Abstract: Embodiments of the present invention relate generally to non-invasive methods and tests that measure biomarkers (e.g., tumor antigens) and collect clinical parameters from patients, and computer-implemented machine learning methods, apparatuses, systems, and computer-readable media for assessing a likelihood that a patient has a disease, relative to a patient population or a cohort population. In one embodiment, a classifier is generated using a machine learning system based on training data from retrospective data and subset of inputs (e.g. at least two biomarkers and at least one clinical parameter), wherein each input has an associated weight and the classifier meets a predetermined Receiver Operator Characteristic (ROC) statistic, specifying a sensitivity and a specificity, for correct classification of patients.

Abstract: Embodiments disclosed herein concern a device for implantation of a cellular transplant into a target region of a subject. The device includes: a handpiece; a shaft anchored with the handpiece and extending distally therefrom; and a tubular sheath. The shaft includes a proximal end, a distal end opposite the proximal end, a curved portion, and forceps at the distal end thereof. The forceps include a pair of distal tips configured to releasably grasp the cellular transplant. The tubular sheath is movably coupled to and extending distally from the handpiece. The tubular sheath includes a distal opening and a lumen configured to slidably receive the shaft and the forceps therein. In a non-deployed state, the distal tips of the forceps are positioned within the lumen of the tubular sheath, and, in a deployed state, the distal tips of the forceps are positioned partially outside the distal opening of the tubular sheath.

Abstract: A method and apparatus is described for performing transaction tracing. The method may include mapping one or more funds flow transactions into each account to one or more funds flow transactions out of said each account based on a first-in-first-out ordering. The method may also include generating an initial graph from the mappings of the transactions for each said account. Furthermore, the method may include transforming the initial graph to a function graph, wherein the functional graph is a directed pseudoforest where each node has an out degree of at most one. Then, the method may include for a node in the functional graph, performing a trace of the transaction generating a set of transactions that contributed to the transaction.

Abstract: The present disclosure relates generally to polypeptides, which may be used of the treatment of neurological diseases or disorders.

Abstract: Embodiments of the present invention relate generally to non-invasive methods and tests that measure biomarkers (e.g., tumor antigens) and collect clinical parameters from patients, and computer-implemented machine learning methods, apparatuses, systems, and computer-readable media for assessing a likelihood that a patient has a disease, relative to a patient population or a cohort population. In one embodiment, a classifier is generated using a machine learning system based on training data from retrospective data and subset of inputs (e.g. at least two biomarkers and at least one clinical parameter), wherein each input has an associated weight and the classifier meets a predetermined Receiver Operator Characteristic (ROC) statistic, specifying a sensitivity and a specificity, for correct classification of patients.

Abstract: A method and apparatus is described for performing transaction tracing. The method may include mapping one or more funds flow transactions into each account to one or more funds flow transactions out of said each account based on a first-in-first-out ordering. The method may also include generating an initial graph from the mappings of the transactions for each said account. Furthermore, the method may include transforming the initial graph to a function graph, wherein the functional graph is a directed pseudoforest where each node has an out degree of at most one. Then, the method may include for a node in the functional graph, performing a trace of the transaction generating a set of transactions that contributed to the transaction.

Abstract: Embodiments of the present invention relate generally to non-invasive methods and tests that measure biomarkers (e.g., tumor antigens) and collect clinical parameters from patients, and computer-implemented machine learning methods, apparatuses, systems, and computer-readable media for assessing a likelihood that a patient has a disease, relative to a patient population or a cohort population. In one embodiment, a classifier is generated using a machine learning system based on training data from retrospective data and subset of inputs (e.g. at least two biomarkers and at least one clinical parameter), wherein each input has an associated weight and the classifier meets a predetermined Receiver Operator Characteristic (ROC) statistic, specifying a sensitivity and a specificity, for correct classification of patients.

Abstract: A method and apparatus is described for performing transaction tracing. The method may include mapping one or more funds flow transactions into each account to one or more funds flow transactions out of said each account based on a first-in-first-out ordering. The method may also include generating an initial graph from the mappings of the transactions for each said account. Furthermore, the method may include transforming the initial graph to a function graph, wherein the functional graph is a directed pseudoforest where each node has an out degree of at most one. Then, the method may include for a node in the functional graph, performing a trace of the transaction generating a set of transactions that contributed to the transaction.

Abstract: Embodiments of the present invention relate generally to non-invasive methods and tests that measure biomarkers (e.g., tumor antigens) and collect clinical parameters from patients, and computer-implemented machine learning methods, apparatuses, systems, and computer-readable media for assessing a likelihood that a patient has a disease, relative to a patient population or a cohort population. In one embodiment, a classifier is generated using a machine learning system based on training data from retrospective data and subset of inputs (e.g. at least two biomarkers and at least one clinical parameter), wherein each input has an associated weight and the classifier meets a predetermined Receiver Operator Characteristic (ROC) statistic, specifying a sensitivity and a specificity, for correct classification of patients.

