Abstract: Light weight fiber-reinforced polymeric structural building panels and methods; sized, configured for fabrication of non-portable wall structures permanently fixed to natural base. The panel main body, and studs, can be fabricated separately, then assembled to each other to complete panel fabrication. Methods for making the main body are hand lay-up, or pultrusion. Studs are typically pultruded, and subsequently prepared having consistent thickness, flat surface, across the width of the stud end wall which is to be mounted to the main body. Foam blocks are between inner and outer layers of the panel. Foam blocks can be prepared in block clusters before assembly to the main body. In the main body, a fibrous layer is between each pair of next adjacent foam blocks. Intercostals extend “y” and “z” dimensions transverse to the length of the main body. Studs can be mounted to the main body using adhesive, mechanical fasteners, or both.

Abstract: Methods and systems described in this disclosure receive a call from a device associated with a caller and request an indication of a context of the call. The system can send a request for authentication credentials in a push notification to the device. The push notification can be linked to an authentication tab or page in an application. After authentication of the caller, the system can direct the application to cause a tab or page associated with the subject matter of the call to be displayed on the qualified device.

Abstract: In a general aspect, a quantum computing method is described. In some aspects, a control system in a quantum computing system assigns subsets of qubit devices in a quantum processor to respective cores. The control system identifies boundary qubit devices residing between the cores in the quantum processor and generates control sequences for each respective core. A signal delivery system in communication with the control system and the quantum processor receives control signals to execute the control sequences, and the control signals are applied to the respective cores in the quantum processor.

Abstract: Techniques are described for generating a seal that is applicable to an object, and scanning the seal to access encoded data to be used for verifying one or more characteristics of the object. The seal may be applied to a tangible document, such as a document printed on paper. The seal may encode data that is particularly associated with the document. For example, the seal may encode a hash of at least a portion of the information (e.g., text) included in the document. In some instances, the seal may encode a digital version and/or metadata of at least a portion of the information in the document. A scan of the seal may retrieve information useable to verify the authorship, provenance, originality, and/or unaltered contents of the documents. In some instances, the seal may encode information that enables the presentation of hidden information and/or metadata associated with the document.

Abstract: Disclosed herein is an NLP system that is able to extract meaning from a natural language message using improved parsing techniques. Such an NLP system can be used in concert with an NLG system to interactively interpret messages and generate response messages in an interactive conversational stream. The parsing can include (1) named entity recognition that contextualizes the meanings of words in a message with reference to a knowledge base of named entities understood by the NLP and NLG systems, (2) syntactically parsing the message to determine a grammatical hierarchy for the named entities within the message, (3) reduction of recognized named entities into aggregations of named entities using the determined grammatical hierarchy and reduction rules to further clarify the message's meaning, and (4) mapping the reduced aggregation of named entities to an intent or meaning, wherein this intent/meaning can be used as control instructions for an NLG process.

Abstract: In a general aspect, a quantum processor has a modular architecture. In some aspects, a modular quantum processor includes first and second quantum processor chips and a cap structure. The first quantum processor chip is supported on a substrate layer and includes a first plurality of qubit devices. The second quantum processor chip is supported on the substrate layer and includes a second plurality of qubit devices. The cap structure is supported on the first and second quantum processor chips and includes a coupler device that provides coupling between at least one of the first plurality of qubit devices with at least one of the second plurality of qubit devices. In some instances, the coupler device is an active coupler device that is configured to selectively couple at least one of the first plurality of qubit devices with at least one of the second plurality of qubit devices.

Abstract: Techniques are described for routing service requests in a service environment. Received requests received may be analyzed to determine characteristics of each request, including a category of the request, a difficulty of the request, and the individual who submitted the request. A list of pending requests may be presented in a user interface (UI) according to a hierarchical set of filters. A service representative (SR) may select a pending request to handle and, in response, a service session may be initiated between the SR and the individual who submitted the request. Each request may be assigned a point value according to a set of configurable rules, e.g., based on the difficulty of the request, the amount of time it has been pending in the queue of requests, and/or other characteristics. The point value of the request may be added to a score of the SR who handles the request.

Abstract: Disclosed herein is an NLP system that is able to extract meaning from a natural language message using improved parsing techniques. Such an NLP system can be used in concert with an NLG system to interactively interpret messages and generate response messages in an interactive conversational stream. The parsing can include (1) named entity recognition that contextualizes the meanings of words in a message with reference to a knowledge base of named entities understood by the NLP and NLG systems, (2) syntactically parsing the message to determine a grammatical hierarchy for the named entities within the message, (3) reduction of recognized named entities into aggregations of named entities using the determined grammatical hierarchy and reduction rules to further clarify the message's meaning, and (4) mapping the reduced aggregation of named entities to an intent or meaning, wherein this intent/meaning can be used as control instructions for an NLG process.

Abstract: In a general aspect, a computing system is configured to execute a quantum approximate optimization algorithm. In some aspects, a control system identifies a pair of qubit devices in a quantum processor. The quantum processor includes a connection that provides coupling between the pair of qubit devices. ZZ coupling between the pair of qubit devices is activated to execute a cost function defined in the quantum approximate optimization algorithm. The cost function is associated with a maximum cut problem, and the ZZ coupling is activated by allowing the pair of qubits to evolve under a natural Hamiltonian for a time period ?. One or more of the pair of qubit devices is measured to obtain an output from an execution of the quantum approximate optimization algorithm.

