Abstract: An apparatus for manufacturing a stator for an electric aircraft motor, wherein the apparatus includes at least a manufacturing device. The manufacturing device further includes at least a work-holding device configured to hold a first segment of teeth. The manufacturing device further includes at least a winding device configured to create a modular winding set in the first segment of teeth, wherein creating a modular winding set further include acquiring a continuous conductor and winding a continuous conducting coil upon each tooth of the plurality of teeth using the continuous conductor. The manufacturing device further includes at least an installation device configured to install a plurality of segment of teeth into the stator.

Abstract: A high density correlation system can train a machine-learned model to determine one or more phenotypes of a cell and identify compounds corresponding to a user-queried phenotype. The high density correlation system can generate training data using single-cell images and train the machine-learned model using the generated training data. The machine-learned model can determine phenotypes of cells based on images of the cells. The high density correlation system can generate a database that includes phenotype-compound mappings generated based on the outputs of the machine-learned model. After receiving a query that identifies a phenotype, the high density correlation system can generate a result set of the query using the database for display at a graphical user interface (GUI). The result set can identify compounds corresponding to the identified phenotype. Additionally, the displayed compounds can be ordered based on a score for each compound.

Abstract: An apparatus for manufacturing a stator for an electric aircraft motor, wherein the apparatus includes at least a manufacturing device. The manufacturing device further includes at least a work-holding device configured to hold a first segment of teeth. The manufacturing device further includes at least a winding device configured to create a modular winding set in the first segment of teeth, wherein creating a modular winding set further include acquiring a continuous conductor and winding a continuous conducting coil upon each tooth of the plurality of teeth using the continuous conductor. The manufacturing device further includes at least an installation device configured to install a plurality of segment of teeth into the stator.

Abstract: Systems and methods that analyze blood-based cancer diagnostic tests using multiple classes of molecules are described. The system uses machine learning (ML) to analyze multiple analytes, for example cell-free DNA, cell-free microRNA, and circulating proteins, from a biological sample. The system can use multiple assays, e.g., whole-genome sequencing, whole-genome bisulfite sequencing or EM-seq, small-RNA sequencing, and quantitative immunoassay. This can increase the sensitivity and specificity of diagnostics by exploiting independent information between signals. During operation, the system receives a biological sample, and separates a plurality of molecule classes from the sample. For a plurality of assays, the system identifies feature sets to input to a machine learning model. The system performs an assay on each molecule class and forms a feature vector from the measured values.

Abstract: A method for in utero and postnatal genome editing of a lysosomal storage disease gene, the method comprising administering to a subject an ABE or CBE complex, wherein the subject is an embryo, a fetus, a neonate, a child or an adult, ABE or CBE complex comprising CRISPR-mediated base editor and a guide RNA (gRNA), the gRNA targeting a mutation in a therapeutic gene; and introducing a modified codon in the therapeutic gene by base editing the therapeutic gene without inducing double strand DNA breaks, wherein the base editing is performed by the adenoviral vector, an adeno-associated viral vector, nucleoprotein complex or an mRNA in a lipid based nanoparticle.

Abstract: Systems and methods that analyze blood-based cancer diagnostic tests using multiple classes of molecules are described. The system uses machine learning (ML) to analyze multiple analytes, for example cell-free DNA, cell-free microRNA, and circulating proteins, from a biological sample. The system can use multiple assays, e.g., whole-genome sequencing, whole-genome bisulfite sequencing or EM-seq, small-RNA sequencing, and quantitative immunoassay. This can increase the sensitivity and specificity of diagnostics by exploiting independent information between signals. During operation, the system receives a biological sample, and separates a plurality of molecule classes from the sample. For a plurality of assays, the system identifies feature sets to input to a machine learning model. The system performs an assay on each molecule class and forms a feature vector from the measured values.

Abstract: In an aspect of the present disclosure is a system for monitoring health of a motor, including at least one sensor configured to detect at least a motor metric and send motor datum based on the at least a motor metric, an augmented reality display configured to display a visual representation of the motor datum, and a computing device communicatively connected to the at least one sensor and the augmented reality display, wherein the computing device is configured to: receive the motor datum from the at least one sensor; and command the augmented reality display to display the visual representation of the motor datum.

Abstract: A method for motor manufacturing using a clip system is illustrated. The method includes sliding a plurality of magnets onto a vertical dowel hoop, wherein the plurality of magnets are stacked on each dowel, attaching a first plate to the top of the vertical dowel hoop and a second plate to the bottom of the vertical dowel hoop, wherein the plates compress the plurality of magnets on each vertical dowel, and curing the combination of the first plate, the second plate, the plurality of magnets and the vertical dowel hoop.

