Abstract: A system and method are disclosed for monitoring health conditions based on data collected by a wearable device such as an activity tracker or a smart watch. Deep learning algorithms are configured to process an input vector that includes monitored parameter data collected by the wearable device as well as embedding data obtained from health records corresponding to a user account registered to the wearable device. In some embodiments, the input vector can also include social determinants data and/or demographic data. The output of the deep learning algorithms provides classifiers that represent probabilities that the user of the wearable device has an underlying health condition. If any underlying health condition is detected, then the user can be notified directly, via the wearable device or an associated application or technology, or indirectly, via a primary care provider associated with the user.

Abstract: Disclosed herein is a computerized method including operations of receiving a request for a treatment recommendation, where the request includes a user ID and where a treatment is a notification, alert, or message to be provided by a network device. The operations further include retrieving a set of user data from an aggregated user data table according to the user ID and treatment data comprised of data related to a set of predefined treatments from a treatment datastore, determine a score for each of the set of candidate treatments through processing of the set of user data, a set of candidate treatments, and a configured objective as input by a machine learning model, generating a ranked list of treatments based on the scoring provided by the machine learning model, and providing the ranked list of the set of candidate treatments and the set of candidate treatments to the network device.

Abstract: Disclosed herein is a computerized method including operations of obtaining user attributes and user event data, generating user embeddings and aggregated user features from the user event data and the user attributes, obtaining treatment attributes and a set of treatments corresponding to the treatment attributes, generating treatment embeddings and aggregated treatment features from the set of treatments and the treatment attributes, and generating a trained machine learning model by processing the user embeddings, the aggregated user features, the treatment embeddings, and the aggregated treatment features by a machine learning algorithm, wherein the trained machine learning machine is configured to generate a score for each treatment of the set of treatments indicative of a likelihood that serving of a particular treatment will result in performance of an objective. The user event data may include event sequence data indicating a sequence of user input actions corresponding to one or more treatments.

Abstract: A method for applying extended reality to simulate an actual flow system, including receiving selection of simulated components of the actual flow system that are graphical elements, receiving component metadata for each simulated component that represents simulated component factors that affect the simulated flow from, through, or to the simulated component, receiving simulation connection metadata for each simulated connection between the simulated components that represents simulated connection factors that affect the simulated flow through the simulated connection, receiving actual data over time, simulating the flow over time through the simulated connections based on the actual data by applying a model using a set of operations to the actual data, the simulation component metadata, and the simulation connection metadata. The method further includes displaying via the extended reality user interface the three or more simulated components as connected by the simulated connections and the simulated flow.

Abstract: A computer-implemented method for controls stability of a vehicle, being a truck or tractor and at least one trailer comprising at least two wheel axles and an electronically controllable suspension system. The method identifies a possible instability state of the vehicle; determines a type of an event that has caused the possible instability state; determining one or more actions comprising adjusting a load distribution between the at least two wheel axles of the trailer based on the possible instability state and based on the type of the event that has caused the possible instability state; and generates and sending a control command to the suspension system to perform the actions. The actions may comprise adjusting the load distribution between the at least two wheel axles of the trailer such that a load on a rear axle is increased and a load on a front axle is decreased.

Abstract: A water-soluble film, comprising a first water-soluble film, wherein the first water soluble film disintegrates in water within less than about 24 hours and dissolves in water within less than about 48 hours as measured by the MSTM-205 at 20° C. The disclosure provides a water-soluble film comprising a first water-soluble film that disintegrates in water within less than 24 hours and dissolves in water within less than 48 hours as measured by MSTM-205 at 20° C. The first water-soluble film optionally may be further characterized in that it does not disintegrate in water for at least about 1 hour and does not dissolve in water for at least about 1 hour as measured by MSTM-205 at 20° C. The disclosure further provides a water-soluble film comprising a first water-soluble film characterized in that the degradation and/or dissolution of the first water-soluble film is adapted to be activated by consumer handling.

Abstract: System, method, and various embodiments for conversation resource deallocation system are described herein. An embodiment operates by initiating a conversation between a chat bot and a user device, allocating a plurality of resources to maintain the conversation, and generating both a state entry and master entry for the conversation in a storage system, whereby the state entry is associated with a timeout period for the conversation. A first list of all master entries and a second list of master entries for which a corresponding one of the state entry is retrieved. A third list of the master entries for which the timeout period has expired is generated based on the first and second lists. Based on the third list, it is determine that the conversation has exceeded the timeout period, and the resources are deallocated.

