plant diseases. The system stores a convolutional neural network (120) trained with a multi-crop dataset. The convolutional neural network (120) has an extended topology comprising an image branch (121) based on a classification convolutional neural network for classifying the input images according to plant disease specific features, a crop identification branch (122) for adding plant species information, and a branch integrator for integrating the plant species information with each input image. The plant species information (20) specifies the crop on the respective input image (10). The system receives a test input comprising an image (10) of a particular crop (1) showing one or more particular plant disease symptoms, and further receives a respective crop identifier (20) associated with the test input via an interface (110).

Abstract: A system (100), method and computer program product for optimization of crop protection, for a particular crop in a particular field. The system receives a predetermined future time interval and real-time weather forecast data and can retrieve corresponding predicted target pressure data (122) representing expected biotic stress factor probabilities for said crop from a crop state prediction model. An optimizer (150) receives the predicted target pressure data (122) for one or more targets and determines an initial target pressure score for the particular field by aggregating all target pressure data in the predetermined future time interval. A protection product recommender (270) provides a plurality of product recommendations with each product recommendation including a mix of protection products suitable for treatment of the one or more targets, and each protection product having protection product characteristics (265) describing the treatment effect of the respective protection product by target.

Abstract: A system (100), method and computer program product for optimization of crop protection. A generator module (120) accesses one or more configuration data structures (220) wherein the one or more configuration data structures include data fields to store crop data (221), advice data (222) related to respective crop data, and crop protection product data (223) related to respective advice. Further, it accesses a plurality of code snippets (230) wherein each code snippet (231, 232, 233) has a condition which relates either to at least one property field of the one or more data structures (220) or to a result of another code snippet, and further includes generic program logic associated with the condition, and wherein each property field is used in the condition of at least one code snippet. The plurality of code snippets is applied to the one or more configuration data structures to generate an advice logic program. The system receives input (210) reflecting a real world field situation.