Abstract: Aspects relate to systems and methods for individualized content media delivery. An exemplary system includes a sensor configured to detect a biofeedback signal as a function of a biofeedback of a user, a display configured to present content to the user, and a computing device configured to control an environmental parameter for an environment surrounding the user as a function of the biofeedback signal, wherein controlling the environmental parameter additionally includes generating an environmental machine-learning model as a function of an environmental machine-learning algorithm, training the environmental machine-learning model as a function of an environmental training set, wherein the environmental training set comprises biofeedback inputs correlated to environmental parameter outputs and generating the environmental parameter as a function of the biofeedback signal and the environmental machine-learning model.

Abstract: In an aspect, an apparatus for bias eliminated performance determination is presented. An Apparatus includes at least a processor and a memory communicatively connected to the at least a processor. A memory includes instructions configuring at least a processor to receive, through a sensing device, biological feedback of a user. At least a processor is configured to compare biological feedback to a performance parameter of a task. At least a processor is configured to generate, as a function of a comparison, a performance determination through a performance determination machine learning model. At least a processor is configured to classify a performance determination to a bias category as a function of a bias classifier. At least a processor is configured to train a performance determination machine learning model with biological feedback and a bias classification of a performance determination.

Abstract: A universal respiratory detector for detecting a respiratory gas. The universal respiratory detector may include a plurality of layers with a visual indicator to quickly and reversibly change color to detect a respiratory gas parameter such as carbon dioxide. The color change may be visible from both sides of the detector. In some examples, the respiratory detector may be a biocompatible and conformable sticker for mounting on a person's face or an oxygen delivery device.

Abstract: An air pump unit having an AC diaphragm air pump and a DC Motor driver circuit. The AC diaphragm air pump has a winding with a first AC power connection at a first end of the winding and a second AC power connection at a second end of the winding. The DC motor driver circuit is configured to provide an OUT1 signal to the first AC power connection and an OUT2 signal to the second AC power connection. The OUT1 and OUT2 signals are each DC square waveforms having a frequency that corresponds to a motor frequency setting. Each of the OUT1 and OUT2 DC square waveforms are 180 degrees out of phase.

Abstract: The present invention is directed in part to soybean variety CL1923017, CL1923048, CL1923819, CL1923940, CL1923860, CL1923072, CL1923908, CL1944752, CL1944558, CL1944786, CL1945742, CL1945662, and/or CL1945514 breeding and development. The present invention particularly relates to soybean variety CL1923017, CL1923048, CL1923819, CL1923940, CL1923860, CL1923072, CL1923908, CL1944752, CL1944558, CL1944786, CL1945742, CL1945662, and/or CL1945514 and its seed, cells, germplasm, plant parts, and progeny, and methods of using CL1923017, CL1923048, CL1923819, CL1923940, CL1923860, CL1923072, CL1923908, CL1944752, CL1944558, CL1944786, CL1945742, CL1945662, and/or CL1945514, e.g., in a breeding program.

Abstract: A computing system is provided, including processing circuitry configured to cause an interaction interface for a trained generative model to be presented, in which the interaction interface is configured to communicate a portion of a user interaction history. The processing circuitry is further configured to receive, via the interaction interface, an input for the trained generative model to generate an output. The processing circuitry is further configured to send a command to create, via the trained generative model or another trained generative model, a whiteboard based on the user interaction history and receive the created whiteboard. The processing circuitry is further configured to generate a prompt based on the whiteboard and the instruction from the user and provide the prompt to the trained generative model. The processing circuitry is further configured to receive a response from the trained generative model and output the response via the interaction interface.

Abstract: One embodiment provides a method, including: receiving, from at least one sensor operatively coupled to a mechanical device, sensor data corresponding to a function of the mechanical device; accessing, from an environmental database, information regarding at least one environmental condition in proximity to a geographical location of the mechanical device; generating, using a processor, a correlative value for the mechanical device, wherein the correlative value identifies a correlation between the sensor data corresponding to a function of the mechanical device and the at least one environmental condition; assigning the correlative value as a baseline correlative value to the mechanical device; monitoring the sensor data corresponding to a function of the mechanical device and the at least one environmental condition and updating the correlative value; identifying, using a processor, the correlative value for the mechanical device has exceeded a predetermined threshold as compared to the baseline correlative

Abstract: A reference to a digital item is stored as a digital card. The digital card can also be contained in, and/or refer to, other digital cards. The digital card can also include properties or attributes that may be added from the digital item that is being referred to. The digital card can be stored in a data pod within a de-centralized data storage system architecture.

Abstract: Aspects relate to methods and systems for detection of atelectasis in flight. An exemplary system includes at least an exhalation sensor configured to detect at least an exhalation parameter of a flight crew member, at least an inhalation sensor configured to detect at least an inhalation parameter of the flight crew member, at least an environmental sensor configured to detect at least an environmental parameter of a cabin within which the flight crew member is housed, and a computing device configured to determine a likelihood of atelectasis for the flight crew member as a function of the at least an exhalation parameter, the at least an inhalation parameter, and the at least an environmental parameter and generate a dosing schedule as a function of the likelihood of atelectasis.

Abstract: A building system including one or more memory devices having instructions stored thereon, that, when executed by one or more processors, cause the one or more processors to receive an event from an event source, the event comprising data and a timestamp. The building system operates to identify first contextual data describing the event in a digital twin, the digital twin comprising a virtual representation of a building, enrich the event with the first contextual data, and provide the enriched event to a consuming system, the consuming system generating an output event based on the enriched event. The building system operates to identify second contextual data describing the output event in the digital twin, enrich the output event with the second contextual data, and provide the enriched output event to the consuming system or another consuming system.