Abstract: A system and method are disclosed for detecting chronic health conditions based on data collected by a wearable device such as an activity tracker or a smart watch. Deep learning algorithms are configured to process the monitored parameter data collected by the wearable device as well as additional embedding data obtained from health records corresponding to a user account registered to the wearable device. In some examples, the input vector can also include embedding data related to social determinants data and/or demographic data. The output of the deep learning algorithms provides predictions that represent probabilities that the user of the wearable device has an underlying health condition. If any underlying health condition is detected, then the user can be notified directly, via the wearable device or an associated application or technology, or indirectly, via a primary care provider associated with the user.

Abstract: A system and method are disclosed for detecting chronic health conditions based on data collected by a wearable device such as an activity tracker or a smart watch. Deep learning algorithms are configured to process the monitored parameter data collected by the wearable device as well as additional embedding data obtained from health records corresponding to a user account registered to the wearable device. In some examples, the input vector can also include embedding data related to social determinants data and/or demographic data. The output of the deep learning algorithms provides predictions that represent probabilities that the user of the wearable device has an underlying health condition. If any underlying health condition is detected, then the user can be notified directly, via the wearable device or an associated application or technology, or indirectly, via a primary care provider associated with the user.

Abstract: A water-soluble film, comprising a first water-soluble film, wherein the first water soluble film disintegrates in water within less than about 24 hours and dissolves in water within less than about 48 hours as measured by the MSTM-205 at 20° C. The disclosure provides a water-soluble film comprising a first water-soluble film that disintegrates in water within less than 24 hours and dissolves in water within less than 48 hours as measured by MSTM-205 at 20° C. The first water-soluble film optionally may be further characterized in that it does not disintegrate in water for at least about 1 hour and does not dissolve in water for at least about 1 hour as measured by MSTM-205 at 20° C. The disclosure further provides a water-soluble film comprising a first water-soluble film characterized in that the degradation and/or dissolution of the first water-soluble film is adapted to be activated by consumer handling.

Abstract: A water-soluble film, comprising a first water-soluble film, wherein the first water soluble film disintegrates in water within less than about 24 hours and dissolves in water within less than about 48 hours as measured by the MSTM-205 at 20° C. The disclosure provides a water-soluble film comprising a first water-soluble film that disintegrates in water within less than 24 hours and dissolves in water within less than 48 hours as measured by MSTM-205 at 20° C. The first water-soluble film optionally may be further characterized in that it does not disintegrate in water for at least about 1 hour and does not dissolve in water for at least about 1 hour as measured by MSTM-205 at 20° C. The disclosure further provides a water-soluble film comprising a first water-soluble film characterized in that the degradation and/or dissolution of the first water-soluble film is adapted to be activated by consumer handling.

Abstract: A system and method are disclosed for detecting chronic health conditions based on data collected by a wearable device such as an activity tracker or a smart watch. Deep learning algorithms are configured to process the monitored parameter data collected by the wearable device as well as additional embedding data obtained from health records corresponding to a user account registered to the wearable device. In some examples, the input vector can also include embedding data related to social determinants data and/or demographic data. The output of the deep learning algorithms provides predictions that represent probabilities that the user of the wearable device has an underlying health condition. If any underlying health condition is detected, then the user can be notified directly, via the wearable device or an associated application or technology, or indirectly, via a primary care provider associated with the user.

Abstract: A laser-sustained plasma (LSP) light source with vortex gas flow is disclosed. The LSP source includes a gas containment structure for containing a gas, one or more gas inlets configured to flow gas into the gas containment structure, and one or more gas outlets configured to flow gas out of the gas containment structure. The one or more gas inlets and the one or more gas outlets are arranged to generate a vortex gas flow within the gas containment structure. The LSP source also includes a laser pump source configured to generate an optical pump to sustain a plasma in a region of the gas containment structure within an inner gas flow within the vortex gas flow. The LSP source includes a light collector element configured to collect at least a portion of broadband light emitted from the plasma.

