Abstract: The present invention generally relates to an electric vehicle hybrid charging system comprises first bank and a second bank of series connected switches an interconnected in between an input voltage terminal and a reference voltage terminal in a series connection; a plurality of switched capacitors (SCs) having a first terminal interconnected between two adjacent switches of the first bank and a second capacitor terminal interconnected between two adjacent switches of the second bank; and a controller having a first frequency by controlling the plurality of switch pairs such that each switch pair is switched at staggered times relating to other plurality of switch pairs during a periodic switching cycle, wherein each switch pair consists of a switch from the first bank and a switch from the second bank, and the periodic switching cycle has a second frequency that is higher than the first frequency.

Abstract: In examples, a developer may define a set of computer-controlled agent attributes, which may be processed by a generative multimodal machine learning model in conjunction with background information associated with a virtual environment (e.g., “lore”) and other agent information to generate multimodal model output with which to control the behavior of the computer-controlled agent. Thus, a player may interact with the computer-controlled agent, such that user input from the player is processed using the ML model to generate model output to affect the behavior of the computer-controlled agent, thereby enabling the user and the computer-controlled agent to interact. As compared to manual dialogue authoring, use of agent information to define the behavior of a computer-controlled agent may result in reduced effort on the part of a creator while also offering increased depth and variety for computer-controlled agents of a virtual environment.

Abstract: In general, embodiments relate to a method for managing a technical support session, comprising: generating a question path graph (QPG) based on a plurality of question sequences associated with technical support sessions, and displaying at least a portion of the QPG to a technical support person (TSP) during a technical support session.

Abstract: In general, embodiments relates to a method for managing a technical support session, comprising: obtaining customer identification information for a technical support session, extracting at least one keyword for the technical support session, identifying a plurality of historical technical support sessions using the at least one keyword and the customer identification information, and displaying at least one of the plurality of historical technical support sessions to a technical support person (TSP) during the technical support session.

Abstract: In general, embodiments relates to a method for managing a technical support session, comprising: obtaining technical support question from a technical support person (TSP) that is conducting the technical support session; determining that the technical support question is a duplicate of a prior technical support question; in response to the determination, obtaining a quality score for the technical support question; and displaying the quality score to the TSP in a user interface on a technical support system that the TSP is using the conduct the technical support session.

Abstract: In general, embodiments relate to a method for managing a technical support session, comprising: determining a technical support issue (TSI) for a technical support session; identifying a question path graph (QPG) associated with the TSI; and displaying at least a portion of the QPG to a technical support person (TSP) during the technical support session.

Abstract: The present application provides methods and systems for detecting and quantifying chromosomal instability from histology images with machine learning. Also described herein are methods for selecting treatments for a medical disease, by determining a chromosomal instability pathological metric from histology images. The disclosed methods and systems may also be used to investigate disease progression and prognosis.

Abstract: In general, in one aspect, embodiments relate to a method for managing technical support sessions, the method comprising: generating a first plurality of local technical support sessions, transmitting at least a portion of the first plurality of local technical support sessions to a technical support hub, and receiving a local technical support session from a second technical support system, wherein the local technical support session is presented to a technical support person (TSP) during a technical support session performed on a first technical support system.

Abstract: Inflatable coveralls provide individuals, who fall frequently, with protection and independence. The coveralls consist of pads on the shoulders and hips to reduce the impact of a fall on the person. When worn and located underneath the fallen person, the coveralls can be inflated with air into a chair, creating a higher platform from which the person can more easily get up. This reduces the dependence these individuals have on a caregiver. Users can fasten the coveralls using hook & loop or magnets, instead of buttons or zippers, because it is easier to wear and they automatically open from the increase in air pressure of the inflated coveralls. Made of lightweight and air-impermeable material, the inflatable coveralls pads the fall of individual and elevated the fallen individual so that they can more easily rise, allowing them to gain independence.

Abstract: In general, embodiments relates to a method for managing technical support sessions, the method comprising generating a first plurality of local technical support sessions, applying a sharing compliance rule to at least a portion of the first plurality of local technical support sessions to generate a second plurality of modified technical support sessions, transmitting the second plurality of modified technical support sessions to a technical support hub, and receiving a local technical support session originating from a second technical support system, wherein the local technical support session is presented to a technical support person (TSP) during a technical support session performed on a first technical support system.

Abstract: Methods are provided for targeting cells for depletion, including without limitation tumor cells, in a regimen comprising contacting the targeted cells with a combination of agents that modulate immunoregulatory signaling. Immunoregulatory modulating agents include (i) an agent that blockades CD47 activity; and (ii) an agent that agonizes an immune costimulatory molecule, e.g. CD137. The regimen may further comprise an agent that specifically binds to the target cell, e.g. an antibody or biologically active fragment or derivative thereof. The level of depletion of the targeted cell is enhanced relative to a regimen in which a single immunoregulatory modulating agent is used; and the effect may be synergistic relative to a regimen in which a single immunoregulatory modulating agent is used.