Abstract: A method and apparatus is described for performing transaction tracing. The method may include mapping one or more funds flow transactions into each account to one or more funds flow transactions out of said each account based on a first-in-first-out ordering. The method may also include generating an initial graph from the mappings of the transactions for each said account. Furthermore, the method may include transforming the initial graph to a function graph, wherein the functional graph is a directed pseudoforest where each node has an out degree of at most one. Then, the method may include for a node in the functional graph, performing a trace of the transaction generating a set of transactions that contributed to the transaction.

Abstract: A multipurpose tool includes a handle having a first end and a second end opposite of the first end. The handle is sized and shaped to fit in a hand of a user. The tool also includes an extendable member protruding from the first end of the handle and a safety cutter disposed in the second end of the handle. The extendable member has an extended configuration and a collapsed configuration. The tool is sized and shaped to fit within a pocket in an article of clothing when the extendable member is in the collapsed configuration. The extendable member has a plurality of telescoping parts and a locking mechanism for locking the telescoping parts in the extended configuration. A distal end of the extendable member includes a hook for engaging objects and pulling them towards the user.

Abstract: Embodiments of the present invention relate generally to non-invasive methods and tests that measure biomarkers (e.g., tumor antigens) and collect clinical parameters from patients, and computer-implemented machine learning methods, apparatuses, systems, and computer-readable media for assessing a likelihood that a patient has a disease, relative to a patient population or a cohort population. In one embodiment, a classifier is generated using a machine learning system based on training data from retrospective data and subset of inputs (e.g. at least two biomarkers and at least one clinical parameter), wherein each input has an associated weight and the classifier meets a predetermined Receiver Operator Characteristic (ROC) statistic, specifying a sensitivity and a specificity, for correct classification of patients.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for tracking offline purchases. One of the methods includes receiving information from a first user device identifying a requested commerce object, a geographical area, and an advertising identifier, identifying a plurality of sources of available inventory data for physical retail locations, searching the plurality of sources to determine one or more physical retail locations that have available inventory of the commerce object, serving instructions for a presentation of a user interface to a second user device, providing instructions for presentation of a prompt regarding whether the requested commerce object was purchased, receiving a response indicating that the requested commerce object was purchased, and storing data indicating the purchase in a memory with the advertising identifier.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining which of multiple vendors have a product in stock.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for tracking offline purchases. One of the methods includes receiving information from a first user device identifying a requested commerce object, a geographical area, and an advertising identifier, identifying a plurality of sources of available inventory data for physical retail locations, searching the plurality of sources to determine one or more physical retail locations that have available inventory of the commerce object, serving instructions for a presentation of a user interface to a second user device, providing instructions for presentation of a prompt regarding whether the requested commerce object was purchased, receiving a response indicating that the requested commerce object was purchased, and storing data indicating the purchase in a memory with the advertising identifier.

Abstract: What this invention does is allow/deny the flow of electricity to a Windows based laptop's AC Adapter from the power outlet, when the laptop's battery reaches the minimum or maximum battery level percentage that is set by the user, in the application that has to be installed in a Windows based laptop. The user is able to change these values at any time or reset the values to their defaults.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining which of multiple vendors have a product in stock.

Abstract: Stereoscopic imaging devices may include stereoscopic imagers, stereoscopic displays, and processing circuitry. The processing circuitry may be used to collect auto white balance (AWB) statistics for each image captured by the stereoscopic imager. A stereoscopic imager may include two image modules that may be color calibrated relative to each other or relative to a standard calibrator. AWB statistics may be used by the processing circuitry to determine global, local and spatial offset gain adjustments to provide intensity matched stereoscopic images for display. AWB statistics may be combined by the processing circuitry with color correction offsets determined during color calibration to determine color-transformation matrices for displaying color matched stereoscopic images using the stereoscopic display.

Abstract: Stereoscopic imaging devices may include stereoscopic imagers, stereoscopic displays, and processing circuitry. The processing circuitry may be used to collect auto white balance (AWB) statistics for each image captured by the stereoscopic imager. A stereoscopic imager may include two image modules that may be color calibrated relative to each other or relative to a standard calibrator. AWB statistics may be used by the processing circuitry to determine global, local and spatial offset gain adjustments to provide intensity matched stereoscopic images for display. AWB statistics may be combined by the processing circuitry with color correction offsets determined during color calibration to determine color-transformation matrices for displaying color matched stereoscopic images using the stereoscopic display.