Abstract: Provided herein are methods of ameliorating experiential negative symptoms of schizophrenia in a user in need thereof. A computing system may obtain a first metric associated with the user prior to a plurality of time instances. The computing system may repeat across a plurality of time instances, identifying a configuration file selected based on an endpoint for ameliorating the experiential negative symptoms. The computing system may repeat presenting the set of content items identified by the configuration file to prompt the user to perform the activity towards achieving the endpoint. The computing system may obtain a second metric associated with the user after the plurality of time instances. The user may show amelioration of experiential negative symptoms of schizophrenia, when the second metric is lower than the first metric. The computing system may increase the efficacy of the medication that the user is taking to address the schizophrenia.

Abstract: For movement of medical sensors for medical imaging, an artificial intelligence (AI) is trained using a contrastive reinforcement learning (CRL) framework. Simulation may be used to provide the training data. For training, the sampling for a given input instance in CRL may use trajectories simulated from different patients for better contrast. CRL, with or without the simulation feature and/or the sampling feature, may provide more generalized navigation, such as in interventional or diagnostic settings.

Abstract: The present embodiments relate to updating a dataflow interactive cluster with zero downtime. A request to update a first dataflow cluster can be received, and a second dataflow cluster can be generated as a replacement cluster to execute received queries. Generating the second dataflow cluster can include identifying a second series of executor nodes that are configured to execute queries from the gateway node via a second driver node. A first update to a configuration of a host configuration node can be performed to register the second dataflow cluster as an active endpoint and identify the first dataflow cluster as an inactive endpoint. When no active queries exist, a second update to the configuration can be provided to remove the first dataflow cluster from the configuration to direct subsequent queries from the gateway node to the second dataflow cluster.

Abstract: Vehicles and related systems and methods are provided for predicting a future maneuver expected to be executed by a driver. One method involves determining a combined probability for a potential maneuver based on constituent probabilities corresponding to different vehicle state variables, and environmental conditions using one or more tuning parameters specific to the respective combination of maneuver and vehicle state variable, determining an adjusted probability for the potential maneuver based at least in part on the combined probability and one or more contextual state variables corresponding to a current operating context for the vehicle, adapted to driver behavior and driving style, identifying the potential maneuver as an expected maneuver to be executed by a driver of the vehicle based on the adjusted probability, and automatically initiating one or more actions in a manner that is influenced by the expected maneuver.

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

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

Abstract: A network operating system (NOS) acquires, for a plurality of network functions that achieve a network slice constructed on a mobile wireless communication network, information on an operation of each network function which is measured by one or more apparatus configured to provide at least a part of the plurality of network functions. The NOS derives an evaluation index value of each of the plurality of network functions based on the information on the operation of each of the plurality of network functions, and derives an evaluation index value of the network slice based on the evaluation index values of the plurality of network functions.

Abstract: An autonomous mobile factory includes: a container; bins arranged within the container and configured to store parts associated with an installation structure; a robotic assembly; and a controller. The controller is configured to: access an instruction associated with assembly of the installation structure; select a part specified in the instruction; identify a bin containing the part; define an assembly toolpath for maneuvering the part from the bin to the assembly station; and derive a grasp pose, aligning the part with the assembly toolpath, for retrieving the part from the bin. The controller is further configured to, via the robotic assembly: trigger a robotic arm to retrieve the part from the bin in the grasp pose; maneuver the robotic arm according to the assembly toolpath to locate the part at the assembly station in the grasp pose; and couple the part to a second part at the assembly station.

Abstract: Techniques pertaining to handling attempt counters when an unavailability period is activated in mobile communications are described. An apparatus (e.g., a user equipment (UE) determines an occurrence of a condition related to an unavailability period such as, for example, the unavailability period being activated. In response to the determining, the apparatus resets a counter such as, for example, a service request attempt counter, an attach attempt counter, a tracking area updating (TAU) attempt counter, and/or a registration attempt counter.

Abstract: In certain embodiments, a computer-implemented method includes: receiving, by a caching system plugin, a request to create a persistent volume for a container application instance; configuring, by the caching system plugin, a local cache volume on a host computing device; configuring, by the caching system plugin, a remote storage volume on a remote storage device; selecting, by a policy manager of the caching system plugin, a cache policy for the container application instance; creating, by the caching system plugin and from a cache manager, a virtual block device associated with the local cache volume, the remote storage volume, and the cache policy; and providing the virtual block device for use by the container application instance as the persistent volume.

Abstract: Conventionally industries delt with diverse categories of products/items recommendation. This gave rise to a display taxonomy for the products. The art of matching products/items with certainty is critical to infer price gaps, which can significantly alter a competitive landscape. Manually comparing product features is time-consuming and error-prone, leading to inaccurate results. Present disclosure provides systems and methods that receive items pertaining to various entities (retail and competitor's) which are pre-processed to obtain pre-processed dataset. Taxonomy codes are tagged to a subset of items amongst pre-processed dataset to obtain code tagged items having attributes. The attributes are converted to feature vectors, and models are built using code tagged items and feature vectors. Using the models, a third set of items is obtained, and features are extracted accordingly.

Abstract: Echocardiography deep learning and cardiovascular outcomes are described. An echocardiogram analysis module may include a deep learning model to generate a video output for an input echocardiogram video, the deep learning model comprising a convolutional neural network and at least one dense layer. The echocardiogram analysis module may further include a cardiac prediction generator to generate a cardiac prediction based on video outputs generated for a plurality of input echocardiogram videos of an echocardiogram study, the cardiac prediction comprising a measurement prediction or a classification prediction.

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.

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: 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: 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.