Abstract: A chewing gum includes a body and a coating. The body includes a gum base polymer, an oil, an active ingredient, an insoluble cellulosic material, and a buffer system. The gum base polymer includes polyvinyl acetate (PVA) in an amount ranging from 35 weight percent to 55 weight percent of the body. The oil includes medium chain triglycerides in an amount ranging from 3 weight percent to 11 weight of the body. The buffer system is present in an amount ranging from 0.1 weight percent to 8 weight percent of the body. The coating is at least partially surrounding the body.

Abstract: A method for identifying correlated users. The method may include: receiving connection data for each of one or more other users; determining a degree of connection of the one or more other users to the first user; receiving query information from one or more electronic devices associated with the first user; receiving authentication information for each of the one or more other users; determining a destination of the first user based on the query information; determining one or more other user destinations for the one or more other users; identifying one or more correlated other users from the one or more other users by comparing the destination of the first user with user destinations of the one or more other users and further based on the degree of connection of the one or more other users; and providing the identified one or more correlated other users to the first user.

Abstract: Systems and methods for forecasting data drift for model monitoring. In some aspects, the system receives a current explainability vector for a machine learning model and a data drift vector for historical data profiles. The machine learning model is trained on historical data including values for a first set of features. The system generates a projected synthetic dataset using the data drift vector and updates the machine learning model based on the projected synthetic dataset. Using the current explainability vector and a future explainability vector for the updated model, the system generates a second set of features and determines a drift threshold vector for the second set of features based on values in the explainability vectors. The system determines a discrepancy score for each feature of the second set of features. The system generates an alert including features in the second set of features and their associated discrepancy scores.

Abstract: A conference system is described that associates at least one of a plurality of devices participating in a conference session with at least one of a plurality of users participating in the conference session, and gathers an audio/video input from the at least one of the plurality of devices. The conference system detects a designated user from the plurality of users by detecting an audio/video cue from the audio/video input, and modifies a setting of the conference session based on the designated user.

Abstract: An actuator, including an electric drive for converting electrical signals into mechanical forces and/or deflections, is disclosed. The drive having at least one coil through which the current of the electrical signal can flow and having at least two magnets which can electromagnetically interact with the coil. The actuator being designed to excite a body which can be connected to the actuator, in particular a flat body, to vibrate, as a result of which the body can emit acoustic sound. The two magnets each being assigned at least one pole plate, the first and the second magnet, each with the at least one associated pole plate, forming at least one first and one second magnetic pole plate packet and the actuator having a frame in which the two magnetic pole plate packets are arranged in a substantially form-fitting manner.

Abstract: Systems and methods for a predictive cache of machine learning models. In some aspects, the system, in response to a user request, trains one or more machine learning models using a training dataset and inserts the machine learning models into a user library. The system, without input from the user, based on a distribution of values for a first feature in the training dataset, generates a search request for labeled data having a distribution of values within a threshold of the distribution of values of the first feature. The system adds to the training dataset values from the labeled data to generate an updated training dataset. The system trains a proximate machine learning model based on the updated training dataset and inserts the proximate machine learning model into a predictive cache of machine learning models.

Abstract: Described herein are systems and techniques for improving accuracies of determinations made using a nuclear magnetic resonance (NMR) sensing device when the NRM sensing device collects data in a wellbore. NMR sensing devices include a magnet that provides a magnetic field that aligns the spins of protons in substances near the NMR sensing device. The magnetic field strength provided by this magnet affects the sensitivity of the NMR sensing device and affects frequencies that the NMR sensing device effectively uses when the NMR sensing device operates. Furthermore, the field strength of magnets used in an NMR sensing device varies with temperature. Since temperatures within a wellbore vary significantly and since these temperatures affect how an NMR sensing device operates, systems and techniques of the present disclosure collect calibration data in a calibration chamber such that data sensed by the NMR sensing device can be interpreted more accurately when temperatures change.

Abstract: The present disclosure relates generally to compositions and methods for inhibiting dipeptide repeat protein (DPR)-ribosomal RNA (rRNA) interaction. In particular, the present technology relates to administering a therapeutically effective amount of one or more compositions that inhibit DPR-rRNA interaction to a subject diagnosed with, or at risk for DPR-associated pathologies, e.g., amyotrophic lateral sclerosis or frontotemporal dementia.

Abstract: A conference system is described that authenticates a user using multiple devices. The conference system authenticates a first device and associates the first device with the user. The conference system provides information for a second authentication method to the user. The conference system authenticates a second device by associating the second device with the user.

Abstract: A method includes extracting, by an analysis computer, a plurality of first datasets from a plurality of graph snapshots using a structural self-attention module. The analysis computer can then extract at least a second dataset from the plurality of first datasets using a temporal self-attention module across the plurality of graph snapshots. The analysis computer can then perform graph context prediction with at least the second dataset.

