Abstract: Techniques and systems include assessing health risk and predicting health events of a patient using measured biosignals. The biosignals may be transformed into a photoplethysmography (PPG) signal or pseudo PPG signal, for example, to measure blood volume changes in the patient's blood flow to derive data indicating a disease state or health-related characteristic, such as blood oxygen level, blood glucose level, heart rate variability, hemoglobin, respiration rate, or arrhythmia. Further, the biosignals can include vocal signals, health labels, and self-reported data related to a patient's health. Assessment and prediction techniques include training an artificial intelligence (AI) model to create embedding vectors based on the measured biosignal(s) that are then ingested by a prediction model to assess and/or predict a patient's health risk and/or health events.

Abstract: This disclosure relates to methods and systems for injecting and/or sequestering carbon-containing materials in underground wells, and, in some examples, for using the carbon-containing materials for enhanced oil recovery and well abandonment. An example method includes: obtaining a mixture including biochar particles and a liquid; and providing the mixture for injection into an underground well.

Abstract: A computer-implemented method of determining affinity profiles, comprises: for each of a plurality of user devices, monitoring user activity including identifying content selected for viewing by the user of the user device; obtaining metadata concerning the selected items of content, the metadata representing at least some properties of the selected items of content; generating or updating a user record for the user, the user record comprising or representing the user activity and/or the associated content metadata; processing the user record to generate an affinity profile for the user based on the user record, the affinity profile comprising at least one selected affinity category or affinity category score, wherein the affinity categories are selected from a stored set of affinity categories, each representing a user's affinity for a respective subject area.

Abstract: A computer-implemented method of using affinity profiles to determine at least one audience category that is expected to consume a selected item of content, the method comprises: obtaining affinity profiles for a plurality of users of a content distribution system, wherein each affinity profile comprises at least one selected affinity category or affinity category score, and the affinity categories are selected from a stored set of affinity categories, each representing a user's affinity for a respective subject area; determine an audience that is expected to consume the selected item of content based on the affinity profiles of the users.

Abstract: A computer-implemented method of determining affinity profiles, comprises: for each of a plurality of user devices, monitoring user activity including identifying content selected for viewing by the user of the user device; obtaining metadata concerning the selected items of content, the metadata representing at least some properties of the selected items of content; generating or updating a user record for the user, the user record comprising or representing the user activity and/or the associated content metadata; processing the user record to generate an affinity profile for the user based on the user record, the affinity profile comprising at least one selected affinity category or affinity category score, wherein the affinity categories are selected from a stored set of affinity categories, each representing a user's affinity for a respective subject area.

Abstract: A computer-implemented method of using affinity profiles to determine at least one audience category that is expected to consume a selected item of content at one or more selected time periods, the method comprises: obtaining affinity profiles for a plurality of users of a content distribution system, wherein each affinity profile comprises at least one selected affinity category or affinity category score, and the affinity categories are selected from a stored set of affinity categories, each representing a user's affinity for a respective subject area; monitoring consumption of items of content or other activity of the users for different time periods; determine the likelihood of, or an expected audience measure for, the selected item of content being consumed during the or each selected time period based on the affinity profiles and the monitored consumption of content or other activity for the different time periods.

Abstract: A computer-implemented method of targeting users based on content consumption comprises: for each of a plurality of users, monitoring user activity including identifying content selected for viewing by the users; obtaining metadata concerning the selected items of content, the metadata representing at least some properties of the selected items of content; generating or updating a user record for each user, the user record comprising or representing the user activity and/or the associated content metadata; and identifying users that have below a threshold level of user activity.

Abstract: A computer-implemented method of determining affinity profiles, comprises: for each of a plurality of user devices, monitoring user activity including identifying television content selected for viewing by the user of the user device; obtaining metadata concerning the selected items of television content, the metadata representing at least some properties of the selected items of television content; generating or updating a user record for the user, the user record comprising or representing the user activity and/or the associated content metadata; processing the user record to generate an affinity profile for the user based on the user record, the affinity profile comprising at least one selected affinity category or affinity category score, wherein the affinity categories are selected from a stored set of affinity categories, each representing a user's affinity for a respective subject area.

