Abstract: Disclosed are systems and methods that automatically classify, segment, and parse content data using artificial intelligence and natural language processing technology, and generate graphical user interfaces that allow end users to dynamically filter content data for display. The systems processes volumes of content data to identify interrogative data, content sources that generated the interrogative data, and subject identifiers relating to the content data. The system generates graphical user interfaces that allow end users to effectively filter the data by choosing between layouts that display one or more of the various categories of data, including the interrogative data, content source identifiers, and/or subject identifiers.

Abstract: A system for data collection in a commercial travel setting is described. The system includes a plurality of sensor circuits that collect a plurality of sensor data values from in-flight entertainment (IFE) network. The system includes a sensor data processor that interprets the plurality of sensor data values. The system includes a passenger profile management controller configured that filters the plurality of sensor data values by processing a plurality of passenger profiles that are related to at least some of the plurality of sensor data values. The system generates a measurement index that is normalized with respect to the plurality of sensor data values or the plurality of passenger profiles.

Abstract: In some examples, an apparatus can include a plunder comprising a cavity, a bezel comprising an aperture having a particular shape, a magnet located in the cavity of the plunger, and a magnetically actuated valve connected to the bezel, where in response to the plunger being moved by a key having a shape corresponding to the particular shape of the aperture of the bezel, the magnet is to cause the magnetically actuated valve to actuate.

Abstract: In one example, a double jointed hinge connects a blow molded plastic door and a blow molded plastic wall panel. The double jointed hinge includes a first hinge element that defines a first axis of rotation, and the first hinge element is connected to the blow molded plastic wall panel, a second hinge element that defines a second axis of rotation and is connected to the blow molded plastic door, and the second hinge element is spaced apart from the first hinge element, and a first link and a second link, the first link and the second link connecting the first hinge element to the second hinge element.

Abstract: The present invention relates to neutralizing antibodies of the human pituitary adenylate cyclase activating polypeptide type I receptor (PAC1) and pharmaceutical compositions comprising such antibodies. Methods of treating or preventing headache conditions, such as migraine and cluster headache, using the neutralizing antibodies are also described.

Abstract: A computing system is configured to generate a predictive model during training of a machine learning program using a training data set including a personal data set of a plurality of first users. The predictive model is configured to predict a first predicted assessment score at a first instance and a second predicted assessment score at a second instance with respect to a second user. The computing system determines whether the first predicted assessment score is different from the second predicted assessment score, and whether a first data entry of the personal data set of the second user changed between the first instance and the second instance. The computing system takes or recommends an action corresponding to a reversal in the change in the first data entry in order to alter the predicted assessment score of the second user.

Abstract: A computing system is configured to generate a predictive model during training of a machine learning program using a training data set including a personal data set of a plurality of first users. The predictive model is configured to generate a predicted assessment score with respect to a second user by correlating a personal data set of the second user to the personal data set of at least one of the first users, with the generating of the predicted assessment score occurring automatically when a data entry of the personal data set of the second user is determined to have changed by the computing system. The computing system is configured to report the automatically generated predicted assessment score to the second user via a user device of the second user.

Abstract: A computing system is configured to generate a predictive model during training of a machine learning program using a training data set including a personal data set of a plurality of first users. The predictive model is configured to generate predicted survey data with respect to a second user by correlating a personal data set of the second user to the personal data set of at least one of the first users. The predicted survey data includes data regarding the predicted responses of the second user to a survey from which the survey data of each first user is derived, as well as one or more assessment scores calculated from the survey. The computing system is configured to take an action with respect to a user device of the second user in reaction to the generating of the predicted survey data regarding the second user.

Abstract: A computing system is configured to generate a predictive model during training of a machine learning program using a training data set including a personal data set of a plurality of first users. The predictive model is configured to predict a predicted assessment score of a second user. A test personal data set is generated with at least one different data entry different from the personal data set utilized in predicting the predicted assessment score, the at least one different data entry corresponding to a change in relationship between the computing system and the second user. The predictive model predicts a test predicted assessment score of the second user based on the test personal data set. The computing system takes further action with respect to the second user when a difference between the predicted assessment score and the test predicted assessment score meets or exceeds a threshold value.

Abstract: An apparatus (2100), including: a hasp (2104) configured to retain a staple therein when in an engaged position (2106); an actuator (2110) that is biased toward a locking position (2112) configured to lock the hasp in the engaged position, where once the hasp is moved into the engaged position the actuator can reach the locking position; an actuator weight (2130) configured to move under the influence of gravity once the apparatus is tilted from an upright orientation by more than an actuator weight threshold amount and to disengage the actuator from the hasp upon reaching an unlocking position (2136) with sufficient force; and a time delay lock assembly (2150) configured to be initiated when the apparatus is tilted from the upright orientation by a time delay lock threshold amount of tilt and configured to prevent movement of the actuator weight only after an initiation and a time delay.

Abstract: Systems and methods for contactless control of a physiological monitor are provided. A number of systems utilize an input device for audio-based control of a physiological monitor and/or an input device for gesture-based control of a physiological monitor. Many systems process audio (e.g., voice) or gesture commands to direct a physiological monitor to perform actions, such as begin monitoring, silencing an alarm, changing parameters, navigating screens and/or menus, and/or any other function. Such contactless systems reduce or eliminate physical contact with a physiological monitor, which can mitigate contamination between patients or individuals, which can occur via traditional systems.

