Abstract: An electrical connector includes: a housing including a mechanical interface, the mechanical interface configured to mechanically connect the electrical connector to a bushing; a current path in the housing, the current path including: an electrical conductor; and a switching apparatus electrically connected to the electrical conductor, the switching apparatus associated with operating states, the operating states including at least a first state that closes the current path and a second state that opens the current path; a switch control apparatus in the housing, the switch control apparatus configured to control the operating state of the switching apparatus; and a power apparatus in the housing, the power apparatus configured to obtain electrical energy from the current path and provide electrical energy to the switch control apparatus.

Abstract: A method includes receiving a three-dimensional (3D) avatar. The method further includes generating two-dimensional (2D) images of the 3D avatar from different angles that surround the 3D avatar. The method further includes providing the 2D images as input to a trained machine-learning model. The method further includes generating, with the machine-learning model, a concatenated embedding of the 2D images. The method further includes analyzing, with the machine-learning model based on the concatenated embedding, at least one attribute associated with the 3D avatar, wherein the at least one attribute is selected from a group of a shape of the 3D avatar, an outfit on the 3D avatar, and combinations thereof. The method further includes outputting, with the machine-learning model, a determination that the at least one attribute of the 3D avatar is abusive.

Abstract: Provided are methods for light-based object localization, which can include comparing unexpected light sources to expected light sources for determination of an agent, such as a partially and/or fully occluded agent. Some methods described also include generating a trajectory for an autonomous vehicle based on the comparison. Systems and computer program products are also provided.

Abstract: An improved buffer for networking and other computing devices comprises multiple memory instances, each having a distinct set of entries. Transport data units (“TDUs”) are divided into storage data units (“SDUs”), and each SDU is stored within a separate entry of a separate memory instance in a logical bank. One or more grids of the memory instances are organized into overlapping logical banks. The logical banks are arranged into views. Different destinations or other entities are assigned different views of the buffer. A memory instance may be shared between logical banks in different views. When overlapping logical banks are accessed concurrently, data in a memory instance that they share may be recovered using a parity SDU in another memory instance. The shared buffering enables more efficient buffer usage in a network device with a traffic manager shared amongst egress bocks. Example read and write algorithms for such buffers are disclosed.

Abstract: A method of preconditioning a battery for use in an unmanned aerial vehicle unmanned aerial vehicle may include fluidly coupling a fluid channel of a thermal management apparatus to an opening in fluid communication with the battery, determining a predicted temperature change of the battery as a result of the unmanned aerial vehicle traversing a predetermined flight path, determining a target initial temperature for the battery, wherein the target initial temperature is based at least in part on the predicted temperature change and is configured to operate the battery within a preferred temperature range during traversal of the predetermined flight path, selectively actuating a covering of the opening to allow air from the fluid channel of the thermal management apparatus to the battery, and at least one of heating or cooling the battery to the target initial temperature by directing air to the battery.

Abstract: Various embodiments classify one or more portions of an image based on deriving an “intrinsic” modality. Such intrinsic modality acts as a substitute to a “text” modality in a multi-modal network. A text modality in image processing is typically a natural language text that describes one or more portions of an image. However, explicit natural language text may not be available across one or more domains for training a multi-modal network. Accordingly, various embodiments described herein generate an intrinsic modality, which is also a description of one or more portions of an image, except that such description is not an explicit natural language description, but rather a machine learning model representation. Some embodiments additionally leverage a visual modality obtained from a vision-only model or branch, which may learn domain characteristics that are not present in the multi-modal network.

Abstract: Disclosed herein is an AI based system and method for generating warning alerts for a location to be excavated. The method comprises obtaining, from at least one external source, at least one underground asset map of the location to be excavated. For each of the at least one underground asset map, the method comprises locating a region of interest within the underground asset map corresponding to an identified underground utility service provider and extracting at least one feature within the region of interest. The at least one extracted feature is then compared with a plurality of features stored in a repository corresponding to the identified underground utility service provider, to determine a match. In response to the determination, the extracted feature is identified as a risk feature corresponding to the identified underground utility service provider and one or more warning alerts indicative of risk assets are generated.

Abstract: A system for reducing blood loss during removal of material from a body lumen includes an elongate shaft, an aspiration lumen, and a flow resistance assembly. The elongate shaft can be placed within a blood vessel and has a distal end with an opening at the distal end. The aspiration lumen extends along the shaft and has a proximal end and a distal opening. The flow resistance assembly is associated with the aspiration lumen and is configured to resist blood flow through the aspiration lumen in a free-flow condition without operating a valve in fluid communication with the aspiration lumen. The flow resistance assembly may include a coiled section of tubing, a static mixer, or flow resistance structures.

