Abstract: An autonomous vehicle includes one or more sensors for detecting an object in an environment surrounding the autonomous vehicle and a vehicle computing system comprising one or more processors receiving canonical route data associated with at least one canonical route, and controlling travel of the autonomous vehicle based on sensor data from the one or more sensors and the canonical route data associated with the at least one canonical route. The at least one canonical route comprises at least one roadway connected with another roadway in a plurality of roadways in a geographic location that satisfies at least one route optimization function derived based on trip data associated with one or more traversals of the plurality of roadways in a geographic location by one or more autonomous vehicles.

Abstract: Bone fusion system, devices, guides, implant and methods for using the bone fusion system, devices, guides and implant are disclosed. The fusion system includes a first alignment guide, a second alignment guide, and an implant. The first alignment guide couples to an intermediate portion of the implant and the second alignment guide couples to a distal portion of the implant. The implant includes a body portion, a first extension portion extending away from a first end of the body portion, a second extension portion extending away from a posterior of the body portion, and a third extension portion extending away from a distal end of the body portion. Finally, methods for using the bone fusion system, devices, guide and implant are disclosed.

Abstract: In one embodiment, an offload platform is an compute platform, adjunct to a router or other packet switching device, that performs packet processing operations including determining an egress forwarding value corresponding to the next-hop node of the packet switching device to which to send an offload-platform processed packet. The offload platform downloads forwarding information from the router, and augments it, such as, but not limited to, representing interfaces of the router as identifiable virtual interface(s) on the offload platform, and including each of one or more next-hop nodes of the router represented as an identifiable virtual adjacency and identifiable tunnel (e.g., identified by the egress forwarding value). In one embodiment, the egress forwarding value is an Multiprotocol Label Switching (MPLS) label or Segment Routing Identifier. The router identifies packets of certain packet flows to send to the adjunct offload platform, rather than processing per its routing information base.

Abstract: A training device including a hub, at least one elastic cord, and at least two arms. The hub including an upper side, a lower side, and a plurality of ports. The at least one elastic cord extending from the hub and is accessible via at least one of the plurality of ports. The at least two arms extending from the hub and are configured to move relative to the hub. The training device is configured to assume (i) a closed state wherein the at least two arms both extend downwardly from the lower side of the hub and (ii) an open state wherein the at least two arms extend laterally outwardly from the hub between the upper side and the lower side of the hub. The at least one elastic cord biases the at least two arms in the open state.

Abstract: A compound of formula (I), or a pharmaceutically acceptable salt thereof.

Abstract: Systems and methods are provided to create training data, validate, deploy and test artificial intelligence (AI) systems in a virtual development environment, incorporating virtual spaces, objects, machinery, devices, subsystems, and actual human action and behavior.

Abstract: A system includes at least one processor to continually monitor at least one resource associated with a computing network for a condition in the computing network that may trigger an authorization control modification, determine that the condition has occurred in the computing network, and dynamically and automatically modify a user authorization control for at least one particular user responsive to the condition.

Abstract: A system includes a memory and at least one processor to set a network throughput level setting to a default network traffic rate in a computer network, begin a data protection operation at the network throughput level setting in the computer network, continually monitor the computer network and determine that a condition has occurred in the computer network, dynamically adjust the network throughput level setting in response to the condition by one of decreasing the network throughput level setting by a network traffic rate increment and increasing the network throughput level setting by the network traffic rate increment, and dynamically shape network or storage traffic for the data protection operation using the network throughput level setting.

Abstract: A system continuously stores, as machine learning data, metadata results associated with a previous cyber-attack, a previous inspection class policy definition at a time of the previous cyber-attack, and a result of a previous data protection operation taken upon indication of the previous cyber-attack; continuously monitors for a new security condition or event; detects the new security condition or event; determines an appropriate inspection class policy from a plurality of inspection class policies based on the new security condition or event; based on the determined inspection class policy and the machine learning training data, determines a specific class of inspection tool from a plurality of classes of inspection tools or a specific level of inspection from a plurality of different levels of inspection for the new security condition or event; and executes the specific class of inspection tool or the specific level of inspection using the specific class of inspection tool on a particular data object to

