Abstract: A composition contains a BCS Class II or IV drug that is acid-base solubilized with a pharmaceutically acceptable acid, and which is complexed with ?-cyclodextrin. The ?-cyclodextrin complexed drug exhibits enhanced bioavailability. The drug may be formulated for oral administration and/or to exhibit rapid release when administered. Preferable compositions may contain no crosslinked or polymerized non-active components.

Abstract: A method for dynamically adjusting a number of virtual machines for a workload, includes: receiving a probability indicator for each of a plurality of N sequential stages, where N is a natural number greater than 1, of a likelihood that a virtual machine assigned to a workload will be evicted during the N sequential stages; predicting a target number of virtual machines to configure in a current stage for a subsequent stage from among the plurality of N sequential stages based on the probability indicator, a target capacity for the workload, and a current price for maintaining a virtual machine; and configuring a number of virtual machines for the workload during the current stage based on the target number to be loaded for the workload for the subsequent stage.

Abstract: A method for recommending a computer hardware configuration, including: receiving, by a processor, a machine-readable specification of a computing task; extracting, by the processor, a plurality of features from the machine-readable specification of the computing task; supplying, by the processor, the plurality of features to a reinforcement learning model to generate a proposed computer hardware configuration to execute the computing task; and providing, by the processor, the proposed computer hardware configuration to a user.

Abstract: Devices and techniques are generally described for semantic clustering and fixing of like-failed processing inputs. In some examples, first embedding data representing a first input may be generated. A first cluster of embeddings including the first embedding data may be generated. Second embedding data of the first cluster may be determined. First metadata for the first input may be determined. The first metadata may be associated with processing of the first input by the processing system. Second metadata for the second input may be determined. A first remedial action may be determined for processing the first input based at least in part on the first metadata and the second metadata.

Abstract: Systems and methods of providing a V2X communications are generally described. A geographically-limited, operator-independent mapping table is used that maps between groups of V2X applications each associated with a different application category and a different RAT preferred for the V2X application category. Each grouping is based on fulfillment of one or more KP Is for the associated V2X application category. Multiple RA Ts are prioritized if able to fulfill the KP Is. The mapping table is modified based on the RATs supported by the V2X UE. Carrier aggregation is used when simultaneous transmission on different RATs is desired.

Abstract: A method, computer program product, and computing system for processing a request to migrate a database command query in a source dialect to a target dialect. An example of the target dialect is obtained by processing the database command query in the source dialect using retrieval-augmented generation (RAG) with the plurality of examples of the target dialect. An instruction is obtained for instructing a generative artificial intelligence (AI) model to translate the database command query in the source dialect to the target dialect by processing the database command query in the source dialect using RAG with the plurality of instructions. A prompt is generated for the generative AI model using the database command query in the source dialect, the example, and the instruction. A candidate database command query is generated by prompting the generative AI model with the prompt to migrate the database command query in the source dialect to the target dialect.

Abstract: Systems, devices, methods, and computer-readable media for guided conversations with a generative artificial intelligence (AI) agent to complete an artifact are provided. A method includes generating a prompt, the prompt including a context, the artifact to be completed during a guided conversation, and rules to be followed in conducting the guided conversation, providing the prompt to the generative AI agent, receiving a response to a message from the generative AI agent, receiving a first function call to update a field of the artifact, the function call including a field and a value, determining, based on the value and a schema of the artifact, a result indicating whether the update is valid or invalid, providing, to the generative AI agent, the result, and receiving, from the generative AI agent, the artifact after the conversation is completed.

Abstract: Systems and methods of providing a V2X communications are generally described. A geographically-limited, operator-independent mapping table is used that maps between groups of V2X applications each associated with a different application category and a different RAT preferred for the V2X application category. Each grouping is based on fulfillment of one or more KP Is for the associated V2X application category. Multiple RA Ts are prioritized if able to fulfill the KP Is. The mapping table is modified based on the RATs supported by the V2X UE. Carrier aggregation is used when simultaneous transmission on different RATs is desired.

Abstract: A computer-implemented method for proactively detecting and remediating anomalous devices includes accessing, via a network, device attributes corresponding to enterprise devices within an enterprise network, providing the device attributes to a supervised machine learning model, and predicting, via the supervised machine learning model, whether each enterprise device is healthy or anomalous, where the enterprise device is predicted to be healthy unless the supervised machine learning model determines that the probability of the enterprise device being anomalous exceeds a specified confidence threshold. The method includes, for each enterprise device that is predicted to be anomalous, perturbing a portion of the corresponding device attributes via an automated counterfactual generator to generate synthetic data representative of counterfactual healthy devices.

Abstract: A video transfer circuit includes: a first communication interface; a second communication interface; and a digital timing generator having an input, an output, and a video timing signal interface. The input is coupled to the first communication interface. The video timing signal interface is coupled to the second communication interface. The digital timing generator is configured to: provide a first video timing signal to the second communication interface via the video timing signal interface responsive to a first mode selection; and receive a second video timing signal from the second communication interface via the video timing signal interface responsive to a second mode selection.

Abstract: A method for recommending a computer hardware configuration, including: receiving, by a processor, a machine-readable specification of a computing task; extracting, by the processor, a plurality of features from the machine-readable specification of the computing task; supplying, by the processor, the plurality of features to a reinforcement learning model to generate a proposed computer hardware configuration to execute the computing task; and providing, by the processor, the proposed computer hardware configuration to a user.

