Abstract: A display device includes a diffusion layer providing a single well, an optical element configured to receive light and output the received image light including a concentric series of lens segments made up of active facets, and a waveguide having an in-coupling grating and a waveguide body optically coupled to the image light, where a polarizing component is disposed over an output surface of the optical element. A method to improve a yield of silicon backplane displays includes connecting a diode having a resolution to a backplane and repairing a defect on a pixel display area by dividing the pixel display area into at least one subcircuit, while improving geometry stylization transfer for 3D models of real-world environments. A method for suppressing crosstalk for user conversations includes receiving multiple speech signals captured by multiple microphones and generating directional data for the multiple speech signals based on spatial filtering.

Abstract: Systems, methods and products for uploading scanned documents for collaboration. A user chooses, prior to uploading a document, whether the user wishes for the document to be converted to a text-searchable PDF and/or processed to recognize objects in the image. When the document is scanned, it is uploaded to the cloud based system with the user-selected options, and the PDF/image is processed. The upload may be a multipart, parallel upload to increase the speed of the upload. When the PDF/image is received at the cloud based system, it is processed according to the user-selected options to generate metadata (text or recognized objects) which is stored with the uploaded document. The PDF/image and metadata are shared with users who can then search the metadata for the PDF/image.

Abstract: An architecture has been designed that introduces a “bootstrap server” into the single sign-on flow to bootstrap a SSO context to a remote browsing session. The bootstrap server provides a session token to a client browser to establish and secure a session between the client browser and a remote browsing system. After the client browser obtains a SSO token and is redirected to the bootstrap server, the bootstrap server provides a session token for a remote browsing session. The bootstrap server also generates a response to the client browser to cause the client browser to connect to the remote browsing system to establish a remote browsing session with the session token provided by the bootstrap server. With the remote browsing session, the client browser conveys the SSO token for use by the remote browser.

Abstract: An apparatus and method for unpaired time series to time series translation is disclosed. The apparatus comprises at least a processor configured to receive an automated analysis of a time series, convert that time series from its initial domain to a usable time series within another user-selected domain, then to validate the conversion against a confidence threshold.

Abstract: An apparatus for the improvement of electrocardiogram visualization is disclosed. The apparatus includes at least a processor and a memory communicatively connected thereto. The memory instructs the processor to receive a plurality of electrocardiogram signals, receive at least one transformation matrix, transform the plurality of electrocardiogram signals into a cardiac vector as a function of the at least one transformation matrix, generate a vectorcardiogram image as a function of the cardiac vector, wherein the vectorcardiogram image comprises a representation of the cardiac vector, wherein the vectorcardiogram includes a time-dependent depiction of the cardiac vector comprising a video generated as a function of a plurality of contiguous time slices, generate an assignment machine-learning model, and assign, as a function of the trained assignment machine-learning model, at least one diagnostic label to the patient as a function of the vectorcardiogram image.

Abstract: Systems/techniques that facilitate explainable confidence estimation for landmark localization are provided. In various embodiments, a system can access a three-dimensional voxel array captured by a medical imaging scanner and can localize, via execution of a first deep learning neural network, a set of anatomical landmarks depicted in the three-dimensional voxel array. In various aspects, the system can generate a multi-tiered confidence score collection based on the set of anatomical landmarks and based on a training dataset on which the first deep learning neural network was trained. In various instances, the system can, in response to one or more confidence scores from the multi-tiered confidence score collection failing to satisfy a threshold, generate, via execution of a second deep learning neural network, a classification label that indicates an explanatory factor for why the one or more confidence scores failed to satisfy the threshold.

Abstract: An apparatus for generating a diagnostic label is disclosed. The apparatus includes at least a processor and memory communicatively connected to the at least a processor. The memory instructs the processor to receive a plurality of electrocardiogram signals and a plurality of electronic health records from a user. The memory instructs the processor to generate a plurality of structured electronic health records using the plurality of electronic health records. The memory instructs the processor to generate a plurality of representations as a function of the plurality of electrocardiogram signals and the plurality of structured electronic health records using a representation machine learning model. The memory instructs the processor to generate a diagnostic label as a function of the plurality of representations. The memory instructs the processor to display the diagnostic label using a display device.

Abstract: Techniques are provided for computing with private healthcare data. The techniques include a de-identification method including receiving a text sequence; providing the text sequence to a plurality of entity tagging models, each of the plurality of entity tagging models being trained to tag one or more portions of the text sequence having a corresponding entity type; tagging one or more entities in the text sequence using the plurality of entity tagging models; and obfuscating each entity among the one or more tagged entities by replacing the entity with a surrogate, the surrogate being selected based on one or more attributes of the entity and maintaining characteristics similar to the entity being replaced.

Abstract: A threat management facility receives data from a variety of sources such as compute instances within an enterprise network, cloud service providers supporting the enterprise network, and third-party data providers such as geolocation services. In order to facilitate prompt notification of potential risks, the threat management facility may incrementally update data for use in threat assessments as the data becomes available from these different sources, and create suitable alerts or notifications whenever the currently accumulated data provides an indication of threat meeting a predetermined threshold.

Abstract: A precoding matrix feedback method includes a terminal measures channel reference signals transmitted by a plurality of TRPs. The terminal obtains, based on a channel reference signal measurement result, a precoding matrix jointly transmitted by a plurality of first TRPs, where the first TRPs are TRPs in the plurality of TRPs. The terminal obtains a target codebook coefficient of the precoding matrix, where the target codebook coefficient is used for obtaining or indicating the precoding matrix. The terminal transmits the target codebook coefficient of the precoding matrix to a network-side device.