Abstract: A system includes a memory and at least one processor to monitor for a condition associated with a first cloud computing resource performing a cloud computing operation, determine that the condition associated with the first cloud computing resource has occurred, analyze the condition associated with the first cloud computing resource and compare the first cloud computing resource with a second cloud computing resource that is capable of performing at least a subset of the cloud computing operation, automatically modify the cloud computing operation that uses the first cloud computing resource to use the second cloud computing resource, and send at least one notification to a computing device about the condition associated with the first cloud computing resource and information associated with a modification of the cloud computing operation from the first cloud computing resource to the second cloud computing resource.

Abstract: A microfluidic system may include a microfluidic chip having a non-conductive substrate and wells connected in common to a microfluidic channel within the non-conductive substrate. Each well may have a galvanic contact with a first portion at an upper surface of the sample well and a second portion that extends into the non-conductive substrate. A plurality of electrodes may be provided as part of an electrical interface, with each electrode configured to contact a respective galvanic contact of the microfluidic chip. The electrical interface may also include at least one shared power amplifier that is configured to generate a power signal (e.g., constant current, constant voltage, pulsed power signal). A selector may be configured to receive the generated power signal from the shared power amplifier and configured to select at least one of the plurality of electrodes and output the received power signal thereto.

Abstract: A system continuously stores metadata results associated with a plurality of ransomware attacks, a plurality of inspection class policy definitions, a plurality of data protection operations, and operational forensics data as machine learning training data, continuously monitors for one of a new security condition and event, detects one of the new security condition and event, determines an appropriate inspection class policy based on the one of the new security condition and event, based on the inspection class policy, determines one to implement of a class of inspection operation, a cyber security analysis, and a data protection operation, and executes one of the class of inspection operation, the cyber security analysis, and the data protection operation based on the machine learning training data.

Abstract: A system continuously monitors, by at least one inspector, an inspection work queue for a class of inspection operation request, detects, by the at least one inspector, the class of inspection operation request in the inspection work queue, removes, by the at least one inspector, the class of inspection operation request from the inspection work queue, determines, by the at least one inspector, one of a class of inspection tool and a specific level of inspection to perform for the class of inspection operation request that references a data object, and executes, by the at least one inspector, the one of the class of inspection tool and the specific level of inspection for the class of inspection operation request that references the data object at one of a certain time and a certain event during a data lifecycle of the data object.

Abstract: A system continuously monitors, by at least one inspector, an inspection work queue for a class of inspection operation request, detects, by the at least one inspector, the class of inspection operation request in the inspection work queue, removes, by the at least one inspector, the class of inspection operation request from the inspection work queue, determines, by the at least one inspector, one of a class of inspection tool and a specific level of inspection to perform for the class of inspection operation request that references a data object, and executes, by the at least one inspector, the one of the class of inspection tool and the specific level of inspection for the class of inspection operation request that references the data object at one of a certain time and a certain event during a data lifecycle of the data object.

Abstract: Systems and methods are provided to create training data, validate, deploy and test artificial intelligence (AI) systems in a virtual development environment, incorporating virtual spaces, objects, machinery, devices, subsystems, and actual human action and behavior.

Abstract: A system includes a memory and at least one processor to disable automatic prioritization of at least one data protection operation in a computer network, begin the at least one data protection operation in the computer network, continually monitor the computer network and determine that a condition has occurred in the computer network, activate automatic prioritization of the at least one data protection operation in the computer network, and instruct backup server tooling software to direct backup data for the at least one data protection operation to move from a first target storage repository to a second target storage repository.

Abstract: A system includes at least one processor to receive training data and generate at least one machine learning rule based on the training data to apply when a condition occurs, continually monitor at least one resource associated with a computing network for the condition in the computing network that may trigger an authorization control modification, the condition comprising one of an active project that uses the at least one resource, a security alert level change, a resource locality change, metadata associated with the condition, a skill assessment, and a business state analysis, determine that the condition has occurred in the computing network, and dynamically and automatically modify a user authorization control for at least one particular user responsive to the machine learning rule.