Abstract: Provided is a nanoparticle comprising a composition comprising a polypeptide having a molecular weight greater than 50,000 g/mol (e.g. IgY antibodies), wherein the composition is encapsulated in a material that includes a biocompatible bioerodible polymer. Also provided is a method of preparing these nanoparticles, and use of the nanoparticles as a therapeutic to treat a disease condition.

Abstract: A method for dynamically adjusting a number of virtual machines for a workload, includes: receiving a probability indicator for each of a plurality of N sequential stages, where N is a natural number greater than 1, of a likelihood that a virtual machine assigned to a workload will be evicted during the N sequential stages; predicting a target number of virtual machines to configure in a current stage for a subsequent stage from among the plurality of N sequential stages based on the probability indicator, a target capacity for the workload, and a current price for maintaining a virtual machine; and configuring a number of virtual machines for the workload during the current stage based on the target number to be loaded for the workload for the subsequent stage.

Abstract: Systems, apparatuses, methods, and computer-readable media are provided for use in a wireless network for dynamic port discovery. Some embodiments are directed to an originator device that includes processor circuitry and radio front circuitry. The processor circuitry can be configured to generate a command frame for dynamic port discovery for communicating with a receiver device using a Reliable Data Service (RDS) protocol. The processor circuitry can be further configured to transmit, using the radio front end circuitry, the command frame to the receiver device and receive, using the radio front end circuitry, a response frame from the receiver device. The processor circuitry can be further configured to assign, using the received response frame, a source port number and a destination port number to an application identifier. The application identifier can be associated with an application on the originator device communicating with a corresponding application on the receiver device.

Abstract: A computer-implemented method for proactively detecting and remediating anomalous devices includes accessing, via a network, device attributes corresponding to enterprise devices within an enterprise network, providing the device attributes to a supervised machine learning model, and predicting, via the supervised machine learning model, whether each enterprise device is healthy or anomalous, where the enterprise device is predicted to be healthy unless the supervised machine learning model determines that the probability of the enterprise device being anomalous exceeds a specified confidence threshold. The method includes, for each enterprise device that is predicted to be anomalous, perturbing a portion of the corresponding device attributes via an automated counterfactual generator to generate synthetic data representative of counterfactual healthy devices.

Abstract: Some embodiments of this disclosure include systems, apparatuses, methods, and computer-readable media for use in a wireless network for communicating data over control plane in a 5G system. For example, some embodiments are directed to a user equipment (UE). The UE includes processor circuitry and radio front end circuitry. The processor circuitry can be configured to transmit, using the radio front end circuitry, a first message for connecting to a 5G network and indicating a capability of the UE relating to Cellular Internet of Things (CIOT). The processor circuitry can be further configured to transmit, using the radio front end circuitry and via a control plane to the 5G network, a second message comprising mobile originated data. The processor circuitry can be further configured to receive, using the radio front end circuitry, a third message from the 5G network.

Abstract: A video transfer circuit includes: a first communication interface; a second communication interface; and a digital timing generator having an input, an output, and a video timing signal interface. The input is coupled to the first communication interface. The video timing signal interface is coupled to the second communication interface. The digital timing generator is configured to: provide a first video timing signal to the second communication interface via the video timing signal interface responsive to a first mode selection; and receive a second video timing signal from the second communication interface via the video timing signal interface responsive to a second mode selection.

Abstract: A computer-implemented method for performing natural language-based data integration includes causing execution of a data integration application on a remote device via a network and causing surfacing of a GUI corresponding to the data integration application on a display of the remote device. The method includes receiving, via the GUI, a natural language input representing a data integration task, generating, via an LLM, a set of ordered activities corresponding to the data integration task represented by the natural language input, and selecting, via the LLM, one or more APIs for performing each activity within the set of ordered activities. The method also includes generating a data pipeline based on the set of ordered activities and the API(s) for performing each activity, as well as back-translating the data pipeline to a desired data format for execution by the data integration application.

Abstract: Disclosed herein is a method of facilitating improving behavioral skills of users, in accordance with some embodiments. Accordingly, the method comprises receiving, using a communication device, a request from a user device. Further, the method comprises obtaining, using a processing device, a content based on the request. Further, the method comprises analyzing, using the processing device, the content using machine learning models. Further, the machine learning models are configured for determining the communication attributes. Further, the method comprises identifying, using the processing device, a behavioral skill from behavioral skills based on the determining. Further, the method comprises generating, using the processing device, a score corresponding to each of the behavioral skill based on the determining of the communication attributes and the identifying. Further, the method comprises transmitting, using the communication device, the score to the device.

Abstract: A computer-implemented method for performing natural language-based data integration includes causing execution of a data integration application on a remote device via a network and causing surfacing of a GUI corresponding to the data integration application on a display of the remote device. The method includes receiving, via the GUI, a natural language input representing a data integration task, generating, via an LLM, a set of ordered activities corresponding to the data integration task represented by the natural language input, and selecting, via the LLM, one or more APIs for performing each activity within the set of ordered activities. The method also includes generating a data pipeline based on the set of ordered activities and the API(s) for performing each activity, as well as back-translating the data pipeline to a desired data format for execution by the data integration application.