Abstract: An example apparatus includes: a pullup circuit coupled to a first USB terminal; a first pulldown circuit coupled to the first USB terminal; a second pulldown circuit coupled to a second USB terminal; a third pulldown circuit coupled to a third USB terminal; a fourth pulldown circuit coupled to a fourth USB terminal; a high-speed termination detection circuit including: a current source including a first supply terminal and a second supply terminal, the first supply terminal coupled to the first USB terminal, the second supply terminal coupled to the second USB terminal; a first comparator including a first comparator terminal and a second comparator terminal, the first comparator terminal coupled to the first USB terminal; and a second comparator including a third comparator terminal and a fourth comparator terminal, the third comparator terminal coupled to the second USB terminal; and a controller including a first control terminal and a second control terminal, the first control terminal coupled to the sec

Abstract: A method of making an acoustic sensor (e.g., a piezoelectric sensor for a piezoelectric microelectromechanical systems microphone) includes forming or depositing one or more piezoelectric layers to define a beam extending between a proximal portion and a distal tip (e.g., unsupported free end), the beam having a width in plan view that is greater at a location distal of the proximal portion than at the proximal portion. The method also comprises attaching the beam to a substrate in cantilever form so that the proximal portion of the beam is anchored to the substrate and the distal tip is a free unsupported end of the beam. One or more electrodes are disposed on or in the proximal portion of the beam.

Abstract: An apparatus and method for locating a position of an electrode on an organ model. The apparatus includes a memory communicatively connected to at least a processor, wherein the memory contains instructions configuring the at least a processor to receive an organ model configured to digitally represent an organ, receive a set of sensor data from at least a sensor including an ultrasound sensor, determine an electrode position within the organ model as a function of the set of sensor data using a position machine-learning module, wherein determining the electrode position includes determining a model position within the organ model as a function of the set of sensor data and determining the electrode position within the model position of the organ model as a function of the set of sensor data and add a visual marker onto the electrode position in the model position of the organ model.

Abstract: Disclosed herein are compounds of Formula (I), or a pharmaceutically acceptable salt thereof, that are inhibitors of inhibitors of epidermal growth factor receptor (EGFR), including EGFR C797S mutants. Also disclosed herein are pharmaceutical compositions comprising the compounds of Formula (I), or pharmaceutically acceptable salts thereof, and one or more pharmaceutically acceptable excipients. Further disclosed herein are methods of treating cancer in a subject in need thereof, comprising administering to the subject an amount of a compound of Formula (I), or a pharmaceutically acceptable salt thereof.

Abstract: Systems and methods are provided for custom online course based on matching content with a course syllabus by parsing a syllabus document submitted by a teacher into course segments and matches course resources with appropriate course segments. The course segments can be automatically placed into an online course structure. The appropriate course materials can then be automatically matched to each course segment. Teachers may then approve, edit, or delete course segments and their matched materials. This approval process may improve the syllabus parsing and content matching and content generation using machine-learning models, such as large language models.

Abstract: This application discloses an information obtaining method and apparatus, an information sending method and apparatus, a terminal, and a network-side device, pertaining to the field of communication technologies. The information obtaining method in embodiments of this application includes: receiving, by a terminal, target signaling sent by a network-side device; and obtaining, by the terminal, a timing advance TA value of the terminal for a first object according to the target signaling; where the target signaling is signaling obtained before the terminal accesses the first object.

Abstract: The present disclosure relates to an aerogel comprising graphene oxide which is crosslinked with a metal ion. The disclosure also relates to methods and apparatus for the use of graphene oxide aerogels, in particular as desiccants.

Abstract: The invention relates to activators of FXR useful in the treatment of autoimmune disorders, liver disease, intestinal disease, kidney disease, cancer, and other diseases in which FXR plays a role, having the Formula (I): wherein L1, A, X1, X2, R1, R2, and R3 are described herein.

Abstract: An IC includes first-third power rails over a semiconductor substrate. The first rail has a first polarity different from the second and third rails. The IC includes multiple first cells on the semiconductor substrate in first and second rows. The first row is separated from the second row by the first power rail. Each first cell includes a first height and a first structure having at least one transistor. For each first cell in the first row, the first structure is entirely between the first and second rails. Further, for each first cell in the second row, the first structure is between the first and third rails. The IC includes an extension cell arranged on the semiconductor substrate in the first row. The extension cell includes a second structure having at least one transistor. A portion of the second structure extends into the second row.

Abstract: A method, non-transitory computer readable medium, and a system for pre-backup anomalous object detection and exclusion rule creation. Enterprise information technology environments often include any number of assets maintaining vast quantities of data and state. Any asset, in turn, may be riddled with various anomalous objects that tend to cause backup failure. Embodiments described herein address backup failure due to the presence of anomalous objects by, during a pre-backup stage, examining any number of assets to identify any anomalous objects there-within. Once identified, the anomalous object(s) (or metadata descriptive thereof) may be recorded within a backup skip list and, subsequently, excluded from the current and/or any future backup(s). Exclusion of the anomalous object(s), from said backup(s), may be enforced through the automatic creation of one or many exclusion rule(s) that impact, and thus adjust, the backup policy/policies associated with the asset(s).