Abstract: Portable, low cost, high speed surface and subsurface vehicles for aquatic data collection, payload delivery, or water quality monitoring. The vehicles can be deployed in pods enable rapid large scale data collection across a wide area. The vehicles are capable of transiting the water surface at speeds of over ten knots, and can also be propelled under the water surface and dive vertically to the floor of the water body. A passive, non-powered internal weight transfer system enhances the vehicle's performance in each of its transit modes. The vehicles can have one or more of the following features: high speed stabilizing wings, a tool-less assembly system, sacrificial standoffs for vertical dives, sacrificial protectors for the control surfaces, and/or a universal mounting system for attaching payloads such as sensors.

Abstract: The present invention is an implantable medical device comprising (i) a base coat layer having an inner and outer surface, the inner surface of the base coat layer contacting the implantable medical device; (ii) a top-coat layer of a hydrophilic polymer chemically crosslinked and covalently bonded to the outer surface of the base coat layer, the hydrophilic polymer comprising an anionic polyelectrolyte; and (iii) an amount of a hydrophilic cationic drug agent added to the top-coat layer sufficient to provide an effective dosage of the drug agent for delivery to a patient, whereby the hydrophilic cationic drug agent is initially adsorbed into the anionic polyelectrolyte of the top-coat layer and the hydrophilic cationic drug agent having a release rate after the medical device is implanted within a patient's body.

Abstract: A method and system for transmission of digital content via e-mail with point of use digital rights management is disclosed. The secured access rights to the digital content may be customized for individual recipients by the sender, and may evolve over time. The access rights are enforced according to a time-dependent scheme. A key server is used to arbitrate session keys for the encrypted content, eliminating the requirement to exchange public keys prior to transmission of the digital content. During the entire process of transmitting and receiving e-mail messages and documents, the exchange of cryptographic keys remains totally transparent to the users of the system. Additionally, electronic documents may be digitally signed with authentication of the signature.

Abstract: The present invention is an implantable medical device comprising (i) a base coat layer having an inner and outer surface, the inner surface of the base coat layer contacting the implantable medical device; (ii) a top-coat layer of a hydrophilic polymer chemically crosslinked and covalently bonded to the outer surface of the base coat layer, the hydrophilic polymer comprising an anionic polyelectrolyte; and (iii) an amount of a hydrophilic cationic drug agent added to the top-coat layer sufficient to provide an effective dosage of the drug agent for delivery to a patient, whereby the hydrophilic cationic drug agent is initially adsorbed into the anionic polyelectrolyte of the top-coat layer and the hydrophilic cationic drug agent having a release rate after the medical device is implanted within a patient's body.

Abstract: The invention relates to a tray for use in large-scale industrial insect farming. More in particular, the invention relates to a live insects tray for incubating insects prepupae and pupae, the tray having a space limited by walls, for housing insect prepupae and pupae, wherein the walls are impenetrable by an insect, and that at least one of the walls is at least partly permeable for gases, such as the top wall. Furthermore, the invention relates to a rack for holding at least one tray and relates to an assembly having said rack and at least one of said trays. The invention also relates to the use of said rack with at least one tray or said assembly for incubating insect prepupae. In addition the invention relates to a method for incubating insect prepupae and/or insect pupae, preferably of black soldier fly.

Abstract: The technology disclosed includes a system to group security alerts generated in a computer network and prioritize grouped security alerts for analysis, through graph-based clustering. The graph used to form clusters includes entities in the computer network represented as scored nodes, and relationships of entities as weighted edges. The technology disclosed includes traversing the graph starting at starting nodes and propagating native scores through and to neighboring nodes connected by the weighted edges. The propagated scores at visited nodes are normalized by attenuation based on contributing neighboring nodes of a respective visited node. An aggregate score for a visited node is calculated by accumulating propagated scores at visited nodes with their respective native scores. The technology disclosed forms clusters of connected nodes in the graph that have a respective aggregate score above a selected threshold. The clusters are ranked and prioritized for analysis, pursuant to the aggregate scores.