Abstract: Disclosed herein is computer technology that applies natural language processing (NLP) techniques to training data to generate information used to train a natural language generation (NLG) system to produce output that stylistically resembles the training data. In this fashion, the NLG system can be readily trained with training data supplied by a user so that the NLG system is adapted to produce output that stylistically resembles such training data. In an example, an NLP system detects a plurality of linguistic features in the training data. These detected linguistic features are then aggregated into a specification data structure that is arranged for training the NLG system to produce natural language output that stylistically resembles the training data. Parameters in the specification data structure can be linked to objects in an ontology used by the NLG system to facilitate the training of the NLG system based on the detected linguistic features.

Abstract: Disclosed herein is an NLP system that is able to extract meaning from a natural language message using improved parsing techniques. Such an NLP system can be used in concert with an NLG system to interactively interpret messages and generate response messages in an interactive conversational stream. The parsing can include (1) named entity recognition that contextualizes the meanings of words in a message with reference to a knowledge base of named entities understood by the NLP and NLG systems, (2) syntactically parsing the message to determine a grammatical hierarchy for the named entities within the message, (3) reduction of recognized named entities into aggregations of named entities using the determined grammatical hierarchy and reduction rules to further clarify the message's meaning, and (4) mapping the reduced aggregation of named entities to an intent or meaning, wherein this intent/meaning can be used as control instructions for an NLG process.

Abstract: Applied Artificial Intelligence Technology for Adaptive Natural Language Understanding Disclosed herein is computer technology that provides adaptive mechanisms for learning concepts that are expressed by natural language sentences, and then applies this learning to appropriately classify new natural language sentences with the relevant concept that they express.

Abstract: Provided herein are methods, systems, and devices for detecting and/or identifying one or more specific microorganisms in a culture sample. Indicator particles, such as surface enhanced Raman spectroscopy (SERS)-active nanoparticles, each having associated therewith one or more specific binding members having an affinity for the one or more microorganisms of interest, can form a complex with specific microorganisms in the culture sample. Further, agitating magnetic capture particles also having associated therewith one or more specific binding members having an affinity for the one or more microorganisms of interest can be used to capture the microorganism-indicator particle complex and concentrate the complex in a localized area of an assay vessel for subsequent detection and identification. The complex can be dispersed, pelleted, and redispersed so that the culture sample can be retested a number of times during incubation so as to allow for real-time monitoring of the culture sample.

Abstract: LED board interconnect schemes for illuminable assemblies are provided. Multiple LED boards may form a partial perimeter along an illuminable assembly. The multiple LED boards and interconnects must fit within a limited width and height of the illuminable assembly. In some implementations, an interconnect board and spring connectors are used to provide a low-profile electrical interconnection while maintaining co-planarity of the LEDs across the LED boards.

Abstract: An engine friction monitor uses commanded torque and measured torque to provide a prognostic feature to identify failure modes of an engine that causes the engine from delivering the commanded torque.

Abstract: Disclosed herein is computer technology that applies natural language processing (NLP) techniques to training data to generate information used to train a natural language generation (NLG) system to produce output that stylistically resembles the training data. In this fashion, the NLG system can be readily trained with training data supplied by a user so that the NLG system is adapted to produce output that stylistically resembles such training data. In an example, an NLP system detects a plurality of linguistic features in the training data. These detected linguistic features are then aggregated into a specification data structure that is arranged for training the NLG system to produce natural language output that stylistically resembles the training data. Parameters in the specification data structure can be linked to objects in an ontology used by the NLG system to facilitate the training of the NLG system based on the detected linguistic features.

Abstract: Disclosed herein is an NLP system that is able to extract meaning from a natural language message using improved parsing techniques. Such an NLP system can be used in concert with an NLG system to interactively interpret messages and generate response messages in an interactive conversational stream. The parsing can include (1) named entity recognition that contextualizes the meanings of words in a message with reference to a knowledge base of named entities understood by the NLP and NLG systems, (2) syntactically parsing the message to determine a grammatical hierarchy for the named entities within the message, (3) reduction of recognized named entities into aggregations of named entities using the determined grammatical hierarchy and reduction rules to further clarify the message's meaning, and (4) mapping the reduced aggregation of named entities to an intent or meaning, wherein this intent/meaning can be used as control instructions for an NLG process.

Abstract: Methods and systems described in this disclosure receive a call from a caller, generate a first session through a first channel associated with the caller when the call is received and then send a request for authentication credentials to a device associated with the caller. In some embodiments, sending the request for authentication credentials generates a second session through a second channel associated with the caller. The caller can be authenticated to the first session using communication received during the second session through the second channel.

Abstract: Applied Artificial Intelligence Technology for Using Natural Language Processing and Concept Expression Templates To Train a Natural Language Generation System Disclosed herein is computer technology that applies natural language processing (NLP) techniques to training data to generate information used to train a natural language generation (NLG) system to produce output that stylistically resembles the training data. In this fashion, the NLG system can be readily trained with training data supplied by a user so that the NLG system is adapted to produce output that stylistically resembles such training data. In an example, an NLP system detects a plurality of linguistic features in the training data. These detected linguistic features are then aggregated into a specification data structure that is arranged for training the NLG system to produce natural language output that stylistically resembles the training data.