Abstract: Disclosed are Respiratory Syncytial Virus (RSV) antigens including a recombinant RSV F protein stabilized in a prefusion conformation. Also disclosed are nucleic acids encoding the antigens and methods of producing the antigens. Methods for generating an immune response in a subject are also disclosed. In some embodiments, the method is a method for treating or preventing a RSV infection in a subject by administering a therapeutically effective amount of the antigen to the subject.

Abstract: The present disclosure relates to chain monitoring systems and methods. In particular, the chain monitoring system is configured to mount onto a portion of a chain and measure one or more parameters associated with one or more characteristics of the chain. The measured parameters are processed by the chain monitoring system and/or transmitted to a remote system for analysis. The analysis may be used to determine a characteristic and/or change in the characteristic of the chain. In some examples, the characteristic is an elongation value associated with the chain, which can be transmitted to a networked system for analysis, display, and/or control. In some examples, a sensor can be employed to measure one or more characteristics of the chain. The sensor may include, but is not limited to, a strain gauge, an accelerometer, an optical, a sonic, and/or a magnetic sensor.

Abstract: A novel maize variety designated X18N926 and seed, plants and plant parts thereof are produced by crossing inbred maize varieties. Methods for producing a maize plant by crossing hybrid maize variety X18N926 with another maize plant are disclosed. Methods for producing a maize plant containing in its genetic material one or more traits introgressed into X18N926 through backcrossing or genetic transformation, and to the maize seed, plant and plant part produced thereby are described. Maize variety X18N926, the seed, the plant produced from the seed, and variants, mutants, and minor modifications of maize variety X18N926 are provided. Methods for producing maize varieties derived from maize variety X18N926 and methods of using maize variety X18N926 are disclosed.

Abstract: Systems and techniques for linguistically-driven automated text formatting are described herein. Data representing the linguistic structure of input text may be received from Natural Language Processing (NLP) Services, including but not limited to constituents, dependencies, and coreference relationships. A text model of the input text may be built using the linguistic components and relationships. Cascade rules may be applied to the text model to generate a cascaded text data structure. Cascaded data may be displayed on a range of media, including a phone, tablet, laptop, monitor, VR/AR devices. Cascaded data may be presented in dual screen formats to promote more accurate and efficient reading comprehension, greater ease in teaching native and foreign language grammatical structures, and tools for remediation of reading-related disabilities.

Abstract: Disclosed herein is a data science platform that is built with a specific focus on monitoring and analyzing the operation of industrial assets, such as trucking assets, rail assets, construction assets, mining assets, wind assets, thermal assets, oil-and-gas assets, and manufacturing assets, among other possibilities. The disclosed data science platform is configured to carry out operations including (i) ingesting asset-related data from various different data sources and storing it for downstream use, (ii) transforming the ingested asset-related data into a desired formatting structure and then storing it for downstream use, (iii) evaluating the asset-related data to derive insights about an asset's operation that may be of interest to a platform user, which may involve data science models that have been specifically designed to analyze asset-related data in order to gain a deeper understanding of an asset's operation, and (iv) presenting derived insights and other asset-related data to platform users.

Abstract: Systems and techniques for linguistically-driven automated text formatting are described herein. Data representing the linguistic structure of input text may be received from Natural Language Processing (NLP) Services, including but not limited to constituents, dependencies, and coreference relationships. A text model of the input text may be built using the linguistic components and relationships. Cascade rules may be applied to the text model to generate a cascaded text data structure. Cascaded data may be displayed on a range of media, including a phone, tablet, laptop, monitor, VR/AR devices. Cascaded data may be presented in dual screen formats to promote more accurate and efficient reading comprehension, greater ease in teaching native and foreign language grammatical structures, and tools for remediation of reading-related disabilities.

Abstract: The Multidimensional Machine Learning Data and User Interface Segment Tagging Engine Apparatuses, Methods and Systems (“MLUI”) transforms ambient condition data, sales data, user interface selections, cognitive intelligence question input inputs via MLUI components into project projections, campaigns, user interface visualizations, cognitive intelligence question output outputs. An update to a survey data file is detected. The updated survey data is stored in a SQL database configured to utilize a composite index of the updated survey data that optimizes database query time. A set of affected entity segment identifiers is determined. A set of affected category identifiers is determined. A set of affected cognitive intelligence (CI) datapoint identifiers is determined as CI datapoint identifiers associated with each combination of an affected entity segment identifier and an affected category identifier.

Abstract: The Multidimensional Machine Learning Data and User Interface Segment Tagging Engine Apparatuses, Methods and Systems (“MLUI”) transforms ambient condition data, sales data, user interface selections, cognitive intelligence question input inputs via MLUI components into project projections, campaigns, user interface visualizations, cognitive intelligence question output outputs. A category identifier selection is obtained via a category selection interaction interface mechanism. Entity segment identifier selections are obtained via entity segment selection interaction interface mechanisms. A set of visualization cognitive intelligence (CI) datapoint identifiers is determined as CI datapoint identifiers associated with each combination of a selected entity segment identifier and the selected category identifier.