Abstract: Aspects of the present invention disclose a method for identifying items that can utilize stabilized delivery in a delivery system. The method includes one or more processors obtaining data indicating a delivery item from an internet of things (IoT) enabled device. The method further includes determining information associated with the delivery item. The method further includes determining whether the information of the delivery item is associated with stabilized delivery. The method further includes scheduling delivery of the delivery item with a delivery vehicle, based at least in part on the information associated with the delivery item.

Abstract: Methods, apparatus, and processor-readable storage media for device component management using deep learning techniques are provided herein. An example computer-implemented method includes obtaining telemetry data from one or more enterprise devices; determining, for each of the one or more enterprise devices, values for multiple device attributes by processing the obtained telemetry data; generating, for each of the one or more enterprise devices, at least one prediction related to lifecycle information of at least one device component by processing the determined attribute values using one or more deep learning techniques; and performing one or more automated actions based at least in part on the at least one generated prediction.

Abstract: A process for fabricating a transversely-excited film bulk acoustic resonator (XBAR) and that XBAR are described. A sacrificial pillar is formed on a surface of a piezoelectric wafer and a highly conforming dielectric layer is deposited on the piezoelectric wafer to bury the sacrificial pillar. The highly conforming dielectric layer is polished to form a planar surface and to leave a thickness of the highly conforming dielectric that covers the sacrificial pillar. The planar surface of the highly conforming dielectric layer is bonded to a surface of a substrate wafer. A conductor pattern is formed on a front surface of the piezoelectric plate and holes are formed through the piezoelectric wafer to the sacrificial pillar. The sacrificial pillar is removed using an etchant introduced through the holes in the piezoelectric wafer to form a cavity under a diaphragm of the piezoelectric wafer spanning the cavity.

Abstract: Acoustic resonator devices and methods are disclosed. An acoustic resonator device includes a substrate having a front surface and an intervening oxide layer on the front surface and having a cavity. A thickness of the intervening oxide layer defines a depth of the cavity, and the substrate has vertical etch-stop material for etching the intervening oxide layer. Lateral fences formed in the intervening oxide layer define a perimeter of the cavity. The lateral fences has a lateral etch-stop material for etching the intervening oxide layer. A single-crystal piezoelectric plate has a back surface attached to the front surface of the intervening oxide layer except for a portion of the piezoelectric plate forming a diaphragm that spans the cavity. An interdigital transducer is formed on the front surface of the single-crystal piezoelectric plate such that interleaved fingers of the IDT are disposed on the diaphragm.

Abstract: The system and methods described herein determine whether to override commands to modify content presentation in a multi-user content consumption environment. A media guidance application detects a first and second user consuming content. Upon receiving a command from the first user to modify the presentation of the content, the media guidance application retrieves a user profile of the second user and compares attributes in the user profile to metadata for the segment of the content. Based on the comparison, the media guidance application determines whether to override the command, for example based on a predicted interest level or importance level determined by the comparison. In response to determining to override the command, the media guidance application refrains from executing the command by canceling or delaying the command and generates a notification message to the user with a reason why the command was overridden.

Abstract: A specification of a first natural language understanding (NLU) machine learning model for a first human communication language is received. The specification specifies a language content associated with one or more intents of the first NLU machine learning model in the first human communication language. An identification of an association between the first NLU machine learning model and a second NLU machine learning model for a second human communication language is received. The first NLU machine learning model and the second NLU machine learning model are managed together. This includes detecting a change to the first NLU machine learning model in the first human communication language and in response automatically assisting in maintaining consistency in the second NLU machine learning model in the second human communication language with respect to the detected change.

Abstract: In some examples, a server may determine a specification associated with a software module that is to be integrated with a software system. The specification identifies how the software module interacts with the software system. The server may execute a machine learning module to perform an analysis of the specification. The machine learning module may suggest at least one modification to at least a first portion of the specification and may automatically modify at least a second portion of the specification. The server may convert the specification to one or more application programming interface (API) calls and provide a system interface that includes the one or more API calls to enable the software module to interact with the software system. The API calls may include calls to a data integration API, a file transfer API, a messaging API, a database API, or any combination thereof.

Abstract: In one example in accordance with the present disclosure, an electronic device is described. An example electronic device includes a processor and memory storing executable instructions that when executed cause the processor to import user feedback for a product from multiple websites. The instructions also cause the processor to combine the user feedback with product health data for the product. The instructions further cause the processor to run a machine-learning (ML) model to determine a rating for the product based on the combined user feedback and product health data. In some examples, the instructions also cause the processor to implement a chatbot to receive a user query and provide a product recommendation based on the user feedback and product rating.

Abstract: Techniques described herein relate to a method for managing support cases of clients. The method may include obtaining a support case associated with a client of the clients; in response to obtaining the support case, obtaining contextual information associated with the support case; obtaining client telemetry data associated with the support case; selecting a portion of training data that is similar to the support case based on the client telemetry data, the contextual information, and the support case; generating a prediction model using the portion of the training data and a classification algorithm; and generating predictions using the prediction model, the client telemetry data, the contextual information, and the support case.