Abstract: The disclosed technology teaches facilitate User and Entity Behavior Analytics (UEBA) by classifying a file being transferred as encrypted or not. The technology involves monitoring movement of a files by a user over a wide area network, detecting file encryption for the files using a trained classifier, wherein the detecting includes processing by the classifier some or all of the following features extracted from each of the files: a chi-square randomness test; an arithmetic mean test; a serial correlation coefficient test; a Monte Carlo-Pi test; and a Shannon entropy test, counting a number of the encrypted files moved by the user in a predetermined period, comparing a predetermined maximum number of encrypted files allowed in the predetermined period to the count of the encrypted files moved by the user and detecting that the user has moved more encrypted files than the predetermined maximum number, and generating an alert.

Abstract: An approach to arrange sensors needed for automated driving, especially where semitrailer trucks are operating in an autonomous convoy with one automated or semi-automated truck following another. The sensors are fitted to a location adjacent to or within the exterior rearview mirrors, on each of the left- and right-hand side of the tractor. The sensors provide overlapping fields of view looking forward of the vehicle and to both the left and right hand sides at the same time.

Abstract: An autonomous vehicle's control systems include an A-kit module that operates autonomy logic to generate a desired trajectory from sensor data. A B-kit module receives the desired trajectory and generates inputs for actuators such as steering, brake and throttle actuators based on the desired trajectory. Safing logic (which may be located in the A-kit, B-kit, both the A-kit and the B-kit or elsewhere within or outside of the vehicle) receives a sensor fault indication and executes a contingency trajectory such as a safing maneuver to bring the vehicle to a safe state.

Abstract: A delivery system includes a shaft including first and second main lumens spaced from each other and forming a common U-shaped lumen at distal portions of the lumens, a delivery device including a first and second members disposed within the first and second main lumens and a manifold coupling the first and second members disposed in the common U-turn lumen, wherein proximal movement of the first member of the delivery device along a first longitudinal axis causes corresponding proximal movement of the manifold within the common U-turn lumen and corresponding proximal movement of the second member along a second longitudinal axis different than the first longitudinal axis.

Abstract: The technology disclosed relates to a method, system, and non-transitory computer-readable media that trains a cloud traffic classifier to classify cross-application communications as malicious command and control (C2) traffic or benign cloud traffic. The training uses blocks of malicious Hypertext Transfer Protocol (HTTP) transactions targeted at a plurality of cloud applications by a plurality of clients prequalified as malicious command and control (C2) cloud traffic, and also blocks of benign HTTP transactions targeted at the plurality of cloud applications by the plurality of clients prequalified as benign cloud traffic. A cloud traffic classifier is trained on the cross-application malicious training example set and on the cross-application benign training example set by processing the blocks of the malicious and benign HTTP transactions as inputs, and generating outputs that classify the training examples as respectively malicious C2 cloud traffic or benign cloud traffic.

Abstract: The disclosed technology teaches facilitate User and Entity Behavior Analytics (UEBA) by classifying a file being transferred as encrypted or not. The technology involves monitoring movement of a files by a user over a wide area network, detecting file encryption for the files using a trained classifier, wherein the detecting includes processing by the classifier some or all of the following features extracted from each of the files: a chi-square randomness test; an arithmetic mean test; a serial correlation coefficient test; a Monte Carlo-Pi test; and a Shannon entropy test, counting a number of the encrypted files moved by the user in a predetermined period, comparing a predetermined maximum number of encrypted files allowed in the predetermined period to the count of the encrypted files moved by the user and detecting that the user has moved more encrypted files than the predetermined maximum number, and generating an alert.

Abstract: The disclosed technology teaches training a classifier that classifies a file being transferred as encrypted or not. The technology involves accessing a plurality of training sample files, each of which is accompanied by a label of encrypted or not encrypted, sampling a configurable number of bytes of each respective file, generating features from the sampled bytes, including generating at least three of the following features: a chi-square randomness test; an arithmetic mean test; a serial correlation coefficient test; a Monte Carlo-Pi test; a Shannon entropy test; applying the generated features to train coefficients of a classifier algorithm to classify the sample files as encrypted or not encrypted; and saving the trained coefficients and classifier, whereby the classifier is trained to classify the sample files as encrypted or not encrypted.

