Abstract: Computer-implemented methods are provided for generating a personalized Boolean model for a genetic disease of a patient. The method includes storing specification data and reference model data. The reference model includes gene nodes, representing genes, connected to Boolean circuitry and a plurality of inputs for receiving binary input values. Each gene node in the reference model comprises a multiplexer. The multiplexer has a first input and an output, a second input for receiving a binary mutation value, and a control input for receiving a binary selector value. The method further comprises using a model checker to determine if the specification is reachable in the reference model. If the specification is reachable, the method includes identifying each multiplexer whose second input was connected to its output in the path reaching the specification to obtain mutation data for the patient, generating a personalized Boolean model, and outputting personal model data.

Abstract: An example of an embodiment is directed to a computer-implemented method for providing a cloud service to execute a computing task of a model specification. The method includes receiving, by the cloud service, the model specification and input data for the model specification from a user. The method further includes generating, by the cloud service, native code from the model specification and executing, by the cloud service, the computing task by executing the native code as a native process with the input data. The method also includes providing, by the cloud service, results of the computing task to the user. Other embodiments further concern a related computing system and a related computer program product.

Abstract: An example of an embodiment is directed to a computer-implemented method for providing a cloud service to execute a computing task of a model specification. The method includes receiving, by the cloud service, the model specification and input data for the model specification from a user. The method further includes generating, by the cloud service, native code from the model specification and executing, by the cloud service, the computing task by executing the native code as a native process with the input data. The method also includes providing, by the cloud service, results of the computing task to the user. Other embodiments further concern a related computing system and a related computer program product.

Abstract: The present disclosure relates to a system and method for extracting information from text data. The method comprises: obtaining a plurality of text elements. A word embedding algorithm may be applied to the obtained text elements by mapping each text element of at least part of the text elements into a vector of a predefined dimension. The mapped text elements may be clustered into groups using the distances between the respective vectors. For each text element of a set of text elements of the mapped text elements a respective distribution of neighbors across the groups may be built. Similarity scores may be computed using the distributions thereby for determining relations between the set of text elements.

Abstract: The present disclosure relates to a system and method for extracting information from text data. The method comprises: obtaining a plurality of text elements. A word embedding algorithm may be applied to the obtained text elements by mapping each text element of at least part of the text elements into a vector of a predefined dimension. The mapped text elements may be clustered into groups using the distances between the respective vectors. For each text element of a set of text elements of the mapped text elements a respective distribution of neighbors across the groups may be built. Similarity scores may be computed using the distributions thereby for determining relations between the set of text elements.

Abstract: Computer-implemented methods are provided for generating a personalized Boolean model for a genetic disease of a patient. The method includes storing specification data and reference model data. The reference model includes gene nodes, representing genes, connected to Boolean circuitry and a plurality of inputs for receiving binary input values. Each gene node in the reference model comprises a multiplexer. The multiplexer has a first input and an output, a second input for receiving a binary mutation value, and a control input for receiving a binary selector value. The method further comprises using a model checker to determine if the specification is reachable in the reference model. If the specification is reachable, the method includes identifying each multiplexer whose second input was connected to its output in the path reaching the specification to obtain mutation data for the patient, generating a personalized Boolean model, and outputting personal model data.

Abstract: A powertrain has a planetary transmission having a planetary gear arrangement and six torque transmitting mechanisms that are controlled to provide six forward ratios and a reverse ratio. The planetary gear arrangement includes two sun gear members, two ring gear members, and a planet carrier assembly member that are disposed in three axially spaced planes of gear mesh. The planet carrier member has a short pinion gear member, meshing (first plane) with one sun gear member, a first long pinion gear member having a small gear section, meshing (first plane) with the small pinion gear member and one ring gear member, and a large gear section, meshing(second plane) with the other sun gear member, and a second long pinion gear member, meshing (second and third planes) with both the large gear section (second plane) and the second ring gear member (third plane).

Abstract: An automatic transmission comprising a housing (12); a planetary gear train (14) mounted within the housing; an input drive shaft (16) for providing input drive to the planetary gear train; an output drive shaft (18) connected with an output drive from the planetary gear train; a first clutch (C1) connected between the input drive shaft and a first drive input (22) to the planetary gear train; a second clutch (C2) connected between a first reaction input (28) to the planetary gear train and the housing; a third clutch (C3) connected between a second reaction input (30) to the planetary gear train and the housing; a fourth clutch (C4) connected between a third reaction input (32) to the planetary gear train and the housing; and a fifth clutch (C5) connected between a second drive input (24) to the planetary gear train and the input drive shaft; wherein for first forward gear ratio the first and second clutches are engaged; for second forward gear ratio the first, second and third clutches are engaged; for thir

Abstract: An automatic transmission (10) comprising a housing (12); a planetary gear train (14) mounted within the housing; an input drive shaft (16) connectable to main drive means (38) to provide input drive to the planetary gear train; an output drive shaft (18) from the planetary gear train; and an auxiliary drive means (E) for providing a variable auxiliary drive input (34) to the planetary gear train; wherein the planetary gear train includes a first planetary gear set (40) and a second planetary gear set (42); the first planetary gear set including a sun gear (44) having a drive input (26) connectable to the input drive shaft and a reaction input (28) connectable to the housing, a pinion gear (46) interengaging with the sun gear, and a pinion carrier (48) on which the pinion gear is rotatably mounted, the pinion carrier having a drive input (24) connectable to the input drive shaft and a reaction input (30,32) connectable to the housing, and being connected with the auxiliary drive input; the second planetary ge