Abstract: Aspects relate to system and methods for determining a user specific mission operational performance, using machine-learning processes.

Abstract: A system for detecting unsafe equipment operation conditions using physiological sensors includes a plurality of wearable physiological sensors, each physiological sensor of the plurality of wearable physiological sensors configured to detect at least a physiological parameter of an operator of an item of equipment, and a processor in communication with the at least a physiological sensor and designed and configured to determine an equipment operation parametric model, wherein the equipment operation parametric rule relates physiological parameter sets to equipment operation requirements, detect using the equipment operation parametric model and the plurality of physiological parameters, a violation of an equipment operation requirement, and generate a violation response action in response to detecting the violation.

Abstract: An example apparatus to monitor media that is presented via a mobile device includes: an application monitor to determine when media presentation software is being executed by the mobile device; and a metering information collector to collect at least one of a signature or a code of the media presented by the media presentation software based on the media presentation software being executed by the mobile device.

Abstract: A continuous desulfurization process and process system are described for removal of reduced sulfur species at gas stream concentrations in a range of from about 5 to about 5000 ppmv, using fixed beds containing regenerable sorbents, and for regeneration of such regenerable sorbents. The desulfurization removes the reduced sulfur species of hydrogen sulfide, carbonyl sulfide, carbon disulfide, and/or thiols and disulfides with four or less carbon atoms, to ppbv concentrations. In specific disclosed implementations, regenerable metal oxide-based sorbents are integrated along with a functional and effective process to control the regeneration reaction and process while maintaining a stable dynamic sulfur capacity. A membrane-based process and system is described for producing regeneration and purge gas for the desulfurization.

Abstract: The present invention is directed in part to soybean variety CL1942054, CL1942363, CL1942176, CL1943529, CL1945058, CL1945072, CL1945600, and/or CL1945322 breeding and development. The present invention particularly relates to soybean variety CL1942054, CL1942363, CL1942176, CL1943529, CL1945058, CL1945072, CL1945600, and/or CL1945322 and its seed, cells, germplasm, plant parts, and progeny, and methods of using CL1942054, CL1942363, CL1942176, CL1943529, CL1945058, CL1945072, CL1945600, and/or CL1945322, e.g., in a breeding program.

Abstract: A computing system for monitoring language model compliance with a rubric of one or more output characteristics. The computing system includes processing circuitry configured to interface with a trained generative language model that receives input of a prompt including natural language text input and, in response, generates an output that includes natural language text output. The processing circuitry is further configured to monitor compliance of the generative language model with the rubric, by feeding the output of the generative language model to a rubric classifier configured to generate a predicted classification for an output characteristic in the rubric, and output the predicted classification.

Abstract: A method for operating and maintaining a wind farm comprising a plurality of wind turbines includes determining an odometer for one or more components of at least one of the pluralities of wind turbines in the wind farm, the odometer representing operational usage of the component(s). The method also includes tracking the operational usage for the component(s) using the odometer and a usage threshold. Further, the method includes predicting an expected time frame for one or more preventative maintenance actions based on a comparison of the tracked operational usage and the usage threshold. Moreover, the method includes triggering scheduling of the one or more preventative maintenance actions when the prediction indicates that the tracked operational usage will exceed the usage threshold. In addition, the method includes shutting down the wind turbine or idling the wind turbine once the one or more preventative maintenance actions are scheduled.

Abstract: The present invention is directed in part to soybean variety CL1941232, CL1941326, CL1941886, CL1941882, CL1941366, CL1941287, CL1941298, CL1941446, CL1941831, and/or CL1942000 breeding and development. The present invention particularly relates to soybean variety CL1941232, CL1941326, CL1941886, CL1941882, CL1941366, CL1941287, CL1941298, CL1941446, CL1941831, and/or CL1942000 and its seed, cells, germplasm, plant parts, and progeny, and methods of using CL1941232, CL1941326, CL1941886, CL1941882, CL1941366, CL1941287, CL1941298, CL1941446, CL1941831, and/or CL1942000, e.g., in a breeding program.

Abstract: A building system of a building including one or more memory devices having instructions thereon, that, when executed by one or more processors, cause the one or more processors to retrieve projection rules for generating a building graph projection. The instructions cause the one or more processors to retrieve a plurality of entities representing elements of the building and a plurality of relationships between the plurality of entities representing relationships between the plurality of entities, construct the building graph projection including a plurality of nodes and a plurality of edges based on the plurality of entities, the plurality of relationships, and the projection rules, and perform one or more operations based on the building graph projection.

Abstract: The present invention is in the field of soybean variety LS1763306, LS1763244, LS1763241, LS1663505, LS1663030, ES1668064, ES1668001, ES1667964, ES1667827, ES1667778, ES1667716, ES1667642, ES1667539, ES1667513, AND/OR CL1561664 breeding and development. The present invention particularly relates to the soybean variety LS1763306, LS1763244, LS1763241, LS1663505, LS1663030, ES1668064, ES1668001, ES1667964, ES1667827, ES1667778, ES1667716, ES1667642, ES1667539, ES1667513, AND/OR CL1561664 and its seed, cells, germplasm, plant parts, and progeny, and methods of using LS1763306, LS1763244, LS1763241, LS1663505, LS1663030, ES1668064, ES1668001, ES1667964, ES1667827, ES1667778, ES1667716, ES1667642, ES1667539, ES1667513, AND/OR CL1561664 in a breeding program.