Abstract: Systems and methods are described for pre-authentication access request screening. A server computer may receive a request for access to a resource comprising access data. The server computer may transmit, to an authentication computer, an authentication request message comprising at least a subset of the access data and receive an authentication response message comprising authentication data. The server computer may determine an access score based on the authentication data. Alternatively, the server computer may determine the access score based on the access data without using/receiving authorization data. The server computer may generate an access indicator based on the access score. The server computer may prepare and transmit an authorization request message comprising the access indicator to an authorization computer. The authorization computer may approve or decline the access to the resource based on the access indicator.

Abstract: An electrically operated aerosol-generating system may include a liquid storage portion configured to store a liquid from which aerosol may be generated, an electric heater, a capillary wick extending between the liquid storage portion and the electric heater and configured to convey liquid from the liquid storage portion to the electric heater and electric circuitry connected to the electric heater. The electric circuitry may be configured to: activate the electric heater for a first heating time period in response to an input to vaporize liquid in the capillary wick, activate the electric heater for a second heating time period upon the elapse of a first cooling time period after the first heating time period, record a temperature measurement of the electric heater during the second heating time period, and determine an amount of liquid in the liquid storage portion based on the temperature measurement.

Abstract: Methods and systems create a data asset generator based on a knowledge-graph-based recommendation engine to present data asset type options to a user generating a data asset. The data asset type options are contained in a template. The user is required to use the templates generated by the system when creating a data asset. The templates are based on ontologies, which are based on a knowledge graph that stores the relationships between data asset types. Data asset types correlate to data asset characteristic clusters, which are clusters of keywords from previously generated data assets. The templates may help users select relevant data asset types and ensure regulatory compliance. By requiring a user to modify or adapt the template, data assets being generated may be standardized among previously generated data assets and data assets being generated, which may reduce querying conflicts and improve the readability and interoperability of datasets.

Abstract: An e-vapor apparatus may include a pod assembly and a dispensing body configured to receive the pod assembly. A vaporizer may be disposed in the pod assembly and/or the dispensing body. The pod assembly may include a pre-vapor formulation compartment, a device compartment, and a vapor channel extending from the device compartment and traversing the pre-vapor formulation compartment. The pod assembly is a smart pod configured to receive, store, and transmit information that can be communicated with the dispensing body and/or another electronic device. The proximal portion of the dispensing body includes a vapor passage and a through-hole. The vapor passage may extend from an end surface of the proximal portion to a side wall of the through-hole. The through-hole is configured to receive the pod assembly such that the vapor channel of the pod assembly is aligned with the vapor passage of the dispensing body.

Abstract: Provided herein are compositions and methods for the viral gene therapy (e.g., AAV-directed gene therapy) of cholesterol storage diseases or disorders, such as Niemann-Pick disease, Type C.

Abstract: A wellbore sealing device may be designed and manufactured using computer-assisted design and a hybrid of automated manufacturing and molding techniques. In one example, a stress analysis is performed to identify a reinforcement region to be reinforced in a sealing device component. Reinforcement fibers are selectively arranged using automated placement of the fibers in a location within a mold corresponding to the reinforcement region. The sealing device component is then molded, with the reinforcement fibers embedded in a matrix material locking the reinforcement fibers in position within the reinforcement region.

Abstract: Methods and systems described herein are directed to automatedly generating entity-specific notifications of a vehicle accident occurrence for entities. In response to a notification system receiving accident data, the system can determine characteristics for the accident occurrence. Using these characteristics, the system can then determine parameters for the notifications defining types of entities which ought to be recipients in accordance with the characteristics. The system can use these parameters to locate specific entities that match the parameters. Having determined the entities, the system can issue notifications to the entities, using templates specific to the entities and with accident characteristics added.

Abstract: An example method includes receiving images that each include an optical code. The method further includes cropping the images to isolate the optical codes and rotating the images to achieve a desired orientation for the optical code of each of the images. The method further includes rectifying, after the cropping and the rotating, a perspective of each of the images to achieve a desired perspective angle for the optical code of each of the images. The method further includes deblurring, after the rectifying, the images to reduce blurring in each of the images. The method further includes binarizing, after the deblurring, the images to correct pixels of the optical code in each of the images. The method further includes performing, after the binarizing, an optical code reading process on the plurality of images to decode optical codes in the images.

Abstract: Systems, methods, and computer program products to provide credit decisioning based on graph neural networks. A lending network graph of a plurality of loans may be received, each loan associated with a creditor and one account. A first node of the graph may be associated with a first creditor and the second node may be associated with a first account. A graph neural network may receive a respective message from each node connected to the first node, each message comprising an embedding vector reflecting a current state of the node. The graph neural network may update weights for the first node in a forward pass. The graph neural network may receive a respective message from each node connected to the second node, each message comprising the embedding vector reflecting the current state of the node. The graph neural network may update weights for the second node in a backward pass.