Abstract: The Multidimensional Machine Learning Data and User Interface Segment Tagging Engine Apparatuses, Methods and Systems (“MLUI”) transforms ambient condition data, sales data, user interface selections, cognitive intelligence question input inputs via MLUI components into project projections, campaigns, user interface visualizations, cognitive intelligence question output outputs. A cognitive intelligence (CI) datapoint identifier cache datastructure is generated, the CI datapoint identifier cache datastructure configured to comprise a category identifier and an entity segment identifier. A CI datapoint value cache datastructure is generated, the CI datapoint value cache datastructure configured to comprise a set of module datastructures, each module datastructure corresponding to a module identifier associated with the category identifier, each module datastructure comprising a set of metric datastructures, each metric datastructure corresponding to a set of calculated metrics.

Abstract: Various examples of approaches for using and implementing cascaded text formatting within electronic publishing and display mediums are described herein. In an example, a method for analyzing and re-formatting a stream of text, includes: obtaining a stream of human-readable text in a natural language processing (NLP) parser to identify parts-of-speech and key phrases in a proper sentence; tagging the identified parts-of-speech according to the respective parts and key phrases; generating a text cascade arrangement for a display of the proper sentence by applying predefined rules to the part-of-speech and key phrases, where such a display of the proper sentence provides breaks and cascading, including indentations, according to the pre-defined rules; and outputting an electronic display of the proper sentence which includes the text cascade arrangement.

Abstract: Systems and methods for improved fluid dispensing process control using a machine learning tool are disclosed. In an example method, successive portions of viscous fluid are dispensed by a dispensing device according to operating parameters to train a machine learning tool to associate defect classifications with images of dispensed portions and/or operating parameters associated with dispensing the dispensed portions. The trained machine learning tool is then used in a closed loop fashion in production to detect and correct for defects associated with the dispensed portions to improve quality and production efficiency.

Abstract: Systems and techniques for linguistically-driven automated text formatting are described herein. Data representing the linguistic structure of input text may be received from Natural Language Processing (NLP) Services, including but not limited to constituents, dependencies, and coreference relationships. A text model of the input text may be built using the linguistic components and relationships. Cascade rules may be applied to the text model to generate a cascaded text data structure. Cascaded data may be displayed on a range of media, including a phone, tablet, laptop, monitor, VR/AR devices. Cascaded data may be presented in dual screen formats to promote more accurate and efficient reading comprehension, greater ease in teaching native and foreign language grammatical structures, and tools for remediation of reading-related disabilities.

Abstract: Aspects of the subject disclosure may include, for example, a system that includes a processing system including at least one processor and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations including receiving a unique identifying number for an entity, a vector associated with the entity, and a timestamp from a requestor, generating a key using the unique identifying number, the vector, and the timestamp, and sending the key to the requestor, wherein the requestor uses the key to store information associated with the entity. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a system that includes a processing system including at least one processor and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations including receiving a unique identifying number for an entity, a vector associated with the entity, and a timestamp from a requestor, generating a key using the unique identifying number, the vector, and the timestamp, and sending the key to the requestor, wherein the requestor uses the key to store information associated with the entity. Other embodiments are disclosed.

Abstract: Systems and techniques for linguistically-driven automated text formatting are described herein. Data representing the linguistic structure of input text may be received from Natural Language Processing (NLP) Services, including but not limited to constituents, dependencies, and coreference relationships. A text model of the input text may be built using the linguistic components and relationships. Cascade rules may be applied to the text model to generate a cascaded text data structure. Cascaded data may be displayed on a range of media, including a phone, tablet, laptop, monitor, VR/AR devices. Cascaded data may be presented in dual screen formats to promote more accurate and efficient reading comprehension, greater ease in teaching native and foreign language grammatical structures, and tools for remediation of reading-related disabilities.

Abstract: Disclosed herein is a data science platform that is built with a specific focus on monitoring and analyzing the operation of industrial assets, such as trucking assets, rail assets, construction assets, mining assets, wind assets, thermal assets, oil-and-gas assets, and manufacturing assets, among other possibilities. The disclosed data science platform is configured to carry out operations including (i) ingesting asset-related data from various different data sources and storing it for downstream use, (ii) transforming the ingested asset-related data into a desired formatting structure and then storing it for downstream use, (iii) evaluating the asset-related data to derive insights about an asset's operation that may be of interest to a platform user, which may involve data science models that have been specifically designed to analyze asset-related data in order to gain a deeper understanding of an asset's operation, and (iv) presenting derived insights and other asset-related data to platform users.

Abstract: Aspects of the subject disclosure may include, for example, a system that includes a processing system including at least one processor and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations including receiving a unique identifying number for an entity, a vector associated with the entity, and a timestamp from a requestor, generating a key using the unique identifying number, the vector, and the timestamp, and sending the key to the requestor, wherein the requestor uses the key to store information associated with the entity. Other embodiments are disclosed.

Abstract: A method and apparatus for controlling a group of the client devices to switch at least one client device of the group of client devices from a first conditional access system to a second conditional access system is disclosed. In one embodiment, the method comprises generating a group identifier identifying the group of the client devices, transmitting a first client device signaling message having the group identifier only to each client device of the identified group of the client devices, and transmitting a second client device signaling message to the plurality of client devices, the second client device signaling message comprising the group identifier and signaling each client device having the group identifier stored in the non-volatile memory to switch from the first system client to the second system client.