Abstract: A priming device for a fluid cartridge, a fluid dispense device configured for priming the fluid cartridge, and a method for priming a fluid cartridge. The priming device includes an impact mechanism for a fluid cartridge, wherein the fluid cartridge is devoid of a backpressure device and has a fluid reservoir and an ejection head chip in fluid flow communication with the fluid reservoir.

Abstract: A priming device for a fluid cartridge, a fluid dispense device configured for priming the fluid cartridge, and a method for priming a fluid cartridge. The priming device includes an impact mechanism for a fluid cartridge, wherein the fluid cartridge is devoid of a backpressure device and has a fluid reservoir and an ejection head chip in fluid flow communication with the fluid reservoir.

Abstract: The technology disclosed relates to a method, system, and non-transitory computer-readable media that classifies cloud traffic between a client and cloud application as malicious command and control (C2) cloud traffic or benign cloud traffic. A cloud traffic classifier, in communication with a network security system, is provided intercepted cloud traffic as an input, and generate an output that classifies the cloud traffic as malicious command and control (C2) cloud traffic or benign cloud traffic. The classifier may use signals such as beaconing behavior, anomalous entity, anomalous agent, anomalous username, anomalous username, anomalous agent, cat's paw behavior of the client, anomalous hostname access patterns, and/or malicious task sequence execution.

Abstract: An insect breeding device comprising at least one insect cage; a bin for holding drinking water or a tap for providing drinking water; a first pipe connected to the tap for receiving the drinking water, wherein the pipe is entering the at least one insect cage through a first opening; a nozzle, coupled to the first pipe, positioned inside the at least one insect cage configured to deliver the drinking water to the interior of the at least one insect cage; and a second pipe, coupled to a second opening, different from the first opening and located in the top wall of the cage or in a side wall of the cage, in the at least one insect cage, configured to deliver conditioned air into the at least one insect cage; and a third pipe, coupled to a third opening, different from the first and second opening and located in the top wall of the cage or in a side wall of the cage opposite to the second opening, in the at least one insect cage, configured to receive the conditioned air from the at least one insect cage.

Abstract: The technology disclosed relates to a method, system, and non-transitory computer-readable media that detects malicious communication between a command and control (C2) cloud resource on a cloud application and malware on an infected host, using a network security system. The network security system reroutes the cloud traffic to the network security system. The incoming requests of the cloud traffic are directed to a cloud application in the plurality of cloud applications, and wherein the cloud application has a plurality of resources. The network security system analyzes the incoming requests, determines that the incoming requests are targeted at one or more malicious resources in the plurality of resources.

Abstract: The technology disclosed includes a system to group security alerts generated in a computer network and prioritize grouped security alerts for analysis, through graph-based clustering. The graph used to form clusters includes entities in the computer network represented as scored nodes, and relationships of entities as weighted edges. The technology disclosed includes traversing the graph starting at starting nodes and propagating native scores through and to neighboring nodes connected by the weighted edges. The propagated scores at visited nodes are normalized by attenuation based on contributing neighboring nodes of a respective visited node. An aggregate score for a visited node is calculated by accumulating propagated scores at visited nodes with their respective native scores. The technology disclosed forms clusters of connected nodes in the graph that have a respective aggregate score above a selected threshold. The clusters are ranked and prioritized for analysis, pursuant to the aggregate scores.

Abstract: The technology disclosed relates to a method, system, and non-transitory computer-readable media that trains a cloud traffic classifier to classify cross-application communications as malicious command and control (C2) traffic or benign cloud traffic. The training uses blocks of malicious Hypertext Transfer Protocol (HTTP) transactions targeted at a plurality of cloud applications by a plurality of clients prequalified as malicious command and control (C2) cloud traffic, and also blocks of benign HTTP transactions targeted at the plurality of cloud applications by the plurality of clients prequalified as benign cloud traffic. A cloud traffic classifier is trained on the cross-application malicious training example set and on the cross-application benign training example set by processing the blocks of the malicious and benign HTTP transactions as inputs, and generating outputs that classify the training examples as respectively malicious C2 cloud traffic or benign cloud traffic.