Abstract: A claim adjudication system including an automatic adjudication pipeline that uses pipeline rules to automatically adjudicate a claim associated with a benefit plan at one or more stages. The automatic adjudication pipeline can redirect the claim to a user interface for manual review when a pipeline rule associated with a manual review condition is triggered. The user interface can present information about the claim relevant to the manual review condition in an integrated format, including highlighting the reasons for the manual review. A user can evaluate the claim in the user interface and provide user input that addresses the manual review condition, and the claim can be routed back to the automatic adjudication pipeline. The user input can also be used as training data for machine learning to adjust pipeline rules that are used to automatically process claims and to redirect future claims for manual review.

Abstract: A datacenter has more computing power than a personal computer. The personal computer sends a request to perform an operation on a data set to the datacenter. The datacenter evaluates various inputs to determine if, despite the datacenter's computing power, the personal computer is likely to complete the operation faster. Based on the determination, the datacenter may perform the operation, send the data set to the personal computer for the personal computer to process, or start a competitive computation. As a result, a user interface can be more responsive. Machine learning processes can be used to improve predictions.

Abstract: A system includes a communication module that receives a request to post content to an event gallery associated with an event. The request in turn includes geo-location data for a device sending the content, and identification data identifying the device or a user of the device. The system further has an event gallery module to perform a first authorization operation that includes determining that the geo-location data corresponds to a geo-location fence associated with an event. The event gallery module also performs a second authorization operation that includes using the identification data to verify an attribute of the user. Finally, based on the first and second authorization operations, the event gallery module may selectively authorize the device to post the content to the event gallery.

Abstract: The disclosure provides a method for treating a subject afflicted with a tumor derived from a small cell lung cancer (SCLC) having a high tumor mutational burden (TMB) status comprising administering to the subject a monotherapy comprising an anti-PD-1 antibody or a combination therapy comprising an anti-PD-1 antibody and an anti-CTLA-4 antibody. The present disclosure also provides a method for identifying a subject suitable for treatment with an anti-PD-1 antibody or a combination therapy comprising an anti-PD-1 antibody and an anti-CTLA-4 antibody comprising measuring a TMB status of a biological sample of the subject. A high TMB status identifies the patient as suitable for treatment with an anti-PD-1 antibody or antigen-binding portion thereof. The TMB status can be determined by sequencing nucleic acids in the tumor and identifying a genomic alteration, e.g., a somatic nonsynonymous mutation, in the sequenced nucleic acids.

Abstract: Methods, systems, and storage media for outputting a synchronized arrangement of a plurality of video streams are disclosed. Exemplary implementations may: select a stage status for a subset of the plurality of client devices; determine, based on the stage status, that a client device of the plurality of client devices is assigned a stage state; send, based on the stage status and the stage state being assigned to the client device, a server state to each client device of the plurality of client devices; determine, based on the server state, a graphical layout comprising a position and size of each video stream of the plurality of video streams to output to a graphical user interface; and provide, to each client device of the plurality of client devices, instructions to display the synchronized arrangement of the plurality of video streams according to the graphical layout.

Abstract: An imaging system comprises multiple light sources, a beam combiner, an optical array sensor, and a computing device. A first light source forms a first beam of light at a first wavelength. A second light source forms a second beam of light at a second wavelength. The beam combiner combines the first beam of light and the second beam of light into a single beam of light and illuminates a specimen with the single beam of light. The optical array sensor detects reflected light that is reflected from the specimen. The computing device accesses sensor data from the optical array sensor, forms a first image based on the first wavelength and a second image based on the second wavelength, and forms a composite image from the first image and the second image.

Abstract: A computer-implemented method, a system, and a computer program product include program code that obtains, from a controller, temporal objectives and configuration specifications. The program code adjusts weighting for multiple concurrent modes. The program code optimizes each mode of the multiple concurrent modes. The program code discovers conflicts exist between the optimized multiple concurrent modes and resolves the conflicts. The program code allocates resources to the optimized multiple concurrent modes.

Abstract: A datacenter has more computing power than a personal computer. The personal computer sends a request to perform an operation on a data set to the datacenter. The datacenter evaluates various inputs to determine if, despite the datacenter's computing power, the personal computer is likely to complete the operation faster. Based on the determination, the datacenter may perform the operation, send the data set to the personal computer for the personal computer to process, or start a competitive computation. As a result, a user interface can be more responsive. Machine learning processes can be used to improve predictions.

Abstract: A computer-implemented method, a computer program product, and a system include a processor(s) that produces a set of beamforming vectors, each vector produced based on a distinct set of parameters. To produce vector of the vectors, the processor(s) obtains, from receive antennas, data comprising a waveform comprising slots with boundaries, from a first collection window. The processor(s) determines the parameters (e.g., silent portion length and signal portion length) and determines which slots of the waveform contain signal operating instructions. The processor(s) aligns the slot boundaries, utilizing the data, based on determining which slots of the waveform contain signal operating instructions. The processor(s) extracts the signal portion and the silent portion, determines a covariance for each, and determines a vector and eigenvalue.