Abstract: A plasma lamp for use in a broadband plasma source of an inspection tool is disclosed. The plasma lamp includes a plasma bulb configured to contain a gas and generate a plasma within the plasma bulb. The plasma bulb is formed from a material at least partially transparent to illumination from a pump laser and at least a portion of broadband radiation emitted by the plasma. The plasma bulb includes a conical pocket. The conical pocket is configured to disrupt a plume rising from the plasma.

Abstract: A method for applying extended reality to simulate an actual flow system, including receiving selection of simulated components of the actual flow system that are graphical elements, receiving component metadata for each simulated component that represents simulated component factors that affect the simulated flow from, through, or to the simulated component, receiving simulation connection metadata for each simulated connection between the simulated components that represents simulated connection factors that affect the simulated flow through the simulated connection, receiving actual data over time, simulating the flow over time through the simulated connections based on the actual data by applying a model using a set of operations to the actual data, the simulation component metadata, and the simulation connection metadata. The method further includes displaying via the extended reality user interface the three or more simulated components as connected by the simulated connections and the simulated flow.

Abstract: A method for applying extended reality to simulate an actual flow system, including receiving selection of simulated components of the actual flow system that are graphical elements, receiving component metadata for each simulated component that represents simulated component factors that affect the simulated flow from, through, or to the simulated component, receiving simulation connection metadata for each simulated connection between the simulated components that represents simulated connection factors that affect the simulated flow through the simulated connection, receiving actual data over time, simulating the flow over time through the simulated connections based on the actual data by applying a model using a set of operations to the actual data, the simulation component metadata, and the simulation connection metadata. The method further includes displaying via the extended reality user interface the three or more simulated components as connected by the simulated connections and the simulated flow.

Abstract: A method for applying extended reality to simulate an actual flow system, including receiving selection of simulated components of the actual flow system that are graphical elements, receiving component metadata for each simulated component that represents simulated component factors that affect the simulated flow from, through, or to the simulated component, receiving simulation connection metadata for each simulated connection between the simulated components that represents simulated connection factors that affect the simulated flow through the simulated connection, receiving actual data over time, simulating the flow over time through the simulated connections based on the actual data by applying a model using a set of operations to the actual data, the simulation component metadata, and the simulation connection metadata. The method further includes displaying via the extended reality user interface the three or more simulated components as connected by the simulated connections and the simulated flow.

Abstract: A water-soluble film, comprising a first water-soluble film, wherein the first water soluble film disintegrates in water within less than about 24 hours and dissolves in water within less than about 48 hours as measured by the MSTM-205 at 20° C. The disclosure provides a water-soluble film comprising a first water-soluble film that disintegrates in water within less than 24 hours and dissolves in water within less than 48 hours as measured by MSTM-205 at 20° C. The first water-soluble film optionally may be further characterized in that it does not disintegrate in water for at least about 1 hour and does not dissolve in water for at least about 1 hour as measured by MSTM-205 at 20° C. The disclosure further provides a water-soluble film comprising a first water-soluble film characterized in that the degradation and/or dissolution of the first water-soluble film is adapted to be activated by consumer handling.

Abstract: A system and method are disclosed for monitoring health conditions based on data collected by a wearable device such as an activity tracker or a smart watch. Deep learning algorithms are configured to process an input vector that includes monitored parameter data collected by the wearable device as well as embedding data obtained from health records corresponding to a user account registered to the wearable device. In some embodiments, the input vector can also include social determinants data and/or demographic data. The output of the deep learning algorithms provides classifiers that represent probabilities that the user of the wearable device has an underlying health condition. If any underlying health condition is detected, then the user can be notified directly, via the wearable device or an associated application or technology, or indirectly, via a primary care provider associated with the user.

Abstract: A system and method are disclosed for predicting unnecessary emergency room visits based on data collected by a wearable device such as an activity tracker or a smart watch. Artificial Intelligence (AI) algorithms are configured to process an input vector that includes monitored parameter data collected by the wearable device as well as embedding data obtained from health records corresponding to a user account registered to the wearable device. The output of the AI algorithms provides classifiers that represent probabilities that the user of the wearable device is likely to experience one or more acute events within a specific time frame or time frames. The acute event can include an emergency room visit, which may be classified as unnecessary and/or preventable, and the user can be notified directly, via the wearable device or an associated application or technology, to attempt to deter preventable emergency room visits.