Abstract: A neuromodulation therapy is delivered via at least one electrode implanted subcutaneously and superficially to a fascia layer superficial to a nerve of a patient. In one example, an implantable medical device is deployed along a superficial surface of a deep fascia tissue layer superficial to a nerve of a patient. Electrical stimulation energy is delivered to the nerve through the deep fascia tissue layer via implantable medical device electrodes.

Abstract: A neuromodulation therapy is delivered via at least one electrode implanted subcutaneously and superficially to a fascia layer superficial to a nerve of a patient. In one example, an implantable medical device is deployed along a superficial surface of a deep fascia tissue layer superficial to a nerve of a patient. Electrical stimulation energy is delivered to the nerve through the deep fascia tissue layer via implantable medical device electrodes.

Abstract: Sharing data among computing systems can include receiving, using a processor, a data transfer event indicating a transfer of a data file from a source system to a target system, querying, using the processor, the source system for an operating system executed by the source system and a file type of the data file, and querying, using the processor, the target system for an operating system executed by the target system. A target application can be determined using the processor. The target application is adapted for execution on the operating system executed by the target system and is adapted for operating on the file type. Installation of the target application on the target system can be initiated. Further, transfer of the data file from the source system to the target system can be initiated using the processor.

Abstract: Disclosed aspects relate to tuple traffic management in a stream computing environment to process a stream of tuples using a set of control group data with respect to a set of operation-system-level virtualization and resource isolation containers. The set of control group data may be collected with respect to a set of containers in the stream computing environment. A tuple flow model may be determined with respect to the set of containers in the stream computing environment based on the set of control group data. The stream of tuples may be processed using the tuple flow model with respect to the set of containers in the stream computing environment.

Abstract: Disclosed aspects relate to tuple traffic management in a stream computing environment to process a stream of tuples using a set of control group data with respect to a set of operation-system-level virtualization and resource isolation containers. The set of control group data may be collected with respect to a set of containers in the stream computing environment. A tuple flow model may be determined with respect to the set of containers in the stream computing environment based on the set of control group data. The stream of tuples may be processed using the tuple flow model with respect to the set of containers in the stream computing environment.

Abstract: Disclosed aspects relate to tuple traffic management in a stream computing environment to process a stream of tuples using a set of control group data with respect to a set of operation-system-level virtualization and resource isolation containers. The set of control group data may be collected with respect to a set of containers in the stream computing environment. A tuple flow model may be determined with respect to the set of containers in the stream computing environment based on the set of control group data. The stream of tuples may be processed using the tuple flow model with respect to the set of containers in the stream computing environment.

Abstract: Disclosed aspects relate to tuple traffic management in a stream computing environment to process a stream of tuples using a set of control group data with respect to a set of operation-system-level virtualization and resource isolation containers. The set of control group data may be collected with respect to a set of containers in the stream computing environment. A tuple flow model may be determined with respect to the set of containers in the stream computing environment based on the set of control group data. The stream of tuples may be processed using the tuple flow model with respect to the set of containers in the stream computing environment.

Abstract: Disclosed aspects relate to tuple traffic management in a stream computing environment to process a stream of tuples using a set of control group data with respect to a set of operation-system-level virtualization and resource isolation containers. The set of control group data may be collected with respect to a set of containers in the stream computing environment. A tuple flow model may be determined with respect to the set of containers in the stream computing environment based on the set of control group data. The stream of tuples may be processed using the tuple flow model with respect to the set of containers in the stream computing environment.

Abstract: Sharing data among computing systems can include receiving, using a processor, a data transfer event indicating a transfer of a data file from a source system to a target system, querying, using the processor, the source system for an operating system executed by the source system and a file type of the data file, and querying, using the processor, the target system for an operating system executed by the target system. A target application can be determined using the processor. The target application is adapted for execution on the operating system executed by the target system and is adapted for operating on the file type. Installation of the target application on the target system can be initiated. Further, transfer of the data file from the source system to the target system can be initiated using the processor.

Abstract: A method, computer program product, and computer system for tracking tuples by ID as the tuples progress through an operator of a chain of operators within a processing element. Dynamic loading may be utilized to load a processing code for the operator in response to invoking fusion for the operator. Ownership of network I/O may be shifted from the operator to a final operator of the chain of operators within the processing element. A tuple ID may be rolled back to a last ID processed by the operator being added into the processing element.

Abstract: A method, computer program product, and computer system for tracking tuples by ID as the tuples progress through an operator of a chain of operators within a processing element. Dynamic loading may be utilized to load a processing code for the operator in response to invoking fusion for the operator. Ownership of network I/O may be shifted from the operator to a final operator of the chain of operators within the processing element. A tuple ID may be rolled back to a last ID processed by the operator being added into the processing element.