Abstract: A computer-implemented method of determining household composition, the method, comprises: determining an affinity profile for a user based on a user record that represents television or other content selection and/or viewing by the user using at least one user device, wherein the user is a user account associated with a household and the method further comprises determining household composition based on the affinity profile for the user account, the affinity profile comprises at least one selected affinity category or affinity category score, and the affinity categories are selected from a stored set of affinity categories, each representing a user's affinity for a respective subject area.

Abstract: A computer-implemented method of determining an affinity profile for a temporary and/or anonymous user of a content distribution system, comprises: monitoring activity of the temporary and/or anonymous user comprising identifying content selected for viewing by the user; obtaining metadata concerning the selected items of content, the metadata representing at least some properties of the selected items of content; generating a user record for the user, the user record comprising or representing the user activity and/or the associated content metadata; processing the user record to generate an affinity profile for the user based on the user record, the affinity profile comprising at least one selected affinity category or affinity category score, wherein the affinity categories are selected from a stored set of affinity categories, each representing a user's affinity for a respective subject area.

Abstract: A computer-implemented method of using affinity profiles to determine at least one audience category that is expected to consume a selected content item type, the method comprises: obtaining affinity profiles for a plurality of users of a content distribution system, wherein each affinity profile comprises at least one selected affinity category or affinity category score, and the affinity categories are selected from a stored set of affinity categories, each representing a user's affinity for a respective subject area; monitoring consumption of selected items of content of the selected type to determine which of the users consumed the items of content of the selected type; determine an audience that is expected to consume the items of content of the selected type based on the affinity profiles of the users that were determined to have consumed the selected items of content.

Abstract: A computer-implemented method of using affinity profiles to obtain audience segments, the method comprises: obtaining affinity profiles for a plurality of users of a content distribution system, wherein each affinity profile comprises at least one selected affinity category or affinity category score, and the affinity categories are selected from a stored set of affinity categories, each representing a user's affinity for a respective subject area; and categorizing each user into one or more of a plurality of user segments based on their affinity profile.

Abstract: The invention is a flywheel rotor that includes a number of adjacent laminations, stacked one on top of another, where each of the laminations has the same shape and is rotationally symmetric around a center axis, and where the shape is substantially circular and includes a plurality of protrusions exterior to the circumference, and each of the laminations includes at least one hole for a fastening bolt to pass through. The invention typically includes an endplate at each end of stack of laminations. One of the two endplates may attach to a stubshaft.

Abstract: A method for classifying magnetic resonance imaging (MRI) pulse sequences includes receiving medical imaging data associated with an MRI scan, determining one or more pulse sequence characteristics for the medical imaging data using a machine learning model, wherein the medical imaging data is provided as an input to the machine learning model and wherein the machine learning model outputs a classification for each of the one or more pulse sequence characteristics, and updating a database containing the medical imaging data to include the one or more pulse sequence characteristics in association with the medical imaging data.

Abstract: A Cornelius keg refrigerated storage, transport, and contents dispensing device holds the keg in the interior of a container equipped with provision for transporting the container, cooling the keg using refrigerated contact along the effective height of the keg, insulating the keg to maintain temperature, and storing the equipment for dispensing the keg contents.

Abstract: According to the invention there is provided a method of processing a mixture of minerals including the steps of: (a) providing a mixture of minerals which includes a metal containing mineral and one or more unwanted gangue minerals; (b) achieving a contact between the mixture of minerals and polymeric material that includes a mineral binding moiety which selectively binds to the metal containing mineral; and (c) separating the gangue minerals and the polymeric material which has the metal containing mineral bound thereto.

Abstract: Exemplary embodiments provide techniques for promoting and providing subscribed content via a messaging platform. An article may be viewed via a social networking service (such as in a social network's news feed), or on a partner website integrated with the social networking service and/or messaging service. When opening the article (e.g., in a web-based view), a banner may be displayed in association with the article indicating that the article could have been received as part of a messaging-based subscription service. The banner may include a control to subscribe to the publisher with the messaging service. Topics related to an article may be suggested in the message thread for the subscription, with the selection of a topic retrieving additional articles from that publisher related to that topic. These additional articles may be selected using social networking topic determination.

Abstract: The invention provides compounds for use in inhibiting a microbial alternative oxidase (AOX) and/or cytochrome bc1 complex. The invention extends to the use of such inhibitors in agrochemicals and in pharmaceuticals, for treating microbial infections, including fungal infections.