Abstract: A datacenter has more computing power than a personal computer. The personal computer sends a request to perform an operation on a data set to the datacenter. The datacenter evaluates various inputs to determine if, despite the datacenter's computing power, the personal computer is likely to complete the operation faster. Based on the determination, the datacenter may perform the operation, send the data set to the personal computer for the personal computer to process, or start a competitive computation. As a result, a user interface can be more responsive. Machine learning processes can be used to improve predictions.

Abstract: There is set forth herein, in one embodiment, obtaining with a radiofrequency receiver a combined radiofrequency signal having a first stream combined with a second stream, wherein the first stream has a first power level, and wherein the second stream has a second power level, the first power level of the first stream being greater than the second power level of the second stream, wherein the radiofrequency receiver includes one or more antenna; processing the combined radiofrequency signal to recover a first digital bitstream associated to the first stream; and recovering a digital bitstream associated to the second stream using the first digital bitstream.

Abstract: Embodiments of the present invention include a system, method and computer program product for mitigating interference in data received by a multiple antenna array. Processor(s) executing program code identify signals from users, including active users, and by identifying these signals, mitigate interference and jamming in the received data, overall.

Abstract: Embodiments of the present invention include a system, method and computer program product for mitigating interference in data received by a multiple antenna array. Processor(s) executing program code identify signals from users, including active users, and by identifying these signals, mitigate interference and jamming in the received data, overall.

Abstract: An imaging system comprises multiple light sources, a beam combiner, an optical array sensor, and a computing device. A first light source forms a first beam of light at a first wavelength. A second light source forms a second beam of light at a second wavelength. The beam combiner combines the first beam of light and the second beam of light into a single beam of light and illuminates a specimen with the single beam of light. The optical array sensor detects reflected light that is reflected from the specimen. The computing device accesses sensor data from the optical array sensor, forms a first image based on the first wavelength and a second image based on the second wavelength, and forms a composite image from the first image and the second image.

Abstract: A datacenter has more computing power than a personal computer. The personal computer sends a request to perform an operation on a data set to the datacenter. The datacenter evaluates various inputs to determine if, despite the datacenter's computing power, the personal computer is likely to complete the operation faster. Based on the determination, the datacenter may perform the operation, send the data set to the personal computer for the personal computer to process, or start a competitive computation. As a result, a user interface can be more responsive. Machine learning processes can be used to improve predictions.

Abstract: A datacenter has more computing power than a personal computer. The personal computer sends a request to perform an operation on a data set to the datacenter. The datacenter evaluates various inputs to determine if, despite the datacenter's computing power, the personal computer is likely to complete the operation faster. Based on the determination, the datacenter may perform the operation, send the data set to the personal computer for the personal computer to process, or start a competitive computation. As a result, a user interface can be more responsive. Machine learning processes can be used to improve predictions.

Abstract: A datacenter has more computing power than a personal computer. The personal computer sends a request to perform an operation on a data set to the datacenter. The datacenter evaluates various inputs to determine if, despite the datacenter's computing power, the personal computer is likely to complete the operation faster. Based on the determination, the datacenter may perform the operation, send the data set to the personal computer for the personal computer to process, or start a competitive computation. As a result, a user interface can be more responsive. Machine learning processes can be used to improve predictions.

Abstract: A datacenter has more computing power than a personal computer. The personal computer sends a request to perform an operation on a data set to the datacenter. The datacenter evaluates various inputs to determine if, despite the datacenter's computing power, the personal computer is likely to complete the operation faster. Based on the determination, the datacenter may perform the operation, send the data set to the personal computer for the personal computer to process, or start a competitive computation. As a result, a user interface can be more responsive. Machine learning processes can be used to improve predictions.

Abstract: Provided are processes for suppressing jamming signals that may include use of a signal processing circuit. A signal processing circuit can be configured to obtain a jamming signal and a feedback signal, process the jamming signal and the feedback signal to determine a cancellation signal for use in suppressing the jamming signal, and output the cancellation signal to a radio-frequency transmitter. The signal processing circuit may be further configured to obtain a transmission signal, determine a jamming channel from the jamming signal and a feedback channel from the feedback signal, and combine the transmission channel, jamming channel, and feedback channel to determine a transfer function, where the transfer function is configured to determine the cancellation signal.

Abstract: Provided are processes for suppressing jamming signals that may include use of a signal processing circuit. A signal processing circuit can be configured to obtain a jamming signal and a feedback signal, process the jamming signal and the feedback signal to determine a cancellation signal for use in suppressing the jamming signal, and output the cancellation signal to a radio-frequency transmitter. The signal processing circuit may be further configured to obtain a transmission signal, determine a jamming channel from the jamming signal and a feedback channel from the feedback signal, and combine the transmission channel, jamming channel, and feedback channel to determine a transfer function, where the transfer function is configured to determine the cancellation signal.