Abstract: Systems and methods are provided for a multi-tenant collective communication fabric for optimal utilization of communication links between compute nodes of an interconnected system. Examples include allocating a plurality of compute nodes to a first workload and obtaining a topology of the interconnected system representative of an indirect path between the allocated compute nodes. The indirect path comprises a non-allocated compute node of the interconnected system. The examples include creating plurality of slices of resources of the non-allocated compute node, with a first slice dedicated to processing and forwarding data traffic along the indirect path and a second slice configured for allocation to a second workload. The examples also include executing the first workload by the allocated compute nodes and the non-allocated compute node, wherein data traffic from the plurality of allocated compute nodes is communicated via the indirect communication path.

Abstract: A composition for oral care is provided having a medium chain triglyceride a hydrophobic anti-microbial agent, and a hydrophobic flavoring agent.

Abstract: Systems and methods for real time three-dimensional left atrial appendage (LAA) quantification. Deep learning is used to perform LAA segmentation, tracking and live quantification on critical measurement in 4D ultrasound sequences. The collected information may be used for device selection and anomaly detection to assist early-phase disease finding.

Abstract: Systems and methods for assessing cardiovascular disease of a patient are provided. Patient data of the patient is received. The patient data may include one or more input medical images of a chest of the patient, results of an assessment of a lung disease performed based on the one or more input medical images, demographic and clinical data of the patient, and cardiovascular imaging exams of the patient. One or more risk scores are computed for the patient based on the patient data using a trained machine learning based network.

Abstract: A device and corresponding method are provided determining a consumed computing capacity of a first networking device exceeds the threshold for total capacity for processing monitoring data for a monitoring metric. An optimization engine determines a second networking device with unused computing capacity sufficient for processing the monitoring data generated by the first networking device. The optimization engine automatically moves the monitoring data for the monitoring metric generated by the first networking device to the second networking device and causes the second networking device to process the monitoring data.

Abstract: Systems and methods for graph based assessment of a patient are provided. Medical imaging data and non-imaging medical data of a patient are received. The medical imaging data and the non-imaging medical data are encoded into encoded features using a graph based machine learning network by comparing the patient with patients of a patient population based on a graph of the patient population. An assessment of the patient is determined based on the encoded features using a machine learning classifier network. The assessment of the patient is output.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generate a digital document hierarchy comprising layers of parent-child element relationships from the visual elements. For example, for a layer of the layers, the disclosed systems determine, from the visual elements, candidate parent visual elements and child visual elements. In addition, for the layer of the layers, the disclosed systems generate, from the feature embeddings utilizing a neural network, element classifications for the candidate parent visual elements and parent-child element link probabilities for the candidate parent visual elements and the child visual elements. Moreover, for the layer, the disclosed systems select parent visual elements from the candidate parent visual elements based on the parent-child element link probabilities. Further, the disclosed systems utilize the digital document hierarchy to generate an interactive digital document from the digital document image.

Abstract: Systems and methods are provided for effectuating a filtering technique that can enable available bandwidth (e.g., on a network path) to be estimated in the presence of moderate losses caused by certain queue management techniques. When packet losses exist on a network path due to certain types of packet queue transmission mechanisms, methods, or models, a bump detection algorithm (BDA) can be used to perform bandwidth estimation. When a pattern of packet loss is identified (from its signature) as being one with which BDA can be performed to accurately estimate available bandwidth on a network path, the BDA-based bandwidth estimate may be used to place/route and load balance network traffic, or otherwise used to engage in network traffic engineering, take other network-related action(s), or reported out. Otherwise, the bandwidth estimation is suppressed and not used.

Abstract: A turn signal indication system includes: at least one turn signal indicator; an adaptive maneuver prediction module configured to predict that a host vehicle is to make a turn or change lanes; an activation decision module configured to, based on the prediction, determine whether the host vehicle is to make a left turn, make a right turn, change to a left lane, or change to a right lane; and a signal indication module configured to automatically activate the at least one turn signal indicator based on the determination of whether the host vehicle is to make a left turn, make a right turn, change to a left lane, or change to a right lane.

Abstract: Efficient scaling of in-network compute operations to large numbers of compute nodes is disclosed. Each compute node is connected to a same plurality of network compute nodes, such as compute-enabled network switches. Compute processes at the compute nodes generate local gradients or other vectors by, for instance, performing a forward pass on a neural network. Each vector comprises values for a same set of vector elements. Each network compute node is assigned to, based on the local vectors, reduce vector data for a different a subset of the vector elements. Each network compute node returns a result chunk for the elements it processed back to each of the compute nodes, whereby each compute node receives the full result vector. This configuration may, in some embodiments, reduce buffering, processing, and/or other resource requirements for the network compute node or network at large.