Abstract: Systems and methods for group monitoring and management of network function statuses are provided. In one example, a method includes: generating a group query for statuses of a plurality of network functions of a network, in response to the group query performing group monitoring of the plurality of network functions to check the real-time status of each one of the plurality of network functions, receiving data corresponding to real-time status of each network function, comparing the data corresponding to real-time status with data corresponding to reference status for each one of the plurality of network functions, identifying presence or absence of an anomaly of each one of the plurality of network functions, based on the comparison, and generating a network function status output including data corresponding to the real-time status and an indication of the presence or absence of an anomaly for each network function.

Abstract: A printing apparatus and method. The printing apparatus is for impinging liquids from at least two liquid sources. The apparatus comprises a first jet actuator configured to dispense a first liquid from a first liquid source and a second jet actuator configured to dispense a second liquid from a second liquid source. The apparatus further comprises an adjustment element configured to adjust a trajectory of at least the first liquid dispensed from the first jet actuator such that the first liquid impinges the second liquid dispensed from the second jet actuator.

Abstract: Disclosed are systems and methods that automatically classify, filter, and reduce large volumes of feedback data as a function of time using artificial intelligence technology. The aggregated feedback data is reduced by representing the feedback data as sets of descriptors corresponding to one or more time periods that are displayed on a graphical user interface. Feedback data packets are parsed by labeling the feedback data packets with a time period identifier. The feedback data packets are processed utilizing neural network technology to classify the feedback data according to one or more subject identifiers that are each associated with a subject vector. A descriptor analysis is used to process the subject vectors and the feedback data packets to generate descriptor sets comprising one or more descriptors as well as weighting data for each descriptor.

Abstract: A transmission hydraulic control system includes a manual valve, a default valve, and a clutch prime valve. The manual valve allows fluid flow from a pressurized line to a drive line when the manual valve is open (when a transmission is in drive or reverse). The manual valve prevents fluid flow from the pressurized line to the drive line when the manual valve is closed (when the transmission is in neutral or park). The clutch prime valve allows fluid to flow from the pressurized line to the drive line, and thereby bypass the manual valve, when the manual valve is closed and the clutch prime valve is open. The default valve allows fluid bypassing the manual valve to flow to prime a clutch of the transmission when the default valve is open. The clutch prime valve prevents fluid from bypassing the manual valve when the clutch prime valve is closed.

Abstract: A method for public key infrastructure for serviceable electronic components is provided. The method includes identifying a plurality of electronic components in electronic communication with each other and establishing that each of the plurality of electronic components is a trusted device according to a certificate history including a plurality of signed public keys stored upon the respective electronic component. The method further includes utilizing Diffie-Hellman key exchange to distribute symmetric message authentication codes to each of the plurality of electronic components and communicating between the plurality of electronic components with the symmetric message authentication codes to achieve tangible functions that may be provided by the plurality of electronic components.

Abstract: A method for attestation of electronic components includes operating a system including the components. The components are configured for electronic communication with each other. A first electronic component provides plug-in hardware and/or configurable software. The method includes utilizing a second electronic component to perform attestation upon the first component using asymmetric key cryptography to verify authenticity. When using the asymmetric key cryptography successfully verifies the authenticity, the method includes selectively enabling one of power or data to the first component and communicating between the first component and the plurality of components to achieve tangible functions. When the cryptography fails to successfully verify the authenticity, the method includes selectively withholding one of power or data connection the first component.

Abstract: A system for interfacing with a meta-database representing data from a plurality of source databases. A key variable repository module operably couples the databases and includes an AI program with a scanner algorithm and a profiler algorithm. The scanner algorithm receives the source data from a source interface, compresses the data, and synchronizes the data with the meta-data using a meta-database interface. The profiler algorithm receives the meta-data from the meta-database interface, generates granular data types for the meta-data, determines variables indicative of the meta-data, generates variable probability distributions, produces variable associations, and modifies the meta-database to include the probability distributions and associations using the meta-data interface.

Abstract: A system for training a model from a subset of data representing decentrally stored source databases. A key variable repository module operably couples the databases and includes an AI program with a scanner algorithm and a profiler algorithm. The scanner algorithm receives the training data from a source interface, compresses the training data, and synchronizes the training data with the meta-data using a meta-database interface. The profiler algorithm receives the meta-data from the meta-database interface, generates granular data types for the meta-data, determines training variables indicative of the meta-data, generates variable probability distributions, produces training variable associations, and modifies the meta-database to include the probability distributions and associations using the meta-data interface. The key interface allows for searching the meta-database for training variables, variable probability distributions, and/or variable associations.

Abstract: A system for maintaining a meta-database including meta-data representing decentralized data from source databases, which cause inefficient selection of modeling data and/or variables. Each of source and meta-data interfaces communicate with the respective database(s). A key variable repository module operably couples the databases and includes an AI program with a scanner algorithm and a profiler algorithm. The scanner algorithm receives the source data from the source interface, compresses the data, and synchronizes the data with the meta-data using the meta-database interface. The profiler algorithm receives the meta-data from the meta-database interface, generates granular data types for the meta-data, determines variables indicative of the meta-data, generates variable probability distributions, produces variable associations, and modifies the meta-database to include the probability distributions and associations using the meta-data interface.