Abstract: An article and method for using the same is disclosed. The article is worn on a user's head and secures a mask to the user's face without requiring loops associated with the mask to be worn over the back of the ears of the user, thereby eliminating strain and discomfort on the user's ears.

Abstract: Disclosed herein are methods and systems for identifying a drug capable of changing a cell's state, function, and/or predicted age, which is useful in, at least, drug discovery. Further disclosed herein are methods and systems for identifying an in vitro cell's state, function, and/or predicted age.

Abstract: A method for motor manufacturing using a clip system is illustrated. The method includes sliding a plurality of magnets onto a vertical dowel hoop, wherein the plurality of magnets are stacked on each dowel, attaching a first plate to the top of the vertical dowel hoop and a second plate to the bottom of the vertical dowel hoop, wherein the plates compress the plurality of magnets on each vertical dowel, and curing the combination of the first plate, the second plate, the plurality of magnets and the vertical dowel hoop.

Abstract: In an aspect of the present disclosure is a system for monitoring health of a motor, including at least one sensor configured to detect at least a motor metric and send motor datum based on the at least a motor metric, an augmented reality display configured to display a visual representation of the motor datum, and a computing device communicatively connected to the at least one sensor and the augmented reality display, wherein the computing device is configured to: receive the motor datum from the at least one sensor; and command the augmented reality display to display the visual representation of the motor datum.

Abstract: Processing circuitry of a connectivity device can receive an audio video signal from a first source. The processing circuitry can also receive an audio signal from a second source. The processing circuitry can transmit the audio video signal to a sink device. When an audio level from the second source exceeds a threshold, the processing circuitry can send the audio signal from the second source along with the video signal from the first source to the sink device.

Abstract: An article and method for using the same is disclosed. The article is worn on a user's head and secures a mask to the user's face without requiring loops associated with the mask to be worn over the back of the ears of the user, thereby eliminating strain and discomfort on the user's ears.

Abstract: Systems and methods that analyze blood-based cancer diagnostic tests using multiple classes of molecules are described. The system uses machine learning (ML) to analyze multiple analytes, for example cell-free DNA, cell-free microRNA, and circulating proteins, from a biological sample. The system can use multiple assays, e.g., whole-genome sequencing, whole-genome bisulfite sequencing or EM-seq, small-RNA sequencing, and quantitative immunoassay. This can increase the sensitivity and specificity of diagnostics by exploiting independent information between signals. During operation, the system receives a biological sample, and separates a plurality of molecule classes from the sample. For a plurality of assays, the system identifies feature sets to input to a machine learning model. The system performs an assay on each molecule class and forms a feature vector from the measured values.

Abstract: Systems and methods that analyze blood-based cancer diagnostic tests using multiple classes of molecules are described. The system uses machine learning (ML) to analyze multiple analytes, for example cell-free DNA, cell-free microRNA, and circulating proteins, from a biological sample. The system can use multiple assays, e.g., whole-genome sequencing, whole-genome bisulfite sequencing or EM-seq, small-RNA sequencing, and quantitative immunoassay. This can increase the sensitivity and specificity of diagnostics by exploiting independent information between signals. During operation, the system receives a biological sample, and separates a plurality of molecule classes from the sample. For a plurality of assays, the system identifies feature sets to input to a machine learning model. The system performs an assay on each molecule class and forms a feature vector from the measured values.

Abstract: Processing circuitry of a connectivity device can receive an audio video signal from a first source. The processing circuitry can also receive an audio signal from a second source. The processing circuitry can transmit the audio video signal to a sink device. When an audio level from the second source exceeds a threshold, the processing circuitry can send the audio signal from the second source along with the video signal from the first source to the sink device.

Abstract: Processing circuitry of a connectivity device can receive an audio video signal from a first source. The processing circuitry can also receive an audio signal from a second source. The processing circuitry can transmit the audio video signal to a sink device. When an audio level from the second source exceeds a threshold, the processing circuitry can send the audio signal from the second source along with the video signal from the first source to the sink device.

Abstract: Processing circuitry of a connectivity device can receive an audio video signal from a first source. The processing circuitry can also receive an audio signal from a second source. The processing circuitry can transmit the audio video signal to a sink device. When an audio level from the second source exceeds a threshold, the processing circuitry can send the audio signal from the second source along with the video signal from the first source to the sink device.

Abstract: Machine-learned models are selectively distributed to a plurality of computer servers according to conditions associated with the computer servers. A server receives travel information from a travel coordination system. The travel information describes a plurality of conditions. The server identifies a hierarchy of one or more parent-child relationships based on the plurality of conditions. The server trains machine-learned models using the plurality of conditions described by the travel information. The server selects machine-learned models for the plurality of conditions responsive to the identified hierarchy. The server distributes machine-learned models to the plurality of computer servers responsive to the identified hierarchy.